Environmental Influences on Happiness

Environmental Influences on Happiness Critical Evaluation: The Contagion Effect of Happiness The thought of happiness had sparked much interest among past psychologists. Dated back in the 20th century, happiness had been a rising area of concern. However, many studies have yet to converge on a universal definition of happiness. Despite so, several longstanding studies permit the definition of happiness to be a subjective well-being construct consisting of positive affect, negative affect and life satisfaction (Bartels Boomsma, 2009; DeNeve Cooper, 1998; Diener, 2009). In recent years, the factors that predict happiness has caught great amount of attention in the realm of psychology. Specifically, the question lies in whether happiness can be contagious either through the social network or genetic influences. A recent paper by Matteson, McGue, and Lacono (2013) has offered insights to address the discrepancy between social network and genetic influences. The central tenet of the paper investigates the contagion hypothesis of happiness. Specifically, it seeks to find the impact of the well-being of family members on individual well-being. In an attempt to account for previous ethological findings by Fowler and Christakis (2008), the authors had adopted an adoption design as an alternative test of shared environment effects on happiness. A sample consisting of 284 adoptive, 208 non-adoptive and 123 mixed families were selected from the Sibling Interaction and Behaviour Study (SIBS; McGue, Keyes, Sharma, Elkins, Legrand, Johnson, 2007). Results revealed that family members have no similar levels of happiness when they are not genetically related. In fact, the authors have noted that the findings demonstrated the consistency with behavioural genetic literature among genetically related famil y. Hence, challenging the contagion hypothesis. In view of these findings, the current paper will review the findings of Matteson et al. (2013) to further justify and suggest drawbacks that may have been oblivious to the authors. In addition, this paper will employ various key works to provide auxiliary for the review of methodology, results and discussion sections of Mattesson et al. (2013). In Fowler and Christakis (2008) study, a social network analysis was employed to study the impact of happiness level of people in an individual’s social network. However, although Mattesson et al. (2013) had also focused on the contagion hypothesis of happiness, they have noted that both genes and environment could have played a role in the influence of happiness among people. Thus, a superior component of Matteson’s study was that they drew on the adoption design to include both genetic and environmental effects in the investigation of the contagion hypothesis. This had allowed them to examine if genetically unrelated family members in a shared environment would have similar levels of happiness (Matteson et al., 2013). However, an adoptive family environment may not be representative of the general family environment (Lemery Goldsmith, 1999). Rueter, Keyes ,Iacono, and McGue (2009) have noted that the interactions between families could have differed between adoptive and non-adoptive families. This suggests that interaction factors could have impacted child adjustments. In addition, McGue et al. (2007) found that there is an increased in parent-child conflict in adoptive as compared to non-adoptive families. Such factors could have influenced the well-being of adoptees. As a result, the inclusion of adoptees for the contagion hypothesis illustrates that the authors could have oversight the assumption of family environment. Also, it should be noted that instead of a shared environment in adoptive studies, siblings might experience a unique environment instead. A unique environment is an environment that is not shared by siblings or families (Neisser, Boodoo,Bouchard, Boykin, Brody, Ceci, Halpern, Loehlin, Perloff, Sternberg, Urbina, 1996). According to Braungart, Plomin, DeFries and Fulker (1992), siblings raised in the same family might experience a unique environment whereby both siblings may have diverse range of peers, attend different education systems and may experience different style of bonds with their parents. As a result, the authors failed to notice that a unique environment may be experienced by siblings in an adoption design. Future research in this area could include the use of family design (Lemery Goldsmith). Family design enables the assessment of siblings, parent versus off-springs. half-siblings, uncle versus nephew, auntie versus niece, grandparent versus grandchild and first cousin pairs (Pike, McGuire, Hetherington, Reiss, Plomin, 1996). This would allow more in-depth opportunity to investigate both shared and unique environments on the contagion hypothesis as it investigates a variety of relationships as compared to the limited parent-child and sibling relationships in an adoption design. Previous work by Fowler and Christakis (2008) utilized the items from the Center of Epidemiological Studies Depression Scale (CES-D; Radloff, 1977) as a measure of happiness. Although the CES-D was developed to examine depression, items pertaining to happiness were chosen to question about experiences and feelings on happiness in the past one week. In contrary, Matteson et al. (2013) had employed a Multidimensional Personality Questionnaire to examine happiness. The MPQ is a personality measure which assesses cognitive and affective components of life. Diener (2009) have noted that test-retest reliabilities have demonstrated that a correlation of .54 to .73 accounts for stability in well-being scales of MPQ. Thus, the use of MPQ could be a reliable measure for the well-being construct of the affective component on happiness. However, the authors could have overlooked the purpose of MPQ as a measure of trait instead of state happiness (Stones, Hadjistavopoulos, Tuuko, Kozma, 1995). As MPQ was mainly developed as a personality measure, the items were inclined towards trait-like properties of well-being and happiness. Thus, the results on happiness construct could have actually reflected the trait happiness instead of state-level happiness. Tellegen (1982) have noted that MPQ is a self report questionnaire to measure the disposition to feel good. Also, the utilization of this measure in other studies tends to yield genetic influences on happiness (Weiss, Bates, Luciano, 2008). In other words, MPQ was oriented towards the assessment of trait happiness instead of state-level happiness. Therefore, the use of MPQ by Matteson et al (2013) may have been an oversight as they failed to recognize that the use of MPQ could