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. 2022 Mar 14;48(4):1128–1146. doi: 10.1111/jmft.12588

The future of divorce support: Is “digital” enough in presence of conflict?

Ana Ciprić 1,✉, Gert Martin Hald 1, Jenna Marie Strizzi 1, Theis Lange 1, David Austin 2, Søren Sander 1, Camilla Stine Øverup 1
PMCID: PMC9790432  PMID: 35288952

Abstract

Divorce conflict is the main driver of adverse postdivorce health adjustments among divorcing families. Despite the growing potential of online divorce support programs, there is concern that such solutions might not be sufficient to impact health‐related disparities among high‐conflict divorcees. The present study examined the effectiveness of the digital “Cooperation after Divorce” intervention as a function of conflict among 1856 recently divorced Danish residents. Linear mixed‐effect regression modeling suggested that, although higher levels of divorce conflict at judicial divorce predicted worse health outcomes up to 1 year following divorce, the effectiveness of the digital divorce intervention did not vary as a function of the initial level of divorce conflict. Individuals in the intervention group with higher conflict in divorce still reported worse health at 12 months follow‐up than those with lower levels of divorce conflict; however, much lower than the control group.

Keywords: digital intervention, divorce conflict, LME, mental and physical health, RCT

INTRODUCTION

Broadly consistent with most developed nations, nearly 40%–45% of marriages in Denmark end in divorce (Centers for Disease Control and Prevention, 2016; European Commission, 2015; Statistics Denmark‐Divorce, 2020). Divorce has been linked to a number of negative mental and physical health outcomes for the individuals involved (Bracke et al., 2010; Corcoran & Nagar, 2010; Hald, Ciprić, Sander, et al., 2020; Kjeld et al., 2020; Nielsen et al., 2014; Sander, Strizzi, et al., 2020; Sbarra, 2015; Strizzi et al., 2021; Walid & Zaytseva, 2011). The quality of the divorcees' relationship during divorce is suggested to be a critical moderator of postdivorce adjustment (Amato, 2010). The quality of divorcees' postdivorce relationship is determined by a number of factors, including the ability to cooperate in important areas of postdivorce life (e.g., child‐rearing and managing finances), the ability to resolve disagreements effectively, and the general attitude toward the former spouse (Hald et al., 2019). Typically, these factors are included in the measurement of divorce conflict (Bonach, 2005; Hald et al., 2019; Johnston, 1994; Symoens et al., 2014). In this article, we specifically focus on divorce conflict at the time of judicial divorce and its associations with mental and physical health at 1 year post divorce and investigate whether the previously documented effects of the “Cooperation after Divorce” (CAD) digital intervention (Cipric et al., 2020; Hald, Ciprić, Øverup, et al., 2020; Hald, Ciprić, Sander, et al., 2020; Øverup et al., 2020; Sanders, Hald, et al., 2020; Sander, Strizzi, et al., 2020) are influenced by the level of divorce conflict at judicial divorce.

DIVORCE CONFLICT

Up to 80% of divorcees report some degree of conflict with their former spouse (Bonach, 2005; Hutson, 2007; Symoens et al., 2014). High‐conflict divorces constitute approximately 5%–25% of the divorcing population but occupy up to 90% of family court resources (Coates et al., 2004; Neff & Cooper, 2004; Ottosen et al., 2017; Smyth & Moloney, 2017). Although there is no internationally standardized definition of divorce conflict, in this study, we understand high divorce conflict to comprise (1) pervasive negative exchanges and (2) a hostile, insecure, emotional environment (Anderson et al., 2010; Hald et al., 2019; Ottosen et al., 2017). Further, there are three dimensions that characterize divorce conflict and its expression (see also Hald et al., 2019). These include (1) the domain dimension, which concerns disagreements over divorce issues, such as finances or childrearing, (2) the tactical dimension, which concerns the manner in which disagreements are managed and resolved, and (3) the attitudinal dimension, which concerns the degree of hostility, (mis)trust, or negative emotion toward the former spouse (Hald et al., 2019; Johnston, 1994).

More generally, divorce conflict is seen as a risk factor for a host of mental and physical health problems for adults and children. These include distress and reduced well‐being (Amato, 2000, 2010, 2014; Lamela et al., 2016; Sander, Strizzi, et al., 2020; Strizzi et al., 2021; Symoens et al., 2014), and mood and anxiety disorders (Hald, Ciprić, Øverup, et al., 2020; Hald, Ciprić, Sander, et al., 2020; Kalmijn & Monden, 2006; Liu & Chen, 2006; Symoens et al., 2014; Thuen, 2001), as well as reduced physical health in general (Liu & Umberson, 2008; Sander, Strizzi, et al., 1991, 2020). Moreover, it has been suggested that the effects of high conflict divorces on children may lead to negative lifetime effects that are worse than the immediate effects of the divorce itself (Booth & Amato, 2001). This may be due to parental hostility (van Dijk et al., 2020) and impaired coparenting (Lamela et al., 2016; van Dijk et al., 2020), which may detrimentally affect the long‐term psychosocial adjustment of the child (Amato, 2006, 2010; Booth & Amato, 2001; Lansford, 2009; Polak & Saini, 2019; van Dijk et al., 2020).

