causes of divorce research paper

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Divorce: Causes and Consequences - By Alison Clarke-Stewart and Cornelia Brentano

2007, Family Court Review

Related Papers

Family Relations

sanford braver , Jeffrey Cookston

In this synthesis of the international literature on psychological aspects of divorce, the causes and consequences of divorce for parents and children are summarized. The majority of parents and children show no major long-term adverse psychological consequences to divorce. Personal and contextual factors that mediate the impact of divorce on parents and children and that may account of the negative impact of divorce on a minority of parents and children are also examined. The impact of mediation and of post-divorce therapy are described and priorities for research and service development identified.

Sociology Compass

Virginia Rutter

What is the case for divorce? Researchers in the sociology of family tend to find that divorce's impact depends on what the comparison is: compared to a distressed marriage, divorce has its benefits. Meanwhile, policy makers and general audiences alike get much of their information about divorce research via the news media, where the negative consequences of divorce tend to be exaggerated, especially when comparisons, selection bias, or other research issues are neglected. Over the past 20 years, U.S. news coverage of divorce illustrates two key, intertwined topics: moral entrepreneurship using divorce as an issue and divorce research using (or not) careful methods of comparison. Three cases discussed below (in 1988–1989, 2002–2004, and 2008) illustrate these two themes. The underlying research on the health and mental health effects (including by gender) of divorce on children and adults reviewed in this article makes a case for divorce. The overlay of media reporting on divorce research illuminates the purpose for offering a case for divorce.

PsycCRITIQUES

Gordon Finley

Canadian Journal of Counselling and Psychotherapy

Cheryl Kier

RELATED PAPERS

Luan Jeremias

Peya Mushelenga

Nur Fitri Hasanah

FEMS Microbiology Ecology

cora guennoc

Eric Justes

The Turkish Journal of Endocrinology and Metabolism

Arif M A N S U R Coşar

ACS synthetic biology

Infection, Genetics and Evolution

Eric Hernández

Cogent Chemistry

Eva Martin del Valle

Bulletin of the American Physical Society

Stefano Leonardi

Nelly Sanabria

arXiv (Cornell University)

Iryna Banakh

Journal of Geophysical Research

Annals of the Rheumatic Diseases

Irene Bultink

Pensares em Revista

Cecilia Mollica

2013 15th European Conference on Power Electronics and Applications (EPE)

Michael Tønnes

AIAA Journal

Matthew E Harvazinski

Seed Science Research

Donato Chiatante

Mariane Ugalde

Türkiye Klinikleri Archives of Lung

Hayati Bilgic

Acta Agrobotanica

Agnieszka Klimek-Kopyra

哪里购买umn学位证书 明尼苏达大学毕业证文凭证书英文托福证书原版一模一样

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

The Causal Effects of Parental Divorce and Parental Temporary Separation on Children’s Cognitive Abilities and Psychological Well-being According to Parental Relationship Quality

• Original Research
• Open access
• Published: 27 July 2020
• Volume 161 , pages 963–987, ( 2022 )

Cite this article

You have full access to this open access article

• Anna Garriga 1 &
• Fulvia Pennoni   ORCID: orcid.org/0000-0002-6331-7211 2  

54k Accesses

14 Citations

12 Altmetric

Explore all metrics

We explore the effects of parental divorce and parental temporary separation on well-being of children at a specific stage of their development according to the parental relationship quality. Despite the importance of this subject, among previous studies only few consider very young children and are based on statistical methods properly tailored to enhance causal evaluations. We attempt to establish the effects on both cognitive abilities and psychological dimensions of children at age five by using data drawn from the first three waves of the UK Millennium Cohort Study. Using an appropriate imputation method, we apply the augmented inverse propensity treatment weighted estimator to infer causality. Overcoming some of the limitations of previous research, we find that the dissolution of high-quality parental unions has the most harmful effects on children, especially concerning conduct problems. We demonstrate the substantial variation on consequences of parental divorce depending on the level of parental relationship quality. We show that parental temporary separation is a type of family disruption that has significant negative effects on young children. In fact, we infer that they have more conduct and hyperactivity problems than children from stable or divorced families. Our results also suggest children to be targeted with appropriate policies aimed to reduce the adverse effect of family disruption.

Similar content being viewed by others

Parental breakup and children’s development: the role of time and of post-separation conditions

Childhood behavioral problems are associated with the intergenerational transmission of low education: a 16-year population-based study, parental health and child behavior: evidence from parental health shocks.

Avoid common mistakes on your manuscript.

1 Introduction

Parental divorce and union dissolution is an increasingly common experience for children in all developed countries. It has raised the debate on whether parental divorce is damaging for children’s well-being and to what extent parents should remain together for the sake of the children. In accordance with this social concern, one of the most extensively discussed topics in the literature has been the average effects of divorce on children well-being. Many social surveys have been considered and various statistical methods have been used putting special emphasis on controlling for parental relationship quality and conflict prior to separation but often without considering that parental conflict does not always precede separation. In fact, a large percentage of low-distress couples divorce, a phenomena that has increased substantially in recent decades (Gähler and Palmtag 2015 ).

For this reason, some studies in the last two decades have offered a more nuanced explanation of the causality of divorce that focuses on the heterogeneity of divorce effects by parental relationship quality (Amato et al. 1995 ; Jekielek 1998 ; Hanson 1999 ; Strohschein 2005 ). They take into account in which way divorce affects different children, either positively or negatively, instead of concentrating on the average causal effect of divorce across the board (Amato 2010 ). These studies suggest that divorce may be a positive experience for children from high-distress marriages, while the dissolution of low-distress marriages may have opposite effects (Amato et al. 1995 ; Booth and Amato 2001 ). Despite the significant ramifications of these findings, to the best of the author’s knowledge only few studies have examined the heterogeneity of the consequences of parental divorce by the level of parental relationship quality. These studies (for instance, see: Amato et al. 1995 ; Jekielek 1998 ; Hanson 1999 ; Morrison and Coiro 1999 ; Booth and Amato 2001 ; Strohschein 2005 ; Fomby and Osborne 2010 ; Yu et al. 2010 ; Kalmijn 2015 ) present the following characteristics: a ) only two are based on non-US data, and only few use nationally representative samples or methods to infer causality; b ) they have mainly analyzed children’s psychological well-being while evidence on other children’s outcomes such as cognitive development is scarce; c ) the most of them focus solely on children in middle childhood or older. Amato ( 2010 ), in his most recent review of the literature, encourages more research concerning this issue. We use a national large sample with several cases of divorce and temporary separations among parents and cohabiting couples representing the current trend in the Western societies. We explore the effects both on the psychological well-being and cognitive development of the children. We investigate if and how these effects are different according to parental relationship quality. The latter is measured in a way to capture not only parental conflicts before separation but also communication, affection and emotions among the couple. We use the first three waves of the Millennium Cohort Study (MCS) which is a nationally representative longitudinal study of a cohort of British children born from 2000 to 2002 in the UK. We move forward from previous work and contribute in respect to the analysis of the interrelationships between family disruption, parental relationship quality and children’s psychological well-being and cognitive development. First, we test whether the hypothesis of heterogeneity of divorce effects by parental relationship quality is also true for children from UK. Second, we aim to assess whether this hypothesis is also valid for young children since only Fomby and Osborne ( 2010 ) account for very young children and do not find evidence of heterogeneity of divorce by parental relationship quality. We have specifically focused on a salient period of children’s lives, namely the transition to school. It is well-demonstrated that children who enter school without the necessary cognitive or socio-emotional skills have greater academic and behavioral difficulties during their school years and beyond than their more “school-ready” counterparts (Romano et al. 2010 ). Third, we aim to assess the heterogeneity hypothesis by improving and extending the methodological and analytical approach proposed in the literature. We focus on many of children’s outcomes rather than just on one or two since we consider the following multiple dimensions of children’s school readiness: three different cognitive abilities (verbal, problem-solving and spatial abilities) and five psychological dimensions (conduct, hyperactivity, internalizing and peer problems, and pro-social behavior). Unlike previous research on parental divorce, we use the Augmented Inverse Propensity Treatment Weighted (AIPTW, Robins et al. 2000 ) estimator in order to yield robust estimates of the effects of interest and an imputation method based on the statistical methodology of chained equations (Raghunathan et al. 2001 ), which allows us to jointly impute missing data for different types of variables. Furthermore, in previous research on the interplay between parental divorce, parental relationship quality and children’s outcomes, the fact that a significant proportion of parents separate only temporarily was not considered. Little is known about the level of relationship quality of these parents before separation and the risks children experience when they face this type of family disruption (Kiernan et al. 2011 ; Nepomnyaschy and Teitler 2013 ).

In sum, by using cohort data similar to that used by Fomby and Osborne ( 2010 ), we aim to test the following three hypotheses: i ) parental relationship quality and family disruption are unrelated processes that have independent effects on children (the independent hypothesis); ii ) the negative association between family disruption and children’s well-being may be spurious because poor relationship quality is related to both family disruption and poor children well-being (the selection hypothesis); iii ) the consequences of family disruption on children are contingent on the level of parental relationship quality experienced prior to this event (the heterogeneity hypothesis). To test this third hypothesis about the heterogeneity of the effects of family disruption by parental relationship quality is the main contribution of our study.

The paper is structured as follows. In Sect.  2 we provide a background section considering the effects of family disruption on children well-being, then we focus on the conceptual framework. In Sect.  3 we describe data and methods. In Sect.  4 we show the main results. In Sect.  5 we provide a discussion. The supplementary material provides further details on data, missing data imputation and additional tables with results.

2 Background

2.1 family disruption on children well-being.

Studies on the effects of parental divorce on children’s well-being that use ordinary least squares (OLS) and logistic models show that part of this effect is spurious and it is only partially explained by parental relationship quality (Hanson 1999 ). Since the late 1990s, several studies have used more innovative research designs to identify the independent effects of parental divorce and father absence such as lagged dependent variable models, growth curve models, individual and sibling fixed effects models, natural experiments and instrumental variables, and propensity score matching. McLanahan et al. ( 2013 ) review these studies and find consistent evidence that parental divorce exerts negative effects on the well-being of offspring. They also show that this evidence is stronger for children’s socio-emotional development, especially in externalizing problems, than for children’s cognitive ability. Nevertheless, they present the following features: a ) most studies of the effect that of parental divorce on cognitive and psychological development are based on US samples b ) very few studies focus on children who experience parental divorce in early childhood, and c ) only one (Strohschein 2005 ) explores the heterogeneity of divorce effects by the quality of the parental relationship prior to separation.

A weakness of existing research is that it does not consider parents who separate only temporarily. Recent studies observe that a non-negligible proportion of parents separate for a short time period and then re-partner with the same person (Kiernan et al. 2011 ; Nepomnyaschy and Teitler 2013 ). However, as stated by Nepomnyaschy and Teitler ( 2013 , 3) “in most studies, this family ‘type’ is usually classified as either intact or separated (depending on when cohabitation status is ascertained), but it may differ in many respects from both of those groups”. The reason this type of family disruption is scarcely considered in previous research is that most studies only use two waves of survey data, and at least three waves are necessary to detect it. The existing research on the characteristics of parents who only separate temporarily show that such couples have a more disadvantaged socio-demographic background than with continuously intact relationships (Kiernan et al. 2011 ; Nepomnyaschy and Teitler 2013 ). Despite that, the only two studies that analyze the consequences of temporary separation on children well-being find evidence of a negative effect, even when controlling for several socio-demographic characteristics (Kiernan et al. 2011 ; Nepomnyaschy and Teitler 2013 ). However, no study controls for the relationship quality of parents before separation and some evidence suggest that couples who separate temporarily have a lower relationship quality than stable couples long before separation occurs (Vennum et al. 2014 ). Thus, if poor parental relationship quality may cause temporary separation, then it is difficult to rule out the possibility that the negative association between parental temporary separation and children’s outcomes may be due to relationship quality rather than this event per se.

2.2 Heterogeneity of the Effects of Parental Divorce by Parental Relationship Quality

2.2.1 conceptual framework.

Two main explanations are provided regarding the heterogeneity of the effects of parental divorce Footnote 1 by parental relationship quality. One is the stress relief hypothesis (Wheaton 1990 ) which concerns the consequences of transitions in life roles. Wheaton ( 1990 , 210) stated that “…instead of being stressful, life events may at times be either non-problematic or even beneficial, offering escape from a chronically stressful role situation, creating the apparent paradox of more ‘stress’ functioning as stress relief”. According to this perspective, the stressful event of parental divorce may be beneficial for children whose parental relationship prior to divorce has been poor, as it takes them away from an aversive and stressful home environment. After divorce, these children should enjoy an improvement in their well-being since they no longer experience the parental conflict (Booth and Amato 2001 ; Strohschein 2005 ).

By contrast, the dissolution of low-distress parental relationships may be detrimental to children’s development. Children from relatively harmonious families may not benefit from divorce, since it is unlikely that they experience this event as stress relief. For these children, divorce may instead give rise to stressful situations such as a decline in their standard of living, moving to a poorer neighborhood, changing schools, and losing contact with the non-custodial parent (Amato 2010 ). Children from non-dysfunctional families may also begin to experience parental discord after separation, since issues such as custody, childrearing, visitation, and child support are potentially conflictual (Booth and Amato 2001 ).

In addition to changes in stress, children’s understanding and perceptions of divorce depend on the level of their parents’ pre-divorce relationship problems, another factor related to children’s adjustment after separation. Children who have witnessed parental disputes may anticipate their parents’ divorce and attribute it to external reasons, such as parental conflict, as argued by Booth and Amato ( 2001 ). For children from low-distress families, by contrast, divorce might come as more of a surprise and they might see divorce as a threat to their happiness. Booth and Amato ( 2001 ) give possible reasons as to how an unexpected divorce may adversely impact on children. First, for these children, it is more difficult to comprehend and accept the reasons for their parents’ separation. As Maes et al. ( 2012 , 276) state: “if children do not understand why their parents have divorced, they make up their own story around things they do know, increasing the danger that children will blame themselves”. Second, children who do not anticipate parental divorce may feel that they have little control over events in their lives (Booth and Amato 2001 ). Children’s self-blame and locus of control are, in turn, negatively related to their adjustment after divorce (Bussell 1996 ; Kim et al. 1997 ).

Are these useful in explaining the heterogeneity of parental divorce for infants and very young children? The explanation of children’s understanding and perceptions of divorce is unlikely to be valid for very young children due to the kind of reasoning needed for children to be able to anticipate this event and blame themselves for it. The stress relief explanation developed for older children and adults, however, can also be applied to infants and very young children. There is a growing and consistent body of research documenting that the exposure to poor parental relationship quality during infancy affects children’s well-being cross-sectionally during infancy and longitudinally during their pre-school years (Fitzgerald 2010 ; Graham et al. 2013 ; Zhou, Cao and Leerkes 2017 ). For example, a possible mechanism is that parental conflict experienced by infants is associated with neural responses to emotional tone of voice, particularly very angry speech (Graham et al. 2013 ). With the existing evidence, it is reasonable to assume that if parental conflict produces stress in infants, then when parental divorce occurs this source of stress will disappear and their well-being will improve.

The second explanation does not focus on the consequences of direct exposure of infants to parental conflict but highlights an indirect pathway through parental well-being: parental relationship quality moderates the effect of parental divorce on very young children because parental relationship quality also moderates the effect of divorce on parent’s well-being. To our knowledge, this explanation has not been mentioned by previous research and is based on two main premises. First, it has been largely demonstrated that parents’ emotional adjustment after divorce is an important predictor of children’s well-being (Amato 1993 ) and that parents’ emotional problems are also clearly associated with adverse children’s outcomes during infancy and early childhood (Petterson and Albers 2001 ; Kiernan and Huerta 2008 ). In addition to that, few empirical studies that have focused on this topic predominantly show that people who enjoyed a high relationship quality prior to divorce suffer the most harmful negative effects on their emotional well-being (for instance, see Wheaton 1990 ; Booth and Amato 2001 ; Williams 2003 ; Waite et al. 2009 ; Ye et al. 2017 ). For people with low levels of relationship quality, the findings are mixed. Some studies give support to the hypothesis that divorce is beneficial for the emotional well-being of people in highly conflictual or unsatisfactory relationships (for instance, see: Wheaton 1990 ; Williams 2003 ; Amato and Hohmann-Marriott 2007 ; Ye et al. 2017 ). Others find evidence that when people divorce from an unsatisfactory relationship, they experience a decrease in their emotional well-being but to a lesser extent than those who divorce from satisfactory relationships (Kalmijn and Monden 2006 ; Waite et al. 2009 ). For these reasons, it seems plausible to hypothesize that if divorce has the most harmful effects on parents who enjoyed a high level of relationship quality, their children would also experience the most harmful effects of this event.

2.2.2 Previous Research

To the extent of our knowledge the current research is based on the possible data according to the characteristics of the sample at the time and on the best method of analysis. Confidence in research findings increases when studies are based on a nationally representative sample with a large sample size. Some studies have less than 300 cases in the divorce group, and only three (Hanson 1999 ; Strohschein 2005 ; Kalmijn 2015 ) use nationally representative surveys. The majority of samples are based on American children, with the exception of Kalmijn ( 2015 ) and Strohschein ( 2005 ), and there is not enough evidence to conclude the hypothesis of heterogeneity of divorce effects is valid in all Western countries or if this hypothesis is country-specific. With exception of Fomby and Osborne ( 2010 ), all relevant studies examine only children whose parents are married; they exclude the large and increasing proportion of children who are living with their biological cohabiting parents (Kiernan et al. 2011 ).

