Relationships Among Risk, Sense of Coherence,and Well-Being in Parents of ChildrenWith and Without Intellectual DisabilitiesMalin B. Olsson*,, Pernilla Larsman, and Philip C. Hwang

*The Vrdal InstituteThe Swedish Institute for Health Sciences; and University of Gothenburg, Gteborg, Sweden

Abstract The authors studied the nature and function of the relationships of the comparative level of risk, sense of coherence (SOC),and well-being, over time, in mothers and fathers of preschool children with and without intellectual disabilities (IDs). Thehypothesis that SOC functions as a moderator between risk and well-being was tested. Parents of children with IDs (mothers: n = 62(46 at follow-up) and fathers: n = 49 (37 at follow-up)) and control parents (mothers: n = 178 (131 at follow-up) and fathers: n = 141(97 at follow-up)) answered self-report measures on risk factors (i.e., child behavior problems, negative impact on the family andsocioeconomic situation) and sense of coherence. Well-being and quality of life were used as outcomes, and were measured at baselineand at a one-year follow-up. The hypothesis of moderation was tested conducting multiple linear regression analyses. The level ofwell-being was moderately stable over the two time points, with parents of children with ID having lower level of well-being thancontrol parents both initially and after one year. Well-being was also related to level of SOC and cumulative risk with parentsexperiencing lower SOC or more risk also reporting lower well-being. The hypothesis of SOC acting as a moderator in the relationbetween cumulative risk and well-being found some support in the longitudinal analyses, but only for well-being (BDI-2r) amongcontrol mothers.

Keywords: intellectual disabilities, parents, resilience, risk, sense of coherence

INTRODUCTION

Individual variation in the experience of parenting a childwith intellectual disability (ID) is evident, as well as individualvariation in outcome (Blacher & Baker, 2007; Erwin & Soodak,1995; Scorgie & Sobsey, 2000; Seltzer, Floyd, & Hindes, 2004;Singer, 2006; Stainton & Besser, 1998; White & Hastings, 2004)but we know very little about the processes leading to thesedifferences. A relevant theoretical construct to understandindividual differences in reaction to stressful life conditions isresilience. Resilience means that some individuals have a relativelygood psychological outcome despite suffering risk experiencesthat would be expected to bring about a serious adverse outcome(Luthar, Sawyer, & Brown, 2006; Rutter, 2006). Resilience startswith the recognition of the individual variation in peoplesresponse to the same experiences and there is evidence that muchof the variation in psychological outcomes can be accounted forby the cumulative effects of risk and protective factors.

The two prerequisites for talking about resilience are (1) thatthe system or individual studied has been challenged by stress or

risk; and (2) that the system or individual studied has managed toreach a favorable outcome despite the adversities experienced.There is agreement that parents of children with ID experienceheightened stress (Most, Fidler, Laforde-Booth, & Kelly, 2006;Plant & Sanders, 2007; Reddon, McDonald, & Kysela, 1992;Singer, 2006) and there is also evidence of positive outcome in amajority of parents (Olsson & Hwang, 2008; Singer, 2006). Thefew studies that have used family quality of life (QoL) as anoutcome suggests that 65% of mothers rate their quality of life asmoderate to excellent (Summers et al., 2007) and these figurescorrespond to the studies using depression as the outcome, whichusually find that approximately 65% of parents of children withID do not report symptoms of depression (Singer, 2006). Theseconsistent findings can be used to argue for resilience as a suitabletheoretical framework for research on individual differences inparents of children with IDs. In the present study, we examinedhow risk factors (socioeconomic situation, negative impact on thefamily, and child behavior problems) and outcomes (well-beingand QoL) are affected by a proposed protective factor (sense ofcoherence, SOC).

The risk factors addressed in the present study are factors thathave been shown to have a strong relation to poorer well-being inparents of children with ID. There is much research showingthat the presence of behavior problems in the child is a majorrisk factor for decreased maternal well-being (Baker et al., 2003;

Received October 23, 2007; accepted July 26, 2008Correspondence: Malin B. Olsson, Department of Psychology, GteborgUniversity, Box 500, Gteborg 405 30, Sweden. Tel: +46 31 786 42 93;E-mail: malin.olsson@psy.gu.se

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Blacher & McIntyre, 2006; Eisenhower, Baker, & Blacher, 2005;Emerson, 2003; Hastings & Brown, 2002; Herring et al., 2006;Lewis et al., 2006; Olsson & Hwang, 2001; Singer, 2006). Thereis also evidence of a strong relation between socioeconomic riskand poorer maternal well-being (Eisenhower & Blacher, 2006;Emerson, Hatton, Llewllyn, & Graham, 2006). Research onresilience has shown that risk factors tend to cluster and theexperience of cumulative risk has a larger effect on outcome oradaptation than have single measures of risk (Luthar et al., 2006).

