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Article

Children of Parents with a Mental Illness: Predictors of Health-Related Quality of Life and Determinants of Child–Parent Agreement

by
Alina Radicke
1,*,
Claus Barkmann
1,
Bonnie Adema
1,
Anne Daubmann
2,
Karl Wegscheider
2 and
Silke Wiegand-Grefe
1
1
Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
2
Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(2), 379; https://doi.org/10.3390/ijerph18020379
Submission received: 4 December 2020 / Revised: 31 December 2020 / Accepted: 2 January 2021 / Published: 6 January 2021
(This article belongs to the Special Issue Psychological Health of Children with Mentally Ill Parents: Basics-Models-Transmissions-Interventions-Implementation-Health Care)
Versions Notes

Abstract

:
(1) Background: Health-related quality of life (HRQoL) is frequently reduced in children of parents with a mental illness (COPMI). Child self- and parent proxy-ratings vary with raters’ characteristics and facets of HRQoL. This study aimed at analyzing risk and protective factors associated with HRQoL in COPMI, and at examining the magnitude, direction, and predictors of child–parent agreement. (2) Methods: Analyses were based on baseline data of the German CHIMPS (children of parents with a mental illness) project with n = 134 parents diagnosed with mental illness and n = 198 children and adolescents aged 8 to 18 years. (3) Results: Both children and parents reported significantly lower HRQoL than the reference population, particularly for the child’s physical and psychological well-being. Parents’ proxy-report indicated a lower HRQoL than the children’s self-report. Child and parental psychopathology, social support, and the child’s age significantly predicted HRQoL. Interrater agreement was satisfactory and better for observable aspects like physical well-being and school environment. The child’s gender-identity and mental health significantly predicted child–parent agreement. (4) Conclusions: Parental psychopathology significantly reduces children’s HRQoL. Interventions should promote resilience in children by targeting risk and protective factors. Child–parent agreement emphasizes the need to obtain both self- and proxy-reports, whenever possible.

1. Introduction

About one in five minor children has at least one parent with a mental illness [1]. Mental illness in primary caregivers can impair the psychosocial development of the offspring. The psychological burden of parental mental illness may not only lead to emotional and behavioral difficulties in children, but also has a more general influence on the children’s social relationships, interests, and academic environment, and thus may affect the children’s overall well-being and life satisfaction. Health-related quality of life (HRQoL) has been increasingly considered as an outcome criterion for children and adolescents to determine the burden of such demanding family conditions [2]. It has been defined as a subjective, multidimensional construct that compromises physical, psychological and social well-being [3]. Research has consistently shown that HRQoL of COPMI is reduced across different types of parental mental illness [4,5,6,7,8]. To prevent adverse psychosocial consequences for COPMI and to improve their HRQoL, it is crucial to examine risk and protective factors that are linked to the children’s well-being. Results can help to develop more efficient clinical interventions. Although self-reports are valuable sources of information, parent proxy-reports are often used as a replacement [9]. When parents suffer from mental disorders, they tend to assess their offspring’s HRQoL lower than the children do [10]. Discrepancies between children’s self- and parents’ proxy-reports can also originate from the raters’ relationship and demographic characteristics (e.g., age, gender-identity), as well as from the observability of the HRQoL domain. Investigating the extent of child–parent agreement and to identify predictors of disagreement is crucial, especially when parents are responsible to make health care decisions for their children, and when their perspective on child HRQoL differs from the child’s own rating [9,11].

1.1. Predictors of HRQoL in COPMI

The dynamic interaction between both risk and protective factors determines the children’s ability to adapt and recover from adverse psychosocial outcomes associated with parental mental illness [12,13,14]. Some of the most relevant risk and protective factors of HRQoL in COPMI include symptom severity of parental psychopathology and disease coping, emotional and behavioral difficulties in COPMI, the family’s mental health literacy, family functioning, social support, and child-related demographic variables. Parental psychopathology has implications for all family members. COPMI are more likely than their peers to experience unstable home environments, family conflicts, and a higher daily strain [15]. Depending on the nature and severity of symptoms, parenting skills can be impaired due to psychopathology and may result in reduced involvement with the child, insensitivity, hostility, rejection, neglect, and potential abuse [15,16]. Difficulties in parenting can also lead to insecure attachment, emotional dysregulation, negative emotionality, and pathological coping strategies, as well as psychopathology in the offspring irrespective of the children’s age [16,17]. Difficulties in parenting have been observed across different types of mental disorders, although most research has been conducted on depression. Parental depression has been associated with a markedly diminished interest in most activities, lack of energy, irritability and depressed mood, which tend to manifest in less child–parent interactions characterized by reduced empathy, verbal communication, and emotional availability, as well as a negative family discord [18,19,20,21]. The way parents appraise and cope with stressors like mental illness has both an impact on their own [22,23] and their offspring’s mental health and quality of life [24]. Research suggests that parents with a mental illness who practice adaptive coping strategies show better adaptions to their mental health condition [22], mitigate the negative outcomes of family burden and stigmatization [25], and improve HRQoL in their offspring [24].
COPMI have a significantly higher psychiatric risk than children with healthy parents due to various genetic and psychological vulnerabilities [26]. When children suffer from psychiatric symptoms, quality of life is poor and even lower compared to physical samples [27,28]. The World Health Organization (WHO) concluded based on a survey with over 51,507 participants that children with one parent with a mental illness have a 1.8 to 2.9 (odds ratio) times higher general psychiatric risk than the general population. When both parents were affected, the risk even raised from 2.2 to 4.6 (odds ratio) [29]. COPMI have a seven-fold risk to somaticize [30] and express psychiatric symptoms by physical complaints like headaches, fatigue, or stomachaches [8], which lowers satisfaction with physical aspects of HRQoL [8,29,30,31,32]. Caregivers’ depressive symptoms also reduce a child’s health-promoting behavior like healthy eating and exercise [32], which may result in dissatisfaction with physical activities and health. High health literacy in parents, which is characterized by a high amount of knowledge about the recognition, management, and prevention of mental disorders, can serve as a protective factor for the children’s mental health and promote their resilience [33].
Family functioning is an important determinant of quality of life in children and adolescents [34,35,36]. Research has consistently shown that family burden is higher in families with parental psychopathology across various psychiatric diagnoses e.g., depression [37], bipolar disorder [38], psychosis [39], and anxiety disorders [40]. Parental psychopathology may be associated with family discord, lower levels of expressiveness and affective involvement, impaired communication [37,38,39,40], and adverse psychosocial outcomes like unemployment and financial difficulties that strain family relations [15]. The extent of family burden has been determined by clinical characteristics such as symptom type and severity, a higher relapse frequency, and the severity of impaired functioning [41].
In line with the stress-buffering hypothesis, social support has been positively associated with HRQoL and psychological well-being and in children and adolescents [34,42,43]. Social support from extrafamilial sources may increase in importance, when family functioning is low. However, especially children from conflict-ridden families had difficulties to find and maintain friends and were viewed less favorably by their peers [44]. About one third of families with parental psychopathology perceive the social support they receive as insufficient [30].
The most consistent results regarding child-related demographic predictors of HRQoL exist regarding the children’s age and gender-identity. In a sample with 22,827 European participants, 8–11 years old children reported higher HRQoL than adolescents aged 12–18. Boys reported higher HRQoL than girls in most HRQoL aspects [45]. Similar age-related decreases in life satisfaction and gender-identity-related differences, especially during adolescence, have been reported in other studies [6,8,46].