Concerning the characteristics of the outcomes and focal variables we observe that seven of the nine studies in this field used the psychological well-being of offspring; there is less consistent evidence of variation in divorce effects in other important outcomes. Among studies concerning the heterogeneity of divorce, only one focus on educational achievement (Hanson 1999 ). For this reason, with the existing research, it is not possible to say whether the hypothesis about the heterogeneity of divorce effects is valid for most children’s outcomes, or only for psychological ones.

In addition, existing research does not focus on a specific stage of children’s development. Instead, samples are used with great variation in the children’s ages at the time of divorce, and the age when response variables are measured. Most studies look at children who experienced parental divorce over a wide range of ages (Booth and Amato 2001 ; Hanson 1999 ; Kalmijn 2015 ). In some of them, divorce occurred any time from when the children were born to when they were adults. Only Fomby and Osborne ( 2010 ) focus on a specific stage of children’s development namely parental divorce that occurs before age 3, and the response variable is measured at age 3. Second, as mentioned, studies finding evidence in favor of the heterogeneity hypothesis analyze children’s outcomes measured during middle childhood and/or adolescence (Hanson 1999 ; Jekielek 1998 ; Morrison and Coiro 1999 ; Strohschein 2005 ) or adulthood (Amato et al. 1995 ; Booth and Amato 2001 ; Yu et al. 2010 ; Kalmijn 2015 ) and the only paper that does not support this hypothesis focuses on outcomes in very young children (Fomby and Osborne 2010 ). These contradictory results may suggest that the effects of divorce only vary by parental relationship quality for children in middle childhood or older. However, with only one study on very young children, there is not enough evidence to conclude whether divorce effects are heterogeneous depending on the age of the child at the time of divorce and/or the age when the outcomes were measured.

3 Materials and Methods

The data correspond to the first three waves of Millennium Cohort Study (MCS) which is a high-quality profile survey representative for the UK (Plewis et al. 2000 ; Hansen and Joshi 2007 ; Plewis 2007 ; Hansen et al. 2012 ). The first sweep was carried out between September 2000 and January 2002. It contains information on 18,819 babies from 18,533 families, collected from the parents when the babies were 9–11 months old. The families were contacted again when the children were aged 3 and 5 years. The response rates achieved for the second (2004/05) and third (2006) waves were 78% and 79% of the target sample, respectively. More than two-thirds of the sample (around 69% representing 13,234 families) responded in all three waves (Ketende 2010 ). The MCS sample design allowed for over-representation of families living in areas with high rates of child poverty and/or high proportions of ethnic minorities. Survey methods were used to take account of the initial sampling design, and adjustments were made for non-response in the recruitment of the original sample and sample attrition over the follow-up period to age five. Footnote 2

We consider children whose family structure is available for all the first three waves of the MCS. The sample includes only singleton children and families where the mother is the main respondent at the first wave. More details on the data and on how we handle missing values are available in Section A1 of the supplementary material.

3.2 Variables

3.2.1 response variables.

The variables of interest for school readiness are measured when children are 5 years old, at the third wave. The Strengths and Difficulties Questionnaire (SDQ) (Goodman 1997 ) assesses children’s behavioral adjustment and is answered by the mother. The SDQ is made up of five subscales assessing emotional symptoms, conduct problems, hyperactivity or inattention problems, peer problems, and pro-social behavior. Each subscale has five items with scores ranging from 0 to 2. Children’s cognitive development is assessed by using the British Ability Scales (BAS II) (Elliott et al. 1997 ). The following BAS subscales were used to measure different domains of cognitive development: the naming vocabulary test, which assesses expressive language; the picture similarities test, which measures pictorial reasoning; and the pattern construction test, which assesses spatial ability. These were conducted by an interviewer at home. The three tests assess the three most significant information-processing skills: verbal reasoning, non-verbal reasoning and spatial abilities (Hill 2005 ). A standardized score is computed for each cohort member according to his/her age band considered every three months. Table  1 shows the average scores for the response variables stratified according to the family situation at age 5 as defined in the following section. Children experiencing parental temporary separation or parental divorce shows lightly more psychological problems and lower scores for cognitive development with respect to children with stable family.

3.2.2 Focal Variables

We use the first three waves of the survey to create the following main family situations: children that experience parental divorce are those whose parents were together (married or cohabiting) until they were at least 9 months old, but who divorced when they were aged between 9 months and 5 years (N = 1177); children that experience parental temporary separation are those whose parents were together (married or cohabiting) when they were born and when they were 9 months and 5 years old (N = 277); however, on one or more occasions, their parents spent more than one month living apart; children in stable families are those whose parents remained in stable married or cohabiting unions from their birth until age 5 (N = 9001).

Partnership quality was derived from the Golombok Rust Inventory of Marital State (GRIMS, Rust et al. 1990 ) which is a psychometric instrument for the assessment of marital discord and the overall quality of a couple’s relationship. We only used the GRIMS scale for responses from the mother, as the fathers’ questionnaire showed a high percentage of missing cases. We use this scale at the first wave (9 months) since it has seven items, as opposed to four items in the subsequent waves.

The following four items, the responses to which were collected at the first wave assess the negative aspects of relationship quality: (1) “my partner doesn’t seem to listen to me”; (2) “sometimes I feel lonely even when I am with my partner”; (3) “I wish there was more warmth and affection between us”; and (4) “I suspect we may be on the brink of separation”. The other three items assess the positive aspects of relationship quality: (1) “my partner is usually sensitive to and aware of my needs”; (2) “our relationship is full of joy and excitement”; and (3) “we can always make up quickly after an argument”. The item responses consist of the following: strongly agree (0); agree (1); neither agree nor disagree (2); disagree (3); strongly disagree (4) and can’t say (5). “Can’t say” responses were considered as missing information. To create an ordinal scale, we included both the positive and the negative items, which involved reversing the answers to the positive items. For these items the answers were: strongly disagree (0); disagree (1); neither agree nor disagree (2); agree (3); strongly agree (4). We then added up respondents’ answers to the seven items, which produced a scale with a minimum of 0 and a maximum of 28.

Most studies, also due to few observed divorced couples, consider the heterogeneity of divorce by accounting for an interaction between parental divorce and the continuous variable measuring parental relationship quality. They assume that the magnitude and sign of the interaction effect is the same across any value of the relationship quality and they do not allow the extent to which the effect of parental divorce diverges in according to the intensity of the relation to be examined. Only Fomby and Osborne ( 2010 ) use a binary variable to identify couples with a low relationship quality if the reported value is below the 25th percentile of the sample distribution. We consider the quartiles of the empirical distribution and we account for the following ordered categories of decreasing union quality: very good, good, poor and very poor. We choose this specification to obtain a more accurate portrayal of children who experience especially poor and very poor parental relationship quality.

Table  2 shows the descriptive statistics of the family situation according to parental relationship quality. In the sample 86% belong to stable family, 11% experience parental divorce and around 3% experience parental temporary separation. The percentages of those reporting different levels of relationship quality are quite similar: 28% and 20% reported high and low quality relationships, respectively. The data reveal that parents who remained together from wave 1 (children were 9 months old) to wave 3 (children were 5 years old) had better relationship quality on average than those who divorced or experienced some period of separation. Comparing the two types of family disruption, parents who subsequently divorce exhibit worse relationship quality than those who only temporarily separate. At wave 1, around 18% of parents in stable family reported the lowest relationship quality compared with 32% of those who later separated temporarily and 39% of those who later divorced. Hence, in accordance with the selection hypothesis, a large number of children with divorced parents were exposed to poor union quality before parental separation. However, contrary to this hypothesis, Table  2 also shows that a considerable proportion of parents who divorced had not experienced poor relationship quality prior to ending their relationship. Among children whose parents divorced, around 17% and 22% belonged to families with the highest (q 1 ) and high (q 2 ) relationship quality, respectively. It is important to acknowledge that children whose parents had the highest relationship quality at wave 1 could experience poor parental relationship quality after this wave and prior to their parents’ divorce since this event occurs between wave 1 and wave 3 of the survey.

Although the percentages show that a large proportion of divorced parents reported the lowest level of relationship quality before separation, the row percentages demonstrate that the majority of parents with poor-quality relationships do not separate. Approximately three-quarters (73%) of mothers with the lowest level of relationship quality at wave 1 remained in a relationship with the father of their child four years later.

Overall, considering only values from Tables  1 and 2 , we cannot say whether the observed differences on school readiness between children from different family situations are explained by differences in parental relationship quality pre-dating the experience of family disruption.

3.2.3 Control Variables

The control variables illustrated in Table 3 are measured when children were 9 months old (wave 1), namely before parental separation took place, and took into account several socio-demographic characteristics related to family disruption and children’s well-being (Booth and Amato 1991 , 2001 ; Wilson and Waddoups 2002 ; Amato and Hohmann-Marriott 2007 ; Kiernan and Huerta 2008 ; Brown 2004 ; Kiernan and Mensah 2009 ; Brooks-Gunn et al. 2010 ; Muluk et al. 2014 ; Idstad et al. 2015 ; Karraker and Latham 2015 ; Oláh and Gähler 2014 ; Sabates and Dex 2015 ).

Concerning the social exchange theory (Levinger 1976 ) we include into the rewards and costs the following variables to control for the selection into family disruption: family income, housing tenure, mother’s educational attainment and ethnicity, mother’s health (depression and longstanding illness) and the presence of half- or step-siblings at home. We consider the following variables as barriers to family disruption: paid work status of the mother; whether the mother lived with someone else as a couple before living with the father of the child; type of parental union (married directly, cohabitation before marriage, or cohabitation); year that parents began living together as a couple; whether parents grew up in a non-stable family and mother’s attitudes to single-parent upbringing. Instrumental support is measured by the following response provided by the mother: “If I had financial problems, I know my family would help if they could”. Finally, another group of control variables is related to the division of unpaid work, which is associated with the probability of divorce: who is mostly responsible for household tasks and who is generally with and looking after the children.

3.3 Methods and Analytical Strategy

The effect of parental divorce (or parental temporary separation) on children’s outcomes is evaluated under the framework of counterfactual reasoning or Potential Outcomes (POs) (Rubin 1974 , Holland and Rosenbaum 1986 ). In this context, we are interested to estimate the Average Treatment Effect (ATE) that is conceived as the difference between the expected values of the POs of the children in the treated and untreated condition. We refer to the POs of individual exposed to treatment as \( Y_{i}^{\left( 1 \right)} \) and not exposed as \( Y_{i}^{\left( 0 \right)} \) for each i , i  = 1,…, n . The treatment is provided only to a fraction of the units, and it is denoted by a binary variable Z i that is equal to 1 if the individual i is treated and to 0 if he/she is not treated. The treatment effect is defined as the difference \( Y_{i}^{\left( 1 \right)} - Y_{i}^{\left( 0 \right)} \) and the same value over the population is the ATE defined as the expected value of the POs as follows

The realized outcome for individual i is given by

In this framework, the outcomes of the children whose parents are divorced or temporary separated are only observed in the presence of the treatment conditions and the outcomes of the children in stable families are only observed in the absence of treatment. That is, a child can experience parental divorce or can live in a stable family from 9 months to age 5. As recently stated by Kim ( 2011 ) the ATE joints the realized developmental outcomes for children had experienced divorce or temporary separation and the counterfactual outcomes for these children had their parents remained together. The effects of family disruption on children’s outcomes can be assessed only on average in this non-experimental study, since each child belongs to one of the treatment or to the control group and one PO is always not realized. Children experiencing family disruption may be not randomly selected, and the family characteristics that determine the disruption may also affect the child’s well-being through other pathways (McLanahan et al. 2013 ).

The Propensity Score (PS, Rosenbaum and Rubin 1983 ) is a multivariate statistical matching method proposed for data collected in non-experimental contexts aimed to reduce the bias of the estimator of the treatment effect by considering the observed pre-treatment covariates (Rosenbaum 2020 ). The PS concerns the conditional probability of the treatment (the probability of experiencing parental divorce or parental temporary separation) given the observed pre-treatment covariates. This aims to mimic an experimental context especially when the observational data are rich as in the context of this application where similar questionnaires are administered to the participants. For estimating the ATE the weighted regression estimator (Rosenbaum 1987 ) defined as the Inverse Propensity Treatment Weighted (IPTW) estimator (Robins et al. 2000 ) weights each unit according to the estimated inverse probability of receiving the treatment actually received. The weights are obtained as the inverse of the estimated PS and in this context they allow us to compare children exposed to divorce despite their low probability of exposure and children not-exposed to divorce. We use observable pre-treatment covariates collected into the column vector \( \varvec{X}_{i} \) whose realized values are denoted with \( \varvec{x}_{i} \) for i  = 1, …,  n . We assume that conditional to the pre-treatment covariates the average outcomes in the treated and control groups in the absence of treatment would be the same. Another assumption is defined as strong ignorability (Rosenbaum and Rubin 1983 ) and postulates that given the pre-treatment covariates the treatment choice is independent of the POs. The positivity assumption is also required meaning that each treatment level occurs with some positive probability. This is also defined overlap assumption since it implies that the support of the conditional distribution of the covariates x i given Z i = 0 overlaps completely with the conditional distribution of x i given Z i = 1 (Imbens and Wooldridge 2009 ).

Disposing of a sample of n independent units, the IPTW estimator uses weights estimated through the maximum likelihood estimates of the parameters of the multiple logistic regression model given by

In this way it is possible to mimic a pseudo-population in which the covariates are balanced between treated and untreated individuals. The Augmented IPTW (AIPTW) estimator has the smallest asymptotic variance among the class of the IPTW estimators (Robins et al. 1994 ) and it is obtained according to the proposal of Lunceford and Davidian ( 2004 ) as follows:

where \( \hat{f}\left(Y_i= {y_{i} |\varvec{v}_{i} } \right) \) denotes the multiple linear regression model estimated for the observed responses by using ordinary least squares or robust inferential methods with \( \varvec{v}_{i} \) denoting the vector of the observed covariates. All the relevant covariates should be included in the sets \( \varvec{x}_{i} \) and \( \varvec{v}_{i} \) . We propose to apply the AIPTW estimator since it corrects for possible mis-specifications in the PS model or in POs model and it is statistically more robust with respect to other methods. The so-called “double robustness” property (Bang and Robins 2005 ; Neugebauer and van der Laan 2005 ) implies that the estimator remains consistent if the POs or PS model are incorrectly specified, see among others, Cao et al. ( 2009 ) and Glynn and Quinn ( 2010 ). When the estimated weights are too large Robins et al. ( 2000 ) propose to truncate such weights up to a specified threshold, preventing to some units being highly influential.

The analytical strategy we follow is to consider the three hypotheses illustrated in the introduction and to show the results according to the following steps. First, we estimate the ATEs of parental divorce and parental temporary separation including the available covariates in the PS model shown in Table  3 and accounting also for the overall weights to consider attrition and the initial sampling design. We estimate the POs model by considering all the variables most directly related to the children’s living conditions selected according to the knowledge in the field. They are the following: sex of the child; number of children at home; mother’s education, ethnicity and labor force participation; household income; housing tenure; mother’s longstanding illness and depression, and type of parental union. Second, to evaluate the selection hypothesis we estimate the ATE including the parental relationship quality in the POs and PS models. Third, to evaluate the heterogeneity for parental divorce we estimate the ATE by considering the quartiles of the variable relationship quality in the POs and PS models. The heterogeneity hypothesis is not considered for children experiencing parental temporary separation. The three steps are repeated for every outcome by considering each time five imputed datasets in order to account for missing values. More details are provided in Section A1 of the supplementary material.

4.1 Average Effects of Family Disruption on Children’s Well-being

In order to evaluate i ) the independent and ii ) the selection hypotheses, we compare the following two models: Model 1, which only includes control variables, and Model 2, which also considers parental relationship quality in both outcome and treatment models. Table  4 reports the results for each psychological and cognitive dimension. As expected, this covariate is significant in predicting the probability of parental divorce and parental temporary separation for each dimension. We refer to Section A2 of the supplementary material for some additional results for conduct problems where we show the estimated regression coefficients of the covariates included in the PO and PS models (Table A1 and A2, respectively). Concerning the results showed in Table  4 we notice that the estimated ATE of parental divorce is significant for all the psychological dimensions and except for the picture similarity test in Model 1 for all the other cognitive dimensions. However, when parental relationship quality is introduced among the control variables (Model 2), the effect of parental divorce is not significant for internalizing problems and peer problems. For conduct and hyperactivity problems, the magnitude of the effect of parental divorce is still significant but is considerably reduced. For conduct problems, parental divorce increases the average score of 0.244 points (Model 1) with respect to the score of children in stable family but this average score decreases to 0.162 when parental relationship quality is included (Model 2). For hyperactivity, the effect of parental divorce is 0.407 in Model 1 and 0.241 in Model 2. By considering parental relationship quality the ATE is reduced of around 34% for conduct problems and around 41% for hyperactivity problems Footnote 3 . Unexpectedly, the effect of parental divorce on pro-social behavior becomes significant in Model 2. For the cognitive dimension, the estimated effect of parental divorce in Model 1 is significant for all cognitive variables with the exception of the picture similarity test. Unlike the results for the most psychological variables, when parental relationship quality is included (Model 2), the effect of parental divorce does not decrease for the pattern construction test, and even increases slightly for the vocabulary test.