Although adverse outcomes associated with divorce conflict are well documented, there is a lack of longitudinal research that could help to understand how, and in which way, conflict influences postdivorce mental and physical health trajectories over time, especially in the first year following a judicial divorce. Most of the research to date has examined the influence of divorce conflict on health long after the judicial divorce (Amato, 2000, 2010, 2014; Kalmijn & Monden, 2006; Lamela et al., 2016; Liu & Chen, 2006; Liu & Umberson, 2008; Symoens et al., 2014; Thuen, 2001). This extended time period makes it difficult to identify whether the long‐term poor health outcomes documented may have been a result of long‐term divorce conflict (Amato, 2001; Grych, 2005; Polak & Saini, 2019), the severity of the initial divorce conflict at judicial divorce, or both. Consequently, research that targets divorcees early in the divorce process, as well as prospective methods, are needed to better understand how initial divorce conflict levels at judicial divorce may influence postdivorce health adjustment. Such knowledge would help inform clinicians, policymakers, and public health professionals about the impact of divorce conflict levels at judicial divorce on divorcees' long‐term health, and thus assist with the identification of couples most at risk and determining the extent to which intervention may be effective in modifying negative health trajectories.

DIGITAL INTERVENTION IN DIVORCE

National administrations are increasingly working to provide strategies for reducing conflict and promoting mental health for divorcing families. For example, in many US states, divorce education is mandated as a prerequisite for obtaining judicial divorce (Schramm & Becher, 2020). The most common approaches to divorce education are based on face‐to‐face communication, similar to services such as therapy, counseling, mediation, and parental coordination (Amato, 2014; Neff & Cooper, 2004). Although documented to be effective in improving coparenting and mental health (Bowers et al., 2014; Schramm et al., 2018; Turner et al., 2019), the time and monetary costliness of these programs highlight a growing need for online self‐directed approaches (Bowers et al., 2011; Schramm & Becher, 2020). Indeed, online‐based programs have been shown to be as effective as face‐to‐face approaches in coparenting education (Schramm & McCaulley, 2012). From a public health perspective, one of the most promising digital divorce interventions currently in operation is “Cooperation after Divorce (CAD)”.

The CAD intervention is an entirely online‐based educational platform that comprises 17 digital modules arranged into three overall themes: yourself, children, and coparenting, with each module taking up to 30 min to complete (see Supporting Information 1). The CAD embodies a user activation principle (Sander et al., 2021) such that participants are activated with interactive exercise elements every 3–4 min to ensure user engagement. This also helps to personalize the content by asking users to choose situations or challenges that they recognize from their own lives and subsequently receive advice and feedback based on their choice. After the study completion, all divorcees with children under the age of 18 years are offered to complete the online education free of charge by the Agency of Family Law in Denmark.

Using randomized controlled trial (RCT) design studies, CAD has been shown effective in reducing stress (Cipric et al., 2020), depression, anxiety, somatization (Hald, Ciprić, Øverup, et al., 2020), and hostility (Øverup et al., 2020), as well as improving general mental and physical health post divorce (Sander, Hald, et al., 2020) with the effect generally maintained over the course of the first year following a judicial divorce. However, no research has yet investigated the CAD RCT trial data to determine whether the intervention works equally well across levels of divorce conflict at judicial divorce. There is a concern that the online mode of intervention/help/education might not be effective or sufficient for high conflict divorces. The assumption here is that high conflict divorces may require a more personal and hands‐on approach to effectively reduce the conflict and conflict‐related health sequelae (Schramm & Becher, 2020). Therefore, it is important to investigate whether the severity of divorce conflict influences the effectiveness of online interventions, such as CAD.

PURPOSE OF THE STUDY

The present study investigates the following research questions:

  • Research Question 1: Are divorce conflict levels at the time of judicial divorce associated with stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health during the first year post divorce?

  • Research Question 2: Do the trajectories of stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health over a 1‐year period post divorce vary as a function of divorce conflict levels at the time of judicial divorce?