1.2. Interrater Agreement on Child HRQoL Measures

Self-reports are generally the principle method with regard to the assessment of subjective experiences of health and well-being [34]. Nonetheless, it is still common that parents provide proxy-reports on their children’s HRQoL, whereas the children’s perspective is either neglected or surveyed only in addition [9]. This practice has been justified for younger age groups by the assumption that younger children lack sufficient cognitive and linguistic abilities to understand and interpret HRQoL questions by themselves [9]. They may also lack the ability to adopt a long-term perspective of events and consequences and have a restricted attention span [34]. Contrary to these assumptions, studies have demonstrated that even young children, who are given the opportunity to assess their own HRQoL with age-appropriate instruments, are able to understand questions and produce valid and reliable answers from the age of eight years onwards [47].
Interrater agreement on standardized child HRQoL measures may vary due to child and parent characteristics as well as with the HRQoL domain of interest. Research indicates that the child’s mental and physical health is linked to interrater-agreement on HRQoL measures [9,48,49]. Parents of healthy children over-report the children’s HRQoL compared to parents of children with physical or mental illness [9,48,49]. Parents of children with chronic conditions under-report their offspring’s quality of life [50]. When children suffer from physical rather than mental illness, child–parent agreement on HRQoL measures is higher [51], probably due to the better observability of physical symptoms [9,49,52]. Inconsistent results have been reported for child-related age and gender-identity effects on child–parent agreement [53,54,55,56]. It has been suggested that interrater agreement may vary for certain HRQoL domains like physical or emotional well-being in different developmental stages, thereby explaining the inconsistency [49].
With regard to the parent’s characteristics, research indicates that the parent’s relationship with the child as well as own perceptions of mental health and HRQoL are more predictive of child–parent agreement than the parent’s sociodemographic attributes. High family functioning characterized by high levels of intimacy and a high amount of shared time increases concordance between children and their parents [57,58]. The higher parents assessed their mental health condition [59,60] and HRQoL [11], the higher they rated their children’s well-being too, suggesting that parents project their own feelings on judgments about their children’s functioning [53]. Parents make more accurate proxy ratings when they assess objective and observable aspects of their children’s well-being (e.g., physical functioning, externalizing behavior) and have more difficulties with subjective and invisible aspects (e.g., the children’s feelings, internalizing behavior) [45]. The discrepancies reported in emotion-focused HRQoL items appear to become more discordant in adolescence compared to younger age groups [61], probably because adolescents spend more time in extrafamilial settings and prefer to discuss emotional needs with peers [49].
There are several research gaps that we aimed to overcome with this study. First, HRQoL has predominantly been investigated in adults with physical or mental disorders, or in normative samples [8,62]. Some studies have examined the HRQoL of COPMI but have either based their conclusions on bivariate correlational research, or focused solely on a few risk factors, thereby neglecting the multidimensionality of HRQoL. The inclusion of multiple predictors and regression analyses to draw conclusions on HRQoL in COPMI is still exceptional [63]. Results from multiple regression analyses may raise awareness for COPMI and allow the development and improvement of appropriate psychological interventions. Second, no study has yet, as far as we know, systematically investigated child–parent agreement regarding the children’s HRQoL when the parents were formally diagnosed with mental disorders according to the ICD-10 classification criteria. Moreover, although research has increasingly considered the children’s perspective in the last two decades, studies have mainly assessed the children’s HRQoL with parent–proxy ratings [11] and had several methodological limitations [11,50]. Small sample sizes have frequently prevented systematic analyses beyond bivariate correlational research, thereby limiting causal inference [50]. Agreement has usually been assessed with Pearson’s product–moment correlation coefficient, although it is not a measure of agreement [52,64]. A more appropriate statistic of agreement would be the intraclass correlation coefficient (ICC) [65]. In addition, predictors of agreement have rarely been investigated in multivariate analyses, which would enable researchers to glean a more realistic picture of child–parent agreement [50].
The aims of this study were, therefore first, to compare the HRQoL of COPMI with a reference population, thereby considering the children’s and the parents’ perspective. The second objective is to examine predictors of global child-related HRQoL. The third objective was the investigation of the magnitude and direction of child–parent agreement on specific and global HRQoL. Lastly, we aimed at examining variables predicting (dis)agreement with multiple child- and family-related variables. We expected that children and their parents with a mental illness reported both lower global and specific HRQoL than the reference population. Moreover, we assumed that child and parent psychopathology, low social support, a female gender-identity, older age, family dysfunction, maladaptive coping behavior were associated with lower global HRQoL in COPMI. Furthermore, we hypothesized that child–parent agreement was only of moderate size, and that disagreement on global HRQoL was predicted by child and parental psychopathology, family functioning, parental HRQoL, and the child’s age and gender-identity.

2. Methodology

2.1. Study Design

Analyses for the present study were conducted using the baseline data (gathered 2014 to 2017) of the randomized controlled CHIMPS (children of parents with a mental illness) project conducted in Germany and Switzerland. This project collected data primarily on the mental health status and HRQoL of parents with a mental illness, their partners, and children by means of standardized psychometric questionnaires to evaluate the effectiveness of the manualized family intervention “CHIMPS”. The aims of the intervention were the reduction of psychopathology in children and the enhancement of their long-term quality of life, as well as the introduction of remarkable children and adolescents to an early intervention. A detailed description of the intervention is provided in the CHIMPS manual [66]. Parents with mental disorders were recruited in multiple German and Swiss inpatient psychiatric hospitals based on the patients’ and their families’ availability and willingness to take part. Ethical approval has been provided by the Ethics Committee of the regional Medical Association (Hamburg, Germany) under the number PV4744. All participants were informed about study aims and procedures. Their participation in the study and the family intervention CHIMPS was voluntary and confidential. Written informed consent was obtained from all adult participants. Written assents of children under 18 years and the permission of their parents were received.

2.2. Participants

The overall sample of the project compromised 214 families with 214 parents with a mental illness, 144 partners, and 335 children. Children outside the questionnaires’ required age range (n = 136), and one remaining child with more than 30% missing data were excluded. The resulting final sample under analysis included n = 134 parents with a mental illness and n = 198 children and adolescents aged 8–18. Participation required parents to be diagnosed by clinicians with at least one ICD-10 psychiatric diagnosis. Participants with acute symptoms requiring inpatient treatment were excluded and referred to acute health services. Table 1 and Table 2 display the sample characteristics.

2.3. Measures

Health-related quality of life. The German self- and proxy-report version of the KIDSCREEN-27 and KIDSCREEN-10 was administered [34]. It covers 27 items of five domains: physical well-being (e.g., “Have you felt fit and well?”), psychological well-being, autonomy and parents, social support and peers, and school environment on a five-point response scale (1 = not at all to 5 = extremely or 1 = never to 5 = always). The KIDSCREEN-10 index contains 10 items and is derived from the 27-item version. The index provides information about global HRQoL, whereas the subscales of the KIDSCREEN-27 differentiate between specific aspects of HRQoL. The KIDSCREEN-10 provides raw values between 10 and 50, and the KIDSCREEN-27 between 27 and 135, with higher values indicating greater well-being. T-values relied on European reference data with a Mean (M) = 50 and a Standard Deviation (SD) = 10 [34]. T-scores < 40 indicate low HRQoL, scores between 40–60 indicate medium HRQoL and values > 60 high HRQoL [34]. Both KIDSCREEN versions have good discriminatory power and internal consistency (Cronbach’s α = 0.80 to 0.84), as well as good test-retest reliability (Intra Class Correlation (ICC) = 0.61 to 0.70) [34]. In the present study, the KIDSCREEN-27 demonstrated acceptable to good internal consistencies for the child-version (Cronbach’s α = 0.65 to 0.84) and the parent-version (Cronbach’s α = 0.73 to 0.91). The internal consistency of the KIDSCREEN-10 was good for both versions (Cronbach’s α = 0.79 to 0.83).
Psychopathology in parents. The Brief Symptom Inventory (BSI) [67] is a 53-item self-report questionnaire that can be answered on a five-point response scale (0 = not at all to 4 = extremely or 0 = never to 4 = always). The Global Severity Index (GSI) was used to measure current or past level of symptomatology, the number and intensity of reported symptoms, and the perceived burden. Scores can range from 0 to 4 with higher scores indicating greater psychopathology. The GSI covers nine primary symptom dimensions (somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism). The authors reported good psychometric properties, including high internal consistency of the GSI (Cronbach’s α = 0.90) [67], which could be replicated in this study (Cronbach’s α = 0.97).
Parental coping with mental illness. The Freiburg Questionnaire of Coping with Illness (FKV-LIS) [68] generates five subscales that represent the respondent’s predominant coping style based on 23 items: depressed processing style, active problem-oriented coping, distraction and self-growth, religiosity and quest for meaning, trivialization, and wishful thinking. Respondents rate on a four-point response scale ranging from 1 = not at all to 5 = very much how often they employ each coping strategy. The authors reported an internal consistency between Cronbach’s α = 0.68 to 0.77 [68]. Internal consistency in this sample ranged from Cronbach’s α = 0.49 (religiosity and quest for meaning) to 0.72 (trivialization and wishful thinking).
Parental health-related quality of life. The EQ-5D [69] is a generic self-report HRQoL measure divided into five dimensions (mobility, self-care, usual activity, discomfort, anxiety, and depression) within three severity levels. For the present study, we calculated an index value, which assigns a single value for all hypothetical health states covered by the five dimensions. An index of 1 represents the best possible state of health, while value 0 represents the opposite. The EQ-5D is a moderately valid instrument to assess HRQoL in adults with mental disorder and has reasonable discriminative ability and reliability [69]. Here, the internal consistency of the index was Cronbach’s α = 0.28.
Psychopathology in children. The Child Behavior Checklist 4–18 [70,71] is a widely used instrument to rate maladaptive emotional and behavioral problems in children aged 4–18 years on a three-point response scale from 0 = not at all to 2 = often. The parent-version has 118 items. It generates eight syndrome scales (withdrawn, somatic complaints, anxious/depressed, social problems, thought problems, attention problems, delinquent behavior, aggressive behavior) and a total score, which was used for calculations in this study. The total score can range from 0 to 111 with higher values indicating greater psychopathology in children. Psychometric validity and reliability have been established in numerous clinical and non-clinical studies [70,71]. In the present study, the total score of the CBCL-4-18 parent version demonstrated excellent internal consistency with Cronbach’s α = 0.95.
Family functioning. The General Family Questionnaire (Allgemeiner Familienbogen; FB-A) has 40 items [72]. This study focused on the total score, which reflects overall family functioning and is the sum of seven subscales (task fulfillment, role behavior, communication, emotionality, affectivity of relations, control, values, and norms). Items are rated on a four-point response scale ranging from 0 = completely true to 3 = not true at all. The total score can range from 0 to 120. Higher scores reflect greater family dysfunction. The authors reported an internal consistency of α = 0.46–0.80, with α > 0.60 for most subscales [72], which could be replicated in this study (Cronbach’s α = 0.63 to 0.74). Here, the total score had an excellent internal consistency of α = 0.93.
Social support. The Oslo Social Support Scale (OSSS-3) [73] consists of three items asking parents to proxy-report for their children the number of close confidants, the sense of concern from other people, and the relationship with neighbors and the accessibility of practical help. The scale of the first item has been adapted for study purposes from a 4 to 5-point response scale (1 = none, 2 = 1–2, 3 = 3–4, 4 = 5–6 and 5 = more than 6). The total score is calculated by summarizing those three items. It ranges from 3 to 15 with higher scores indicating greater social support. The OSSQ-3 has demonstrated good validity and reliability in a representative sample with 2524 German participants [74]. The modified version in this study demonstrated an adequate internal consistency of α = 0.69.