The effect of parental temporary separation is not significant in any model for internalizing, peer problems and pro-social behavior. In contrast, parental temporary separation has a significant negative effect on children’s hyperactivity and conduct in both models. For parental divorce, parental relationship quality does not reduce the effect of parental temporary separation in any of these psychological dimensions. It is also important to point out that for conduct and for hyperactivity problems, the magnitude of the effect of parental temporary separation is greater than the effect of parental divorce. The results of Model 2 show that the estimated PO mean for the conduct scores of children in stable family is 1.287. Parental temporary separation increases this score by an average of 0.384 while parental divorce increases it by an average of 0.162. In other words, the effect of parental temporary separation increases conduct problems by around 30% while parental divorce only increases conduct problems by around 16%. Similar differences result for hyperactivity problems. Turning to cognitive variables, the effect of parental temporary separation is not significant in any model for the pattern construction and vocabulary tests and this effect is only significant in Model 1 for the picture similarity test.

4.2 Heterogeneous Effects of Parental Divorce According to Parental Relationship Quality

The third hypothesis is evaluated according to the results showed in Table  5 reporting the ATE estimated according to the relationship quality. With regard to the psychological dimension, the effect of parental divorce on conduct problems is only significant for children that experienced extreme levels of parental relationship quality. Among children whose parents reported the highest relationship quality (q 1 ), the PO mean in stable family is 0.960, with parental divorce increasing it by 0.349. In other words, children with parental divorce experiencing good relationship quality show more conduct problems than children in stable family. The difference in percentage is lower among children whose parents had a very poor relationship quality (q 4 ).

For hyperactivity problems, the effect of parental divorce is significant only for those whose parents had a very poor relationship. Children with parental divorce experiencing very poor relationships among parents, have a higher probability of reporting hyperactivity problems compared to children with a stable family; the difference in percentage is around 11%.

As it can be seen, for internalizing problems the average effect of parental divorce is not significant once parental relationship quality is considered. However, when this effect is analyzed according to the quartiles of parental relationship quality, we get similar results to those obtained for conduct problems. The effect of parental divorce is significant in the extreme level of the relationship quality: within the group of children whose parents showed very good relationships, those who experience parental divorce have a higher probability of manifesting internalizing problems compared to children from stable family; the difference in percentage is around 20% Footnote 4 . Within the group of children whose parents had very poor relationships, the difference in percentage is lower, at around 12%. For peer problems, the effect of parental divorce is only significant for children whose parents had a good relationship (q 2 ) and, for pro-social behavior, the effect is only significant for those with bad relationships (q 3 ).

With regard to the cognitive dimension of children’s school readiness, although the average effect of parental divorce on the picture similarity tests is not significant Table  4 , the results are different in Table  5 . The effect of parental divorce is significant and equal to − 1.326 among children with parents reporting very poor relationships (q 4 ). The effect for those experiencing very good relationships (q 1 ) among parents is not significant. For the vocabulary test, it is interesting to note that the estimated ATE is significant and negatively large for those children exposed to a very good relationship (q 1 ) among parents. In this category, parental divorce decreases the score of the vocabulary test by an average of 3.319 points. It is also significant but lower in magnitude for those whose parents had a bad relationship (q 3 ). For the pattern construction test the estimated ATE is significant and negative for children experiencing poor and very poor relationships.

5 Discussion

This work is an attempt to elucidate the interrelationships between family disruption and parental relationship quality by testing the following three main hypotheses: i ) parental relationship quality and family disruption are unrelated processes that have independent effects on children (the independent hypothesis); ii ) the apparent effect of family disruption is explained according to the parental relationship quality (the selection hypothesis); iii ) the effect of family disruption on children depends on the quality of the parental relationship (the heterogeneity hypothesis).

We advance previous research in several ways. First, we evaluate the importance of these hypotheses using a comprehensive view of child development rather than focusing on a single outcome. We analyze multiple domains of children’s school readiness: cognitive and psychological well-being. Second, we focus on very young children who are at a key point in their development, namely the transition to school, while most research focuses on children in middle childhood or older. Third, we also analyze parental temporary separation which is a type of family disruption that is only scarcely covered in previous literature. Fourth, unlike most previous research, our study examines the heterogeneity of divorce effects by parental relationship quality outside of the US by using a UK nationally representative sample. Fifth, we use a proper multivariate method to impute the missing values and we employ the augmented inverse propensity treatment weighted estimator to infer the causal effects in each imputed dataset and we combine the results. Up to our knowledge this estimator has not been used by previous studies to assess the effect of parental divorce on children well-being.

We find mixed support for the i ) independent and the ii ) selection hypotheses, obtaining a different pattern for each outcome and type of family disruption. The selection hypothesis is supported by the potential outcome models regarding the average effect of parental divorce on pro-social behavior, internalizing and peer problems. Nevertheless, there is evidence in favor of the independent hypothesis in five of the eight outcomes.

Parental temporary separation only has a significant effect on conduct and hyperactivity problems; however, the magnitude of the effect of this type of family disruption is greater than the magnitude of the effect of divorce. These results indicate that, although children experiencing parental temporary separation have been invisible in most previous research and family policies, they are also at risk, and more research on this type of family disruption is needed (Nepomnyaschy and Teitler 2013 ; Halpern-Meekin and Turney 2016 ).

With regard to the third hypothesis related to the heterogeneity of divorce effects, this study shows that the average independent effects mask the substantial variation of the effect of parental divorce. First, we find that a non-negligible proportion of children from divorced families did not experience parental relationship problems. For this group of children, the idea that the negative effects of parental divorce are explained by parental relationship quality is not valid. In addition, our findings clearly support the hypothesis that the dissolution of high-quality parental unions has the most harmful effects on children’s lives. We find that among children whose parents had a very good relationship quality, there are substantial differences between those whose parents divorce and those that remain together in six of the eight analyzed dimensions. In four outcomes, the effect of parental divorce is greater for them with respect to the others.

Our findings for children of non-distressed families are in accordance with the existing literature on the heterogeneity of divorce effects based on children in middle childhood, adolescence or adulthood using US and Canadian data. However, it is important to point out that our results based on children at age 5 clearly diverge from those obtained by Fomby and Osborne ( 2010 ) with children at age 3, which find that parental divorce is not harmful for children in high- and low-conflict families. This discrepancy is probably due to the fact that these authors categorize three-quarters of the unions as high-quality, while we consider of very good quality only those unions above the 75th percentile (highest relationship quality) of the sample distribution. This result is consistent with research on the heterogeneity of divorce effects in adults which shows that divorce has the most harmful emotional effects among those who had satisfactory relationships prior to separation. Therefore, it is reasonable to assume that the children of these parents, especially the very young, are also affected more strongly.

We do not find any evidence that corroborates the hypothesis that the effect of parental divorce is positive for children who experienced poor parental relationship quality (see also Booth and Amato 2001 ; Hanson 1999 ). It is also important to acknowledge that we do not expect to obtain this finding in a country such as the UK where fewer children are living in poor families compared to the US (OECD 2017 ). Comparative research on the heterogeneity of the effects of parental divorce is needed in order to determine to what extent this hypothesis varies by country and the mechanisms that may explain this variation such as the generosity of family policies.

In addition to that, we explain why we find a divergence between our result and the one obtained by previous studies. First, as mentioned, these studies have used a continuous measure of parental relationship quality and they consider the interaction effect between parental divorce and parental relationship quality instead we evaluate to what extent the effect of divorce differs between very good, good, poor and very poor relationship quality. This allow us to detect a non-linear pattern in some of our outcomes: children whose parental relationship lay in the extremes (very good or very poor) are those most affected by divorce while children whose parental relationship was moderately good or bad are the least affected. Making a comparison with adult data, our results are in line with the findings of Williams ( 2003 ). Second, the proposed model specification based on the augmented inverse probability weighted estimator which requires to specify a potential outcome model along with the propensity score model, has never been proposed in this context. Third, most previous research has focused on parental conflict measured in terms of the frequency of disagreements, rather than on a measure of overall marital discord and quality, the millennium cohort study does not, however, provide a direct measure of the disagreement among parents. Also, our measure of parental relationship quality is derived from the mother’s perceptions and therefore misses the father perceptions. Due to these limitations, we are not able to capture the overall level of relationship quality that children experience at home. For this reason, we cannot rule out the possibility that if we had better measures to assess disharmonious families, we may have found positive effects of parental divorce for children living in them. Future research may be improved by using more subtle measurements of relationship quality and focusing on the heterogeneity effects of divorce on very young children.

Another reason that could explain why parental separation is not beneficial for children who experienced poor parental relationship quality is that we are not able to capture its duration. Research shows that there are different trajectories of parental relationship quality over time and that experiencing persistent poor parental relationship quality has more negative effects on children’s well-being than experiencing temporary poor parental relationship quality. Hence, it is reasonable to hypothesize that parental separation can be positive for children whose parents experienced a chronically poor parental relationship quality while the same event can be damaging for children that only experienced temporary poor parental relationship quality prior to separation. An important contribution of future research would be to include the measurement of the duration and trajectories of parental relationship quality in the studies of the heterogeneity effects of parental divorce. In addition to that, future studies should not only analyze the heterogeneity effects of parental divorce but also the heterogeneity effects of other forms of family transitions such as parental temporary separation. Children experience an increase in the number and types of family dissolution experiences during childhood: parents separate and then they may get back together or have a new partner and may separate again (Amato 2010 ).

Overall, the present study makes two main contributions to the literature by employing a suitable model to infer causality by reporting that parental temporary separation has detrimental effects for children, and that parental divorce exerts the most harmful effects among children whose parents enjoyed a very good parental relationship quality prior to separation. Our results can be used also to define policies targeted to those children for whom the detrimental effect of divorce might be stronger.

We are only able to empirically study the heterogeneous effects of parental divorce and not the heterogeneous effects of parental temporary separation due to data limitations. For this reason, we only theoretically discuss the heterogeneous effects of parental temporary separation in this section. In addition to that, the literature does not provide any theoretical explanation about the heterogeneity of the effects of parental temporary separation.

Details on the survey, its origins, objectives, and sampling, as well as the content of the survey waves, are contained in the documentation attached to the data deposited at the UK Data Archive at Essex University.

These percentages are calculated by considering the estimated ATE multiplied by 100 and divided by the estimated PO referred to stable family.

The percentages are computed as explained in the previous footnote.

Amato, P. R. (1993). Children’s adjustment to divorce: Theories, hypotheses, and empirical support. Journal of Marriage and Family, 55, 23–38.

Article   Google Scholar  

Amato, P. R. (2010). Research on divorce: Continuing trends and new developments. Journal of Marriage and Family, 72, 650–666.

Amato, P. R., & Hohmann-Marriott, B. (2007). A comparison of high-and low-distress marriages that end in divorce. Journal of Marriage and Family, 69, 621–638.

Amato, P. R., Loomis, L. S., & Booth, A. (1995). Parental divorce, marital conflict, and offspring well-being during early adulthood. Social Forces, 73, 895–915.

Bang, H., & Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics, 61, 962–973.

Booth, A., & Amato, P. R. (1991). Divorce and psychological stress. Journal of Health Social Behavior, 32, 396–407.

Booth, A., & Amato, P. R. (2001). Parental predivorce relations and offspring post divorce well-being. Journal of Marriage and Family, 63, 197–212.

Brooks-Gunn, J., Han, W. J., & Waldfogel, J. (2010). First-year maternal employment and child development in the first seven years. Monographs of the Society for Research in Child Development, 75, 7–9.

Google Scholar  

Brown, S. L. (2004). Family structure and child well‐being: The significance of parental cohabitation. Journal of Marriage and Family, 66, 351–367.

Bussell, D. A. (1996). A pilot study of African American children’s cognitive and emotional reactions to parental separation. Journal of Divorce and Remarriage, 24, 1–22.

Cao, W., Tsiatis, A. A., & Davidian, M. (2009). Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data. Biometrika, 96, 723–734.

Elliott, C. D., Smith, P., & McCulloch, K. (1997). Technical manual British Ability Scales II . Berks: NFER-NELSON Publ. Co, Windsor.

Fitzgerald, K. A. (2010). Interparental conflict and emotional in security: coparenting and parent - child relationships as mediating family processes . Masters Thesis. Western Washington University.

Fomby, P., & Osborne, C. (2010). The influence of union instability and union quality on children’s aggressive behaviour. Social Science Research, 39, 912–924.

Gähler, M., & Palmtag, E. L. (2015). Parental divorce, psychological well-being and educational attainment: Changed experience, unchanged effect among Swedes born 1892–1991. Social Indicators Research, 123, 601–623.

Glynn, A. N., & Quinn, K. M. (2010). An introduction to the augmented inverse propensity weighted estimator. Political Analysis, 18, 36–56.

Goodman, R. (1997). The strengths and difficulties questionnaire: A research note. Journal of Child Psychology and Psychiatry, 38, 581–586.

Graham, A. M., Fisher, P. A., & Pfeifer, J. H. (2013). What sleeping babies hear: A functional MRI Study of interparental conflict and infants’ emotion processing. Psychological Science, 24, 782–789.

Halpern-Meekin, S., & Turney, K. (2016). Relationship churning and parenting stress among mothers and fathers. Journal of Marriage and Family, 78, 715–729.

Hansen, K., & Joshi, H. (2007). Millennium Cohort Study second survey: A user’s guide to initial findings . London: Centre for Longitudinal Study, Institute of Education.

Hansen, K., et al. (2012). Millennium Cohort Study: A guide to datasets (seventh editions). First, second, third and fourth surveys . London: Centre for Longitudinal Study, Institute of Education.

Hanson, T. L. (1999). Does parental conflict explain why divorce is negatively associated with child welfare? Social Forces, 77, 1283–1316.

Hill, V. (2005). Through the past darkly: A review of the British ability scales second edition. Child and Adolescent Mental Health, 10, 87–98.

Holland, P. W., & Rosenbaum, P. R. (1986). Conditional association and unidimensionality in monotone latent variable models. Annals of Statistics, 14, 1523–1543.

Idstad, M., Torvik, F. A., Borren, I., Rognmo, K., Røysamb, E., & Tambs, K. (2015). Mental distress predicts divorce over 16 years: The HUNT study. BMC Public Health, 15, 1.

Imbens, G. W., & Wooldridge, J. M. (2009). Recent developments in the econometrics of program evaluation. Journal of Economic Literature, 47, 5–86.

Jekielek, S. M. (1998). Parental conflict, marital disruption and children’s emotional well-being. Social Forces, 76, 905–936.

Kalmijn, M. (2015). How childhood circumstances moderate the long-term impact of divorce on father–child relationships. Journal of Marriage and Family, 77, 921–938.

Kalmijn, M., & Monden, C. W. (2006). Are the negative effects of divorce on well-being dependent on marital quality? Journal of Marriage and Family, 68, 1197–1213.

Karraker, A., & Latham, K. (2015). In sickness and in health? Physical illness as a risk factor for marital dissolution in later life. Journal Health and Social Behavior, 56, 420–435.

Ketende, S. (2010). MCS technical report on response . London: Centre for Longitudinal Studies.

Kiernan, K. E., & Huerta, M. C. (2008). Economic deprivation, maternal depression, parenting and children’s cognitive and emotional development in early childhood. Bristish Journal Sociology, 59, 783–806.

Kiernan, K., McLanahan, S., Holmes, J., & Wright, M. (2011). Fragile families in the US and UK. Centre for Research on Child Well-Being. Working Paper WP 11 - 04 - FF , Princeton University, Princeton, NJ.

Kiernan, K. E., & Mensah, F. K. (2009). Poverty, maternal depression, family status and children’s cognitive and behavioural development in early childhood: A longitudinal study. Journal of Social Policy, 38, 569–588.

Kim, H. S. (2011). Consequences of parental divorce for child development. American Sociological Review, 76, 487–511.

Kim, L. S., Sandler, I. N., & Tein, J. Y. (1997). Locus of control as a stress moderator and mediator in children of divorce. Journal of Abnormal Child Psychology, 25, 145–155.

Levinger, G. (1976). A social psychological perspective on marital dissolution. Journal of Social Issues, 32, 21–47.

Lunceford, J. K., & Davidian, M. (2004). Stratification and weighting via the propensity score in estimation of causal treatment effects. Statistics in Medicine, 23, 2937–2960.

Maes, S. D., De Mol, J., & Buysse, A. (2012). Children’s experiences and meaning construction on parental divorce: A focus group study. Childhood, 19, 266–279.

McLanahan, S., Tach, L., & Schneider, D. (2013). The causal effects of father absence. Annual Review of Sociology, 39, 399–427.

Morrison, D. R., & Coiro, M. J. (1999). Parental conflict and marital disruption: Do children benefit when high-conflict marriages are dissolved? Journal of Marriage and Family, 61, 626–637.

Muluk, N. B., Bayoğlu, B., & Anlar, B. (2014). Language development and affecting factors in 3-to 6-year-old children. European Archives of Oto-Rhino-Laryngology, 271, 871–878.

Nepomnyaschy, L., & Teitler, J. (2013). Cyclical cohabitation among unmarried parents in fragile families. Journal of Marriage and Family, 75, 1248–1265.

Neugebauer, R., & van der Laan, M. (2005). Why prefer double robust estimators in causal inference? Journal of Statistical Planning and Inference, 129, 405–426.

OECD. (2017). Social policy division—directorate of employment, labour and social affairs. OECD Family Database. CO2.2: Child poverty, http://www.oecd.org/els/family/database.htm . Accessed 20 April 2020.

Oláh, L. S., & Gähler, M. (2014). Gender equality perceptions, division of paid and unpaid work, and partnership dissolution in Sweden. Social Forces, 93, 571–594.

Petterson, S. M., & Albers, A. B. (2001). Effects of poverty and maternal depression on early child development. Child Development, 72, 1794–1813.

Plewis, I. (2007). Non-response in a birth cohort study: the case of the Millennium Cohort Study. International Journal of Social Research Methodology, 10, 325–334.

Plewis, I., Calderwood, L., Hawkes, D., Hughes, G., & Joshi, H. (2000). Millennium Cohort Study: Technical Report on Sampling . London: Centre for Longitudinal Study, Institute of Education.