  • Research Question 3: Do the intervention effects of the CAD digital intervention on stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health over the course of 1 year post divorce vary as a function of divorce conflict levels at the time of judicial divorce? That is, is the intervention more or less effective for participants in the intervention group as a function of divorce conflict levels of juridical divorce?

MATERIALS AND METHODS

Procedure

Data were obtained from a 12‐month (four‐wave) longitudinal RCT study of a digital postdivorce intervention platform “Cooperation after Divorce” (CAD). The study assessed the effects of the CAD intervention on general mental and physical health, self‐perceived stress, anxiety, depression, hostility, and somatization post judicial divorce (see Cipric et al., 2020; Hald, Ciprić, Øverup et al., 2020; Øverup et al., 2020; Sander, Hald, et al., 2020; Sander, Strizzi, et al., 2020). Data collection spanned from January 2016 to January 2018 and was conducted in collaboration with the Danish State Administration (DSA). When individuals received their divorce decree, they were also sent an invitation letter to participate in the present study together with study information and a digital link to the online questionnaire. The DSA did not include the study invitation in all divorce decrees sent out during the data collection period and did not keep a record of the total number of invitations sent out, which precludes an estimation of response rate. For 70% of divorcees in Denmark, judicial divorce is granted within 2–3 weeks of applying for divorce, without any separation period. Participants were randomized to either the intervention group (1031) or the control group (825). This was accomplished by sending invitations to either the intervention or control group alternately during 28 consecutive 2‐week intervals (for a total of 110 weeks). Although uneven allocation ratios occurred, there were no significant differences observed in the odds ratios for belonging to either the intervention or control group. For the uneven allocation ratios, please see Cipric et al. (2020). The baseline assessment was followed by three further survey assessments (at 3, 6, and 12 months post divorce). The study was approved by the Danish Data Protection Agency and was exempt from further ethical evaluations by the Scientific Ethical Committees of Denmark. To read more about the study procedure, please see Cipric et al. (2020), Hald, Ciprić, Øverup, et al. (2020), Øverup et al. (2020), Sanders, Hald, et al. (2020), and Sanders, Strizzi, et al. (2020).

Participants

The criteria for participation in the study were to have Danish citizenship, to be previously married and granted a divorce by the DSA between January 2016 and January 2018, to be able to read and write in the Danish language, and to have access to the Internet. Of 1856 study participants, there were 1239 women and 617 men, with a mean age of approximately 45 years. A total of 89% of the sample reported being parents with, on average, two children per participant. On average, participants had been married for 12.83 (SD = 7.99) years and initiated study participation within 4.62 (SD = 7.2) days of judicial divorce. For 88.1% of the sample, this was their first divorce. For more detailed information on participants' sociodemographic characteristics, see Table 1 and Cipric et al. (2020), Hald, Ciprić, Øverup et al. (2020), Hald, Ciprić, Sander et al. (2020), Sanders, Hald et al. (2020), and Sander, Strizzi et al. (2020).

Table 1.

Participant sociodemographic information (n = 1856)

Variable Control group (n = 825) Intervention group (n = 1031)
Gender (%), women 67.80 66.00
Age (years), M (SD) 45.26 (8.58) 45.37 (8.72)
Number of children, M (SD) 1.88 (1.01) 1.88 (0.96)
Baseline Perceived Stress Scale, M (SD) 19.46 (7.10) 19.52 (7.04)
Baseline Anxiety Scale, M (SD) 0.88 (0.78) 0.91 (0.80)
Baseline Depression Scale, M (SD) 1.46 (0.94) 1.47 (0.94)
Baseline Hostility Scale, M (SD) 0.62 (0.60) 0.66 (0.65)
Baseline Mental Health Scale, M (SD) −1.55 (1.36) −1.56 (1.35)
Baseline Physical Health Scale, M (SD) 0.79 (0.81) 0.79 (0.81)
Divorce Conflict Scale Score, M (SD) 13.70 (4.84) 13.79 (4.99)
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Note: No group differences were detected.

The study sample was representative of the background population of people who divorced in the country during the study period (the data obtained from Statistic Denmark) in terms of age, income, and marriage duration (p > 0.05). However, in an alignment with the expectations that women and higher educated individuals would be more likely to seek treatment for psychological symptoms (Wellstead, 2011), our sample included more female individuals, χ 2(1, n = 1856) = 208.45, p < .001, and more highly educated, χ 2(2, n = 1856) = 1135.23, p < 0.001, individuals, who had divorced fewer times (t (1855) = −8.47, p < 0.001), compared to the background population.