2.4. Data Analysis

We first examined whether our sample’s HRQoL differentiated significantly from the reference population [34]. Normative data were considered for both the child- and proxy reports. As children within families were more correlated than children from different families (ICC ≥ 0.10), differences were analyzed with linear mixed models. For the same reason, the impact of multiple predictors on child proxy-rated HRQoL was evaluated with linear mixed models. Coefficients, standard errors, and p-values were calculated for each predictor, and overall model fit was reported. To estimate child–parent agreement on HRQoL measures, ICC estimates were calculated with a two-way mixed effects model based on single ratings. ICC estimates were defined by both consistency and absolute agreement. According to Cicchetti’s guidelines, ICC < 0.4 are classified as poor, 0.40–0.59 as fair, 0.60–0.74 as good, and 0.75–1.00 as excellent reliability [75]. Multiple linear regression was performed to analyze the impact of various predictors on total disagreement of HRQoL between children and their parents with a mental illness. Total disagreement was calculated by subtracting the children’s index from the parents’ index. Family clusters were not considered as ICC values were <0.10. The scores of both regression analyses were based on raw values assessed by parents with a mental illness. All metric predictors were grand mean-centered. Questionnaire-related missings were imputed according to the Expectation–Maximization algorithm (EM) [76]. Statistical significance was set at α ≤ 0.05 two-sided. All statistical analyses were performed using IBM SPSS 25 (IBM, Armonk, NY, USA).

3. Results

3.1. Descriptive Statistics

The sample compromised 134 families (n = 102 mothers with a mental illness, n = 32 fathers with a mental illness, n = 198 children and adolescents). Characteristics of parents and children are described in Table 1 and Table 2, respectively. Parents with a mental illness had a mean age of M = 41.59 (SD = 6.77). About half of the sample was married. Most parents had 10 to 13 years of school education. The most prominent primary psychiatric ICD-10 diagnoses were mood (affective) disorders (F30–F39, e.g., major depressive disorder), followed by disorders of adult personality and behavior (F60–F69, e.g., paranoid personality disorder), and neurotic, stress-related and somatoform disorders (F40–F48, e.g., phobias, obsessive-compulsive disorder). Less prevalent were schizophrenia, schizotypal, and delusional disorders (F20–F29, e.g., delusional disorder), mental and behavioral disorders due to psychoactive substance use (F10–F19, e.g., alcohol dependence) and behavioral and emotional disorders with onset usually occurring in childhood and adolescence (F90–F98, e.g., attention deficit hyperactivity disorder). Almost half of the parents had comorbid psychiatric ICD-10 diagnoses. Most parents reported a psychologically remarkable symptom burden (BSI raw score ≥ 0.62). Parents with a mental illness frequently employed active problem-oriented coping, followed by a depressed processing style. Parents reported moderate satisfaction with current health. The n = 198 participating children and adolescents had a mean age of M = 12.19 (SD = 3.09) years. Boys and girls were equally represented. Most of the children shared the household with their parents with a mental illness and had either biological or step siblings. The sample’s mean raw value of the CBCL 4-18 was M = 37.90 (SD = 25.72), and M = 10.25 (SD = 2.40) on the OSSS-3. Children and adolescents self-reported slightly higher HRQoL on the KIDSCREEN-10 than their parents.

3.2. HRQoL of Children and Adolescents from the Children’s and the Parents’ Perspective

Table 3 and Table 4 show the average values of HRQoL in COPMI from the parents’ and the children’s report, respectively. Parents’ proxy reports for their children’s global and specific HRQoL were lower than the assessments of parents from the reference sample (M = 50, SD = 10). Differences were significant for the KIDSCREEN-10 index and all KIDSCREEN-27 subscales, except for autonomy and parents (all p < 0.01). Mean values were rated lowest for psychological and physical well-being and highest for autonomy and parents. Parents assessed their offspring’s HRQoL lower than the children did on all aspects, except for physical well-being. On average, children self-reported both lower global and specific HRQoL than the reference population. Significant differences between the sample and the reference population were found for the index as well as for the subscales physical and psychological well-being (all p < 0.01). Both the children’s and the parents’ perspective can be considered to represent a medium HRQoL rating [34]. Children within families were more correlated than children from different families (ICC ≥ 0.10).

3.3. Prediction of HRQoL in Children and Adolescents

Table 5 shows the prediction of HRQoL in children and adolescents aged 8–18 years. Family clusters were considered in the analysis as children within families were more similar to each other than children from different families (ICC = 0.45). All calculations were based on raw values. Adding the predictors to the null model significantly improved the model fit ( χ 2 (df) = 98.98 (12), p < 0.001). Significant predictors of HRQoL were child psychopathology, social support, the child’s age, and parental psychopathology (all p < 0.05). Lower HRQoL was associated with child and parental psychopathology, as well as older age in children. Social support was associated with higher HRQoL. Whereas the added child-related predictors in model 1 explained 53.41% of the residual variance, family-related predictors explained only 6.23%. The model had a significant amount of variation left unexplained by the information included. Nonetheless, the fit of model 1 was significantly better than the fit of the null model.

3.4. Child–Parent Agreement on HRQoL in Children and Adolescents

Table 6 displays the child–parent agreement on the children’s HRQoL. Interrater agreement was significant for all global and specific aspects of HRQoL (all p < 0.001). ICC consistency and absolute agreement values ranged from 0.34 (social support and peers) to 0.49 (school environment), which indicates fair congruence between ratings.

3.5. Predictors of Child–Parent Agrement on HRQoL in Children and Adolescents

The difference between child- and parent-reports was calculated to analyze the impact of various predictors on child–parent agreement on HRQoL in children. Predictors of total child–parent disagreement on HRQoL in children and adolescents are displayed in Table 7. Parents rated their offspring’s HRQoL lower than the children did. The multiple regression model with all seven predictors explained 19.5% of the variance in the dependent variable. When the effects of all predictors are held constant, the rater show b = 3.84 deviation points. Significant predictors of disagreement were the child’s psychopathology and the child’s gender-identity (all p < 0.05). The difference between child- and parent-reports was smaller, when children were male and had psychological difficulties. Age, family functioning, parents’ mental health problems, and their HRQoL did not contribute to the model.