Researchers focusing on resilience have suggested that amongthe most important resiliency factors is stress processing abilities;that is, an individuals initial appraisal of the event and its emo-tional meaning, ones ability to sufficiently regulate ones emo-tions and arousal to initiate problem solving and gather moreinformation, and the employment of coping behaviors (Green-berg, 2006; Masten & Obradovic, 2006). A variety of copingbehaviors have been found in parents of children with ID in theirefforts to deal with a variety of demands (Beresford, 1996; Dykens& Hodapp, 2001; Glidden, Billings, & Jobe, 2006; Judge, 1998;Kim, Greenberg, Seltzer, & Krauss, 2003; Luescher, Dede, Gitten,Fennell, & Maria, 1999; Reddon et al., 1992) and a larger reper-toire and more use of coping is related to more positive adapta-tion (Taanila, Syrjl, Kokkonen, & Jrvelin, 2002).

The use of some types of coping behaviors has been shown tobe linked to personality factors (Glidden et al., 2006). Studies ondifferent personality factors have shown that more optimisticoutlooks, higher SOC, more internal locus of control and lowerneuroticism is related to higher well-being in parents of childrenwith ID (Baker, Blacher, & Olsson, 2005; Glidden & Schoolcraft,2003; Glidden et al., 2006; Hassall & Rose, 2005; Hastings, 2002;Oelofsen & Richardson, 2006; Olsson & Hwang, 2002; Ylvn,Bjrck-Akesson, & Granlund, 2006). These empirical results fromparents of children with ID seem to support Antonovskys theoryof SOC (Antonovsky, 1987). He suggested that the strength inpeople with high SOC is not that they are especially successful inusing one or the other kind of coping strategy, but that theyapproach the world with the generalized expectation that stressorsare meaningful and comprehensible. Instead of rigidly relying onone coping strategy, people with a strong SOC are characterized byflexibility. Antonovsky (1987) developed his theory to understandwhat makes people manage their lives despite high levels of stressvery similar to the concept of resilience. From interviews withholocaust survivors, he concluded that although different in type,shape, duration, and function, resistance resources all have onething in common: they contribute to make stressors understand-able, manageable, and meaningful.

The cumulative experience of stressors as understandable,manageable, and meaningful will, with time, create a strong SOCin the individual. SOC is defined as a global orientation thatexpresses the extent to which one has a pervasive, enduring thoughdynamic feeling of confidence that (1) the stimuli deriving fromones internal and external environments in the course of living arestructured, predictable, and explicable; (2) the resources are avail-able to meet the demands posed by these stimuli; and (3) thesedemands are challenges, worthy of investment and engagement(Antonovsky, 1987, pp. 1618). Based on analyses of interviews,Antonovsky developed the orientation to life scale consisting of29 items, designed to measure SOC (Antonovsky, 1987). So far,only a few studies have used the concept of SOC in research on

parents of children with ID, but high SOC has been shown to berelated to better well-being in both mothers and fathers of childrenwith ID (Oelofsen & Richardson, 2006; Olsson & Hwang, 2002),and parents of children with ID have also been shown to have lowerSOC than control parents (Oelofsen & Richardson, 2006; Olsson &Hwang, 2002) with mothers having lower SOC than fathers. Onestudy found that parents of children with ID with higher SOClevels had fewer registered days of absence due to sickness (Hedov,Wikblad, & Annern, 2006). From this research, it seems clear thatthere exists a positive relationship between SOC and well-beingbut the nature and function of this relationship has not beenstudied. In the present study, SOC is investigated as a possibleprotective factor, moderating the relationship between the experi-ence of cumulative risk and well-being.