As expected for longitudinal online assessments (Cugelman et al., 2011; Eysenbach, 2005; Geraghty et al., 2013; Lie et al., 2017), the response rate at T2 dropped to 27.9% (n = 541) compared to T1 (n = 1882), although attrition stabilized thereafter (n T3 = 466 and n T4 = 420; see Supporting Information 2). Comparing those who only participated at T1 to those who responded to a follow‐up survey on sociodemographic and health outcome variables, logistic regression showed that those who stayed in the study had slightly higher odds of being older (adjusted odds ratio [AOR] = 0.99, p < 0.01) and of better physical health (AOR = 0.91, p < 0.01), suggesting only a small bias in attrition (see Supporting Information 3).

Measures

Sociodemographic and divorce‐related variables

The following sociodemographic variables included in the present study were assessed: (a) gender 0 = “male” and 1 = “female,” (b) age at divorce (in years), (c) the number of children (number), (d) the number of previous divorces (number), (e) marriage duration (in years from marriage date to judicial divorce date), and (f) judicial divorce duration (in days from judicial divorce date to study initiation date).

Divorce conflict

The degree of divorce conflict was assessed by the 6‐item self‐report Divorce Conflict Scale (DCS) (Hald et al., 2019). The DCS assesses conflict over three facets: (1) the domain dimension (areas of disagreements, e.g., child‐rearing or finances), (2) the tactical dimension (the manner in which disagreements are resolved and managed), and (3) the attitudinal dimension (the general level of trust and hostility related to the former spouse). Therefore, the six scale items included were: “How do you perceive the degree of conflict in connection with your divorce?,” “My former spouse and I are generally good at dealing with conflicts between us,” “During the last three months, communication with my ex has been good,” “My former spouse and I can both participate in important family events without creating a bad atmosphere,” “My former spouse and I have no trouble talking about issues concerning our child/children,” and “I respect my former spouse as a person,” with Liker‐type response options (see Hald et al., 2019). The internal consistency of the scale was high in the present study (Cronbach's alpha = 0.88).

Mental and physical health variables

The level of self‐perceived stress levels was measured by the Danish version of the Perceived Stress Scale (PSS; Eskildsen et al., 2015). The PSS is a 10‐item instrument with a five‐point Likert‐type response scale from 0 (never) to 4 (very often). Higher scores indicate higher self‐perceived stress levels. The instrument had high internal consistency throughout the study (Cronbach's alpha = 0.90–0.92).

Anxiety, depression, and hostility were assessed by the respective subscales from the Danish version of the Symptom Checklist‐90‐Revised (Derogatis, 2009). The anxiety subscale comprises 10 items, depression 13 items, and the hostility subscale comprises 6 items. The assessment is anchored on a five‐point Likert‐type scale with response options from 0 (not at all) to 4 (very much). Higher scores indicate higher symptom severity for all subscales. The measures demonstrated high internal consistency at all time points (Cronbach's alpha = 0.78–0.95).

General mental and physical health was assessed by the physical health and mental health summary variables of the second Danish version of the Short Form 36 (SF‐36) Health Assessment (Bjørner et al., 1997; Maruish, 2011). This self‐report instrument comprises 36 items, representing eight health‐related quality of life domains (Maruish, 2011). The assessment is anchored on either Likert‐type scale response options or yes/no response options. All eight domains (i.e., 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) are used to calculate the physical and mental health summary scores based on their relative factorial weights (see Maruish, 2011). Higher scores indicate better health. All eight health scales had high internal consistency throughout the study (Cronbach's alpha = 0.81–0.93).

Data analyses

Linear mixed‐effect regression modeling (LME) with the lme4 package for R version 3.5.3 was used to investigate the effect of divorce conflict level on the outcomes. A restricted maximum likelihood estimation approach was used to ensure the robustness of the longitudinal estimates and to protect against informative missing patterns (Little, 2013) by not imputing, but using all available information and providing with population parameters that would most likely produce the estimates from the sample data analyzed. This method remains consistent under the weaker assumption of missing at random. We constructed several different models that were then compared using likelihood ratio tests, that allowed us to examine which model fits the data best. Model 0 assumed no effect of conflict at all (conflict was not included in the analyses), Model 1 assumed the main effect of conflict (time invariant; i.e., that conflict levels were linearly associated with health outcomes), Model 2 assumed conflict‐level specific trajectories in health across time (i.e., a conflict × time interaction, i.e., that the rate of change in the outcomes varied as a function of conflict levels), and Model 3 assumed intervention group by conflict‐level specific trajectories across time (i.e., group × conflict × time interaction), allowing for a test of whether the previously established effectiveness of the intervention depends on the conflict level. Analyses for Models 0, 1, and 2 controlled for the intervention effects (i.e., removing the effects of the intervention) to assess the role of the conflict levels on the outcomes for all the participants regardless of group placement.