4. Discussion

We aimed at analyzing the impact of various risk and protective factors on HRQoL in COPMI and at examining the magnitude, direction, and prediction of child–parent (dis)agreement. As expected, both parents and children reported considerable lower global and specific HRQoL than the reference population, although ratings still indicated medium life satisfaction [34]. Parents reported lower child HRQoL than their children on most HRQoL domains. Physical and psychological well-being were the most impaired aspects of HRQoL from both perspectives. In general, these results are in line with prior research confirming that HRQoL of COPMI is underreported by parents and lower than in the general population [4,5,6,7,8,48]. More pronounced impairments in psychological and physical aspects of HRQoL are common findings in previous studies too [8,29,30,31,32]. The results show that parental mental illness impairs many facets of HRQoL in children and adolescents. To prevent adverse outcomes in those children and to improve the children’s resilience, interventions should target risk and protective factors of HRQoL in COPMI. To identify those, we analyzed the impact of various predictors of the children’s life satisfaction. Overall, results were in line with our expectations. The most influential risk and protective predictors were child and parental psychopathology, social support, and the child’s age. Of those, only social support was associated with higher HRQoL. The magnitude and the direction of the significant effects are consistent with other research [24,27,28,42,43,45,77,78,79]. The child’s gender-identity, the interaction between the child’s age and gender-identity, family functioning, and parental coping did not contribute significantly to the model, although the direction of the effects was in line with previous research [45]. Future research may evaluate whether these findings relate to overlap between predictors, the measurement instruments, sample characteristics, or whether their influence on HRQoL is lower as indicated by previous research [24,34,35,36,45]. The results imply that clinical interventions for COPMI should primarily focus on the improvement of psychological health of both children and parents, and on the increase of the children’s supportive network (e.g., relatives, peers, professionals). Although the individual needs are diverse, research indicates that most children and adolescents prioritize learning more about their parent’s mental illness, about ways to cope with it, and confidential support that is easy to access [80].
Mental health problems may affect parents’ judgments regarding their children’s HRQoL [10]. As parents are sometimes asked to make clinical decisions for their children, it is important to investigate the extent of child–parent agreement and to find probable explanations for disagreement. Consistent with our assumptions, reliability of interrater agreement between family members was fair for most global and specific aspects of HRQoL. It was slightly lower than in a study validating the proxy-version of the KIDSCREEN-27 in the general population (ICC = 0.44–0.61) [34]. However, this is in line with studies that have linked parental stress and mental health problems to higher informant discrepancies in the assessment of psychopathology and HRQoL [28,50,59,60,81]. The highest agreement was found for HRQoL relating to the school environment and the child’s physical well-being. Family members disagreed most on the child’s social relationships with peers and friends. Parents make more accurate proxy-ratings for observable aspects of behavior or for aspects like school environment for which they can rely on external sources (e.g., teachers’ reports, grades) [45,82]. The quality of relationships with peers and the perceived social support by children are often outside the parents’ visibility, especially during adolescence [49,61]. Social support and peers were also the subscale with the lowest agreement (ICC = 0.44) in the study validating the proxy-version of the KIDSCREEN-27 in the general population [34]. The most influential predictors of child–parent (dis)agreement on HRQoL in COPMI were mental health problems in children and the children’s gender-identity. They explained 19.5% of the variance in the dependent variable. The difference between child–parent reports was lower when children were male and had emotional and behavioral difficulties. Overall, results are in line with other studies that identified similar predictors of (dis)agreement [45,49,50,57]. It has been suggested that there may be more child–parent agreement in children with mental health problems, and that the parent’s perspective can provide additional valuable information on HRQoL in these situations [54]. The child’s age, family functioning, parental psychopathology, and parental HRQoL did not contribute to the model, maybe because differences between child–parent ratings were too small to find significant effects. Although controversial results exist regarding effects of age [54,56], research has consistently demonstrated that highly functional families show higher child–parent agreement [57,58], and that the parent’s mental health [10,59,60,83] and HRQoL [11] affect the proxy-ratings of their child’s HRQoL. Differences in child–parent reports regarding the children’s HRQoL have to be anticipated and regarded as valuable information in clinical and research contexts. Parents’ perceptions may be influenced by their psychiatric symptoms, concerns, and by the burden of care-giving [52]. Moreover, children and parents may experience different situations and vary in their understanding of HRQoL, indicating the need to obtain information from multiple informants if possible [52].
This study had several limitations. Because all predictors and outcome variables were simultaneously assessed in this cross-sectional study, no temporal relationship between exposure and the outcome can be made. Longitudinal data are needed to make causal inferences. As with any regression analysis, support for the model predicting HRQoL in COPMI does not necessarily mean that the results can be generalized to other populations. The generalizability of the results to the population as a whole may further be limited due to the convenience sampling method. Results may be biased due to the reasons why volunteering participants chose to take part in the CHIMPS family intervention and others did not. Furthermore, no information was available on socioeconomic status and the children’s physical condition. The latter may be a relevant predictor for physical aspects of HRQoL. Although we measured parents’ perceived burden of symptoms, we did not differentiate between psychiatric diagnoses, symptom frequency, chronicity, prognosis, and duration of mental illness. Future studies may include these predictors to explain more variance in child HRQoL and to examine the model fit with regard to different psychopathologies.

5. Conclusions

Our findings suggest that HRQoL is impaired in COPMI. Interventions should concentrate on the children’s psychological and physical well-being, as these seem to be the most impaired facets. To improve these domains of children’s HRQoL, interventions should focus on the whole family. They may target the parental psychopathology with psychological interventions or provide social support for the children, as these aspects appear to be closely related to the children’s HRQoL. Offering peer support groups may be one of many options to promote resilience and wellbeing in affected children by fostering psychoeducation, coping skills, and mutual support. Physical HRQoL in COPMI may be improved by cognitive interventions like mindfulness training and relaxation techniques. The disagreement found between children and parents on some aspects of the children’s HRQoL emphasizes the need to obtain both self- and proxy-reports, whenever possible. Children should be provided the opportunity to describe their subjective view, especially when it comes to HRQoL aspects that are less observable from the outside, such as psychological well-being and social relationships with peers. Parent proxy-reports may be particularly useful when children are unable to self-report due to severe cognitive deficits or a young age, as well as when children tend to overreport high HRQoL to protect their parents. Research should continue to explore the direction and magnitude of child–parent agreement on HRQoL measures, and investigate reasons for disagreement. Results may aid clinicians to decide which HRQoL instrument is appropriate for a given sample, and in which contexts children’s self and parents’ proxy reports show high deviations.

Author Contributions

Conceptualization, A.R.; methodology, C.B., A.D., and K.W.; formal analysis, A.R.; original draft preparation, A.R.; writing—review and editing, A.R., C.B., and A.D.; visualization, A.R.; project administration, B.A. and S.W.-G.; funding acquisition, S.W.-G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Federal Ministry of Education and Research, grant number 01GY1337.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of the regional Medical Association (Hamburg, Germany) under the number PV4744, 05.08.2014).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data available in a publicly accessible repository.