Researchers have typically addressed the main effects of pre-dictor variables on parental psychological well-being. However,the psychological theories on stress (e.g., Lazarus, 1999) andresilience (i.e., Rutter, 2006), suggest that the interrelationshipsbetween variables are likely to be crucial in understanding theimpact of stress on well-being. Family researchers in ID havebegun to examine the interrelationships between personality orrelated cognitive variables that may relate to coping with thechallenges of child rearing. Baker et al. (2005) found parentaloptimism to moderate the strong relationship between childbehavior problems and parental depression and marital adjust-ment, especially for mothers. When child behavior problems werehigh, mothers who were less optimistic reported lower scores onmeasures of well-being than did mothers who were more opti-mistic (Baker et al., 2005). Hastings and Brown (2002) found thatself-efficacy mediated the effect of child behavior problems onmothers anxiety and depression whereas it functioned as amoderator between child behavior problems and anxiety anddepression for fathers. Fathers with high self-efficacy were lessanxious than were those with low self-efficacy when their childhad high levels of behavior problems. When their child had lowlevels of behavior problems, fathers self-efficacy had no effect ontheir anxiety. The difference in the mechanism of action of self-efficacy and optimism between mothers and fathers of childrenwith ID emphasizes the importance of studying mothers andfathers separately.

In the present study, we test the hypothesis that SOC func-tions as a protective factor (a moderator) between cumulative riskand parental well-being, over time. In general terms, a moderatoris a qualitative or quantitative variable that affects the directionand/or strength of the relationship between an independent orpredictor variable and a dependant or criterion variable (Baron &Kenny, 1986). The action of moderators is dependent on thecontext of risk. At low levels of risk, they have no effect becausethere is nothing to protect against. However, under conditions ofhigh risk, they reduce negative outcomes (Hastings & Brown,2002). According to Antonovsky (1987), it is the strength of SOCin the individual encountering a potentially stressful event thatwill predict whether the outcome will be harmful, neutral, orhealth-promoting. Even under high stress or high level of risk,parents with high SOC may appraise the situation as a challengeand adapt positively, while parents with low SOC are more likelyto appraise the situation as a threat and be at increased riskof lower well-being. If this is the case, SOC will function as amoderator between stress/negative impact and poor well-being.

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The purpose of the present study was to investigate the natureand function of the relationship among level of risk, SOC, andwell-being, over time, in mothers and fathers of preschool chil-dren with and without intellectual disabilities. The hypothesisthat SOC functions as a moderator between risk and well-beingwas tested. We propose that this is true if high risk is morestrongly related to poor well-being in parents with low SOC thanin parents with high SOC.

METHODS

Participants and Procedure

In the southwest of Sweden, parents of children with ID wererecruited through centers providing support to families with chil-dren with disabilities. We wanted to contact parents as soon asthey learned about their childs difficulties and use the timefrom when they had first been in contact with the service centers(rather than the childs age) as inclusion criteria. The centersmailed information about the study to new families who metthe following inclusion criteria: (1) the child should have beenreferred to the support centers within the last 6 months; and (2)the child should be diagnosed with autism or ID or be underevaluation for either condition.

Information was sent out to approximately 150 families.Parents from 70 families indicated their interest in taking part inthe study by mailing back an answer card with their contactinformation to the research team. Mothers and fathers were thenmailed an extensive survey in the same envelope but wereinstructed to answer the questions independently of each other.We provided separate prepaid answer envelopes so that mothersand fathers could mail their answered surveys separately of eachother. If parents were not living together, the parent who receivedthe mailed survey was asked to distribute the survey to the otherparent. Reminders were sent out after two weeks; after anothertwo weeks, a reminder together with a new survey was mailed tothe parents who had not answered. Each parent received a giftcertificate equivalent to 10 euros after their completed surveyswere received.

Complete surveys were received from families of 62 childrenwith ID (response rate 41%), composed of 62 mothers and 49fathers. The children had a primary diagnosis of autism (n = 16),Down syndrome (n = 9), ID-NOS (n = 6), under evaluation(n = 10), and other diagnoses (e.g., specific chromosomal abnor-malities; n = 19). The children had received their diagnoses atdifferent ages (9 received their diagnosis at birth, 9 during the firstyear of life, 9 during the second year of life, 13 during their fourthyear of life, 4 during their fifth year of life, and the rest of thechildren were either undiagnosed or had received their diagnosislater). Parents indicated on a 5-point scale how their child per-formed compared with peers on fine and gross motor skills, con-centration, speech, and interaction with peers. The functionalstatus of the children was significantly below the children in thecontrol group (t(222) = -15.9, p < 0.01).

Addresses of 500 randomly selected control children wereobtained from the SPAR-register (Statens Person-och AdressRegistera nationwide register including all individuals regis-

tered as living in Sweden). The control children were

the high well-being group), and those scoring below one standarddeviation of the mean (called the low well-being group).