A comparison of Model 0 and Model 1 allowed for a test of whether divorce conflict levels at the time of judicial divorce associated with stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health during the first year post divorce (RQ1). A comparison of Model 1 and Model 2 allowed for a test of whether the trajectories of stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health over a 1‐year period post divorce vary as a function of divorce conflict levels at the time of judicial divorce (RQ2). A comparison between Model 2 and Model 3 allowed for a test of whether the intervention effects of the CAD digital intervention on stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health over the course of 1 year post divorce vary as a function of divorce conflict levels at the time of judicial divorce (RQ3). For all models, we controlled for gender and the number of children. Divorce conflict and the number of children were entered as continuous variables, while time, intervention group, and gender were entered as categorical variables. Divorce conflict level effects were quantified as mean differences at each time point, whereas a random intercept accounted for individual differences in initial outcome levels (no other random effects were specified). The sizes of mean differences are reported with the Cohen's d effect size estimate.

RESULTS

Generally, when divorce conflict was included in the models (Models 1, 2, and 3), the models had a better fit to data as compared with the baseline model (which did not contain conflict); therefore, suggesting a significant contribution of divorce conflict to health outcomes (see Table 2). However, which of the subsequent models fit best varied by the outcome.

Table 2.

Results for the likelihood ratio tests comparing the three models tested for Divorce Conflict Scale Scores

Outcome Model 0a versus Model 1b Model 1b versus Model 2c Model 2c versus Model 3d
Stress χ 2(13) = 136.59, p < 0.001 χ 2 (16) = 13.10,  p  = 0.004 χ 2(20) = 1.36, p = 0.851
Anxiety χ 2(13) = 92.01, p < 0.001 χ 2 (16) = 14.98,  p  = 0.002 χ 2(20) = 7.59, p = 0.108
Depression χ 2 (13) = 75.12,  p  < 0.001 χ 2(16) = 6.77, p = 0.080 χ 2(20) = 8.11, p = 0.088
Hostility χ 2(13) = 111.57, p < 0.001 χ 2 (16) = 23.40,  p  < 0.001 χ 2(20) = 4.38, p = 0.357
Mental health χ 2 (13) = 55.58,  p  < 0.001 χ 2(16) = 2.99, p = 0.393 χ 2(20) = 6.13, p = 0.190
Physical health χ 2 (13) = 10.90,  p  = 0.001 χ 2(16) = 0.75, p = 0.862 χ 2(20) = 1.96, p = 0.744
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Note: Text in bold denotes the most appropriate model according to the likelihood ratio tests (i.e., a significant test comparing Models 1 and 2 indicates that Model 2 has the best fit to data; a significant test comparing Models 2 and 3 indicates that Model 3 has the best fit to data).

a

Model 0 did not include divorce conflict as a predictor.

b

Model 1 assessed for the (time‐invariant) main effect of divorce conflict.

c

Model 2 assessed for a divorce conflict by time interaction.

d

Model 3 assessed for a divorce conflict by time and intervention interaction.

  • RQ1: Are divorce conflict levels at the time of judicial divorce associated with stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health the first year post judicial divorce?

The likelihood ratio tests suggested that the first‐order model, which assumed a linear association of divorce conflict level with the health outcomes over the first year post judicial divorce, was the most appropriate model for depression and mental and physical health (see Tables 2 and 3), such that higher divorce conflict was consistently associated with higher levels of symptoms of depression and poorer mental and physical health the first year post divorce.

Table 3.

Results for the study outcomes using linear mixed effect modeling for Conflict Scale Scores