Acknowledgments

We thank the CHIMPS study group for providing the opportunity to evaluate the data. Members of the CHIMPS study group are: Wiegand-Grefe, Martin Lambert, Reinhold Kilian, Bonnie Adema, Karl Wegscheider, Anne Daubmann, Klaus-Thomas Kronmüller, Kai von Klitzing, Sibylle Winter, Kurt Albermann, Doris Mallmann, Christine Norra, and Mareike Busmann. We are grateful to all participants who gave their time and were willing to participate in this study.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Maybery, D.; Reupert, A. The number of parents who are patients attending adult psychiatric services. Curr. Opin. Psychiatry 2018, 31, 358–362. [Google Scholar] [CrossRef] [PubMed]
  2. Days, M.H. Population Assessment of Health-Related Quality of Life; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2000. [Google Scholar]
  3. Ravens-Sieberer, U.; Bullinger, M. Assessing health-related quality of life in chronically ill children with the German KINDL: First psychometric and content analytical results. Qual. Life Res. 1998, 7, 399–407. [Google Scholar] [CrossRef] [PubMed]
  4. Dittrich, K.; Fuchs, A.; Bermpohl, F.; Meyer, J.; Führer, D.; Reichl, C.; Reck, C.; Kluczniok, D.; Kaess, M.; Attar, C.H.; et al. Effects of maternal history of depression and early life maltreatment on children’s health-related quality of life. J. Affect. Disord. 2018, 225, 280–288. [Google Scholar] [CrossRef] [PubMed]
  5. Ferro, M.A.; Avison, W.R.; Campbell, M.K.; Speechley, K.N. The impact of maternal depressive symptoms on health-related quality of life in children with epilepsy: A prospective study of family environment as mediators and moderators. Epilepsia 2010, 52, 316–325. [Google Scholar] [CrossRef] [PubMed]
  6. Giannakopoulos, G.; Dimitrakaki, C.; Pedeli, X.; Kolaitis, G.; Rotsika, V.; Ravens-Sieberer, U.; Tountas, Y. Adolescents’ wellbeing and functioning: Relationships with parents’ subjective general physical and mental health. Health Qual. Life Outcomes 2009, 7, 100. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Goetz, M.; Sebela, A.; Mohaplova, M.; Ceresnakova, S.; Ptacek, R.; Novak, T. Psychiatric Disorders and Quality of Life in the Offspring of Parents with Bipolar Disorder. J. Child Adolesc. Psychopharmacol. 2017, 27, 483–493. [Google Scholar] [CrossRef]
  8. Hagen, K.A.; Hilsen, M.; Kallander, E.K.; Ruud, T. Health-related quality of life (HRQoL) in children of ill or substance abusing parents: Examining factor structure and sub-group differences. Qual. Life Res. 2019, 28, 1063–1073. [Google Scholar] [CrossRef]
  9. Upton, P.; Lawford, J.; Eiser, C. Parent–child agreement across child health-related quality of life instruments: A review of the literature. Qual. Life Res. 2008, 17, 895–913. [Google Scholar] [CrossRef]
  10. Cremeens, J.; Eiser, C.; Blades, M. Factors influencing agreement between child self-report and parent proxy-reports on the Pediatric Quality of Life Inventory™ 4.0 (PedsQL™) Generic Core Scales. Health Qual. Life Outcomes 2006, 4, 58. [Google Scholar] [CrossRef]
  11. Berman, A.H.; Liu, B.; Ullman, S.; Jadbäck, I.; Engström, K. Children’s Quality of Life Based on the KIDSCREEN-27: Child Self-Report, Parent Ratings and Child-Parent Agreement in a Swedish Random Population Sample. PLoS ONE 2016, 11, e0150545. [Google Scholar] [CrossRef]
  12. Rutter, M. Resilience: Some conceptual considerations. J. Adolesc. Health 1993. [Google Scholar] [CrossRef]
  13. Olsson, C.A.; Bond, L.; Burns, J.M.; Vella-Brodrick, D.A.; Sawyer, S.M. Adolescent resilience: A concept analysis. J. Adolesc. 2003, 26, 1–11. [Google Scholar] [CrossRef]
  14. Mowbray, C.T.; Bybee, D.; Oyserman, D.; Allen-Meares, P.; Macfarlane, P.; Hart-Johnson, T. Diversity of Outcomes Among Adolescent Children of Mothers With Mental Illness. J. Emot. Behav. Disord. 2004, 12, 206–221. [Google Scholar] [CrossRef] [Green Version]
  15. Plass-Christl, A.; Haller, A.-C.; Otto, C.; Barkmann, C.; Wiegand-Grefe, S.; Hölling, H.; Schulte-Markwort, M.; Ravens-Sieberer, U.; Klasen, F. Parents with mental health problems and their children in a German population based sample: Results of the BELLA study. PLoS ONE 2017, 12, e0180410. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Hosman, C.M.; van Doesum, K.T.; van Santvoort, F. Prevention of emotional problems and psychiatric risks in children of parents with a mental illness in the Netherlands: I. The scientific basis to a comprehensive approach. AeJAMH Aust. e-J. Adv. Ment. Health 2009, 8, 250–263. [Google Scholar] [CrossRef]
  17. Reedtz, C.; Lauritzen, C.; Stover, Y.V.; Freili, J.L.; Rognmo, K. Identification of Children of Parents With Mental Illness: A Necessity to Provide Relevant Support. Front. Psychiatry 2019, 9, 728. [Google Scholar] [CrossRef] [Green Version]
  18. Moore, K.A.; Matthews, G.; Carrano, J. Symptoms of major depression in a sample of fathers of infants: Sociodemographic correlates and links to father involvement. J. Fam. Issues 2007, 28, 61–99. [Google Scholar]
  19. Leinonen, J.A.; Solantaus, T.S.; Punamaki, R.-L. Parental mental health and children’s adjustment: The quality of marital interaction and parenting as mediating factors. J. Child Psychol. Psychiatry 2003, 44, 227–241. [Google Scholar] [CrossRef]
  20. Pilowsky, D.J.; Wickramaratne, P.; Nomura, Y.; Weissman, M.M. Family Discord, Parental Depression, and Psychopathology in Offspring: 20-Year Follow-up. J. Am. Acad. Child Adolesc. Psychiatry 2006, 45, 452–460. [Google Scholar] [CrossRef] [Green Version]
  21. Solantaus-Simula, T.; Punamäki, R.-L.; Beardslee, W.R. Children’s Responses to Low Parental Mood. II: Associations With Family Perceptions of Parenting Styles and Child Distress. J. Am. Acad. Child Adolesc. Psychiatry 2002, 41, 287–295. [Google Scholar] [CrossRef]
  22. Peay, H.L.; Dl, R.; Biesecker, B.B. Adaptation to bipolar disorder and perceived risk to children: A survey of parents with bipolar disorder. BMC Psychiatry 2013, 13, 327. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Toscano, A.; Blanchin, M.; Bourdon, M.; Antignac, A.B.; Sébille, V. Longitudinal associations between coping strategies, locus of control and health-related quality of life in patients with breast cancer or melanoma. Qual. Life Res. 2020, 29, 1271–1279. [Google Scholar] [CrossRef] [PubMed]
  24. Jeske, J.; Bullinger, M.; Plass, A.; Petermann, F.; Wiegand-Grefe, S. Risk factor coping with a disease: Associations between coping and health related quality of life of children with a mentally ill parent. Z. Psychiatr. Psychol. Psychother. 2009, 57, 207–213. [Google Scholar]
  25. van der Sanden, R.L.; Pryor, J.B.; Stutterheim, S.E.; Kok, G.; Bos, A.E.R. Stigma by association and family burden among family members of people with mental illness: The mediating role of coping. Soc. Psychiatry Psychiatr. Epidemiol. 2016, 51, 1233–1245. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Weber, S.; Jud, A.; Landolt, M.A.; Goldbeck, L. Predictors of health-related quality of life in maltreated children and adolescents. Qual. Life Res. 2017, 26, 2717–2727. [Google Scholar] [CrossRef] [PubMed]
  27. Sawyer, M.; Whaites, L.; Rey, J.M.; Hazell, P.L.; Graetz, B.W.; Baghurst, P. Health-Related Quality of Life of Children and Adolescents With Mental Disorders. J. Am. Acad. Child Adolesc. Psychiatry 2002, 41, 530–537. [Google Scholar] [CrossRef]
  28. Bastiaansen, D.; Koot, H.M.; Ferdinand, R.F.; Verhulst, F.C. Quality of Life in Children With Psychiatric Disorders: Self-, Parent, and Clinician Report. J. Am. Acad. Child Adolesc. Psychiatry 2004, 43, 221–230. [Google Scholar] [CrossRef] [Green Version]