Raghunathan, T. E., Lepkowski, J. M., Van Hoewyk, J., & Solenberger, P. (2001). A multivariate technique for multiply imputing missing values using a sequence of regression models. Survey Methodology, 27, 85–96.

Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11, 550–560.

Robins, J. M., Rotnitzky, A., & Zhao, L. P. (1994). Estimation of regression coefficients when some regressors are not always observed. Journal of American Statistical Association, 89, 846–866.

Romano, E., Babchishin, L., Pagani, L. S., & Kohen, D. (2010). School readiness and later achievement: Replication and extension using a nationwide Canadian survey. Developmental Psychology, 46, 995–1007.

Rosenbaum, P. R. (1987). Model-based direct adjustment. Journal of the American Statistical Association, 82, 387–394.

Rosenbaum, P. R. (2020). Modern algorithms for matching in observational studies. Annual Review of Statistics and its Applications, 7, 143–176.

Rosenbaum, P. R., & Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.

Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688–701.

Rubin, D. B. (1996). Multiple imputation after 18 + years. Journal of American Statistical Association, 91, 473–489.

Rubin, D. B. (2002). Introduction to multiple imputation . Stat. Anal. Missing Data, 2nd Ed NY, Wiley, pp. 85–93.

Rust, J., Bennun, I., Crowe, M., & Golombok, S. (1990). The GRIMS: A psychometric instrument for the assessment of marital discord. Journal of Family Therapy, 12, 45–57.

Sabates, R., & Dex, S. (2015). The impact of multiple risk factors on young children’s cognitive and behavioural development. Children and Society, 29, 95–108.

Strohschein, L. (2005). Parental divorce and child mental health trajectories. Journal of Marriage and Family, 67, 1286–1300.

Vennum, A., Lindstrom, R., Monk, J. K., & Adams, R. (2014). “It’s complicated” The continuity and correlates of cycling in cohabiting and marital relationships. Journal of Social and Personal Relationship, 31, 410–430.

Waite, L. J., Luo, Y., & Lewin, A. C. (2009). Marital happiness and marital stability: Consequences for psychological well-being. Social Science Research, 38, 201–212.

Wheaton, B. (1990). Life transitions, role histories, and mental health. American Sociological Review, 55, 209–223.

Williams, K. (2003). Has the future of marriage arrived? A contemporary examination of gender, marriage, and psychological well-being. Journal of Health Social Behavior, 44, 470.

Wilson, S. E., & Waddoups, S. L. (2002). Good marriages gone bad: Health mismatches as a cause of later-life marital dissolution. Population Research Policy Review, 21, 505–533.

Ye, M., DeMaris, A., & Longmore, M. A. (2017). Role of marital quality in explaining depressive symptoms after marital termination among older adults. Marriage Family Review, 1, 1–16.

Yu, T., Pettit, G. S., Lansford, J. E., Dodge, K. A., & Bates, J. E. (2010). The interactive effects of marital conflict and divorce on parent-adult children’s relationships. Journal of Marriage and Family, 72, 282–292.

Zhou, N., Cao, H., & Leerkes, E. M. (2017). Interparental conflict and infants’ behavior problems: The mediating role of maternal sensitivity. Journal of Family Psychology, 31, 464–474.

Download references

Acknowledgements

Open access funding provided by Università degli Studi di Milano - Bicocca within the CRUI-CARE Agreement. Garriga thanks the grants of the Spanish Ministry of Economy and Competitiveness (Grants CSO2012-33476 and CSO2015-69439-R). Pennoni thanks the grant “Finite mixture and latent variable models for causal inference and analysis of socio-economic data” (FIRB—Futuro in Ricerca) funded by the Italian Government (RBFR12SHVV). The authors thank Isabella Romeo for her contribution to preliminary data analyses.

Author information

Authors and affiliations.

Department of Political and Social Science, Pompeu Fabra University, Barcelona, Spain

Anna Garriga

Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy

Fulvia Pennoni

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Fulvia Pennoni .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 140 kb)

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Garriga, A., Pennoni, F. The Causal Effects of Parental Divorce and Parental Temporary Separation on Children’s Cognitive Abilities and Psychological Well-being According to Parental Relationship Quality. Soc Indic Res 161 , 963–987 (2022). https://doi.org/10.1007/s11205-020-02428-2

Download citation

Accepted : 06 July 2020

Published : 27 July 2020

Issue Date : June 2022

DOI : https://doi.org/10.1007/s11205-020-02428-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Augmented inverse propensity treatment weighted estimator
• Conduct problems
• Family instability
• Missing values
• Find a journal
• Publish with us
• Track your research

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

Publications

• Our Methods
• Short Reads
• Tools & Resources

Read Our Research On:

Marriage & Divorce

In a growing share of u.s. marriages, husbands and wives earn about the same.

Among married couples in the United States, women’s financial contributions have grown steadily over the last half century. Even when earnings are similar, husbands spend more time on paid work and leisure, while wives devote more time to caregiving and housework.

About six-in-ten Americans say legalization of same-sex marriage is good for society

College grads in u.s. tend to partner with each other – especially if their parents also graduated from college, rising share of u.s. adults are living without a spouse or partner, sign up for our weekly newsletter.

Fresh data delivery Saturday mornings

Among young adults without children, men are more likely than women to say they want to be parents someday

Among adults ages 18 to 34, 69% of those who have never been married say they want to get married one day.

Striking findings from 2023

Here’s a look back at 2023 through some of our most striking research findings.

Across Asia, views of same-sex marriage vary widely

A median of 49% of people in 12 places in Asia say they at least somewhat favor allowing gays and lesbians to marry legally.

How people around the world view same-sex marriage

Among the 32 places surveyed, support for legal same-sex marriage is highest in Sweden, where 92% of adults favor it, and lowest in Nigeria, where only 2% back it.

Public Has Mixed Views on the Modern American Family

Americans are more pessimistic than optimistic about the institution of marriage and the family. At the same time, the public is fairly accepting of diverse family arrangements, though some are seen as more acceptable than others.

The Modern American Family

Key trends in marriage and family life in the United States.

About 8 in 10 women in opposite-sex marriages say they took their husband’s last name

Younger women, women with a postgraduate degree and Democratic women are more likely to keep their last name after marriage.

A record-high share of 40-year-olds in the U.S. have never been married

As of 2021, 25% of 40-year-olds in the United States had never been married, a significant increase from 20% in 2010.

Single women own more homes than single men in the U.S., but that edge is narrowing

In 2022, single women owned 58% of the nearly 35.2 million homes owned by unmarried Americans, while single men owned 42%.

REFINE YOUR SELECTION

Research teams.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

Copyright 2024 Pew Research Center

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2024 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

Gray Divorce: Why Older Couples Are Splitting Up More Often

Ending your marriage later in life brings unique challenges—and opportunities

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Dr. Sabrina Romanoff, PsyD, is a licensed clinical psychologist and a professor at Yeshiva University’s clinical psychology doctoral program.

Charday Penn / Getty Images

• Contributing Factors
• Financial Considerations
• Emotional and Psychological Impact
• Maintaining Health and Wellness

Resources and Support for Gray Divorcees

When people think about retirement, they often imagine spending their golden years enjoying the life they've built with their partner. However, a growing number of older American adults are doing something completely unexpected for their age group—getting divorced. A 2021 report by the U.S. Census Bureau suggests that more and more couples over the age of 65 are calling quits, often after being married for years, if not decades.

This phenomenon, dubbed "gray divorce," is one explanation for the growing number of single-person U.S. households. 

Gray divorce is often defined as divorce that occurs after the age of 50 following a long-term marriage. These individuals have often been married for many years or decades but ultimately decide to split during the later years of their lives. 

Why are so many older couples getting divorced? Whereas younger couples divorce because of incompatible parenting styles or difficult relatives, older divorcees are more likely to split due to empty nest syndrome, infidelity, and financial differences. Instead of fighting over custody of the kids, elderly couples are more likely to argue over pension plans and retirement savings. Divorce can take a massive financial toll, and older adults who are closer to retirement age—or already retired—have less time to recover.

At a Glance

Gray divorce is on the rise, and the reasons behind it are complex and varied. Statistics suggest that Baby Boomers are more prone to divorce, and factors like empty nest syndrome, shifting priorities, financial problems, and reduced stigma surrounding divorce can all play a role. Keep reading to learn more about why divorcing after age 50 is becoming more common and the potential effects this can have on a person’s well-being.

How Common Is Gray Divorce?

One 2022 study looking at historical trends in gray divorce found that divorce rates among middle-aged and older adults have increased since 1970. Gray divorce was relatively uncommon in 1970 and grew only modestly until 1990. In 1990, 8.7% of marriages among people over age 50 ended in divorce. By 2019, that number had grown to 36%.

The researchers also noted that people over the age of 65 are the only age group with growing divorce rates. In contrast, the divorce rate among adults in their 20s and 30s has actually declined in recent years.

Generational Influences

One explanation for growing gray divorce rates is that Baby Boomers—adults born between 1946 and 1964—make up the bulk of the age group over 50 and this generation is more likely to divorce than older and younger generations. Boomers were more likely to divorce during their younger adult years, and their divorce rates have also continued to rise as they age.

Other factors that increase the risk for gray divorce include the number of previous marriages and the number of years a person has been married. Remarriages are less likely to last, and people who have been married nine years or less are more likely to divorce.

While length of marriage is a risk factor for gray divorce, many couples who split after the age of 50 have been in marriages lasting decades. According to statistics by the Pew Research Center, 34% of gray divorces are between couples married for at least 30 years, and 12% are between couples married 40 years or longer.

Factors Contributing to Gray Divorce

So why are many couples opting to split after weathering many of the challenges they’ve faced earlier in their relationship? The reasons why a long-term couple opts for divorce vary from one situation to the next. Some common factors that appear to play a major role include:

Empty Nest Syndrome

Kids leaving the home can create a big shift in a relationship, sometimes resulting in what is commonly called " empty nest syndrome ." Couples may find that once their children no longer live at home, they have little in common outside of their roles as parents. This can make it hard to find closeness and connection , leading many adults to seek fulfillment outside their relationship.

"For many couples, the children have been the source of their connection," says Kimberley Best, RN, MA, a dispute resolution expert and founder of Best Conflict Solutions. "When the children are gone, some couples realize they have drifted apart and no longer have shared interests or a strong connection."

Financial Issues

Arguments over money can become more pronounced as couples near retirement age. It becomes harder to find common ground and maintain the peace, as people contemplate leaving the workforce.  Financial infidelity —such as hiding bills, large purchases, debts, or secret bank accounts—can also affect the stability of a long-term marriage.

Retirement plans may hang in the balance when a couple's financial behavior and goals are out of sync. Ending the relationship may sometimes seem like the only way to resolve such differences.

Cheating is one of the most common reasons for divorce at any age, including among older couples. Infidelity is a bitter betrayal. After spending a lifetime building shared memories with another person, watching it crumble down due to unfaithfulness can make it too difficult to repair the trust and intimacy a couple once shared.

Health Problems

Health challenges like a serious chronic condition can majorly strain a relationship. Some couples find that they're unable to handle health issues that emerge as they age.

Notably, research indicates there is a gender disparity in how health problems affect couples. Studies reported a higher divorce risk if the wife develops a chronic illness, whereas men who become disabled or ill do not face the same level of risk.

Growing Apart

One of the most significant causes of gray divorce is the changes people experience as they age . Growing apart is the most frequently cited reason for divorce at any age. For older adults specifically, aging represents a big change, and people’s priorities, interests, and needs may shift as they grow older.

Some couples might grow closer during this time, but others might find their values and priorities too different, leading some couples to choose separate paths.

Changing Expectations

Our expectations for what we consider a healthy, satisfying marriage have also changed over time. Today, couples are more likely to place a greater emphasis on how the relationship makes them feel, including whether it contributes to their overall happiness and fulfillment. When a relationship or a person's needs shift, it may no longer meet these criteria, which is why some people may opt to end things.

Societal Changes

Societal changes have also influenced this relationship upheaval. Older adults were often raised with the expectation that they would marry, have children, and grow old together. Today, many now recognize that there is no one-size-fits-all path to a happy life, and women have more freedom and financial independence to past generations. 

"The majority of all divorces are initiated by women, and this is true for gray divorce as well," explains Kate Engler, LMFT, CST, a licensed couples and sex therapist at Three Points Relationships. "In the last 50 years, women have gained greater economic independence and have held and maintained their own careers. This has created more options for women on many fronts, including deciding to divorce."

As a result, people are less likely to stay in marriages that don’t meet their needs, even if it means calling it quits after spending decades together.  Engler notes that other factors such as increased life expectancy have also played a part. 

"With increased life expectancy, many people—particularly women—look down the road at what remains of their life and think, 'Why would I want to spend these years in a bad marriage? I still have a life to live, and I want to be happy,'" she adds.

One study found that attitudes toward divorce have become more supportive among people over the age of 50. Reduced stigma around the idea of divorce may also lead people to choose to leave rather than stay in an unhappy or unsatisfying relationship.

Financial Considerations in Gray Divorce

It’s important to note that divorce can have serious financial consequences for couples that end their marriages later in life.

"Gray divorce can be financially devastating to both parties," Best explains. "Often people are saving for a joint retirement. This will likely be split with divorce, leaving people with far less income than they anticipated."

While divorce has economic impacts at any age, some considerations that are particularly significant for middle-aged and older adults include:

• Dividing assets : This involves splitting up financial resources, possessions, and property that have been accumulated over the course of a marriage. This can include the shared home and any savings, investments, pensions, and other personal possessions. Laws about how these assets are divided vary by state, so they may become the source of considerable contention.
• Retirement savings: Splitting retirement savings can affect how much each person has available to support themselves during retirement. 
• Healthcare costs : Gray divorce can also affect healthcare expenses. One spouse may lose access to insurance benefits previously provided by their partner, which can be a significant concern for older adults with increased health concerns.
• Housing and legal expenses : Other costs associated with divorce, including housing expenses and legal fees, can add up quickly.

Gray Divorce Can Reduce Financial Security

Evidence indicates that a late-life divorce has a major effect on an individual’s financial situation and well-being. For example, research has shown that gray divorcees have less financial security than their married or widowed peers.

While both men and women take a significant financial hit, evidence indicates there is a gender disparity in these effects. This risk is particularly high for gray divorced women, as they receive lower Social Security benefits, and 25% of them experience poverty.

Men and women both feel the financial toll, but the effect on women is much larger. One study found women who divorce after the age of 50 experience a 45% drop in their standard of living, compared to men who experience a 21% drop.

On the societal level, older couples who divorce can create challenges for an already strained housing market. Finding housing that is affordable, accessible, and safe for the needs of an aging population can be particularly difficult.

Emotional and Psychological Impact of Gray Divorce

Gray divorce also has profound emotional effects. It's a significant life change at any age, but this transition can be especially difficult when it happens after a long-term marriage. Elderhood is often a point where many people feel settled but gray divorces can have their sense of security upended.

Grief and Loss

It's normal for people to feel a sense of grief and loss when they let go of a shared connection and the dreams and hopes they once shared together. For some, the loss of what was one of the most significant relationships in their life can feel very much like experiencing the death of a loved one .

Engler explains that people often experience what is known as "ambiguous loss," characterized by feelings of grief. This loss is considered ambiguous because while the person is still out there, they are no longer present in your life.

Stress, Anxiety, and Depression

The mental health effects of gray divorce are also important to consider. Some people experience a sense of renewal and freedom as they let go of a relationship that no longer serves them. Others, particularly those who didn't initiate the divorce, may be left struggling with feelings of stress, anxiety, or depression.

"When a lifetime partnership ends , they must find a way to readjust and rethink what brings them meaning, purpose, and connection," explains Michelle Feng, MD , Chief Clinical Officer at the behavioral healthcare team of Executive Mental Health. "Divorce can take away some of the built in structure of interacting with others that occurs as a couple and a family. Without it, we can feel aimless, not a part of the rest of society, and lonely."

Loss of Identity

A loss of identity might also be a consequence of gray divorce. People are forced to grapple with changes to their sense of self and find ways to redefine themselves outside of their marriage. A person's self-esteem and self-worth can also take a hit. They may be left struggling with feelings of inadequacy and rejection .

Loneliness and Isolation

Older adults are particularly at risk for experiencing loneliness as they grow older, and that risk can be heightened following a late-life divorce. One report found that one-third of people over age 45 and one-quarter of those over 65 are considered socially isolated .

The loss of a partner, changes in their social networks, and the challenges of adjusting to life as a single person can make a person feel overwhelmed and alone.

Engler notes that loneliness is a problem she sees often in her own practice, particularly among men. "They typically focused their time and energy on work throughout their lives, often letting friendships lapse or they leaned heavily on their wives to maintain their social life," she says. "Once divorced, they find themselves without the skills or confidence to do it on their own."

Social isolation and loneliness are linked to a higher risk for health problems, including dementia, coronary artery disease, and stroke.

Health Effects

Gray divorce can also have a range of health effects. In general, marriage is associated with better health and greater longevity. Married people tend to be healthier and live longer than their unmarried counterparts.

While that might be the case more generally, that doesn't mean that each individual marriage is good for a person's health. An unhappy marriage can be a source of considerable stress and strife, which is associated with a range of negative health effects.

In such instances, a low-quality marriage may actually lead to worse health outcomes. For people in unhealthy relationships , ending the marriage may ultimately have a positive impact on overall health and well-being.

Maintaining Health and Wellness During Gray Divorce

Gray divorce can be a major transition, but there are steps you can take to help maintain your health and well-being if you decide to split from your partner later in life.