Model 1a Model 2b Model 3c
Variable Estimate SE Cohen's d p Estimate SE Cohen's d p Estimate SE Cohen's d p
Stress
Conflict at baseline 0.36 0.03 0.07 <0.001 0.41 0.03 0.08 <0.001 0.39 0.05 0.08 <0.001
Conflict 3 months −0.15 0.05 0.03 0.003 −0.01 0.10 0.00 0.898
Conflict 6 months −0.14 0.05 0.03 0.007 0.09 0.11 0.02 0.408
Conflict 12 months −0.10 0.06 0.02 0.079 −0.05 0.11 0.01 0.682
Anxiety
Conflict at baseline 0.33 0.00 0.06 <0.001 0.04 0.00 0.06 <0.001 0.03 0.01 0.05 <0.001
Conflict 3 months −0.01 0.01 0.02 0.015 −0.01 0.01 0.02 0.273
Conflict 6 months −0.01 0.01 0.02 0.009 −0.01 0.01 0.01 0.418
Conflict 12 months −0.02 0.01 0.03 0.001 −0.03 0.01 0.05 0.009
Depression
Conflict at baseline 0.04 0.00 0.05 <0.001 0.04 0.00 0.06 <0.001 0.03 0.01 0.04 <0.001
Conflict 3 months −0.01 0.01 0.01 0.407 −0.02 0.01 0.03 0.076
Conflict 6 months −0.01 0.01 0.02 0.043 0.00 0.01 0.00 0.938
Conflict 12 months −0.02 0.01 0.02 0.035 −0.03 0.01 0.04 0.036
Hostility
Conflict at baseline 0.03 0.00 0.06 <0.001 0.03 0.00 0.07 <0.001 0.03 0.00 0.07 <0.001
Conflict 3 months −0.01 0.00 −0.03 0.001 0.01 0.01 0.01 0.562
Conflict 6 months −0.01 0.00 −0.03 0.002 −0.01 0.01 0.02 0.236
Conflict 12 months −0.02 0.01 −0.04 <0.001 −0.01 0.01 0.02 0.256
Mental health
Conflict at baseline −0.44 0.06 −0.05 <0.001 −0.47 0.06 −0.05 <0.001 −0.33 0.10 −0.03 0.001
Conflict 3 months 0.04 0.10 0.00 0.687 0.32 0.19 0.03 0.098
Conflict 6 months 0.15 0.10 0.02 0.134 0.14 0.20 0.01 0.484
Conflict 12 months 0.13 0.11 0.01 0.231 0.36 0.22 0.04 0.100
Physical health
Conflict at baseline −0.12 0.04 −0.02 0.001 −0.13 0.04 −0.02 0.001 −0.16 0.06 −0.02 0.007
Conflict 3 months 0.03 0.05 0.01 0.519 0.09 0.10 0.01 0.356
Conflict 6 months 0.01 0.05 0.00 0.813 0.01 0.11 0.00 0.945
Conflict 12 months 0.04 0.06 0.01 0.471 0.07 0.12 0.01 0.541
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Note: Model estimates in bold are the most appropriate model according to the likelihood ratio tests.

a

Model 1 assessed for the main effect of divorce conflict (the estimate is a linear association between conflict level and stress at baseline).

b

Model 2 assessed for a divorce conflict by time interaction (the estimate is a linear association between conflict level and stress at different time points).

c

Model 3 assessed for a divorce conflict by time and intervention interaction (the estimates is a linear association between conflict level and stress at different time points for intervention vs. control group). For ease of readability, we did not include estimates for the covariates.

  • RQ 2: Do divorce conflict levels at the time of judicial divorce moderate trajectories of stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health over a 1‐year period post judicial divorce?

The likelihood ratio tests suggest that the second‐order model, which assumed that conflict level moderates trajectories of the outcome variables over the first year post judicial divorce, was the most appropriate model for stress, anxiety, and hostility (see Tables 2 and 3 and Figure 1), such that those who reported higher levels of divorce conflict experienced a more pronounced decline in symptoms of stress, anxiety, and hostility over time.

Figure 1.

Figure 1

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Study outcome trajectories generated by linear mixed‐effect modelling for Conflict Scale Scores. (A) Stress, (B) anxiety, and (C) hostility. The significant interactions were plotted according to Aiken and West (1991), probing at ±1 SD from the mean (i.e., high and low values for conflict)

  • RQ3: Do divorce conflict levels at the time of judicial divorce moderate the intervention effects of the CAD digital intervention on stress, symptoms of anxiety, depression, general hostility, and overall mental and physical health over the course of one year from judicial divorce?

The likelihood ratio tests suggested that the third‐order model, which assumed that conflict level moderates intervention effects of the CAD digital intervention on the outcome variables over the first year post judicial divorce, was not the most appropriate model for any of the health outcomes (see Tables 2 and 3). This suggests that participants benefited equally from the CAD program in terms of the mental and physical health variables assessed, regardless of the initial conflict level that they reported at the time of divorce.

DISCUSSION

The present study aimed to fill gaps in knowledge of the impact of divorce conflict at judicial divorce on health at 1 year following divorce and, more importantly, to test whether the efficacy of a digital divorce intervention is impacted by the conflict level reported at divorce. Using a 1‐year RCT study of a large sample of Danish divorcees, the study found that, as predicted, the higher the initial divorce conflict, the higher the symptoms of depression and the poorer the mental and physical health in the first year following divorce (RQ1). The study also found that conflict level at judicial divorce moderated the time trajectories for stress, anxiety, and hostility (RQ2), such that those with higher initial divorce conflict at judicial divorce experienced a greater reduction in symptoms of stress, anxiety, and hostility during the first year following a divorce. Lastly, the study found no moderating effects of initial levels of divorce conflict on the efficacy of the CAD intervention (RQ3). This suggests that the previous findings of the effectiveness of the CAD intervention platform on stress, depression, anxiety, and mental and physical health (Cipric et al., 2020; Hald, Ciprić, Øverup, et al., 2020; Øverup et al., 2020; Sanders, Hald, et al., 2020; Sanders, Strizzi, et al., 2020) held true, regardless of the severity of divorce conflict at the time of judicial divorce.