Overall quality of life was measured by two questions: Ingeneral how would you describe your health? rated from 4(= excellent) to 1 (= poor) and How satisfied are you, overall,with your life situation right now? rated from 7 (= completelysatisfied) to 1 (= very dissatisfied). Answers on the two questionswere summed. Cronbachs alpha was 0.52.

Risk Factors

Socioeconomic situation and hardship were evaluated by calcu-lating the number of items that the parent would like to possess orparticipate in but could not afford. The items related to socialactivities (six items) and clothing (five items) (adapted afterEmerson et al., 2006). Parents indicated for each item 0 if theycould afford it, 1 if they occasionally could not afford it, and 2 ifthey could not afford it (Cronbachs alpha 0.77). The parent also

indicated if the family had received government support duringthe last year (scored 0 if they had not, 1 it they had occasionallyreceived welfare, and 2 if they had regularly relied on welfare), andif the family lacked savings equivalent to at least 1,400 euros(scored 0/1). The sum of the 11 hardship items and the sum of thetwo items on welfare and saving items were standardized andsummed together to a measure on socioeconomic risk.

Child behavior problemswere measured by 10 of the 66 items ofthe behavior problem subscale of the Nisonger scale, see Table 3(Aman, Tass, Rojahn, & Hammer, 1996). Parents were asked toindicate on a 4-point scale ranging from 0 (= the behavior did notoccur or was not a problem) to 3 (= the problem occurred a lot orwas a severe problem). Cronbachs alpha was 0.66.

Negative impact of child on the family was measured by 17questions from the Family Impact Questionnaire (Donenberg &Baker, 1993). Parents were asked to rate on a 4-point scale howmuch their child had an impact on the parent or the familycompared with other children his or her age (0 = not at all to3 = very much).The questions dealt with negative impact on sociallife (11 items, e.g., My family avoids social situations (restaurantand public places) more because of his/her behavior) and nega-tive feelings toward the child (6 items, e.g.,My child makes me feelmore frustrated and angry). Cronbachs Alpha was 0.83.

A cumulative risk index was formed by adding the socioeco-nomic risk index, child behavior problems, and negative impactof the child. This cumulative risk index was used as a predictorvariable in the multiple linear regression analyses. For someanalyses, three groups were formed; those scoring within onestandard deviation above and below the mean were called themedium-risk group, those scoring above one standard deviationof the mean were called the high-risk group, and those scoringbelow one standard deviation of the mean were called the no-riskgroup.

Protective Factor

Sense of coherence was measured with the short orientationto life questionnaire (13 items) (Antonovsky, 1991). Items were

TABLE 2Examples of items in BDI-2r

Happiness/sadnessa.) I could not possibly be happier.b.) I am happy all the time.c.) I am happy much of the time.d.) I do not feel sad.e.) I feel sad much of the time.f.) I am sad all the time.g.) I am so sad or unhappy that I cant stand it.

Energya.) I am more energized than ever to do anything.b.) I have more energy to do much more than I used to do.c.) I have more energy than I used to have.d.) I have as much energy as ever.e.) I have less energy than I used to have.f.) I dont have enough energy to do very much.g.) I dont have enough energy to do anything.

Self-like/self-dislikea.) I am very pleased with myself.b.) I am content with myself.c.) I have more confidence in myself than before.d.) I feel the same about myself as ever.e.) I have lost confidence in myself.f.) I am disappointed in myself.g.) I dislike myself.

Control of cryinga.) I seldom feel like crying.b.) I can control my crying like a normal person does.c.) I cry less than I used to.d.) I dont cry any more than I used to.e.) I cry more than I used to.f.) I cry over every little thing.g.) I feel like crying, but I cant.

TABLE 3The 10 items used from the Nisonger scale

Hits or slaps own head, neck, hands, or other body partsRocks body or head back and forth repetitivelyHas rituals such as head rolling or floor pacingHarms self by scratching skin or pulling hairRepeatedly flaps or waves hands, fingers, or objects (such as

pieces of string)Gouges self, puts things in ears, nose, etc., or eats inedible

thingsRepeats the same sound, word, or phrase over and over againRepeatedly bites self hard enough to leave tooth marks or break

skinOdd repetitive behaviors (e.g., stares, grimaces, rigid postures)Engages in meaningless, repetitive body movements

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rated on a 7-point Likert scale (e.g., Do you have the feeling thatyou dont really care about what goes on around you? andAre your everyday chores a source of satisfaction?). The shortversion of the SOC scale has shown good psychometric propertiesin previous studies, testretest reliability (0.520.97), and excel-lent internal consistency (0.740.91) (Antonovsky, 1993; Schny-der, Bchi, Sensky, & Klaghofer, 2000). The mean from five Israeliand U.S. studies using SOC-13 on adult, normal populationsreported by Antonovsky (1993) was 66. Mean score in the presentstudy was 70.4 and Chronbachs alpha was 0.87. For some analy-ses, three groups were formed; those scoring within one standarddeviation above and below the mean were called the mediumSOC group, those scoring above one standard deviation of themean were called the high SOC group, and those scoring belowone standard deviation of the mean were called the low SOCgroup.

