Predicting well-being longitudinally for mothers rearing offspring with intellectual and developmental disabilities.

An almost exclusively pathological focus on the outcomes for families rearing children with intellectual or other developmental disabilities (IDD) characterized research in the mid-20th century. Investigators focused on the poor outcomes associated with stress in the families, primarily at one time period or over short spans of time (Helff & Glidden, 1998). However, more recently there has been an emerging consensus that most families demonstrate resilience and that both short- and long-term outcomes reflect that although problems exist, they are often accompanied, or balanced, by rewards and satisfactions (Crnic, Pedersen y Arbona, Baker, & Blacher, 2009; Floyd, Costigan & Piazza, 2009; Glidden, 2012). Critical to this consensus has been the large number of studies from a variety of countries that have all arrived at similar conclusions (Glidden & Schoolcraft, 2007; Hastings & Taunt, 2002; Jokinen & Brown, 2005). Nonetheless, there is substantial variation in the balance of rewards and problems within research samples. Given that psychology’s scientific objectives are to understand and explain behavior, it is essential that investigators identify the important antecedents that predict such variation in the outcomes of interest. These antecedents can immediately precede the outcome, such as the antecedent of a child’s diagnosis and the outcome of a parent’s initial response to it. Alternatively, the antecedents can also occur decades earlier, as in the case of a mother’s childhood and young adult experiences with disability predicting her reactions to the transition to adulthood of her own son or daughter with disabilities. If the latter, longitudinal methodologies where the same individuals are followed over time are a powerful tool for understanding how contemporary reactions to offspring life circumstances develop and are maintained. Models of family functioning often include features that may account for such development over time, and lead to predictions about the type and degree of change. For example, the ABCX and Double ABCX models (Hill, 1949, 1958; McCubbin & Patterson, 1983) have had heuristic value, generating substantial empirical research in families with individuals with disabilities (Paynter, Riley, Beamish, Davies, & Milford, 2013; Thompson, Hiebert-Murphy, & Trute, 2013; Weiss, Robinson, Fung, Tint, Chalmers, & Lunsky, 2013). In its most basic form, the A factor specifies variables that represent demands or stressors on the family; the B factor identifies resources that families possess, and the C factor is defined by appraisal, viz., the family’s perception of the stressor or demands. These three factors act together, resulting in adaptation that can range from highly positive to highly negative. The double aspect of the model indicates that the process is iterative, and that stressors can increase or decrease, resources can be used up or multiplied, and perceptions of stressors can change, as the family appraises not only the original demands, but also changes over time, including their own reactions. In research involving families with children or adults with disabilities, many of the variables investigated can be classified as stressors, resources, perceptions of stressors, and adaptation outcomes that fit this Double ABCX model. For example, antecedent or predictor variables that have been studied as stressor variables have included diagnostic category (Corrice & Glidden, 2009; Hodapp, Ricci, Ly, & Fidler, 2003), child adaptive behavior (Blacher & McIntyre, 2006; Griffith, Hastings, Oliver, Howlin, Moss, Petty, & Tunnicliffe, 2011), and child maladaptive behavior (Hauser-Cram, Warfield, Shonkoff, & Krauss, 2001; Nalavany, Glidden, & Ryan, 2009). Family resources have frequently been defined by parent education (Glidden, Bamberger, Turek, & Hill, 2010; Hodapp, Fidler, & Smith, 1998), family income (Shapiro, Blacher, & Lopez, 1998), marital status ((Dellve, Samuelsson, Tallborn, Fasth, & Hallberg, 2006; Glidden, 1991), and parental coping strategies (Glidden, Billings, & Jobe, 2006; Seltzer, Greenberg, & Krauss, 1995). Various parental personality traits have been viewed as relevant to the C factor of stressor perception (Glidden & Schoolcraft, 2003; Shapiro et al., 1998). Outcome variables representing family adaptation and adjustment have also been numerous, reflecting both parental negative outcomes, such as stress and depression (Glidden & Schoolcraft, 2007; Singer, 2006), as well as positive outcomes such as subjective well-being and quality of life (Glidden, 2012; Turnbull, Brown, & Turnbull, 2004). This high number of both antecedent and outcome variables utilized in past research suggests that a complex constellation of qualities and characteristics of both children and their parents or families explain parental outcomes in families of children with IDD. Moreover, although some research has identified antecedent variables that predict multiple outcome variables, it is also likely that the best combination of predictors is quite different for different outcomes, implying an even greater complexity. For example, Floyd et al. (2009) summarized results from a 15-year longitudinal study of families with young adults with either mild or moderate intellectual disability. The level of disability predicted some, but by no means all, the variables of interest: No differences between IDD groups were found for parent contact and involvement or the level of participation in family activities. However, the participants with mild IDD were more likely to have been married and have a child and to be employed. Seltzer and Krauss (1989) also reported variation in predictor-outcome patterns. In a sample of 203 older mothers caring for adult offspring with IDD, they found that maternal characteristics such as age, education, income, and marital status were better predictors of physical health and life satisfaction, whereas offspring characteristics, such as type and severity of disability, predicted more variance in parenting stress and burden. For both types of outcome variables, antecedent family and child characteristics, some of which had been in place for many years, successfully predicted later measures, yet each outcome variable was better predicted by a somewhat different subset of antecedents. Not only will different variables predict different outcomes, but the relation between predictors and outcomes may also change over time, adding another layer of complexity to predictor-outcome relationships. In earlier research with a sample overlapping with the one in the current study, Glidden and Jobe (2009) measured depression four times over 19 years in mothers who had knowingly adopted children with IDD and in a comparable sample of mothers and fathers who had similar children by birth. Depression was initially measured when the children were first diagnosed or adopted, and three more times at approximately six-year intervals. They found large and highly significant differences initially, with adoptive mothers reporting low scores, indicating non-depressed functioning, and birth mothers reporting much higher scores, with approximately half the sample meeting criterion for clinical depression. In the three subsequent data collections, the birth mother scores had declined dramatically and were no longer significantly different from those of the adoptive mothers. Thus, adoptive-birth status, an initially powerful predictor of depression, no longer had predictive value for the outcome of depression at later time periods, after the crisis of diagnosis had subsided. This variation evident in previous research led us to focus on three related aims in the current study: Our primary aim was to determine the degree to which a set of variables measured when children were young would predict well-being and depression outcomes for their mothers over a 20-year period. The predictors were selected based on their prominence in theories of family functioning and adaptation, all of which generally focus on family, parent, and child characteristics (Blacher, 2001; McCubbin & Patterson, 1983). We also considered the predictive effectiveness of these variables in previous empirical findings. A second and related aim was to explain the variability in the effectiveness of these predictors, exploring the patterns of variability and assessing to what degree these patterns could lead to the generation of hypotheses for future study. A component of understanding outcome constructs is to know what antecedent variables predict them. Finally, a third aim was to determine the degree to which these predictors were relatively stable for the same outcomes over time. This third aim will be addressed in a comparison of the data reported in the current study with previously published research from earlier times of the same longitudinal sample.