Cross‐sectional research has found that higher levels of initial divorce conflict are associated with higher levels of depression and poorer mental and physical health post divorce (Hald, Ciprić, Sander, et al., 2020; Liu & Chen, 2006; Liu & Umberson, 2008; Sander, Strizzi, et al., 2020; Thuen, 2001). Extending this cross‐sectional research, our longitudinal examinations suggested that higher levels of initial divorce conflict predict more pronounced improvements in symptoms of stress, anxiety, and hostility following the divorce. That is, those with higher divorce conflict at judicial divorce experienced greater improvements in stress, anxiety, and hostility following the CAD intervention (RQ2). It should be noted, however, that these findings could be due to the fact that, compared to the participants who reported lower initial divorce conflict, participants who reported higher divorce conflict initially scored higher on all three psychological outcomes, which may have provided them with more “room” within which to improve. That is, the larger reduction in stress, anxiety, and hostility over time for those who reported higher conflict may partly be explained by the regression to the mean effect stemming from their higher initial stress, anxiety, and hostility scores (Linden, 2013). However, these larger reductions experienced by those with higher initial conflict scores could also be tentatively explained by the temporal proximity of the stressful stimulus (i.e., the high‐conflict divorce). It could be that divorce/separation lessens the intensity, frequency, and/or duration of the interactions between former spouses, thus making their conflict more distal, which can result in decreasing stress, anxiety, and hostility levels over time (Ingram et al., 2007; Jackson & Finney, 2002). This notion is also supported by some research demonstrating that divorce may (also) lead to positive outcomes for some individuals (Ahrons, 1994; Kalmijn & Monden, 2006; Symoens et al., 2014; Waite et al., 2009; Wheaton, 1990). In further support of this contention, Waite and colleagues (2009) found that among those unhappily married, those who divorced experienced significant improvements in psychological well‐being some years later, compared to those who remained in their unhappy marriages. Nevertheless, the impact of high initial conflict in divorce seems to be more time invariant for depression and mental and physical health (RQ1). Depression and declining mental and physical health have previously been linked to unsuccessful adaptation to stressful stimuli, which in this case could be the divorce and related conflict with the former spouse (Ahola et al., 2014; Gilbert et al., 2019; Ingram et al., 2007; Magnusson Hanson et al., 2014; Shirom & Ezrachi, 2003; Tennant, 2002).

One of the most interesting study findings is that the efficacy of the CAD digital intervention program did not vary as a function of divorce conflict (RQ3). That is, the program appears to have the potential to facilitate divorcees' resilience in terms of postdivorce adjustment across different levels of divorce conflict. These findings are aligned with the divorce‐stress‐adjustment theory (DSA; Amato, 2000), which suggests that by supplementing individual coping ability, one could reduce conflict‐induced mental and physical health concerns, regardless of the conflict levels experienced in divorce (Cohen et al., 1997; Mancini et al., 2009). Therefore, public health intervention in divorce, such as CAD, could provide structural support in supplementing individual coping strategies in dealing with high conflict in divorce.

Moreover, opposing the concern that the digital mode of intervention/help might not be effective or sufficient for high conflict divorces and that a more personal and hands‐on approach is needed, the results indicated that the digital intervention could be equally helpful for high as well as moderate or low conflict divorces in ameliorating the potentially negative health impacts of divorce. This may be of policy relevance, as digital interventions are generally less time and resource costly, and thus, may be associated with reduced public spending. Moreover, they have the ability to reach a larger number of divorcing couples experiencing conflict. These factors may be key to its efficacy across conflict levels. Given its relative ease of access and remote (nonpersonal) mode of engagement, some people may be more likely to complete portions of the intervention, especially if they are reluctant to attend face‐to‐face services (for time, costs, or other factors; Schramm & Becher, 2020). Moreover, digital modes have the benefit of creating a natural distance from the target of frustration and conflict (i.e., the former partner). In face‐to‐face settings, former partners may be directly faced with each other and may become defensive (e.g., as they anticipate restatement of blame and escalation of conflict). Such defensiveness may reduce people's ability to constructively engage in the therapeutic session. The distance naturally created by the digital medium may reduce the defensiveness to a point at which people are better able to engage with the therapeutic content and thus, reap the benefits of intervention.