Statistical Analysis

Differences in proportions were calculated by Chi-square anddifferences between the subgroups were analyzed using analysis ofvariance with Scheff post hoc test. The hypothesis of moderationwas tested conducting multiple linear regression analyses usingSPSS version 16.0. In these analyses, well-being and QoL, respec-tively, were treated as the dependent variables, while SOC, cumu-lative risk and their interaction were treated as the independentvariables and entered simultaneously into the model. In thesemodels, a statistically significant interaction effect betweencumulative risk and SOC were considered indicative of modera-tion, that is, if such interaction effects were found they wereinterpreted as indicating that the relationship between cumula-tive risk and well-being was moderated by SOC.

Separate analyses were conducted for the subgroups mothersof children with ID, control mothers, fathers of children with ID,and control fathers. For all tests, statistical significance was set toa < 0.05.

RESULTS

Analyses of Means

Means and standard deviations for each of the separate riskmeasures, SOC, and the two outcome measures are listed inTable 4. Parents of children with ID scored higher on socioeco-nomic risk and negative family impact than did control parents,and mothers of children with ID scored higher than did controlparents on child behavior problem. Mothers of children with IDscored lower on SOC and the two well-being measures comparedwith control parents and fathers of children with ID.

Parental Well-Being Measures: Interrelationships and Stability

There were moderate relationships among the measures ofparental well-being (see Tables 5 and 6). At initial assessments,measures of well-being (BDI-2r) and QoL correlated betweenr = 0.53 and r = 0.64 in the different subgroups, and at follow-upmeasurements, these associations were similar; between r = 0.42and r = 0.60 in these groups. These measures of well-being arethus correlated, but because the associations are only moderate insize subsequent analyses treat them as separate domains.

Stability over time for these measures (see Tables 5 and 6) wasalso moderate in size both for well-being (BDI-2r; where r varied

TABLE 4Means and standard deviations on sense of coherence (SOC), negative family impact (FIQ), socioeconomic (SES) risk, childbehavior problem (child BP), and well-being (BDI-2r and QoL)

ID mothersN = 62

ID fathersN = 49

Control mothersN = 178

Control fathersN = 141

ANOVA resultsM SD M SD M SD M SD

SOCa 62.0 9.3 65.6 7.3 65.5 8.1 65.7 7.5 F(3, 426) = 3.70, p < 0.05FIQb 20.7 10.4 18.6 8.4 9.8 4.6 10.3 4.3 F(3, 426) = 68.83, p < 0.05SES riskc 0.6 2.0 -0.0 1.6 -0.8 1.6 -0.4 1.3 F(3, 426) = 6.24, p < 0.05Child BPd 2.3 3.0 1.4 2.0 0.4 0.7 0.6 1.1 F(3, 426) = 26.58, p < 0.05BDI-2r (T1)a 96.3 13.9 105.4 10.9 104.8 12.8 107.3 12.4 F(3, 426) = 10.96, p < 0.05BDI-2r (T2)a 98.8 11.6 104.8 9.6 105.9 12.9 107.3 10.3 F(3, 307) = 6.20, p < 0.05QoL (T1)a 7.7 1.7 8.6 1.4 8.9 1.5 8.8 1.5 F(3, 426) = 11.12, p < 0.05QoL (T2)c 7.9 1.1 8.5 1.2 8.8 1.4 8.7 1.3 F(3, 307) = 4.40, p < 0.05aID mothers differ from the other parents (p < 0.05).bID parents differ from control parents (p < 0.05).cID mothers differ from control parents (p < 0.05).dID parents differ from control parents (p < 0.05) and ID mothers differ from ID fathers (p < 0.05).ID, intellectual disability; QoL, quality of life; T1, Time 1; T2, Time 2.

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between 0.40 and 0.62 in the subgroups), and for QoL (where rvaried between 0.40 and 0.65). There were no differences in sta-bility in the outcome measures between mothers and fathers orbetween control and ID parents.

