The sibling relationship is the longest most people will enjoy in their lifetimes and is central to the everyday lives of children.
A new Tel Aviv University and University of Haifa study finds that relationships between children and their siblings with intellectual disabilities are more positive than those between typically developing siblings.
The research examines the relationships of typically developing children with siblings with and without intellectual disabilities through artwork and questionnaires.
It was conducted by Prof. Anat Zaidman-Zait of the Department of School Counseling and Special Education at TAU’s Constantiner School of Education and Dr. Dafna Regev and Miri Yechezkiely of the University of Haifa’s Graduate School of Creative Art Therapies. The study was recently published in Research in Developmental Disabilities.
“Having a child with a disability in a family places unique demands on all family members, including typically developing siblings,” Prof. Zaidman-Zait explains. “Although challenges exist, they are often accompanied by both short- and long-term positive contributions.
“Through our research, we found that relationships among children with siblings with intellectual disabilities were even more supportive than those among typically developed siblings.
Specifically, we found that children with siblings with intellectual disabilities scored higher on empathy, teaching and closeness and scored lower on conflict and rivalry than those with typically developing siblings.”
Until now, research on how having a sibling with a developmental disability affects children’s social-emotional and behavioral outcomes generated mixed findings. At times, the findings suggested that having a sibling with developmental disabilities led to greater variability in typically developing children’s behavior and adjustment.
“But these studies did little to tap into the inner worlds of children, which really can only be accessed through self-expression in the form of art or self-reporting, independent of parental intervention, which is the route we took in our study,” Prof. Zaidman-Zait says.
The scientists assessed some 60 children aged 8-11, half with typically developing siblings, half with intellectually disabled siblings, through drawings and a questionnaire about their relationships with their siblings. Mothers of both sets of siblings were also asked to answer a questionnaire about their children’s sibling relationship quality.
“We drew on the basic assumption that artistic creation allows internal content to be expressed visually and that children’s self-reports have special added value in studies measuring sibling relationship qualities, especially in areas where parents might have less insight,” Prof. Zaidman-Zait says.
Both sets of typically developing children, with and without siblings with intellectual disabilities, were asked to draw themselves and their siblings. Licensed art therapists then used several set criteria to “score” the illustrations: the physical distance between the figures; the presence or absence of a parent in the illustration; the amount of detail invested in either the self-portrait or the sibling representation; and the amount of support given to a sibling in the picture.
The children were then asked to complete the Sibling Relationship Questionnaire, which assessed the feelings of closeness, dominance, conflict and rivalry they felt for their siblings.
Reviewing the children’s illustrations and questionnaires, as well as the questionnaires completed by the children’s mothers, the researchers found that the children with siblings with intellectual disabilities scored significantly higher on empathy, teaching and closeness in their sibling relationship and scored lower on conflict and rivalry in the relationships than those with typically developing siblings.
At times, the findings suggested that having a sibling with developmental disabilities led to greater variability in typically developing children’s behavior and adjustment.
“Our study makes a valuable contribution to the literature by using an art-based data gathering task to shed new light on the unique aspects of the relationships of children with siblings with intellectual disabilities that are not revealed in verbal reports,” Prof. Zaidman-Zait concludes. “We can argue that having a family member with a disability makes the rest of the family, including typically developing children, more attentive to the needs of others.”
The researchers hope their study, supported by The Shalem Foundation in Israel, will serve as a basis for further research into art-based tools that elicit and document the subjective experience of children.
DD (Marquis, Hayes, & McGrail, 2019). Studies have examined effects upon sibling wellbeing (Emerson & Giallo, 2014), stress (Nixon & Cummings, 1999), adjustment (Giallo & Gavidia-Payne, 2006), anxiety (Pollard, Barry, Freedman, & Kotchick, 2013), physical health (Hogan, Park, & Goldscheider, 2003), behavior (Platt, Roper, Mandleco, & Freeborn, 2014) and mental health (Giallo, Gavidia-Payne, Minett, & Kapoor, 2012; Goudie, Havercamp, Jamieson, & Sahr, 2013; Lovell & Wetherell, 2016).
However, findings have often been conflicting (Marquis et al., 2019), with some studies reporting no deleterious effect upon siblings (Cuskelly & Gunn, 2006; Dempsey, Llorens, Brewton, Mulchandani, & Goin-Kochel, 2012; Tomeny, Barry, & Bader, 2012), some reporting a positive effect upon siblings (Connors & Stalker, 2003) and some reporting negative effects (Constantino et al., 2006; Hogan et al., 2003).