Nevertheless, although intervention effectiveness did not vary as a function of conflict level, it should be noted that those with higher levels of conflict continued to report higher levels of negative health outcomes relative to those with lower levels of conflict. That is, this group of divorcees remain at higher risk of disadvantageous health outcomes. Consequently, it may be that the CAD or similar interventions could be used as a supplement to other services for those experiencing high conflict divorces to further mitigate adverse health effects related to their divorce. For example, in Denmark, many high conflict divorces receive municipal or governmental help to (further) tackle the conflict, in the form of mediation or face‐to‐face counseling with social workers and psychologists. In assessing the preference for e‐mental health interventions, Phillips et al. (2021) documented a clear preference for blended care that includes face‐to‐face contact with a psychotherapist. Therefore, for these cases, the digital intervention may be used as a basis for the counseling (e.g., as “homework” or “prelearning,” which is then discussed and expanded upon during the in‐person counseling sessions). However, due to the previously listed concerns regarding face‐to‐face counseling, remote counseling has been proposed as a good alternative to traditional in‐person approaches (Simon, 2020). The incorporation of a remote counseling feature in the intervention could enable personalization of the therapy for individuals in a psychologically demanding divorce situation. Future research should seek to examine the relative efficacy of the stand‐alone digital intervention relative to stand‐alone face‐to‐face counseling and combined digital intervention and distance counseling for those who experience higher divorce conflict.

Study limitations

Although the current study had significant strengths, including the use of a large RCT sample of newly divorced people undergoing the CAD intervention at judicial divorce, several limitations should be noted. The shortcomings related to the RCT sample have been elaborated in Cipric et al. (2020), Hald, Ciprić, Øverup, et al. (2020), Øverup et al. (2020), Sanders, Hald et al. (2020), and Sanders, Strizzi et al. (2020) and include study attrition, which could increase the chances of selection (into the study) and attrition (from the study) biases (Cugelman et al., 2011; Eysenbach, 2005). That is, people who elected to participate in the study may have differed from those who did not participate on variables that we are unable to assess (see analyses on the representativeness of the sample in the Materials and Methods section). However, in this regard, it should be noted that previous attrition and sample bias (i.e., logistic regression) analyses of the included study sample have shown only a slight overrepresentation of older and physically healthier individuals, which did not seem to affect the sample's overall representativeness (as suggested by its comparison to the general population; Cipric et al., 2020; Hald, Ciprić, Øverup, et al., 2020; Øverup et al., 2020; Sanders, Hald, et al., 2020; Sanders, Strizzi, et al., 2020).

Another study limitation pertains to the fact that divorce conflict was only measured at the study baseline and not subsequently over the course of the first year post judicial divorce. As a result, it is not clear if changes in divorce conflict levels over time, if any, mediates changes in the health outcomes. The study findings are therefore limited to investigations of divorce conflict at the time of judicial divorce and its possible health‐related effects over the first year post divorce only. Therefore, we encourage more longitudinal studies similar to the current one, but where divorce conflict is measured repeatedly (i.e., at judicial divorce and at regular intervals post divorce), and, moreover, that the longitudinal design may extend beyond 1 year post divorce.

Finally, for the methodological feasibility of collecting populational sample in the collaboration with the DSA, the moment of the legal divorce was considered the time of divorce in this study, although we are aware that the divorce process may precede the judicial formalization of divorce.

CONCLUSION

Using a large RCT sample of 1856 recently divorced Danish residents, the study explored the longitudinal associations between the initial divorce conflict levels and stress, depression, anxiety, hostility, and general mental and physical well‐being. Moreover, we examined whether the efficacy of the CAD digital divorce intervention varied as a function of initial divorce conflict. The findings suggest that there is a longitudinal association between the initial level of divorce conflict and health trajectories the first year following divorce, but that the efficacy of the CAD intervention on these health outcomes is not influenced by the level of divorce conflict at judicial divorce. Relevant to both health policy strategies and practitioners, the findings suggest that digital divorce interventions may be useful regardless of the initial level of divorce conflict at judicial divorce.

Supporting information

Supporting information.

Click here for additional data file. (1.4MB, docx)

ACKNOWLEDGMENTS

We wish to thank the Egmont Foundation for support with the development of the digital platform “Cooperation After Divorce” (CAD), 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.” This study was supported by financial support from “The Carlsberg Foundation Distinguished Associate Professor Fellowship” (second author) under Grant No. CF16‐0094.

Ciprić, A. , Hald, G. M. , Strizzi, J. M. , Lange, T. , Austin, D. , Sander, S. , & Øverup, C. S. (2022). The future of divorce support: Is “digital” enough in presence of conflict? Journal of Marital and Family Therapy, 48, 1128–1146. 10.1111/jmft.12588

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