Cumulative Risk, SOC, and Well-Being

As can be seen from Tables 5 and 6, there were bivariate cor-relations between SOC and well-being and QoL at baseline, andbetween SOC at baseline and well-being and QoL at follow-up.There were also correlations between cumulative risk and well-being and QoL at both baseline and follow-up.

Parents who experienced medium cumulative risk and whoalso had low SOC more often had low well-being compared withthose who had higher levels of SOC (see Table 7). Among thosewith medium risk and high SOC, there was a larger group withhigh well-being compared with those with lower levels of SOC.Parents who experienced high cumulative risk and who also had

low SOC more often had low well-being compared with thosewho had higher levels of SOC. From Table 7, it could be said that65% (40 of the 60 parents in the high-risk group) were resilient,that is, despite experiencing high levels of stress they had mediumor high well-being.

Analyses of Moderation

The hypothesis that SOC moderates the relationship betweencumulative risk and well-being was addressed conducting mul-tiple linear regression analyses. The results of these analyses arepresented in Tables 8 and 9. A statistically significant interactioneffect between baseline cumulative risk and SOC on well-being atfollow-up was found among the control mothers, suggesting thatSOC may moderate the relation between cumulative risk andwell-being in this group. Within this group, a higher cumulativerisk was related to lower well-being, but only when SOC was low.A similar pattern was found among the ID mothers but this was

TABLE 5Bivariate correlations between cumulative risk, sense of coherence (SOC), and well-being (BDI-2r and QoL)a

Risk T1 SOC T1 BDI T1 QoL T1 BDI T2 QoL T2

Risk T1 r = -0.35** r = -0.29** r = -0.32** r = -0.30** r = -0.27**SOC T1 r = -0.31* r = 0.58** r = 0.48** r = 0.35** r = 0.18*BDI T1 r = -0.18 r = 0.68** r = 0.60** r = 0.55** r = 0.34**QoL T1 r = -0.47** r = 0.59** r = 0.64** r = 0.36** r = 0.40**BDI T2 r = -0.39** r = 0.59** r = 0.62** r = 0.54** r = 0.60**QoL T2 r = -0.44** r = 0.32* r = 0.22 r = 0.55** r = 0.46**

*p < 0.05.**p < 0.01.aCorrelations for control mothers (n = 178 for baseline measurements and n = 131 for follow-up measurements) are presented above the diagonal, whilecorrelations for mothers of children with intellectual disability (n = 62 for baseline measurements and n = 46 for follow-up measurements) are presented belowthe diagonal.QoL, quality of life; T1, Time 1; T2, Time 2.

TABLE 6Bivariate correlations between cumulative risk, sense of coherence (SOC), and well-being (BDI-2r and QoL)a

Risk T1 SOC T1 BDI T1 QoL T1 BDI T2 QoL T2

Risk T1 r = -0.18* r = -0.37** r = -0.26** r = -0.45** r = -0.14SOC T1 r = -0.35* r = 0.56** r = 0.44** r = 0.40** r = 0.21*BDI T1 r = -0.35* r = 0.52** r = 0.64** r = 0.62** r = 0.25*QoL T1 r = -0.33* r = 0.35* r = 0.53** r = 0.42** r = 0.55**BDI T2 r = -0.34* r = 0.27 r = 0.54** r = 0.44** r = 0.42**QoL T2 r = -0.22 r = 0.30 r = 0.26 r = 0.52** r = 0.59**

*p < 0.05.**p < 0.01.aCorrelations for control fathers (n = 141 for baseline measurements and n = 97 for follow-up measurements) are presented above the diagonal, while correlationsfor fathers of children with intellectual disability (n = 49 for baseline measurements and n = 37 for follow-up measurements) are presented below the diagonal.QoL, quality of life; T1, Time 1; T2, Time 2.

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not statistically significant. The hypothesis of SOC as a moderatorwas not supported by the analyses in the other groups or for QoL.

DISCUSSION

Principal Findings

The level of well-being was moderately stable over the twotime points, with parents of children with ID having a lower levelof well-being than control parents, both initially and after oneyear. Well-being was also related to level of SOC and cumulativerisk, with parents experiencing lower SOC or more risk reportinglower well-being. The hypothesis of SOC acting as a moderator inthe relation between cumulative risk and well-being found somesupport in the longitudinal analyses, but only for well-being(BDI-2r) among control mothers.