  29. A McLaughlin, K.; Gadermann, A.M.; Hwang, I.; Sampson, N.A.; Al-Hamzawi, A.; Andrade, L.H.; Angermeyer, M.C.; Benjet, C.; Bromet, E.J.; Bruffaerts, R.; et al. Parent psychopathology and offspring mental disorders: Results from the WHO World Mental Health Surveys. Br. J. Psychiatry 2012, 200, 290–299. [Google Scholar] [CrossRef] [Green Version]
  30. Wiegand-Grefe, S.; Werkmeister, S.; Bullinger, M.; Plass, A.; Petermann, F. Health-related quality of life and social support of children with mentally ill parents: Effects of a manualized family intervention. Kindh. Entwickl. 2012, 21, 64–73. [Google Scholar] [CrossRef]
  31. Kayed, N.S.; Jozefiak, T.; Rimehaug, T.; Tjelflaat, T.; Brubakk, A.-M.; Wichstrom, L. Resultater fra Forskningsprosjektet Psykisk Helse hos barn og unge i Barneverninstitusjoner; NTNU Regionalt Kunnskapssenter for barn og unge-Psykisk Helse og Barnevern: Trondheim, Norway, 2015. [Google Scholar]
  32. Yoo, J.P.; Chung, G.H.; Lee, S.-G. The Associations Between Socioeconomic Status, Caregivers’ Depressive Symptoms, Children’s Health-Promoting Behavior, and Children’s Physical Health: A Mediation Model. Asian Soc. Work. Policy Rev. 2015, 9, 177–193. [Google Scholar] [CrossRef]
  33. Sanders, L.M.; Shaw, J.S.; Guez, G.; Baur, C.; Rudd, R. Health Literacy and Child Health Promotion: Implications for Research, Clinical Care, and Public Policy. Pediatrics 2009, 124, S306–S314. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Ravens-Sieberer, U. The Kidscreen Questionnaires: Quality of Life Questionnaires for Children and Adolescents; Handbook; Pabst Science Publ.: Lengerich, Germany, 2006. [Google Scholar]
  35. Green, J.G.; McLaughlin, K.A.; Berglund, P.A.; Gruber, M.J.; Sampson, N.A.; Zaslavsky, A.M.; Kessler, R.C. Childhood adversities and adult psychiatric disorders in the National Comorbidity Survey Replication I: Associations with first onset of DSM-IV disorders. Arch. Gen. Psychiatry 2010, 67, 113–123. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. McLeod, B.D.; Wood, J.J.; Weisz, J.R. Examining the association between parenting and childhood anxiety: A meta-analysis. Clin. Psychol. Rev. 2007, 27, 155–172. [Google Scholar] [CrossRef] [PubMed]
  37. Letourneau, N.; Tramonte, L.; Willms, J.D. Maternal Depression, Family Functioning and Children’s Longitudinal Development. J. Pediatr. Nurs. 2013, 28, 223–234. [Google Scholar] [CrossRef] [PubMed]
  38. Freed, R.D.; Tompson, M.C.; Wang, C.H.; Otto, M.W.; Hirshfeld-Becker, D.R.; Nierenberg, A.A.; Henin, A. Family functioning in the context of parental bipolar disorder: Associations with offspring age, sex, and psychopathology. J. Fam. Psychol. 2015, 29, 108–118. [Google Scholar] [CrossRef] [PubMed]
  39. Koutra, K.; Vgontzas, A.N.; Lionis, C.; Triliva, S. Family functioning in first-episode psychosis: A systematic review of the literature. Soc. Psychiatry Psychiatr. Epidemiol. 2014, 49, 1023–1036. [Google Scholar] [CrossRef] [PubMed]
  40. Wang, J.; Chen, Y.; Tan, C.; Zhao, X. Family functioning, social support, and quality of life for patients with anxiety disorder. Int. J. Soc. Psychiatry 2016, 62, 5–11. [Google Scholar] [CrossRef] [PubMed]
  41. Grandón, P.; Jenaro, C.; Lemos, S. Primary caregivers of schizophrenia outpatients: Burden and predictor variables. Psychiatry Res. 2008, 158, 335–343. [Google Scholar] [CrossRef]
  42. Chu, P.S.; Saucier, D.A.; Hafner, E. Meta-Analysis of the Relationships Between Social Support and Well-Being in Children and Adolescents. J. Soc. Clin. Psychol. 2010, 29, 624–645. [Google Scholar] [CrossRef]
  43. Raffaelli, M.; Andrade, F.C.; Wiley, A.R.; Edwards, L.L.; Cappello, O.S.-A.; Aradillas-Garcia, C. Stress, Social Support, and Depression: A Test of the Stress-Buffering Hypothesis in a Mexican Sample. J. Res. Adolesc. 2012, 23, 283–289. [Google Scholar] [CrossRef]
  44. Criss, M.M.; Pettit, G.S.; Bates, J.E.; Dodge, K.A.; Lapp, A.L. Family Adversity, Positive Peer Relationships, and Children’s Externalizing Behavior: A Longitudinal Perspective on Risk and Resilience. Child Dev. 2002, 73, 1220–1237. [Google Scholar] [CrossRef] [PubMed]
  45. Ravens-Sieberer, U.; Auquier, P.; Erhart, M.; Gosch, A.; Rajmil, L.; Bruil, J.; Power, M.; Duer, W.; Cloetta, B.; Czemy, L.; et al. The KIDSCREEN-27 quality of life measure for children and adolescents: Psychometric results from a cross-cultural survey in 13 European countries. Qual. Life Res. 2007, 16, 1347–1356. [Google Scholar] [CrossRef] [PubMed]
  46. Meade, T.; Elizabeth, D. Health-related quality of life in a sample of Australian adolescents: Gender and age comparison. Qual. Life Res. 2015, 24, 2933–2938. [Google Scholar] [CrossRef] [PubMed]
  47. Riley, A.W. Evidence That School-Age Children Can Self-Report on Their Health. Ambul. Pediatrics 2004, 4, 371–376. [Google Scholar] [CrossRef] [PubMed]
  48. Dey, M.; Landolt, M.A.; Mohler-Kuo, M. Assessing parent–child agreement in health-related quality of life among three health status groups. Soc. Psychiatry Psychiatr. Epidemiol. 2013, 48, 503–511. [Google Scholar] [CrossRef] [Green Version]
  49. Eiser, C.; James, W. Varni, Health-related quality of life and symptom reporting: Similarities and differences between children and their parents. Eur. J. Pediatrics 2013, 172, 1299–1304. [Google Scholar] [CrossRef] [PubMed]
  50. White-Koning, M.; Arnaud, C.; Dickinson, H.O.; Thyen, U.; Beckung, E.; Fauconnier, J.; McManus, V.; Michelsen, S.I.; Parkes, J.; Parkinson, K.; et al. Determinants of Child-Parent Agreement in Quality-of-Life Reports: A European Study of Children With Cerebral Palsy. Pediatrics 2007, 120, e804–e814. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Kiss, E.; Kapornai, K.; Baji, I.; Mayer, L. Vetró, Ágnes Assessing quality of life: Mother–child agreement in depressed and non-depressed Hungarian. Eur. Child Adolesc. Psychiatry 2009, 18, 265–273. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Eiser, C.; Morse, R. Can parents rate their child’s health-related quality of life? Results of a systematic review. Qual. Life Res. 2001, 10, 347–357. [Google Scholar] [CrossRef]
  53. Cremeens, J.; Eiser, C.; Blades, M. Characteristics of Health-related Self-report Measures for Children Aged Three to Eight Years: A Review of the Literature. Qual. Life Res. 2006, 15, 739–754. [Google Scholar] [CrossRef]
  54. Rajmil, L.; Rodríguez-López, A.; López-Aguilà, S.; Alonso, J. Parent–child agreement on health-related quality of life (HRQOL): A longitudinal study. Health Qual. Life Outcomes 2013, 11, 101. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Ronen, G.M.; Streiner, D.L.; Rosenbaum, P.; Network, C.P.E. Health-related Quality of Life in Children with Epilepsy: Development and Validation of Self-report and Parent Proxy Measures. Epilepsia 2003, 44, 598–612. [Google Scholar] [CrossRef] [PubMed]
  56. Annett, R.D.; Bender, B.G.; Duhamel, T.R.; Lapidus, J. Factors influencing parent reports on quality of life for children with asthma. J. Asthma 2003, 40, 577–587. [Google Scholar] [CrossRef] [PubMed]
  57. De Los Reyes, A.; Kazdin, A.E. Informant discrepancies in the assessment of childhood psychopathology: A critical review, theoretical framework, and recommendations for further study. Psychol. Bull. 2005, 131, 483. [Google Scholar] [CrossRef] [PubMed]
  58. Treutler, C.M.; Epkins, C.C. Are discrepancies among child, mother, and father reports on children’s behavior related to parents’ psychological symptoms and aspects of parent–child relationships? J. Abnorm. Child Psychol. 2003, 31, 13–27. [Google Scholar] [CrossRef]