Feng stresses that separation and divorce are highly personal. "Don’t let the statistics make you afraid or drive you in a way that is not in line with what you want to do," she says. "It is easier now to get a divorce, although still difficult financially. But like any great lifestyle change, it will require a period of adjustment."

The experts we spoke to suggest taking the following steps to protect your well-being and help you thrive following a divorce:

Find Support

Having the support of friends and family is pivotal. Loneliness is a common problem for older single adults, so maintaining social connections outside of your marriage can help mitigate this risk.

Get out of the house and interact with other people. Join a class, go to the park, volunteer. Whether it’s with people you know or complete strangers, do something to reactivate that social part of you. The more you engage, the easier this new stage of life becomes.

Give Yourself Time

While divorce is difficult at any age, ending a long-term relationship might be harder to process. Give yourself time and grace as you navigate these complex emotions. It's normal to feel grief, sadness, anger, bitterness, and relief.

Set Boundaries

Create and maintain boundaries with your ex, as well as with kids and friends who may feel the need to express their opinions about the end of your relationship. 

Practice Self-Care

The sudden change in your routine, relationships, and living situation can throw a wrench into your normal self-care routine. That’s why it is important to make an effort to maintain routines and stick with your self-care goals.

Talk to a Financial Counselor

Because financial and economic changes are common after a gray divorce, consider talking to a financial professional. They can help you develop a budget appropriate for your new financial situation and help manage debt, so you're better prepared for your financial future. 

Manage Stress

Divorce is stressful, and dealing with the changes you’re experiencing can sometimes make it hard to cope. Look for relaxation techniques that can help combat symptoms of stress. Deep breathing , progressive muscle relaxation, yoga, mindfulness , and meditation are just a few you might try.

Cultivate New Connections

The reality is that your relationships will likely change after a gray divorce. You may spend less time with many of your shared friends or even lose those relationships altogether. That’s why it’s so important to seek out new social connections as you rebuild your life as a single person. This can involve making new friends , or it might even include eventually dating again , whether that involves casual dating or seeking a new long-term partner.

As hard as it can feel to do this, try to push the edges of your comfort zone when you can. Try new things, meet new people, and do the things you always wanted to do but didn't when you were married. The clients I see do this and end up feeling empowered and fulfilled in ways they never imagined they could.

While divorce signifies the end of one of the most significant and long-lasting relationships in your life, that doesn't mean that you need to go it alone. There are a variety of resources and support networks that can help gray divorcees navigate the challenges that come from these later-in-life events.

"Finding support and community are critical during and after a divorce," Engler says. "Find a therapist. Find a support group. Find other people who have experienced divorce, understand what you have been through, and don't judge you."

A few options include:

Family and Friends

Friends, family, and loved ones can be one of your most powerful forms of support. In addition to offering practical assistance and guidance (since they may have experience with their own divorces), trusted friends and family members can also be a source of companionship and emotional support.

Mental Health Professionals

For divorcees struggling with the aftereffects of a divorce, a licensed mental health professional can be a valuable source of insight and support. Talking to a therapist can help you process your emotions, develop new coping strategies, and make a plan for how to deal with some of the challenges you will face during and after a divorce.

Financial Advisors

Since gray divorce has significant financial implications, it's important to work with a qualified financial planner or advisor. Look for someone with experience advising divorced clients, so you can receive the best possible guidance on how to budget, plan for retirement, and manage your debts.

Legal Experts

Talk to a divorce attorney to learn more about your legal rights and obligations as you navigate your divorce. Best also recommends seeking help from a mediator/conflict manager to resolve disputes that arise during a gray divorce. 

"Mediation is a confidential, blame-free, nonjudgmental way to be heard, to listen to the underlying needs, and to try to design a way forward that works for both parties and their circles of influence," she explains. "If you decide being apart is best, you can work together with a mediator to decide how to do that."

Support Groups

Look in your area or check online for a divorce support group . You might join a more general group or one that is specifically geared toward older adults. This can be a great way to learn from others, gain validation, and build a sense of community with people who have similar experiences.

Online Resources

You may also find it helpful to explore online articles, forums, and organizations that offer information and advice regarding gray divorce. Reading stories about other people's experiences can be a helpful way to learn from the lived experiences of others who have been in the same place as you.

U.S. Census Bureau. Love and loss among older adults .

Brown SL, Lin IF. The graying of divorce: A half century of change . Cong Z, ed. The Journals of Gerontology: Series B . 2022;77(9):1710-1720. doi:10.1093/geronb/gbac057

Pew Research Center. Led by baby boomers, divorce rates climb for America's 50+ population .

Pew Research Center. Led by Baby Boomers, divorce rates climb for America's 50+ population .

Gravningen K, Mitchell KR, Wellings K, et al. Reported reasons for breakdown of marriage and cohabitation in Britain: Findings from the third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) . PLoS One . 2017;12(3):e0174129. doi:10.1371/journal.pone.0174129

Baker LR, McNulty JK, VanderDrift LE. Expectations for future relationship satisfaction: Unique sources and critical implications for commitment .  J Exp Psychol Gen . 2017;146(5):700-721. doi:10.1037/xge0000299

Brown SL, Wright MR. Divorce attitudes among older adults: Two decades of change . J Fam Issues . 2019;40(8):1018-1037. doi:10.1177/0192513X19832936

Lin IF, Brown SL, Hammersmith AM. Marital biography, social security receipt, and poverty . Res Aging . 2017;39(1):86-110. doi:10.1177/0164027516656139

Lin IF, Brown SL. The economic consequences of gray divorce for women and men . Carr DS, ed. The Journals of Gerontology: Series B . 2021;76(10):2073-2085. doi:10.1093/geronb/gbaa157

National Academies of Sciences, Engineering, and Medicine. Social Isolation and Loneliness in Older Adults: Opportunities for the Health Care System . Washington, DC: The National Academies Press. 2020. doi:10.17226/25663

Donovan NJ, Blazer D. Social isolation and loneliness in older adults: Review and commentary of a National Academies Report . Am J Geriatr Psychiatry . 2020;28(12):1233-1244. doi:10.1016/j.jagp.2020.08.005

Jia H, Lubetkin EI. Life expectancy and active life expectancy by marital status among older U.S. adults: Results from the U.S. Medicare Health Outcome Survey (HOS) . SSM Popul Health . 2020;12:100642. doi:10.1016/j.ssmph.2020.100642

Robles TF. Marital quality and health: Implications for marriage in the 21st century . Curr Dir Psychol Sci . 2014;23(6):427-432. doi:10.1177/0963721414549043

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

• Election 2024
• Entertainment
• Newsletters
• Photography
• Personal Finance
• AP Investigations
• AP Buyline Personal Finance
• AP Buyline Shopping
• Press Releases
• Israel-Hamas War
• Russia-Ukraine War
• Global elections
• Asia Pacific
• Latin America
• Middle East
• Election Results
• Delegate Tracker
• AP & Elections
• Auto Racing
• 2024 Paris Olympic Games
• Movie reviews
• Book reviews
• Personal finance
• Financial Markets
• Business Highlights
• Financial wellness
• Artificial Intelligence
• Social Media

Rory McIlroy files for divorce from his wife of 7 years ahead of the PGA Championship

Rory McIlroy, of Northern Ireland, holds the trophy after winning the Wells Fargo Championship golf tournament at the Quail Hollow Club Sunday, May 12, 2024, in Charlotte, N.C. (AP Photo/Chris Carlson)

Rory McIlroy, of Northern Ireland, celebrates after an eagle on the 15th hole from the bunker during the final round of the Wells Fargo Championship golf tournament at the Quail Hollow Club Sunday, May 12, 2024, in Charlotte, N.C. (AP Photo/Chris Carlson)

Rory McIlroy, of Northern Ireland, celebrates after winning the Wells Fargo Championship golf tournament at the Quail Hollow Club Sunday, May 12, 2024, in Charlotte, N.C. (AP Photo/Chris Carlson)

• Copy Link copied

LOUISVILLE, Ky. (AP) — Rory McIlroy has filed for divorce after seven years of marriage, according to court records in Palm Beach County, Florida, a stunning development going into the PGA Championship .

McIlroy and his wife, Erica Stoll, had a storybook meeting during the Ryder Cup in 2012, began dating two years later and were married in 2017 . They have one daughter, Poppy, born in September 2020.

TMZ first reported on the filing, which was made Monday.

The petition for divorce described the marriage as irretrievably broken and asked that a prenuptial agreement signed about a month before their April 21, 2017, wedding be validated and enforced. The prenuptial agreement was sealed.

McIlroy’s attorney was listed as Thomas Sasser, the same attorney who represented Tiger Woods when his wife divorced him in 2010.

“Rory McIlroy’s communications team confirmed today that a divorce has been filed. They stressed Rory’s desire to ensure this difficult time is as respectful and amicable as possible,” said a statement from his manager, Sean O’Flaherty.

He said there would be no further comment.

McIlroy arrived at Valhalla on Tuesday. He has gone 10 years since winning a major, the last one at Valhalla in 2014 for the PGA Championship. His pre-tournament news conference was scheduled for Wednesday.

McIlroy and Stoll met under unusual circumstances. She worked for the PGA of America in 2012 during the Ryder Cup at Medinah in the Chicago suburbs, where McIlroy nearly missed his Sunday singles match because he said he forgot he was in the Central time zone.

Stoll arranged for a police escort to Medinah, and McIlroy barely arrived in time. He won his match over Keegan Bradley as Europe rallied to win.

McIlroy was dating tennis star Caroline Wozniacki at the time. They were engaged just over a year later, but then McIlroy abruptly broke it off over the phone.

He and Stoll began dating later that year. They were engaged in 2015.

McIlroy filed for the divorce a day after he won the Wells Fargo Championship in Charlotte, North Carolina, his second straight PGA Tour win and the 26th of his career. Asked if he planned to go straight to Valhalla on Sunday night, McIlroy said, “I’ll probably go home and just sort of reset, then head up to Louisville tomorrow night or Tuesday morning.”

The divorce filing comes amid chaos in golf created by the launch of Saudi-funded LIV Golf. McIlroy has been a central figure over the last two years, harshly criticizing LIV and then changing his views and pushing for some form of reunification.

He resigned from the PGA Tour board last November, then was involved in a plan to rejoin the board by replacing Webb Simpson. That move was met by resistance from other player directors. Instead, McIlroy was appointed to a committee that is negotiating with the Public Investment Fund of Saudi Arabia over potentially becoming a minority investor.

Associated Press Writer Terry Spencer in Palm Beach, Florida, contributed to this report.

AP golf: https://apnews.com/hub/golf

High-profile TV shrink wife secretly bugged $4M Greenwich mansion to spy on ex’s calls before ugly divorce: lawsuit

Marital mind games in a wealthy Greenwich, Conn., divorce have sparked business intrigue in the Big Apple.

A high-profile psychologist in the tony town who has appeared on CNN, CBS, and Fox News, allegedly bugged her now ex-husband’s room while he worked from home, then talked about getting a “big check” from the CEO of his Manhattan real estate company, according to court papers.

The alleged surreptitious recordings have prompted Brad Zackson’s company, Dynamic Star, and its CEO Gary Segal, to sue Judith Zackson in Manhattan Supreme Court, claiming Zackson engaged in “illegal eavesdropping” and misconduct by recording Brad’s business calls.

But Judith denied the allegations, calling them meritless.

Judith and Brad began living in separate rooms in their $4 million, six-bedroom, 7.5-bath, 6,727-square-foot Greenwich mansion in 2020, as their marriage began to break down.

Judith — an expert in anxiety, depression and attention deficit disorder who is worth more than $4.4 million — is accused of secretly hiding recording devices in Brad’s rooms in 2021 and 2022, and even placing one on his vehicle.

“Dr. Zackson cynically and secretly invaded Dynamic as a ploy in defense of a divorce action in Connecticut . . . in an attempt to extort money from Dynamic or Gary,” Dynamic claims in court papers.

Dynamic Star’s business deals include Fordham Landing in the University Heights section of The Bronx, a giant, $2.5 billion mixed-use development on the Harlem River.

Brad allegedly discovered one of the recorders in April 2022, when he noticed a flashing red light near the bathroom ceiling.

He filed for divorce the following month, records show.

Their split has yet to be finalized.

In a successful bid to have Judith pay his legal fees in their divorce, Brad Zackson claimed to be $9 million in debt, $5.7 million of which is owed to Segal, who gives him $40,000 a month, according to a Connecticut Superior Court document.

Brad maintained he’s not paid taxes since 2012, and the court noted in the document his claim that Segal also had financial difficulties — because Dynamic’s properties were “underwater, and they could not refinance the debt due to the market.”

Judith — who owns three limited liability companies and keeps $100,000 cash in a safe deposit box, according to court records — admitted to the espionage during the divorce proceedings, and even quipped that she hoped to get a “a big check from Uncle Gary,” Dynamic claimed.

“The scope of these transgressions is unknown. The number of recordings is unknown. The location of them is unknown. The disclosure or use of them is unknown,” according to the lawsuit.

She recorded calls between Brad, Dynamic’s co-founder and director of development, and other senior executives; attorneys; New York City officials, prospective investors and others, Dynamic said.

“Dr. Zackson has been spying on Brad for years which means that Dr. Zackson has been spying on [Dynamic] and its business affairs for years,” the filing claims.

Dynamic “seeks to remove the threat to its existence,” it said in the litigation, which demands all recordings be turned over.

“Damages alone will not protect Dynamic. The business and real estate projects are or likely will be valued in the hundreds of millions of dollars, well beyond the ability of Dr. Zackson to answer in money damages. There is no way to calculate the damage that she can cause to interpersonal relationships and business opportunities,” Dynamic contended.

“Dynamic Star and Ms Zackson have no financial relationship. Dynamic Star is fighting an ongoing vindictive, ugly campaign being waged by an ex-wife of a principal. We are confident court will see the truth,” a company spokesman said.

Judith Zackson wants to “protect herself from her spouse,” according to her attorney.

In May 2022 Brad Zackson was caught with a firearm, despite a prior felony conviction making possession of the weapon illegal, according to Connecticut criminal records and a report.

He also twice violated an order of protection in 2022, leading to further arrests, Connecticut records show.

New York State records show Brad Zackson was convicted of robbery and criminal possession of a weapon in Nassau County in 1983.

“Mr. Zackson has repeatedly violated a restraining order issued because of his abusive and threatening behavior, leading to two additional arrests,” her attorney, Peter Zeidenberg, said in a statement.

A spokesman for Brad Zackson did not immediately respond to questions about the arrests.

• Find a Lawyer
• Ask a Lawyer
• Research the Law
• Law Schools
• Laws & Regs
• Newsletters
• Justia Connect
• Pro Membership
• Basic Membership
• Justia Lawyer Directory
• Platinum Placements
• Gold Placements
• Justia Elevate
• Justia Amplify
• PPC Management
• Google Business Profile
• Social Media
• Justia Onward Blog

Q: How much will it take to get divorce papers through email or regular mail

• Louisville, KY
• Licensed in Kentucky
• (502) 589-6916
• Email Lawyer
• View Website

A: Just whatever they cost plus the shipping if you’re seeking fill in the blank legal documents. It will then cost $16–$18 to have them served by mail upon the opposing party.

Justia Ask a Lawyer is a forum for consumers to get answers to basic legal questions. Any information sent through Justia Ask a Lawyer is not secure and is done so on a non-confidential basis only.

The use of this website to ask questions or receive answers does not create an attorney–client relationship between you and Justia, or between you and any attorney who receives your information or responds to your questions, nor is it intended to create such a relationship. Additionally, no responses on this forum constitute legal advice, which must be tailored to the specific circumstances of each case. You should not act upon information provided in Justia Ask a Lawyer without seeking professional counsel from an attorney admitted or authorized to practice in your jurisdiction. Justia assumes no responsibility to any person who relies on information contained on or received through this site and disclaims all liability in respect to such information.

Justia cannot guarantee that the information on this website (including any legal information provided by an attorney through this service) is accurate, complete, or up-to-date. While we intend to make every attempt to keep the information on this site current, the owners of and contributors to this site make no claims, promises or guarantees about the accuracy, completeness or adequacy of the information contained in or linked to from this site.

• Bankruptcy Lawyers
• Business Lawyers
• Criminal Lawyers
• Employment Lawyers
• Estate Planning Lawyers
• Family Lawyers
• Personal Injury Lawyers
• Estate Planning
• Personal Injury
• Business Formation
• Business Operations
• Intellectual Property
• International Trade
• Real Estate
• Financial Aid
• Course Outlines
• Law Journals
• US Constitution
• Regulations
• Supreme Court
• Circuit Courts
• District Courts
• Dockets & Filings
• State Constitutions
• State Codes
• State Case Law
• Legal Blogs
• Business Forms
• Product Recalls
• Justia Connect Membership
• Justia Premium Placements
• Justia Elevate (SEO, Websites)
• Justia Amplify (PPC, GBP)
• Testimonials

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Front Psychol

When Love Hurts – Mental and Physical Health Among Recently Divorced Danes

Associated data.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The last decades of research have consistently found strong associations between divorce and adverse health outcomes among adults. However, limitations of a majority of this research include (a) lack of “real-time” research, i.e., research employing data collected very shortly after juridical divorce where little or no separation periods have been effectuated, (b) research employing thoroughly validated and population-normed measures against which study results can be compared, and (c) research including a comprehensive array of previously researched sociodemographic- and divorce-related variables. The current cross-sectional study, including 1,856 recently divorced Danes, was designed to bridge these important gaps in the literature. Mental and physical health were measured using the Short Form 36 (SF-36)-2. Analyses included correlational analyses, t- test comparisons, and hierarchical multiple regression analyses. The study found that the health-related quality of life of Danish divorcees was significantly worse than the comparative background population immediately following divorce. Across gender, higher levels of divorce conflict were found to predict worse mental health, and worse physical health for women, even when controlling for other socio-demographic variables and divorce characteristics. Among men, lower age and higher income predicted better physical health, while more children, more previous divorces, participant divorce initiation, new partner status, and lower levels of divorce conflict predicted better mental health. Among women, higher income, fewer previous divorces, new partner status, and lower levels of divorce conflict predicted better physical health while higher income, participant divorce initiation, new partner status, and lower levels of divorce conflict predicted better mental health. The findings underscore the relevance of providing assistance to divorcees who experience higher levels of divorce conflict immediately following divorce, in seeking to reduce potential long-term negative health effects of divorce.