Sex Role Differences

In accord with previous studies, this study too, found mothersof children with ID to report lower levels of well-being and morenegative impact of the child with ID compared with the fathers(Olsson & Hwang, 2001). Furthermore, the patterns of relationsbetween the variables analyzed were different for fathers com-pared with that for mothers. It seems as if fathers are affected andreact differently than mothers of children with ID (Baker et al.,

2005; Hastings & Brown, 2002). It is possible that the consistentfinding of mothers experiencing more distress than do fathers isdue to the fact that mothers take on a larger part of the extra careand practical work that the child with disabilities requires(Bristol, Gallagher, & Schopler, 1988; Moes, Koegle, Schreibman,& Loos, 1992; Olsson & Hwang, 2006). They more often give uptheir jobs and feel unable to pursue their own interests (Breslau,Staruch, & Mortimer, 1982). The mothers self-competence mayalso be more related to the parenting role than that of the father,and mothers may therefore be more vulnerable when stress anddifficulties arise in the parenting domain. It may also be thatfathers show their distress in other ways than mothers, in waysnot captured by our measures. In order to better understand theprocesses behind paternal well-being, fathers need to be includedand studied separately in studies using other instruments than thetraditional outcome measures.

Theoretical and Clinical Implications

The findings give support for the usefulness of a risk andresilience perspective in both research and clinical work withfamilies of children with ID. Parents who experienced high cumu-lative risk had lower well-being than those experiencing lowerlevel of risk. Taking the families whole situation into account inthe planning of support and services therefore seems important.The results of this study suggest that interventions should havetheir primary focus on decreasing the known risk factors such associoeconomic stress and difficult child behavior. As many pre-vious studies have found, most parents of children with ID hadhigh well-being and QoL (Singer, 2006; Summers et al., 2007), butthere were also more parents of children with ID who had lowwell-being compared with control parents. In the analyses ofmoderation, SOC did function as a protective factor, but only forwell-being (BDI-2r) among control mothers. For mothers of chil-dren with ID, the pattern was the same and the lack of support formoderation can in part be due to the small sample size. Otherreasons for the lack of support for SOC as a moderator could bethat the short version of the SOC scale may not have capturedSOC accurately, the variation in well-being may have been toosmall, the procedure of controlling for well-being level at baselinein the analyses of well-being at follow-up may have reduced mostof the variance that SOC could have explained, and SOC may notbe a relevant construct for understanding individual variation inresponse to stressors over time. Because of the lack of support forour hypothesis, it seems important to further explore the conceptof SOC as well as other possible protective factors and theirrelationship to individual variation in well-being and adaptationover time in parents of children with ID.

SOC had a strong main effect in cross-sectional analyses sug-gesting that increasing parental SOC may affect well-being or theother way around. In Antonovskys original theory, SOC isdescribed as a stable, personality-like construct (Antonovsky,1987), but more recent empirical work questions this assumption(Eriksson & Lindstrm, 2005). Viewed longitudinally, SOCincreases with age, but SOC has also been found to decrease inresponse to negative life events (Volanen, Suominen, Lahelma,Koskenvuo, & Silventoinen, 2007). An initially strong SOC doesnot seem to protect SOC from decreasing as a result of negative

TABLE 7Frequencies of parents in the total sample who fell into the low,medium, and high groups on well-being (BDI-2r), cumulativerisk, and sense of coherence (SOC)

Well-being

Low Medium High Total

Low riskLow SOC 1 1 0 2Medium SOC 1 8 6 15High SOC 0 1 4 5Total 2 10 10 22

Medium riska

Low SOC 20 29 0 49Medium SOC 17 207 23 247High SOC 0 33 19 52Total 37 269 42 348

High riskb

Low SOC 12 9 0 21Medium SOC 8 30 0 38High SOC 0 0 1 1Total 20 39 1 60

a(c2 (4, N = 348) = 88.8, p < 0.01).b(c2 (4, N = 60) = 68.0, p < 0.01).

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life events (Volanen et al., 2007). Studies on parents of childrenwith ID have also found that mothers of children with ID havelower SOC than control mothers (Oelofsen & Richardson, 2006;Olsson & Hwang, 2002). As SOC does not seem to be as stableas previously thought, it may also be possible to support andincrease SOC in parents by interventions focusing on strength-ening parents sense of manageability, comprehensibility, andmeaningfulness. The potential moderator as well as mediatoreffects of SOC need to be investigated further in larger longitu-dinal studies, using the full 29-item SOC scale instead of theSOC-13. Intervention studies using SOC as an outcome measurewould also be interesting.