  59. Janicke, D.M.; Marciel, K.K.; Ingerski, L.M.; Novoa, W.; Lowry, K.W.; Sallinen, B.J.; Silverstein, J.H. Impact of Psychosocial Factors on Quality of Life in Overweight Youth. Obesity 2007, 15, 1799–1807. [Google Scholar] [CrossRef] [Green Version]
  60. Kobayashi, K.; Kamibeppu, K. Quality of life reporting by parent-child dyads in Japan, as grouped by depressive status. Nurs. Health Sci. 2011, 13, 170–177. [Google Scholar] [CrossRef]
  61. Chang, P.C.; Yeh, C.H. Cancer, Agreement between child self-report and parent proxy-report to evaluate quality of life in children with cancer. Psycho-Oncology 2005, 14, 125–134. [Google Scholar] [CrossRef]
  62. Wallander, J.L.; Koot, H.M. Quality of life in children: A critical examination of concepts, approaches, issues, and future directions. Clin. Psychol. Rev. 2016, 45, 131–143. [Google Scholar] [CrossRef] [Green Version]
  63. Plass, A.; Haller, A.-C.; Habermann, K.; Barkmann, C.; Petermann, F.; Schipper, M.; Wiegand-Grefe, S.; Hoelling, H.; Ravens-Sieberer, U.; Klasen, F. Factors promoting mental health in children of parents with mental health problems: Results of the BELLA cohort study. Kindh. Entwickl. 2016, 25, 41–49. [Google Scholar] [CrossRef]
  64. Ottenbacher, K.J. An examination of reliability in developmental research. J. Dev. Behav. Pediatrics 1995. [Google Scholar] [CrossRef]
  65. Koo, T.K.; Li, M.Y. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J. Chiropr. Med. 2016, 15, 155–163. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. Wiegand-Grefe, S.; Halverscheid, S.; Plass, A. Kinder und ihre Psychisch Kranken Eltern: Familienorientierte Prävention-der CHIMPs-Beratungsansatz; Hogrefe Verlag: Göttingen, Germany, 2011. [Google Scholar]
  67. Derogatis, L.R.; Derogatis, L. Brief Symptom Inventory (BSI). In Administration, Scoring, and Procedures Manual; Beltz Test GmbH: Göttingen, Germany, 2001. [Google Scholar]
  68. Muthny, F.A. Freiburger Fragebogen zur Krankheitsverarbeitung: FKV; Beltz Weinheim: Weinheim, Germany, 1989. [Google Scholar]
  69. Sonntag, M.; Konnopka, A.; Leichsenring, F.; Salzer, S.; E Beutel, M.; Herpertz, S.; Hiller, W.; Hoyer, J.; Joraschky, P.; Nolting, B.; et al. Reliability, validity and responsiveness of the EQ-5D in assessing and valuing health status in patients with social phobia. Health Qual. Life Outcomes 2013, 11, 215. [Google Scholar] [CrossRef] [PubMed]
  70. Pluck, J.; Bolte, S.; Lenz, K.; Melchers, P.; Heim, K. Arbeitsgruppe Deutsche child behavior checklist. Elternfragebogen über das Verhalten von Kindern und Jugendlichen; deutsche Bearbeitung der Child Behavior Checklist (CBCL/4-18). Einführung und Anleitung zur Handauswertung. Einführung Anleit. Handauswertung 1998, 2, 301–312. [Google Scholar]
  71. Bird, H.R.; Canino, G.; Gould, M.S.; Ribera, J.; Rubio-Stipec, M.; Woodbury, M.; Huertas-Goldman, S.; Sesman, M. Use of the Child Behavior Checklist as a Screening Instrument for Epidemiological Research in Child Psychiatry: Results of a Pilot Study. J. Am. Acad. Child Adolesc. Psychiatry 1987, 26, 207–213. [Google Scholar] [CrossRef]
  72. Cierpka, M.; Frevert, G. Die Familienbögen: Ein Inventar zur Einschätzung von Familienfunktionen; Hogrefe, Verlag f. Psychologie: Göttingen, Germany, 1994. [Google Scholar]
  73. Dalgard, O.S.; Dowrick, C.; Lehtinen, V.; Vazquez-Barquero, J.L.; Casey, P.; Wilkinson, G.; Ayuso-Mateos, J.L.; Page, H.; Dunn, G.; the Odin Group. Negative life events, social support and gender difference in depression. Soc. Psychiatry Psychiatr. Epidemiol. 2006, 41, 444–451. [Google Scholar] [CrossRef]
  74. Kocalevent, R.-D.; Berg, L.; E Beutel, M.; Hinz, A.; Zenger, M.; Härter, M.; Nater, U.; Brähler, E. Social support in the general population: Standardization of the Oslo social support scale (OSSS-3). BMC Psychol. 2018, 6, 1–8. [Google Scholar] [CrossRef]
  75. Cicchetti, D.V.; A Sparrow, S. Developing criteria for establishing interrater reliability of specific items: Applications to assessment of adaptive behavior. Am. J. Ment. Defic. 1981, 86, 127–137. [Google Scholar]
  76. Dempster, A.P.; Laird, N.M.; Rubin, D.B. Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B Methodol. 1977, 39, 1–22. [Google Scholar]
  77. Reupert, A.; Goodyear, M.; Maybery, D. Engaging with, and understanding children whose parents have a dual diagnosis. Child Adolesc. Ment. Health 2011, 17, 153–160. [Google Scholar] [CrossRef]
  78. Wiegand-Grefe, S.; Jeske, J.; Bullinger, M.; Plass, A.; Petermann, F. Quality of life of children with psychiatrically ill parents: Relationship between characteristics of parental disorder and health-related quality of life of the children from the parents’ perspective. Z. Psychiatr. Psychol. Psychother. 2010, 58, 315–322. [Google Scholar]
  79. Cleaver, H.; Unell, I. Children’s Needs-Parenting Capacity: Child Abuse, Parental Mental Illness, Learning Disability, Substance Misuse, and Domestic Violence; The Stationery Office: London, UK, 2011. [Google Scholar]
  80. Grové, C.; Reupert, A.; Maybery, D. The Perspectives of Young People of Parents with a Mental Illness Regarding Preferred Interventions and Supports. J. Child Fam. Stud. 2016, 25, 3056–3065. [Google Scholar] [CrossRef]
  81. Klassen, A.; Miller, A.R.; Fine, S. Agreement between parent and child report of quality of life in children with attention-deficit/hyperactivity disorder. Child Care Health Dev. 2006, 32, 397–406. [Google Scholar] [CrossRef] [PubMed]
  82. Robitail, S.; Simeoni, M.-C.; Erhart, M.; Ravens-Sieberer, U.; Bruil, J.; Auquier, P. Validation of the European Proxy KIDSCREEN-52 Pilot Test Health-Related Quality of Life Questionnaire: First Results. J. Adolesc. Health 2006, 39, 596.e1–596.e10. [Google Scholar] [CrossRef] [PubMed]
  83. Vance, Y.H.; Jenney, M.E.; Eiser, C.; Morse, R.C. Issues in measuring quality of life in childhood cancer: Measures, proxies, and parental mental health. J. Child Psychol. Psychiatry Allied Discip. 2001, 42, 661–667. [Google Scholar] [CrossRef]
Table
Table 1. Characteristics of the parents with a mental illness.
Table 1. Characteristics of the parents with a mental illness.
Characteristicsn (%)M (SD)
Sociodemographic data
 Age (in years) 1 41.59 (6.77)
 Female 1102 (76.1%)
 Number of children 1 2.14 (0.94)
 Married 175 (56.4%)
 School education 1
    11–13 years education39 (30.5%)
    10 years education60 (46.9%)
    9 years education26 (20.3%)
    No secondary education3 (2.3%)
Risk and protective factors
 Psychiatric diagnosis (ICD-10) 2, a
    F10–F192 (1.5%)
    F20–F294 (3.0%)
    F30–F3975 (56.0%)
    F40–F4815 (11.2%)
    F60–F6937 (27.6%)
    F90–F981 (0.7%)
 Comorbidity (ICD-10) 2, a56 (41.8%)
 Symptom burden (BSI, raw score) 1, b109 (83.2%)1.36 (0.72)
 Parental Coping (FKV-LIS, raw score) 1, c
    Depressed processing style 15.43 (3.79)
    Active problem-oriented coping 16.12 (3.78)
    Distraction and self-growth 13.85 (3.31)
    Religiosity and quest for meaning 13.11 (3.38)
    Trivialization and wishful thinking 7.87 (3.13)
 Parental health-related quality of life (EQ-5D, raw score) 1, d 0.57 (0.22)
Note. n = 134. Questionnaire-related scores were based on raw data; for measures, see text (Measures). 1 based on parent self-reports. 2 based on proxy-ratings by clinicians. a International Classification of Diseases (ICD-10) codes: mental and behavioral disorders due to psychoactive substance use (F10–F19), schizophrenia, schizotypal, and delusional disorders (F20–F29), mood (affective) disorders (F30–F39), neurotic, stress-related and somatoform disorders (F40–F48), disorders of adult personality and behavior (F60–F69), behavioral and emotional disorders with onset usually occurring in childhood and adolescence (F90–F98); b Brief Symptom Inventory (BSI); c Freiburg Questionnaire of Coping with Illness (FKV-LIS); d parental HRQoL (EQ-5D).