Introduction

The last 20 years of research have consistently found strong associations between divorce and adverse health outcomes among adults. Generally, divorcees report poorer physical and mental health and more symptoms of stress, anxiety, depression, and social isolation than the general population ( Amato, 2000 , 2010 ; Kessing et al., 2003 ; Hewitt and Turrell, 2011 ; Hewitt et al., 2012 ; Hald et al., 2020b ). Furthermore, divorce is associated with more frequent hospitalization ( Nielsen et al., 2014 ), substance use ( Waite et al., 2009 ), higher suicide rates ( Kposowa, 2000 ), lower levels of psychological well-being ( Bracke et al., 2010 ; Colman et al., 2012 ), and greater overall mortality risk ( Kposowa, 2000 ; Sbarra and Nietert, 2009 ). However, four limitations relate to a significant part of this research.

First, often studies include only one or two health-related outcomes per study (e.g., stress and/or depression) (e.g., Lindström, 2009 ; Hewitt et al., 2012 ; Knöpfli et al., 2016 ). While this is important in mapping out specific effects of divorce, it limits the ability to gain insight into more comprehensive physical and mental health profiles among divorce populations. These could be important for more accurate and comprehensive assessments and profiling of the effects of divorce on health. Second, most countries in the world require separation periods before juridical divorce is granted. This means that divorce studies able to employ “real-time” research are scarce and there has been a call for such studies (e.g., Thuen, 2001 ; Cipric et al., 2020 ). The concept of “real-time” research usually refers to the collection of data among divorcees with little or no separation periods before formal juridical divorce ( Hald et al., 2020a ). When studying health effects of divorce, this may be especially important since many health outcomes related to divorce may be sensitive to a “time heals effect,” whereby negative effects of divorce naturally decline over time ( Amato, 2010 ; Sander et al., 2020 ). Therefore, current research on adverse health effects of divorce may, in fact, underestimate negative health effects of divorce as data have often been collected after a divorce that was preceded by significant periods of separation and thus is likely to be subject to the “time heals effect” ( Sander et al., 2020 ). Third, studies employing thoroughly validated and population-normed measures are few. Validated measures are needed for accurate assessment of the health outcomes studied. However, these assessments may benefit from contextualization by having background population norms against which the results can be directly compared. This allows for more direct insights into the degree to which divorcees may differ from background population norms and thus the relative impact of the divorce on health. Fourth, studies are needed that include a more comprehensive array of previously researched sociodemographic- and divorce-related predictor or explanatory variables of mental and physical health. This would allow for a more thorough assessment of the individual and combined effect of these variables on mental and physical health. The current study was designed to bridge these four important gaps in health research related to divorce.

Divorce theory and divorce research suggest that there are sociodemographic variables and divorce-related characteristics that may moderate the effects of divorce on mental and physical health. Theoretically, Amato’s Divorce-Stress-Readjustment perspective (DSR; Amato, 2000 ) suggests that adverse effects of divorce depend on a number of risk and protective factors experienced during and following the divorce process. Examples of risk factors include lower standards of living, loss of benefits associated with marriage, and conflict with the former partner, whereas examples of protective factors include having a new romantic partner, adequate income, and holding positive views about the divorce. According to the DSR, it is the interplay between risk and protective factors that may be important in determining the effects of divorce on mental and physical health ( Amato, 2010 ).

From an empirical perspective, studies suggest that lower socioeconomic status, being unemployed, lower levels of education, and lower family income ( Barrett, 2000 ; Simon, 2002 ; Symoens et al., 2013b ) are associated with lower mental and physical health following divorce. In addition, younger age has been found to be associated with lower mental health following divorce ( Bulloch et al., 2017 ). In relation to divorce characteristics, mutual divorce agreement initiation ( Weiss, 1976 ; Gray and Silver, 1990 ; Wang and Amato, 2000 ; Sweeney and Horwitz, 2001 ; Sakraida, 2008 ; Cohen and Finzi-Dottan, 2012 ; Symoens et al., 2013a ), having a new partner ( Mastekaasa, 1994 ; Amato, 2000 ; Øygard, 2004 ; Blekesaune, 2008 ; Kulik and Heine-Cohen, 2011 ; Symoens et al., 2013b ; Symoens et al., 2014 ) and lower levels of divorce-related conflict ( Symoens et al., 2014 ; Petren et al., 2017 ) have been found to be associated with better mental and physical health. Both empirically and from an applied point of view, divorce conflict has been found to adversely affect or accelerate declines in mental health among divorcees. While the cross-sectional nature of the current study does not allow for investigation of the impact of divorce conflict on mental health over time, it does allow for an independent assessment of the explanatory value of divorce conflict on mental health, accounting for basic sociodemographic variables and other divorce-related characteristics. Compared with previous research, this allows for a more thorough and “independent” investigation of divorce conflict on mental health immediately following divorce.

The current study took place in Denmark, providing a unique perspective on divorce and divorce-related processes. First, in Denmark, there is high societal acceptance of divorce ( Uggla and Andersson, 2018 ), and in general, divorce is not associated with societal stigma, as it is in many other parts of the world. Second, Denmark is a country with high levels of equality, both in terms of gender equality ( European Institute for Gender Equality, 2018 ) and income equality ( OECD, 2018 ). As such, Denmark offers a unique context in which to study whether sociodemographic and divorce-related factors predict post-divorce mental and physical health.

Based on the above, the current study sought to investigate mental and physical health among recently divorced Danes using a well-known, comprehensive, and population-normed mental and physical health measure. Further, the study sought to examine the explanatory value of a comprehensive array of previously identified sociodemographic variables and divorce-related characteristics on overall mental and physical health. Finally, the study sought to compare overall mental and physical health to relevant population norms. Accordingly, the following two research questions and one study hypothesis guided the study investigation:

• RQ1: What is the mental and physical health among recently divorced individuals and how does it compare to population norms?
• RQ2: What is the explanatory value of sociodemographic variables (i.e., age, number of children, income, education) and divorce-related characteristics (i.e., marriage duration, number of previous divorces, divorce initiator status, new partner status, and divorce conflict) on overall mental and physical health among recently divorced individuals?
• H1: Divorce conflict will significantly add to the explanatory value of mental health after accounting for basic sociodemographic variables (i.e., age, number of children, income, education) and divorce-related characteristics (i.e., marriage duration, number of previous divorces, divorce initiator status, and new partner status).

Materials and Methods

Participants.

The study sample comprised 1,856 participants of which 66% were women. The average age of women was 44.65 years ( SD = 8.34), while for men, it was 46.66 years ( SD = 9.31). The majority of participants had at least a medium educational level and earned at least the national average salary (see Table 1 ). The majority of the sample (88.3%) were parents, with an average of 1.88 ( SD = 0.99) children per participant. The average marriage duration for men was 12.22 years ( SD = 8.11) and for women 13.0 ( SD = 7.98), and for approximately 88% of the sample, this was their first divorce. A majority of women (52%) reported to have initiated the divorce, with 29% of men reporting to be divorce initiators. The majority of both male and female participants did not have new partners following their divorce (65% men, 64% women). The mean legal divorce duration before survey completion was 4.47 days ( SD = 6.97) for men and 5.23 ( SD = 7.66) days for women. Of note, there were some gender differences in sociodemographic and divorce-related characteristics. Specifically, compared to men, women were younger, had been married slightly longer, were more highly educated, earned less than men, had initiated the divorce more often, and had a different partner status than men [age ( t (1854) = 4.74, p < 0.001); duration of marriage ( t (1854) = −1.972, p = 0.049); education (χ 2 = 32.61, p < 0.001); income (χ 2 = 107.41, p < 0.001); initiator status (χ 2 = 90.50, p < 0.001); new partner (χ 2 = 14.82, p = 0.002)].

Participant demographics ( N = 1,856).

Data on all people who divorced in Denmark during the study period were obtained from Statistics Denmark and compared to the study sample. The study sample was found to be representative in terms of age, income, and marriage duration ( p > 0.05). There were statistically significant differences between participants and the comparison population in terms of gender (more women participated: χ 2 = 208.45, p < 0.001), educational attainment (study participants were more highly educated: χ 2 = 1135.23, p < 0.001), and the number of previous divorces [participants had on average fewer previous divorces than the average Danish divorcee: t (1855) = −8.47, p < 0.001].

During the study period (January 2016 to January 2018), those seeking divorce in Denmark initiated formal legal divorce and separation procedures by submitting an application to the Danish State Administration (DSA). Legal divorce was granted immediately when there was a mutual agreement to the marital dissolution. However, if there was disagreement regarding the divorce itself or its terms, a 6-month separation period was instituted, after which divorce was granted even in the absence of mutual agreement. The DSA reports that approximately 30% of couples underwent the 6-month separation period. The average processing time required by the DSA to issue divorce decrees was 2–3 weeks.

Invitations to the present study were sent by the DSA along with the divorce decree. The invitation letter described the 12-month Randomized Controlled Trial intervention study entitled “Cooperation after Divorce” that sought to investigate the effects of a digital intervention platform called “Cooperation after Divorce (CAD)” on divorcees’ mental and physical health. As the DSA sent out invitations, we were unable to send re-invitations to those who did not respond to the initial invitation sent out by the DSA. Those who completed the baseline survey received invitations from the intervention platform to complete surveys at 3, 6, and 12 months; for each of these time points, two reminder e-mails were sent out, one after 3 days and one after 14 days, if no response had been provided.

Cooperation after Divorce covers three main areas: (1) the divorce, (2) children, and (3) cooperation following divorce, employing 17 learning modules delivered through an online platform. This paper reports only the baseline results of the study, therefore, please also see Hald et al. (2020a) for a more thorough description of the CAD platform. The letter also described the procedure for participation, which consisted of clicking on a web-link in the invitation letter, provide informed consent, and respond to the baseline questionnaire anonymously. The research received approval from the Danish Data Protection Agency and was exempt from further ethical evaluations following the rules and regulations as set forth by the Scientific Ethical Committees of Denmark.

The exact response rate is not possible to report because the DSA could not provide the precise number of study invitations sent during the study period. There were 32,487 legal divorces in Denmark during the RCT enrollment period; however, it is unknown whether all individuals who divorced received an invitation along with their divorce decree. In total, 1,882 people began the study and due to impossible or invalid responses, 26 were excluded (i.e., those who did not report gender, reported to be married less than 1 day, or to have married the same year as they were born). Thus, 1,856 participants were included in the final analytical study sample.

Sociodemographic Variables

(a) Age at divorce was measured in years and months. (b) Sexual identity was determined by answering: “Are you a man or a woman?” with the response options: 1 = “Man” 2 = “Woman.” (c) Education level was assessed by answering: “What is the highest education you have completed?” with the following response options: 1 = “low level of education” (e.g., primary school, high school, business high school, vocational education), 2 = “medium level of education” (e.g., medium-length tertiary education, bachelor’s degree), and 3 = “high level of education” (e.g., master’s degree or higher). (d) Income was measured with the question “What is your monthly income before tax?” in Danish Crowns (1 USD = 6.35 DKK). The response options were: 1 = “Below 10,000DKK,” 2 = “10–20,000DKK,” 3 = “20–30,000DKK,” 4 = “30–40,000DKK,” 5 = “40–50,000DKK,” 6 = “50–60,000DKK,” 7 = “60–70,000DKK,” 8 = “70–80,000DKK,” 9 = “More than 80,000DKK.” These categories were reduced for descriptive purposes for Table 1 so that 1–3 = “Below average,” 2–4 = “Average,” 5+= “Above average”; however, in all analyses the original scale was used. (e) The number of children was obtained by asking how many children participants had from 0 to 8.

Divorce-Related Variables

(a) Marriage duration was calculated in years and months from marriage date to divorce date; (b) legal divorce duration was calculated in days from the legal divorce date to survey response date; (c) number of divorces was obtained by asking, “How many time have you divorced?” with response options including 1 = “One time,” 2 = “Two times,” 3 = “Three times,” and 4 = “More than three times”; (e) divorce initiator status was ascertained with the question “Who initiated your divorce” and 1 = “Me,” 2 = “Mostly me,” 3 = “We mutually agreed,” 4 = “Mostly my former spouse,” 5 = “My former spouse,” 6 “Not sure.” Initiator status responses were reduced so that 1–2 = “Me,” 3 = “We mutually agreed,” 4–5 = “My former spouse,” and 6 = “System missing” [only seven participants (0.4%) responded “not sure”]; (f) New partner status was obtained with the question “Do you or your ex have a new partner?” with the following response options: 1 = “Yes, we both have a new partner,” 2 = “No, none of us have a new partner,” 3 = “I have a new partner, but not my ex,” 4 = “My ex has a new partner, but not me”; (g) Divorce conflict was assessed employing the six-item self-report Divorce Conflict Scale (DCS). The DCS measures six dimensions of divorce-related conflict: communication, co-parenting, global assessment of former spouse, negative and pervasive negative exchanges and hostile, insecure emotional environment, and self-perceived conflict ( Hald et al., 2020d ). The internal consistency of the DCS scale was high (α = 0.88).

Physical and Mental Health

The second version of the Short Form 36 (SF-36) Health Assessment was used for the core outcomes of this study. The SF-36 is a 36-item self-report measure that is a widely used instrument to assess health-related quality of life over the previous 4 weeks among general populations and diverse patient groups ( Maruish, 2011 ). The instrument includes the following eight domains which are measured using 35 items: physical functioning, role physical (role participation with physical health problems), bodily pain, general health, vitality, social functioning, role-emotional (role participation with emotional health problems), and mental health. The final item is not included in the domains subscales and addresses self-evaluation health transition. The responses are given with a Likert scale or a yes/no format. Domain scores are reported in 0–100 transformed scores and t -scores that are calculated from the raw scores and higher scores indicate better health status (see Maruish, 2011 for more information). The physical health and mental health summary variables are calculated using all eight health domains based on their relative factor analytical weights. Many language versions of the SF-36 exist and the instrument has been determined to be a valid and reliable instrument for a wide range of populations ( Bjorner et al., 1998 ; Maruish, 2011 ). In this study, all of the eight health scales demonstrated high internal consistency (Cronbach’s α = 0.85–0.93).

Data Analyses

Missing data were less than 5% for all variables in the present paper, which is below the proportion of missingness that may bias results ( Schafer, 1999 ; Bennett, 2001 ; Dong and Peng, 2013 ). Thus, the data were omitted “listwise” in analyses. For the legal divorce duration variable, outliers were changed to missing values using the moderately conservative ± 2.5 times the median absolute deviation (MAD) threshold, as recommended by Leys et al. (2013) . To assess gender differences, sociodemographic and divorce-related characteristics were compared using two-sample t -tests and chi-square tests.

Prior to any other data analyses, a rake weight was constructed and applied to the data. The rake weight was based on gender, education, and previous number of divorces and adjusted for sample representativeness (see section “Participants”). When constructing rake weights, a set of variables for which the distribution is known are chosen, and the statistical program creates weights for each case until the sample distribution aligns with the population for those variables. The resultant weight was applied to the data. Thus, all following data analyses (correlations, comparisons to norms, cut-off score comparison, and hierarchical regressions) reflect results with the weight applied.

One-sample t -tests were employed to compare our sample with the available Danish normative data from the Danish SF-36 user’s manual, which comprise a random population sample of 4,080 Danish adults (52% women) from the SF-36 Health Assessment Danish Manual study (for more information regarding this normative population sample, see also Bjorner et al., 1998 ). For comparisons, the SF-36 0–100 transformed scale scores were used.

Pearson correlation analyses were used for assessing bivariate correlations between variables. Hierarchical multiple regression analyses were used to assess the independent contribution to the explanation of the variance SF-36 physical and mental health summary t -scores. In a first step, age, number of children, income, and education were entered as predictors; in a second step, marriage duration, number of previous divorces, divorce initiator status, and new partner status were entered as predictors. DCS scores were entered as a predictor in the third step. This approach allows for an assessment of the unique contributions of sets of variables (i.e., demographics and divorce-related variables), and specifically, allows for an assessment of the unique contribution of divorce conflict, beyond the contribution of demographics and divorce-related factors.

When compared with Danish normative data, male participants reported lower role physical scores [ t (878) = −9.38, p < 0.001, d = 0.32], worse general health [ t (878) = −5.66, p < 0.001, Cohen’s d = 0.19], lower vitality [ t (875) = −31.88, p < 0.001, Cohen’s d = 1.08], decreased social functioning [ t (878) = −23.51, p < 0.001, Cohen’s d = 0.79], lower role emotional scores [ t (878) = −25.63, p < 0.001, Cohen’s d = 0.87], and worse mental health [ t (875) = −40.79, p < 0.001, Cohen’s d = 1.38], but better physical functioning [ t (879) = 6.66, p < 0.001, Cohen’s d = 0.23] and lower levels of bodily pain [ t (878) = 2.34, p = 0.020, Cohen’s d = 0.08], than the Danish normative male population.