Strengths and Weaknesses of the Study

The major strengths of our study are: (1) the homogenous agegroup; (2) the inclusion of fathers; (3) the use of two outcomemeasures that allow for differentiation in the positive as well asthe negative end of the well-being spectrum (BDI2-r and QoL);(4) testing of a well-grounded theoretical model; and (5) inclu-sion of longitudinal data.

The main weaknesses of the study are (1) the relatively lowresponse rate and the resulting small sample size; and (2) thereliance on self-report measures. The size, as well as the compo-sition of the sample is of importance when it comes to drawingaccurate conclusions on interaction effects. Larger sample sizeshave greater power to detect such effects. In the present study, thesample size is rather small especially when analyses are carried outwithin the subgroups. The subgroups are also unequal in size andthe differences in sample size may be one explanation for why wefind more statistically significant effects for control mothers thanin any other group because this is the group with the mostindividuals.

Families of children with ID as well as control families do notseem to be easily motivated in taking part in research, and there isthe risk of systematic response bias because parents with lowereducation, non-Swedish background, and poorer well-being maybe less likely to answer a rather extensive survey. There weresignificantly more answers from families from the rural areas andless from the city of Gothenburg, which may have to do with alarger proportion of immigrants and the greater pace and stressthat seems to be evident in the cities compared with rural areas.We only collected data with self-report measures and it is well

TABLE 8Results of regression analyses predicting well-being (BDI-2r) and quality of life (QoL) among control mothers and mothers ofchildren with intellectual disability (ID)

Predictor variables

Standardized regression coefficients for control mothers Standardized regression coefficients for ID mothers

BDI T1 BDI T2a QoL T1 QoL T2b BDI T1 BDI T2a QoL T1 QoL T2b

Cumulative risk -0.14 -0.09 -0.18* -0.18 0.02 -0.25 -0.40* -0.22Sense of coherence 0.55* 0.01 0.43* -0.07 0.71* 0.29 0.66* 0.02Interaction effect -0.07 0.18* -0.02 0.02 -0.03 -0.08 -0.26 -0.03

*p < 0.05.aThe model predicting well-being at T2 controls for the effects of well-being at T1.bThe model predicting QoL at T2 controls for the effects of QoL at T1.T1, Time 1; T2, Time 2.

TABLE 9Results of regression analyses predicting well-being (BDI-2r) and quality of life (QoL) among control fathers and fathers of childrenwith intellectual disability (ID)

Predictor variables

Standardized regression coefficients for control fathers Standardized regression coefficients for ID fathers

BDI T1 BDI T2a QoL T1 QoL T2b BDI T1 BDI T2a QoL T1 QoL T2b

Cumulative risk -0.25* -0.16 -0.15 -0.02 -0.22 -0.15 -0.17 0.03SOC 0.49* 0.02 0.38* -0.06 0.50* -0.08 0.16 0.16Interaction effect 0.06 0.13 0.11 -0.01 -0.11 -0.04 0.23 -0.15

*p < 0.05.aThe model predicting well-being at T2 controls for the effects of well-being at T1.bThe model predicting QoL at T2 controls for the effects of QoL at T1.T1, Time 1; T2, Time 2.

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established that mood, response style, and personality may biasanswers on questionnaires (Shaugnessy, Zecjmeister, & Zech-meister, 2006; Watson, 2004). A mother with high well-being, in agood mood, on a good day, is more likely to rate her own health,her child, and her life situation more positively than a parent withlower well-being, and a depressed mood on a bad day, causing aseeming correlation between measures at one time point thatmay not correspond to an actual or objective correlation. Thisphenomenon will cause lack of stability and reliability betweenpoints of measurement. Research relying on self-report measuresshould be interpreted with caution. Another central question iswhether well-being and SOC are really different concepts. If youcan have low SOC scores without having low well-being, this isone indication that SOC and well-being are different entities. Inthe present study, the majority of those with low SOC did nothave low well-being, suggesting that well-being and SOC could beunderstood as separable constructs.

CONCLUSIONS

The results gave limited support to the theoretically derivedhypothesis regarding SOC as a protective factor. They suggest thatinterventions directed at increasing parental well-being and QoLin parents of children with ID should focus on both lowering thenegative impact of risk factors and strengthening the positiveimpact of protective factors. In order to better understand whatthese protective factors may be, we need more research exploringthe interrelationships among risk factors, possible protectivefactors, and outcomes. Important in such studies would be theinclusion of outcome measures (allowing for variation in boththe positive and the negative end of the well-being spectrum) aswell as the use of larger samples, including separate analyses formothers and fathers.

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