Conflicting findings may be due to methodological differences among studies (Marquis et al., 2019; Stoneman, 2009). Studies often have differing theoretical underpinnings and/or interests of the researchers (Hodapp, Glidden, & Kaiser, 2005; Stoneman, 1993, 2005, 2009); differ in outcome measures (Constantino et al., 2006; Dempsey et al., 2012; Griffith, Hastings, & Petalas, 2014; Hogan et al., 2003; Nixon & Cummings, 1999; Stoneman, 1993, 2009); differ in the type of disability examined and how DD is defined (Marquis et al., 2019); and use differing measurement tools (Marquis et al., 2019).
In addition, studies of siblings of children with a DD have often been limited by methodological issues of small sample size (Burke & Fujiura, 2013; Hodapp et al., 2005), the practice of combining different types of DD to increase sample size (Marquis et al., 2019), convenience sampling (Burke & Fujiura, 2013), availability and use of an appropriate control group (Hodapp et al., 2005; Stoneman, 2009), lack of accurate data on the incidence and prevalence of DD (Fujiura, Rutkowski-Kmitta, & Owen, 2010; Lin et al., 2013, 2014), reliance upon self-reports (Marquis et al., 2019), and whether or not the study included variables other than having/not having a sibling with a DD (Marquis et al., 2019; Rossiter & Sharpe, 2001).
There is evidence of complex interactions among social determinants of health, the characteristics of the child with the DD, characteristics of the non-DD sibling, and family factors which can be related to the mental health of siblings of children who have a DD (Marquis et al., 2019).
Studies have included different variables, among these are: sex of the non-DD sibling (Walton & Ingersoll, 2015); sex of the child with the DD (Begum & Blacher, 2011; Petalas, Hastings, Nash, Lloyd, & Dowey, 2009); type of DD (Constantino et al., 2006; Fisman, Wolf, Ellison, & Freeman, 2000; Hastings, 2007; Pilowsky, Yirmiya, Gross-Tsur, & Shalev, 2007; Pollard et al., 2013); birth order (Dyke, Mulroy, & Leonard, 2009; Tomeny, Barry, & Bader, 2014); number of children in the family (Mulroy, Robertson, Aiberti, Leonard, & Bower, 2008); family income measures (Emerson & Giallo, 2014; Giallo & Gavidia-Payne, 2006; Mulroy et al., 2008; Neely-Barnes & Graff, 2011; Platt et al., 2014); and neighborhood characteristics (Emerson & Giallo, 2014). However, there is little agreement in the literature on the effects of these variables and there are few studies using population level data to study the range of variables (Marquis et al., 2019).
This study used population level administrative data from the Ministry of Health in British Columbia, Canada. The data are collected from physicians for billing purposes and contains information on the reason for each visit made by a patient to a physician or hospital expressed as a diagnostic code (ICD-9 or ICD-10).
These data were used to examine the relationship between having a sibling with a DD and the mental health of siblings who do not have a DD. Administrative data have many benefits for studying disability related issues and address several of the weaknesses of previous studies. The most significant advantage of using administrative data is the size of the data set (Burke & Fujiura, 2013; Glasson & Hussain, 2008; Jutte, Roos, & Brownell, 2011).
Large data set size can improve the generalizability of the findings, reduce problems with selection bias (Burke & Fujiura, 2013), enhance the capacity to study low prevalence associations and relatively small population (Andresen, 2011; Hogan, Msall, & Drew, 2006; Jutte et al., 2011), and provide the ability to select varying control groups (Glasson & Hussain, 2008). In addition, administrative data provide information on the prevalence of DD (Lin et al., 2014; Marquis, McGrail, Hayes, & Tasker, 2018), include data on demographics, reduce recruitment problems (Andresen, 2011), maintain privacy (Glasson & Hussain, 2008), and do not rely on self-reports.
By linking administrative data with other data sources additional variables which may have an association with outcomes can be included in analyses. At the time this study was initiated no other literature examining the mental health of siblings was found that used large samples and population-based measures that are not based upon self-reports.
This study adds to the body of research by using population level data to ask the question:
In British Columbia (B.C.), Canada, is the mental health (as measured by use of health services) of siblings of children who have a developmental disability different from the mental health of siblings of children who do not have a developmental disability?
There is evidence in the literature that having a sibling with a DD is associated with poor mental health of siblings without a DD. However, much of the evidence has been conflicting (Marquis et al., 2019). The purpose of this study was to add to the population health perspective of the relationships between the presence of a child with a DD and the mental health of siblings by using data available through administrative health data in B.C. This is the first time in Canada that administrative health data have been used to study the health of siblings of children who have a DD.