Statistically significant differences were found on the SF-36 domains for women. Compared with the Danish normative female population, female participants reported lower role physical scores [ t (880) = −3.00, p = 0.003, d = 0.10], worse general health [ t (883) = −7.25, p < 0.001, Cohen’s d = 0.24], lower vitality [ t (878) = −33.00, p < 0.001, Cohen’s d = 1.11], lower social functioning scores [ t (880) = −23.19, p < 0.001, Cohen’s d = 0.78], decreased role emotional capacity [ t (880) = −25.86, p < 0.001, Cohen’s d = 0.87], and worse mental health [ t (878) = −38.31, p < 0.001, Cohen’s d = 1.29], but better physical functioning [ t (883) = 9.94, p < 0.001, Cohen’s d = 0.33] and lower levels of bodily pain [ t (880) = 2.92, p = 0.004, Cohen’s d = 0.10] (see Figures 1 , ​ ,2 2 ).

SF-36 physical health domain means compared to normative data.

SF-36 mental health domain means compared to normative data.

Comparison cut-off scores were created such that those with t -scores below 44 were categorized as poor functioning, those with t -scores between 44 and 56 (i.e., average) were categorized as normal functioning, and those with t -scores above 56 (i.e., above) were categorized as superior functioning. The comparisons revealed that for the intervention group, 8.3% fell below the cut-score on physical health (normal = 23.8% and superior = 68%) and 73.6% fell below the cut-score on mental health (normal = 19.9% and superior = 6.6%). Similarly, for the control group, 8.0% fell below the cut-score on physical health (normal = 22.5% and superior = 69.5%) and 72.6% fell below the cut-score on mental health (normal = 23.8% and superior = 3.6%).

Among men, bivariate correlation analyses demonstrated that lower age, higher income, higher education, shorter duration marriages, fewer previous divorces, and lower mental health scores were significantly associated with better physical health ( p < 0.05). Among women, lower age, higher income, higher educational level, fewer previous divorces, new partner status, lower divorce conflict, and lower mental health scores were significantly associated with better physical health ( p < 0.05). Among men, higher age, longer marriage duration, more previous divorces, initiator and new partner status, and lower divorce conflict scores were significantly associated with better mental health, while for women higher income, fewer previous divorces, initiator status, and lower divorce conflict scores were significantly associated with better mental health ( p < 0.05; see also Table 2 ).

Correlations among sociodemographic variables, divorce conflict scale scores, physical and mental health summary scores ( N = 1856, men n = 617, women n = 1239).

Force enter hierarchical multiple regression analyses were used to assess whether socio-demographic and divorce characteristics predicted mental and physical health and whether divorce conflict added to the explanatory value of mental health after controlling for sociodemographic variables and divorce characteristics. The first step of the analyses included the sociodemographic variables of age, number of children, income, and education, and the second step included the divorce-related variables of marriage duration, number of previous divorces, divorce initiator status, and new partner status, while the third and final step included divorce conflict. The variables (Step 3) explained 14.6% of the variance of the physical health summary scores for men [ F (12,875) = 12.33, p < 0.001, R 2 = 0.146] and 8.8% for women [ F (12,878) = 6.96, p < 0.001, R 2 = 0.088]. Among men, lower age and higher income significantly added to the prediction of better physical health ( p < 0.05). Among women, higher income, fewer previous divorces, new partner status, and lower divorce conflict added to the prediction of better physical health ( p < 0.05) (see also Table 3 ).

Multiple regression analyses predicting SF-36 physical health summary t -scores.

For mental health, sociodemographic and divorce-related variables, as well as divorce conflict (Step 3) accounted for 19.3% of the explained variance among men [ F (12,875) = 17.15, p < 0.001, R 2 = 0.193] and 9.9% among women [ F (12,878) = 7.89, p < 0.001, R 2 = 0.099]. Factors that significantly added to the prediction of better mental health for men were more children, more previous divorces, participant divorce initiation, new partner status, and lower divorce conflict, while for women, higher income, participant divorce initiation, new partner status, and lower divorce conflict significantly added to the prediction of better mental health.

Regarding the study hypothesis, among both men and women, divorce conflict was found to significantly add to the explanation of mental health after controlling for basic sociodemographic variables and divorce characteristics (see also Table 4 ).

Multiple regression analyses predicting SF-36 mental health summary t -scores.

Pertaining to research question one, across gender, the study found that the mental health of Danish divorcees was significantly different from and worse than the Danish background population immediately following divorce. Further, across all mental health indicators, the magnitudes of these differences were large [i.e., Cohen’s ( d ) = 0.78–1.38]. The results for physical health were more equivocal. While both male and female divorcees reported better physical functioning in everyday life than the Danish background population, both genders also reported worse general health than the background population immediately following divorce.

The results for mental health corroborate existing research in the field and, notably, the effect sizes here were large, which may mainly reflect the timing of the collection of baseline data. With the unique opportunity to collect data very close to the juridical divorce (on average less than five days from juridical divorce) and the fact that the majority of the sample divorced without any prior separation period, data may have been less subject to a “time heals effect” ( Hald et al., 2020a ). Following Amato (2000) DSR, this means that time has not yet had a chance to mitigate the adverse effects of the divorce. Further, although caution needs to be taken regarding the generalizability of the sample, due to the non-probability sampling process, the results offer some of the first insights into how adverse the impacts of divorce on mental health may be immediately following divorce, using a range of common mental health indicators ( Sander et al., 2020 ).

The equivocal findings concerning physical health among divorcees immediately following divorce, we speculate, mainly have to do with (a) the study sample, (b) the content of questions of the outcome measure, and (c) the timing of measurements. Accordingly, the study sample comprised relatively younger individuals as compared to the background population sample used for comparisons. The majority of the items from the physical health scale include responses to tasks most non-elderly individuals would easily be able to accomplish, but which may prove increasingly difficult with age (e.g., walking one block, dressing and bathing, or lifting or carrying groceries), and this may account for the better physical health among our study sample as compared to the background population. Further, as first suggested by Sander et al. (2020) , when it comes to physical health, a “time hurts” effect may also be at play, whereby physical health is more adversely affected over the course of time following divorce than immediately after the divorce. A causal mechanism may be that reduced mental health increasingly adversely affects physical health over time ( Sander et al., 2020 ). We encourage future studies to further investigate this.

From an applied point of view, across diverse samples and patient groups, better health-related quality of life as measured by the SF-36 has been found to be associated with lower risk of morbidity, mortality, cancer as well as the recurrence of cancer, anxiety, and depressive symptoms (e.g., Lacson et al., 2010 ; Saquib et al., 2011 ; Folker et al., 2019 ). Further, multiple studies have found that worse health-related quality of life as measured by the SF-36 instrument is predictive of higher occurrence of work absence due to sickness, hospitalizations, and higher health care costs among both general populations and across multiple subpopulations (e.g., Lacson et al., 2010 ; Laaksonen et al., 2011 ; Pymont and Butterworth, 2015 ). In conjunction with the study results, especially for mental health, this means that there is sound human and financial reasoning in developing interventions that may help divorcees cope with adverse (mental) health effects of their divorce and, that among many divorcees, the need for help may be especially pronounced immediate following their divorce.

Pertaining to research question 2 and the study hypothesis, it was found that for men, lower age and higher income added to the prediction of better physical health. Among women, higher income, fewer previous divorces, new partner status, and lower levels of divorce conflict added to the prediction of better physical health. For mental health, among men, it was found that more children, more previous divorces, participant divorce initiation, new partner status, and lower levels of divorce conflict added to the prediction of better mental health, while for women, higher income, participant divorce initiation, new partner status, and lower levels of divorce conflict were found to add to better mental health. Moreover, our study hypothesis that divorce conflict would add to the overall prediction of mental health, even when other sociodemographic variables and divorce characteristics were controlled for, was supported. Of note, lower divorce conflict also predicted better physical health for women.

The current study indicates that, already at the time of or close to juridical divorce, higher degrees of divorce conflict are associated with worse mental health, even after accounting for other sociodemographic variables and divorce-related factors. This may not be surprising, given that higher degrees of divorce conflict are likely to negatively interfere with or complicate important decisions and life choices around the time of juridical divorce, like division of property, co-parenting, and child custody. This study finding accentuates the need to focus on divorce conflict levels already at divorce onset ( Hald et al., 2020d ).

Amato’s DSR theory stipulates that the adverse effects of divorce depend on the interplay between risk and protective factors ( Amato, 2010 ). These factors include many of those found in this study to significantly predict both mental and physical health, including income (DSR = economic security, standards of living), new partner status (DSR = having a new partner), and levels of divorce conflict (DSR = conflict with the former partner). Accordingly, the results of this study may be seen as support for Amato’s DSR theory, in that DSR theory views divorce “not as a discrete event, but as a process that unfolds over months and even years” ( Amato, 2010 , p. 10). Moreover, it follows that mental and physical health may already be adversely affected prior to the juridical divorce as a consequence of a prolonged stressful and/or unsatisfactory relationship ( Hald et al., 2020c ). Therefore, the measurements of mental and physical health employed in this study, done immediately after juridical divorce with little or no prior separation period, may “capture” the mental and physical health consequences of this “…process that unfolds over months and even years” ( Amato, 2010 , p. 10).

Notably, even in an egalitarian society such as the Danish one, with a large public sector, a well-developed welfare system, and fewer differences between rich and poor as compared to most other Western countries, higher income still significantly predicted mental well-being among women and physical well-being among both men and women. In accordance with DSR theory, this suggests that income may be a key protective factor against negative divorce-related health impacts ( Leopold, 2018 ), even in highly egalitarian societies. Even more so, income may be more important than level of education, a variable previously found to be related to post-divorce psychological and physical health outcomes ( Cohen and Finzi-Dottan, 2012 ; Perrig-Chiello et al., 2015 ), but which was not found to significantly predict mental or physical well-being in this study.

To the best of our knowledge, this study is the first to include a large sample of very recently divorced individuals, employ standardized and validated mental and physical health measures consisting of multiple health-related indicators with available background population data for direct comparisons, and a multitude of sociodemographical and divorce-related variables previously shown to be associated with health-related outcomes. However, when evaluating the results, the following study limitations should be taken into consideration. The study used a non-probability sample of divorcees and employed self-report measures, which may limit the generalizability of findings. Specifically, the study sample may have consisted of individuals with more conflicts and more mental and physical problems than those who did not participate in the study, as these individuals may have believed that the intervention platform would be particularly helpful to them. Conversely, it may also be that people with more conflicts and more mental and physical problems may have decided not to participate because it may have felt threatening to their sense of self ( Howell and Shepperd, 2012 ; DiBello et al., 2015 ), and thus, are underrepresented in the current study. Additionally, we were unable to determine if both partners in a prior marriage participated in the study, which may affect the assumption of independence of data in the analyses. Further, due to the cross-sectional nature of our data, the results preclude causal inferences. Lastly, while the Danish context is interesting for several reasons, including the minimal societal stigma surrounding divorce and the presence of greater gender and income equality, there is also great acceptance of non-marital cohabitation, such that many couples choose to not get legally married. As the study targeted formerly legally married individuals, individuals who cohabitate were not recruited, and thus, it is unclear whether the study results may generalize to this group of individuals. However, we expect that the relationship dissolution process is similar for married and cohabitating individuals, to the extent that there can be children involved and shared assets (e.g., house). Therefore, we do not have reason to expect that non-married individuals differ from married individuals; however, future research should seek to examine this point.

In conclusion, the study found that the health-related quality of life of Danish divorcees immediately following divorce was significantly different from and worse than the comparative Danish background population. Further, higher levels of divorce conflict predicted worse mental health even after controlling for other sociodemographic variables and divorce characteristics often targeted in research on the interplay between divorce and health. The findings underscore the relevance of providing divorce interventions for divorcees as early as possible following their divorce to improve health-related quality of life.

Data Availability Statement

Ethics statement.

The studies involving human participants were reviewed and approved by the Danish Data Protection Agency and the Regional Scientific Ethical Committee of Copenhagen, Denmark. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

This original research report is part of the doctoral thesis for SS. SS and GH were responsible for the design of the intervention and the study protocol and also responsible for the manuscript writing. JS was responsible for data analysis. CØ and AC were responsible for feedback and editing. All authors have read and approved the final manuscript.

Conflict of Interest

For due diligence, we would like to declare that the University of Copenhagen, Denmark, where the authors work, owns the digital intervention platform “Cooperation after Divorce (CAD)” while two of the co-authors (GH and SS) hold the commercial license and intellectual property rights to the platform through the Company “CAD” (Samarbejde Efter Skilsmisse ApS). The reviewer LL declared a shared affiliation, with no collaboration, with the author to the handling editor at the time of the review.

Acknowledgments

We wish to thank the Egmont Foundation for support with the development of the digital platform “Cooperation After Divorce,” the Danish State Administration for help during the data collection process, and the Carlsberg Foundation for their funding of the research project “When Marriage Fails.”

Funding. This work was financially supported by “The Carlsberg Foundation Distinguished Associate Professor Fellowship” (the last author) under Grant No. CF16-0094.