Table
Table 2. Characteristics of the children and adolescents aged 8–18 years.
Table 2. Characteristics of the children and adolescents aged 8–18 years.
Characteristicsn (%)M (SD)
Sociodemographic data
 Age (in years) 2 12.19 (3.09)
 Female 2110 (56.1%)
 Shared household with parent with a mental illness 2165 (86.4%)
 (Step) siblings 1164 (82.4%)
Risk and protective factors
 Mental health problems (CBCL 4-18, raw score) 2, a 37.90 (25.72)
 Social support (OSSS-3, raw score) 2, b 10.25 (2.40)
 Family functioning (FB-A, raw score) 2, c 38.63 (14.70)
Health-related quality of life
 Child self-report (KIDSCREEN-10, raw score) 1, d 37.84 (6.71)
 Parent proxy-report (KIDSCREEN-10, raw score) 2 36.60 (5.70)
Note. n = 198 children. Questionnaire-related scores were based on raw data; for measures, see text (Measures). 1 based on child self-reports. 2 based on parent proxy-reports. a Child Behavior Checklist 4–18 (CBCL 4-18); b Oslo Social Support Scale (OSSS-3); c General Family Questionnaire (FB-A); d child HRQoL (KIDSCREEN-10).
Table
Table 3. Average HRQoL in children from the parents’ perspective.
Table 3. Average HRQoL in children from the parents’ perspective.
CategoriesModel-Based
Adjusted Mean95% CIICC
KIDSCREEN-27 Subscale
 Physical well-being43.81 ***(42.42, 45.22)0.25
 Psychological well-being43.04 ***(41.05, 45.04)0.13
 Autonomy and parents48.61(47.03, 50.20)0.71
 Social support and peers46.63 **(44.75, 48.51)0.41
 School environment46.94 **(45.18, 48.70)0.25
KIDSCREEN-10 Index44.09 ***(42.57, 45.61)0.40
Note. n = 189. CI = confidence interval, ICC = intraclass correlation coefficient; calculations were based on average T-scores and analyzed with a linear mixed model, for measures, see text (Measures). ** p < 0.01; *** p < 0.001.
Table
Table 4. Average HRQoL in children from the children’s perspective.
Table 4. Average HRQoL in children from the children’s perspective.
CategoriesModel-Based
Adjusted Mean95% CIICC
KIDSCREEN-27 Subscale
 Physical well-being43.23 ***(41.69, 44.78)0.27
 Psychological well-being46.41 **(44.39, 48.43)0.33
 Autonomy and parents49.57(47.79, 51.34)0.16
 Social support and peers48.27(46.42, 50.12)n.a. 1
 School environment49.13(47.30, 50.97)0.16
KIDSCREEN-10 Index47.42 **(45.59, 49.25)0.33
Note. n = 136. CI = confidence interval, ICC = intraclass correlation coefficient; calculations were based on average T-scores and analyzed with a linear mixed model, for measures, see text (Measures). 1 The ICC could not be estimated and was thus set to zero. ** p < 0.01; *** p < 0.001.
Table
Table 5. Prediction of HRQoL (KIDSCREEN-10, raw score) in children and adolescents aged 8–18 years.
Table 5. Prediction of HRQoL (KIDSCREEN-10, raw score) in children and adolescents aged 8–18 years.
CategoriesModel 1
CoefficientsSE
Fixed Effects
 Intercept30.06 ***0.49
 Child-related predictors
    Child psychopathology (CBCL 4-18, raw score)−0.09 ***0.01
    Social support (OSSS-3, raw score)0.72 ***0.15
    Female0.940.62
    Age (years)−0.37 *0.15
    Age by gender-identity0.100.19
 Family-related predictors
    Parental psychopathology (BSI, raw score)−1.62 **0.61
    Family functioning (FB-A, raw score)−0.040.03
    Parental coping (FKV-LIS, raw score)
    Depressed processing style0.090.11
    Active problem-oriented coping−0.070.11
    Distraction and self-growth−0.220.13
    Religiosity and quest for meaning0.000.11
    Trivialization and wishful thinking0.160.13
Random Effects
 Variance of residuals9.66 ***1.98
 Variance of intercepts7.76 **2.56
 ICC0.45
Model Fit
 Deviance1047.44
  χ 2 (df)98.98 (12) ***
 BIC 1057.71
Note. n = 183. SE = standard error, ICC = intraclass correlation coefficient, χ 2 (df) = chi-squared (degrees of freedom), BIC = Bayesian information criterion; all calculations were based on raw data and analyzed with a linear mixed model; all metric predictors were mean-centered; for measures, see text (Measures). * p < 0.05; ** p < 0.01; *** p < 0.001.
Table
Table 6. Child–parent agreement on HRQoL in children and adolescents aged 8–18 years.
Table 6. Child–parent agreement on HRQoL in children and adolescents aged 8–18 years.
CategoriesICC ConsistencyICC Absolute Agreement
ICC (95% CI)ICC (95% CI)
KIDSCREEN-27 Subscale
 Physical well-being0.46 *** (0.31, 0.59)0.46 *** (0.31, 0.59)
 Psychological well-being0.45 *** (0.30, 0.58)0.43 *** (0.28, 0.56)
 Autonomy and parents0.42 *** (0.26, 0.55)0.42 *** (0.26, 0.55)
 Social support and peers0.40 *** (0.24, 0.54)0.34 *** (0.13, 0.51)
 School environment0.49 *** (0.35, 0.61)0.49 *** (0.35, 0.61)
KIDSCREEN-10 Index0.46 *** (0.31, 0.59)0.45 *** (0.30, 0.58)
Note. n = 127. CI = confidence interval, ICC = intraclass correlation coefficient; for measures, see text (Measures). *** p < 0.001.
Table
Table 7. Predictors of child–parent disagreement on HRQoL (KIDSCREEN-10) in children and adolescents aged 8–18 years.
Table 7. Predictors of child–parent disagreement on HRQoL (KIDSCREEN-10) in children and adolescents aged 8–18 years.
Fixed EffectsbSE
Intercept3.84 *1.88
 Child-related predictors
    Child psychopathology (CBCL 4-18, raw score)−0.05 *0.02
    Female−3.88 **1.21
    Age (years)0.780.63
    Age by gender-identity−0.420.42
Family-related predictors
 Family functioning (FB-A, raw score)−0.050.04
 Parental health-related quality of life (EQ-5D, raw score)5.373.16
 Parental psychopathology (BSI, raw score)0.981.13
Note. n = 124, F = 5.25. df = 7/116. Model fit: adjusted R2 = 19.5%. b = unstandardized coefficient SE = standard error, CI = confidence interval; all calculations were based on raw data and analyzed with a linear mixed model; all metric predictors were mean-centered; for measures, see text (Measures). * p < 0.05; ** p < 0.01.
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Radicke, A.; Barkmann, C.; Adema, B.; Daubmann, A.; Wegscheider, K.; Wiegand-Grefe, S. Children of Parents with a Mental Illness: Predictors of Health-Related Quality of Life and Determinants of Child–Parent Agreement. Int. J. Environ. Res. Public Health 2021, 18, 379. https://doi.org/10.3390/ijerph18020379

AMA Style

Radicke A, Barkmann C, Adema B, Daubmann A, Wegscheider K, Wiegand-Grefe S. Children of Parents with a Mental Illness: Predictors of Health-Related Quality of Life and Determinants of Child–Parent Agreement. International Journal of Environmental Research and Public Health. 2021; 18(2):379. https://doi.org/10.3390/ijerph18020379

Chicago/Turabian Style

Radicke, Alina, Claus Barkmann, Bonnie Adema, Anne Daubmann, Karl Wegscheider, and Silke Wiegand-Grefe. 2021. "Children of Parents with a Mental Illness: Predictors of Health-Related Quality of Life and Determinants of Child–Parent Agreement" International Journal of Environmental Research and Public Health 18, no. 2: 379. https://doi.org/10.3390/ijerph18020379

APA Style

Radicke, A., Barkmann, C., Adema, B., Daubmann, A., Wegscheider, K., & Wiegand-Grefe, S. (2021). Children of Parents with a Mental Illness: Predictors of Health-Related Quality of Life and Determinants of Child–Parent Agreement. International Journal of Environmental Research and Public Health, 18(2), 379. https://doi.org/10.3390/ijerph18020379

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