At the population level in B.C. there were significantly higher odds of a diagnosis of depression or another mental health problem in sisters and brothers of children who have a DD compared to the siblings of children who do not have a DD. In addition, siblings who have a diagnosis of depression or a mental health problem and who have a sibling with a DD, use the health care system more often for their diagnosed depression or mental health problem compared to siblings of children who do not have a DD and who have a diagnosis of depression or a mental health problem.
In addition, this study added to the research on associations between income, the sex of the sibling without the DD, birth order and mental health outcomes. These are important additions to the literature as previous studies have often had conflicting results.
Differing results between this study and previous studies may in part be due to differing methodology and sample size. Many previous studies used poorly defined populations of disabled children or poorly defined comparison groups, were done over short time periods, did not differentiate between sisters and brothers, and/or relied solely upon self-reported health data (Stoneman, 2009).
This study expanded the research by using population level administrative data, a variety of defined variables, diagnoses provided by physicians, definitions of DD according to International Classification of Disease codes, and several large comparison populations.
Differing results may also be due to the complexity of studying families, many previous studies have not accounted for the complexity inherent in studies of families. By stratifying the analyses according to gender (sister/brother) and age (younger and older siblings) and by including variables such as socioeconomic measures, complex inter-relationships were found in this study that may not have been apparent in previous studies.
Similar to studies that found lower incomes among families with a child with a DD (Parish, Rose, Grinstein-Weiss, Richman, & Andrews, 2008; Parish, Seltzer, Greenberg, & Floyd, 2004), in this study, there was a greater proportion of siblings of a child with a DD in the lowest neighborhood income quintiles compared to siblings of children without a DD.
This study found some evidence of increased odds of depression or a mental health diagnosis in lower income groups. However, this study found that the association between having a sibling with a DD and the odds of depression or another mental health problem remained when income measures were held constant, indicating that although income plays a role in the outcomes of depression and mental health problems, that other factors also play a role.
Limitations of this study include limitations specific to the algorithm and codes used to identify children with a DD. As Lin, Balogh, et al. (2013) found, the number of people identified with a DD in administrative data is affected by the algorithm used. In this study children with a DD were identified as those with at least two occurrences of the ICD-9 codes identifying DD in MSP data or at least one occurrence of DD identified by ICD-9 or ICD-10 codes in hospital separation data.
There is also evidence that the quality and completeness of physician coding is greater for three digit ICD-9 codes than for four and five digit ICD-9 codes (Hu, 1996). This study used some four and five digit ICD-9 codes to identify particular disabilities. Therefore, there may have been under-representation of some disabilities including FAS and some of the rarer disabilities such as Prader-Willi syndrome.
However, the estimate of prevalence of children who have a DD in B.C. found in this study and reported elsewhere (Marquis et al., 2018) was equal to or higher than prevalence reported in the literature. The prevalence in 1990 was 0.68% and the prevalence in 2000 was 1.45% (Marquis et al., 2018), compared to prevalence estimates of 0.72–1.10% reported for children in the province of Manitoba (Ouellette-Kuntz et al., 2009). The prevalence findings in this study therefore appear to be in line with rates previously reported in the literature.
This study used two measures of income, neighborhood income quintiles provided by Statistics Canada, and MSP subsidy levels. The neighborhood divisions used in the neighborhood income quintiles include the variety of incomes which may occur within a geographic area.
This obscuring of the heterogeneity of individual incomes may be particularly problematic in rural areas where the “neighborhood” may be a very large geographic area. In addition, because the last available neighborhood income quintile and MSP subsidy values were used results regarding the relationship with socioeconomic status must be interpreted with caution.
This study was unable to account for all variables which may affect sibling mental health; particularly it could not account for the effects of potentially important individual variables such as ethnicity, marital status of parents, severity of the disability, child behavior, stigma experienced, and parenting styles. However, this study did incorporate a range of both individual level and population level variables.
This is the first study to link family members in administrative data for the purpose of studying the effects of developmental disability. This is both a strength and a limitation of the research. The unique character of the research adds significantly to the literature, however, there has been no independent validation of the methodological approach.
Lastly, large data sets can have problems associated with large sample size fallacy (Lantz, 2013; Lin, Lucas, & Shmueli, 2013; Veldhuizen, Pasker-De Jong, & Atsma, 2012). As recommended in the literature (Lin, Lucas, et al., 2013; Veldhuizen et al., 2012), this issue was addressed in this study by stratifying the samples, reporting odds ratios and confidence intervals and by assessing the results in light of previous literature.