• Amato P. R. (2000). The consequences of divorce for adults and children. J. Marriage Family 62 1269–1287. 10.1111/j.1741-3737.2000.01269.x [ CrossRef ] [ Google Scholar ]
• Amato P. R. (2010). Research on divorce: continuing trends and new developments. J. Marriage Family 72 650–666. 10.1111/j.1741-3737.2010.00723.x [ CrossRef ] [ Google Scholar ]
• Barrett A. E. (2000). Marital trajectories and mental health. J. Health Soc. Behav. 41 451–464. 10.2307/2676297 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bennett D. A. (2001). How can i deal with missing data in my study? Aus. N. Z. J. Public Health 25 464–469. 10.1111/j.1467-842X.2001.tb00294.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bjorner J. B., Thunedborg K., Kristensen T. S., Modvig J., Bech P. (1998). The danish SF-36 health survey. J. Clin. Epidemiol. 51 991–999. 10.1016/S0895-4356(98)00091-92 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Blekesaune M. (2008). Partnership transitions and mental distress: investigating temporal order. J. Marriage Family 70 879–890. 10.1111/j.1741-3737.2008.00533.x [ CrossRef ] [ Google Scholar ]
• Bracke P. F., Colman E., Symoens S. A. A., Van Praag L. (2010). Divorce, divorce rates, and professional care seeking for mental health problems in europe: a cross-sectional population-based study. BMC Public Health 10 : 224 . 10.1186/1471-2458-10-224 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bulloch A. G. M., Williams J. V. A., Lavorato D. H., Patten S. B. (2017). The depression and marital status relationship is modified by both age and gender. J. Affect. Disord. 223 65–68. 10.1016/j.jad.2017.06.007 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cipric A., Strizzi J. M., Øverup C. S., Lange T., Štulhofer A., Sander S., et al. (2020). Cooperation after divorce: an RCT study of the effects of a digital intervention platform on self-perceived stress. Psychosoc. Intervent. 29 113–123. 10.5093/pi2020a7 [ CrossRef ] [ Google Scholar ]
• Cohen O., Finzi-Dottan R. (2012). Reasons for divorce and mental health following the breakup. J. Divorce Remarriage 53 581–601. 10.1080/10502556.2012.719413 [ CrossRef ] [ Google Scholar ]
• Colman El, Symoens S., Bracke P. (2012). Professional health care use and subjective unmet need for social or emotional problems: a cross-sectional survey of the married and divorced population of flanders. BMC Health Serv. Res. 12 : 420 . 10.1186/1472-6963-12-420 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• DiBello A. M., Neighbors C., Ammar J. (2015). Self-Affirmation theory and cigarette smoking warning images. Add. Behav. 41 87–96. 10.1016/j.addbeh.2014.09.026 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dong Y., Peng C.-Y. J. (2013). Principled missing data methods for researchers. SpringerPlus 2 : 222 . 10.1186/2193-1801-2-222 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• European Institute for Gender Equality (2018). Gender Equality Index. Vilnius: European Institute for Gender Equality. [ Google Scholar ]
• Folker A. P., Hegelund E. R., Mortensen E. L., Wimmelmann C. L., Flensborg-Madsen T. (2019). The association between life satisfaction, vitality, self-rated health, and risk of cancer. Q. Life Res. 28 947–954. 10.1007/s11136-018-2083-2081 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Gray J. D., Silver R. C. (1990). Opposite sides of the same coin: former spouses’ divergent perspectives in coping with their divorce. J. Personal. Soc. Psychol. 59 1180–1191. 10.1037/0022-3514.59.6.1180 [ CrossRef ] [ Google Scholar ]
• Hald G. M., Ciprić A., Øverup C. S., Štulhofer A., Lange T., Sander S., et al. (2020a). Randomized controlled trial study of the effects of an online divorce platform on anxiety, depression, and somatization. J. Family Psychol. 34 740–751. 10.1037/fam0000635 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hald G. M., Ciprić A., Sander S., Strizzi J. M. (2020b). Anxiety, depression and associated factors among recently divorced individuals. J. Mental Health 10.1080/09638237.2020.1755022 [Epub ahead of print]. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hald G. M., Ciprić A., Strizzi J. M., Sander S. (2020c). “Divorce Burnout” among recently divorced individuals. Stress Health 36 457–468. 10.1002/smi.2940 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hald G. M., Strizzi J. M., Ciprić A., Sander S. (2020d). The divorce conflict scale. J. Divorce Remarriage 61 83–104. 10.1080/10502556.2019.1627150 [ CrossRef ] [ Google Scholar ]
• Hewitt B., Turrell G. (2011). Short-term functional health and well-being after marital separation: does initiator status make a difference? Am. J. Epidemiol. 173 1308–1318. 10.1093/aje/kwr007 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hewitt B., Turrell G., Giskes K. (2012). Marital loss, mental health and the role of perceived social support: findings from six waves of an australian population based panel study. J. Epidemiol. Comm. Health 66 308–314. 10.1136/jech.2009.104893 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Howell J. L., Shepperd J. A. (2012). Reducing information avoidance through affirmation. Psychol. Sci. 23 141–145. 10.1177/0956797611424164 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kessing L. V., Agerbo E., Mortensen P. B. (2003). Does the impact of major stressful life events on the risk of developing depression change throughout life? Psychol. Med. 33 1177–1184. 10.1017/S0033291703007852 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Knöpfli B., Cullati S., Courvoisier D. S., Burton-Jeangros C., Perrig-Chiello P. (2016). Marital breakup in later adulthood and self-rated health: a cross-sectional survey in switzerland. Int. J. Public Health 61 357–366. 10.1007/s00038-015-0776-776 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kposowa A. J. (2000). Marital status and suicide in the national longitudinal mortality study. J. Epidemiol. Comm. Health 54 254–261. 10.1136/jech.54.4.254 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kulik L., Heine-Cohen E. (2011). Coping resources, perceived stress and adjustment to divorce among israeli women: assessing effects. J. Soc. Psychol. 151 5–30. 10.1080/00224540903366453 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Laaksonen M., Kääriä S.-A., Leino-Arjas P., Lahelma E. (2011). Different domains of health functioning as predictors of sickness absence – a prospective cohort study. Scand. J. Work Environ. Health 37 213–218. 10.5271/sjweh.3131 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Lacson E., Xu J., Lin S.-F., Dean S. G., Lazarus J. M., Hakim R. M. (2010). A comparison of SF-36 and SF-12 composite scores and subsequent hospitalization and mortality risks in long-term dialysis patients. Clin. J. Am. Soc. Nephrol. 5 252–260. 10.2215/CJN.07231009 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Leopold T. (2018). Gender differences in the consequences of divorce: a study of multiple outcomes. Demography 55 769–797. 10.1007/s13524-018-0667-6 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Leys C., Ley C., Klein O., Bernard P., Licata L. (2013). Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J. Exp. Soc. Psychol. 49 764–766. 10.1016/j.jesp.2013.03.013 [ CrossRef ] [ Google Scholar ]
• Lindström M. (2009). Marital status, social capital, material conditions and self-rated health: a population-based study. Health Policy 93 172–179. 10.1016/j.healthpol.2009.05.010 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Maruish M. E. (2011). User’s Manual for the SF-36v2 Health Survey , 3rd Edn Lincoln: QualityMetric Incorporated. [ Google Scholar ]
• Mastekaasa A. (1994). Psychological well-being and marital dissolution: selection effects? J. Family Issues 15 208–228. 10.1177/0192513X94015002004 [ CrossRef ] [ Google Scholar ]
• Nielsen N. M., Davidsen R. B., Hviid A., Wohlfahrt J. (2014). Divorce and risk of hospital-diagnosed infectious diseases. Scand. J. Public Health 42 705–711. 10.1177/1403494814544398 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• OECD (2018). Income Inequality (indicator). Paris: OECD. [ Google Scholar ]
• Øygard L. (2004). Divorce support groups: what factors are of importance regarding friendship development in the groups? Soc. Work Groups 26 59–77. 10.1300/J009v26n04_05 [ CrossRef ] [ Google Scholar ]
• Perrig-Chiello P., Hutchison S., Morselli D. (2015). Patterns of psychological adaptation to divorce after a long-term marriage. J. Soc. Personal Relationships 32 386–405. 10.1177/0265407514533769 [ CrossRef ] [ Google Scholar ]
• Petren R. E., Ferraro A. J., Davis T. R., Pasley K. (2017). Factors linked with coparenting support and conflict after divorce. J. Divorce Remarriage 58 145–160. 10.1080/10502556.2017.1300013 [ CrossRef ] [ Google Scholar ]
• Pymont C., Butterworth P. (2015). Longitudinal cohort study describing persistent frequent attenders in australian primary healthcare. BMJ Open 5 : e008975 . 10.1136/bmjopen-2015-008975 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sakraida T. J. (2008). Stress and coping of midlife women in divorce transition. Western J. Nurs. Res. 30 869–887. 10.1177/0193945907311324 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sander S., Hald G. M., Cipric A., Øverup C. S., Strizzi J. M., Gad Kjeld S., et al. (2020). A randomised controlled trial study of the effects of a digital divorce platform on mental and physical health. Appl. Psychol. Health Well-Being 12 863–886. 10.1111/aphw.12213 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Saquib N., Pierce J. P., Saquib J., Flatt S. W., Natarajan L., Bardwell W. A., et al. (2011). Poor physical health predicts time to additional breast cancer events and mortality in breast cancer survivors. Psycho-Oncology 20 252–259. 10.1002/pon.1742 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sbarra D. A., Nietert P. J. (2009). Divorce and death: forty years of the charleston heart study. Psychol. Sci. 20 107–113. 10.1111/j.1467-9280.2008.02252.x [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Schafer J. L. (1999). Multiple imputation: a primer. Stat. Methods Med. Res. 8 3–15. 10.1177/096228029900800102 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Simon R. W. (2002). Revisiting the relationships among gender, marital status, and mental health. Am. J. Soc. 107 1065–1096. 10.1086/339225 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sweeney M. M., Horwitz A. V. (2001). Infidelity, initiation, and the emotional climate of divorce: are there implications for mental health? J. Health Soc. Behav. 42 295–309. 10.2307/3090216 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Symoens S., Bastaits K., Mortelmans D., Bracke P. (2013a). Breaking up, breaking hearts? characteristics of the divorce process and well-being after divorce. J. Divorce Remarriage 54 177–196. 10.1080/10502556.2013.773792 [ CrossRef ] [ Google Scholar ]
• Symoens S., Van de Velde S., Colman E., Bracke P. (2013b). Divorce and the multidimensionality of men and women’s mental health: the role of social-relational and socio-economic conditions. Appl. Res. Q. Life 9 197–214. 10.1007/s11482-013-9239-9235 [ CrossRef ] [ Google Scholar ]
• Symoens S., Colman E., Bracke P. (2014). Divorce, conflict, and mental health: how the quality of intimate relationships is linked to post-divorce well-being. J. Appl. Soc. Psychol. 44 220–233. 10.1111/jasp.12215 [ CrossRef ] [ Google Scholar ]
• Thuen F. (2001). Psychiatric symptoms and perceived need for psychiatric care after divorce. J. Divorce Remarriage 34 61–76. 10.1300/J087v34n01_04 [ CrossRef ] [ Google Scholar ]
• Uggla C., Andersson G. (2018). Higher divorce risk when mates are plentiful? evidence from Denmark. Biol. Lett. 14 : 20180475 . 10.1098/rsbl.2018.0475 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Waite L. J., Luo Y., Lewin A. C. (2009). Marital happiness and marital stability: consequences for psychological well-being. Soc. Sci. Res. 38 201–212. 10.1016/j.ssresearch.2008.07.001 [ CrossRef ] [ Google Scholar ]
• Wang H., Amato P. R. (2000). Predictors of divorce adjustment: stressors, resources, and definitions. J. Marriage Family 62 655–668. 10.1111/j.1741-3737.2000.00655.x [ CrossRef ] [ Google Scholar ]
• Weiss R. S. (1976). The emotional impact of marital separation. J. Soc. Issues 32 135–145. 10.1111/j.1540-4560.1976.tb02484.x [ CrossRef ] [ Google Scholar ]

• Search Please fill out this field.
• Manage Your Subscription
• Give a Gift Subscription
• Newsletters
• Sweepstakes
• Entertainment

Rory McIlroy Files for Divorce from Wife Erica Stoll After 7 Years of Marriage

The pro-golfer filed for divorce on May 13 in Palm Beach County, Florida, according to court documents obtained by PEOPLE

Ross Kinnaird/Getty

Rory McIlroy is divorcing wife Erica Stoll after seven years of marriage.

The 35-year-old pro-golfer filed for divorce from Stoll, 36, according to court documents filed in Florida, and obtained by PEOPLE. McIlroy filed the petition to dissolve the marriage on May 13.

Stoll and McIlroy share one daughter, Poppy , who they welcomed in 2020.

McIlroy and Stoll married on April 22, 2017, during a lavish ceremony at Ashford Castle in County Mayo, Ireland. According to E! News , the wedding had very tight security and included several A-list celebrity guests from  Stevie Wonder  to actor  Jamie Dornan .

Over the course of their relationship, Stoll had been a supportive figure for McIlroy at his tournaments, from caddying for him at the 2023 Masters Par 3 contest to cheering him on at the Ryder Cup in Italy.

Stoll, a former employee of the PGA of America, met McIlroy in 2012 at the Ryder Cup where she had been working as a transport official. After McIlroy overslept because of a time zone mixup and nearly missed his tee time, Stoll got him a police escort to the course in Medinah, Illinois.

However, the couple didn't become romantically involved until years later in 2014. McIlroy had been dating tennis player  Caroline Wozniacki  when he first met Stoll.  McIlroy and Wozniacki got engaged  on New Year's Eve in 2013 but  he broke things off a few months later .

McIlory recalled his first time meeting Stoll during an interview on the  Golf Channel .

"Erica that week was always the one that was checking us in and out. She was there at transportation, so she was always in the car park over there. But yeah, it's still cool to look around and think about that week, and obviously everything that's happened since then. It's pretty cool," he said.

Never miss a story — sign up for  PEOPLE's free daily newsletter  to stay up-to-date on the best of what PEOPLE has to offer, from juicy celebrity news to compelling human interest stories.

Stoll and McIlroy officially started dating in late 2014, but kept their relationship quiet and didn't make many public appearances as a couple at the start.

In May 2015, about six months into dating, McIlroy  spoke to the  Times of London  about his relationship with Stoll. "I am very happy in my love life. We haven't really been putting it out there. She is from America, which is why I like to spend time in Palm Beach … The past six or seven months have been really nice. That part of my life is going great," McIlroy said.

Related Articles

2024 Oscars: The Complete Winners List

Oscars: watch emma stone's tearful, chaotic speech and more best moments, cher and boyfriend ae can't stop kissing on pda-filled cannes carpet, ‘evil’ cast dishes on the fourth and final season (exclusive), ‘dead poets society’ turns 35: watch on-set interviews with the late robin williams, patti labelle weighs in on a possible music collab with ‘buddy’ cardi b (exclusive), how jennifer love hewitt's kids are helping with her return to scream queen status (exclusive), how snoop dogg is preparing for ‘the voice’ coaching gig (exclusive), kylie jenner’s exes travis scott and tyga connected to brawl at cannes film festival, remembering morgan spurlock: a look back at the filmmaker’s career, lady gaga rocks car bumper as fashion statement at tour film premiere, travis kelce addresses harrison butker's controversial graduation speech, pat sajak stunned by 'wheel of fortune' contestant's nsfw guess, millie bobby brown and jake bongiovi are married, whoopi goldberg shares promising 'sister act 3' update (exclusive), inside 'furiosa's massive set, chris hemsworth's makeup and more behind-the-scenes secrets, sofia richie and husband elliot grainge welcome first child, morgan spurlock, ‘super size me’ documentary filmmaker, dead at 53, why jennifer love hewitt is 'terrified' to return to 'i know what you did last summer' (exclusive), lady gaga reacts to beyoncé 'telephone' sequel fan theories (exclusive), katie taylor vs. amanda serrano: fighters share why they think they'll win (exclusive), kris jenner addresses scott disick's weight loss after previous 'struggles', the 96th academy awards closed out the 2024 awards season.

The Academy of Motion Picture Arts and Sciences closed out an eventful awards season with the 2024 Oscars ceremony  on Sunday. The 96th annual Academy Awards were handed out live at the Dolby Theatre in Los Angeles, California, during a ceremony hosted by Jimmy Kimmel .

Oppenheimer  and Poor Things dominated the night with the most wins.  Cillian Murphy secured the trophy for Best Actor in a Leading Role, and Emma Stone was crowned Best Actress in a Leading Role. 

Joining them were  Da'Vine Joy Randolph  and  Robert Downey Jr ., who took home their very first Oscars.

So who else won Oscars this year? Check out the full list of the night's big winners -- marked in bold.

Best Picture American Fiction Anatomy of a Fall Barbie The Holdovers Killers of the Flower Moon Maestro Oppenheimer   -- **WINNER! Past Lives Poor Things The Zone of Interest

Actor in a Leading Role Bradley Cooper -  Maestro Colman Domingo -  Rustin Paul Giamatti -  The Holdovers Cillian Murphy -  Oppenheimer  -- **WINNER! Jeffrey Wright -  American Fiction

Actress in a Leading Role Annette Bening -  Nyad Lily Gladstone -  Killers of the Flower Moon Sandra Hüller -  Anatomy of a Fall Carey Mulligan -  Maestro Emma Stone - Poor Things -- **WINNER!

Actor in a Supporting Role Sterling K. Brown -  American Fiction Robert De Niro -  Killers of the Flower Moon Robert Downey Jr. -  Oppenheimer -- **WINNER! Ryan Gosling -  Barbie Mark Ruffalo -  Poor Things

Actress in a Supporting Role Emily Blunt -  Oppenheimer Danielle Brooks -  The Color Purple America Ferrera -  Barbie Jodie Foster -  Nyad Da'Vine Joy Randolph -  The Holdovers  -- **WINNER!

Directing Justine Triet -  Anatomy of a Fall Martin Scorsese -  Killers of the Flower Moon Christopher Nolan -  Oppenheimer  -- **WINNER! Yorgos Lanthimos -  Poor Things Jonathan Glazer -  The Zone of Interest

Writing (Adapted Screenplay) American Fiction -  Cord Jefferson   -- **WINNER! Barbie -  Greta Gerwig & Noah Baumbach Oppenheimer -  Christopher Nolan Poor Things -  Tony McNamara The Zone of Interest -  Jonathan Glazer

Writing (Original Screenplay) Anatomy of a Fall -  Justine Triet and Arthur Harari   -- **WINNER! The Holdovers -  David Hemingson Maestro -  Bradley Cooper & Josh Singer May December -  Screenplay by Samy Burch; Story by Samy Burch & Alex Mechanik Past Lives -  Celine Song

Animated Feature Film The Boy and the Heron  -- **WINNER! Elemental  Nimona  Robot Dreams  Spider-Man: Across the Spider-Verse

Documentary (Feature) Bobi Wine: The People's President The Eternal Memory Four Daughters To Kill a Tiger 20 Days in Mariupol -- **WINNER!

Documentary (Short Subject) The ABCs of Book Banning The Barber of Little Rock Island In Between The Last Repair Shop -- **WINNER! Nǎi Nai and Wài Pó

International Feature Film Io Capitano  - Italy Perfect Days  - Japan Society of the Snow  - Spain The Teachers' Lounge  - Germany The Zone of Interest  - UK -- **WINNER!

Film Editing Anatomy of a Fall The Holdovers Killers of the Flower Moon Oppenheimer -- **WINNER! Poor Things

Cinematography El Conde Killers of the Flower Moon Maestro Oppenheimer  -- **WINNER! Poor Things

Sound The Creator Maestro Mission: Impossible - Dead Reckoning Part One Oppenheimer The Zone of Interest   -- **WINNER!

Music (Original Score) American Fiction Indiana Jones and the Dial of Destiny Killers of the Flower Moon Oppenheimer   -- **WINNER! Poor Things

Music (Original Song) "The Fire Inside" from  Flamin' Hot;  Music and Lyric by Diane Warren "I'm Just Ken" from  Barbie ; Music and Lyric by Mark Ronson and Andrew Wyatt "It Never Went Away" from  American Symphony ; Music and Lyric by Jon Batiste and Dan Wilson "Wahzhazhe (A Song for My People) from  Killers of the Flower Moon ; Music and Lyric by Scott George "What Was I Made For" from  Barbie ; Music and Lyric by Billie Eilish and Finneas O'Connell   -- **WINNER!

Costume Design Barbie Killers of the Flower Moon Napoleon Oppenheimer Poor Things   -- **WINNER!

Makeup and Hairstyling Golda Maestro Oppenheimer Poor Things   -- **WINNER! Society of the Snow

Production Design Barbie Killers of the Flower Moon Napoleon Oppenheimer Poor Things   -- **WINNER!

Visual Effects The Creator Godzilla Minus One -- **WINNER! Guardians of the Galaxy Vol. 3 Mission: Impossible - Dead Reckoning Part One Napoleon

Short Film (Animated) Letter to a Pig Ninety-Five Senses Our Uniform Pachyderme THE WAR IS OVER! Inspired by the Music of John & Yoko   -- **WINNER!

Short Film (Live Action) The After Invincible Knight of Fortune Red, White and Blue The Wonderful Story of Henry Sugar   -- **WINNER!

The  2024 Academy Awards , hosted by Jimmy Kimmel, airs live from the Dolby Theatre in Los Angeles on Sunday, March 10, at 4 p.m. PT/7 p.m. ET on ABC. Follow along at  ETonline.com  for full Oscars coverage, including red carpet arrivals and more.

Updates on Celebrity News, TV, Fashion and More!

RELATED CONTENT:

Oscars 2024: Jimmy Kimmel Pokes Fun at 'Barbie' Snubs in Fun Monologue

Jennifer Lawrence Looks Pretty in Polka Dots at the 2024 Oscars

Mark Ronson Says Amy Winehouse Biopic 'Nailed Her Humor' (Exclusive)

Mark Ronson Promises 'Kenergy Everywhere' During Ryan Gosling's Oscars Performance (Exclusive)

Zendaya Slays at the 2024 Oscars