have skewed the data towards the findings of trait personality instead of happiness on the ba sis of situations. Hence, resulting in their findings of familial correlations among genetically related instead of unrelated family members. It is suggested that the authors could have employed the Oxford Happiness Questionnaire (OHQ) in conjunction with the MPQ to assess the subjective well-being of participants (Hills Argyle, 2002). The OHQ is a 29 item measure that taps on the self-esteem, sense of purpose, social interest and sense of humour. The combination of both OHQ and MPQ would serve as a better stringent methodology to elicit an equal amount of trait and state-level happiness. Extensive studies by McGue et al. (2007) have demonstrated that the Siblings Interaction and Behaviour Study (SIBS) provides a good basis for the selection of participants for adoption design. Participants from the SIBS consisted of adoptive, non-adoptive and mixed families. This allowed identifications of characteristics between biological and adoptive families. Matteson et al. (2013) employed participants from the SIBS which is fairly representative for an adoption design. However, McGue et al. (2007) have noted that in order to differentiate adoptive and non-adoptive families in SIBS, they recruited participants on the basis of selection effects of certain factors. Evidence by Stoolmiller (1999) has shown that selection effects in a research study could actually affect participants who do and do not participate in the study. As cited in Matteson et al. (2013), McGue et al. (2007) have noted that after interviewing non-participants in adoptive and non-adoptive families, non-participating but eligible families differed minimally from participating families. However, the authors failed to recognize that McGue et al. (2007) were unable to interview 27% of non-participating families and this 27% could have differed significantly from the interviewed participating and non-participating families. Ruggles, Sobek, Alexander, Fitch, Goeken, and Hall (2004) concluded that this difference could have resulted in minimal sampling bias. Therefore, the details concer ning recruitment of SIBS sample could have inadvertently influence the results obtained. Furthermore, there are issues regarding the generalizability of the results presented by Matteson et al. (2013). The author did not report in the paper that SIBS samples were recruited from Minnesota only and not internationally. McGue et al. (2007) noted that adoptive families were ascertained from infant placements made by Minnesota agencies and non-adoptive families were determined by Minnesota State birth records. This suggests that the average sample were from Minnesota and hence, the results can only be generalizable to families of Minnesota. Therefore, the sample chosen could have implicated the results. A further consideration influencing the generalizability of the results presented by Matteson et al. (2013) is the choice of participants. Despite the participants being from the SIBS study, the authors did acknowledge that eligibility is limited to siblings of five years apart and adopted siblings who were adopted before age of two years (McGue et al., 2007). However, this age criteria suggest the limitation of generalizing the results to siblings of more than five years apart or adopted after the age of two years. Thus, the age criteria could have been an oversight by the authors as it suggests the inability to further generalize the results to others in a shared environment. Another limitation noted within the research was the onetime assessment of parent’s personality within the three years interval of the study. An established body of knowledge on personality have shown that personality changes throughout the lifespan (Haan, 1981). Findings by Haan (1981) revealed that re-test intervals on personality yielded that it does not remain stable overtime. In addition, Moss and Susman (1980) converged on a conclusion that the increased in time interval between personality tests contributes to the evidence of decreasing stability in personality. Matteson et al. (2013) have taken the changes in personality into consideration. In their study, the authors assessed well-being twice across a three years interval; allowing change over time. However, they had only assessed parent’s personality once. As mentioned, personality stability decreases over time. Thus, neglecting a second assessment of parent’s personality over the three years interval m ay have accounted for important information being overlooked and distorted the results. It is suggested that parent’s personality should be assessed at least twice as it constantly changes across the lifespan (Haan, 1981). Other methodological constraints in Matteson et al. (2013) paper include the use of results after a large dropout rate. Out of the adolescents participating at intake, only 83% returned and completed the well-being measure at follow-up. In other words, 17% of the adolescent have failed to complete the well-being measure at follow-up. It is possible that this 17% of dropout could have found the procedure to be dull or mundane which in turn, inflated the results attained. In addition, the authors had included the scores of the dropouts who had previously completed the intake but not the follow-up. Although they noted that the intake well-being scores of those who did not complete the well-being measure did not differ significantly from the well-being scores of those who did return, it should be known clearly that those results should not be taken into account as it reflected only the intake and not the follow-up scores (Matteson et al., 2013). Thus, it is inappropriate for the authors to make an assumption that the similar results would be obtained for the follow-up. Hence, the comparison was not clear and fair. As a result, the inclusion of the 17% at the intake results could have affected the entire study’s results. In summary, the findings suggest that shared environmental influences on happiness may not reflect contagion effects. While shared environment is an important aspect in the adoption design, it should also be noted that siblings in both adoptive and non-adoptive families may experience unique environments (Neisser et al., 1996). As such, biologically related siblings showed more support as genes could have played a higher factor in the influence of happiness as compared to environment. This suggests that the findings of the paper by Matteson et al. (2013) do provide some novel insights. However, intense research is required to understand more details between shared environment and unique environment. The authors have failed to recognize that despite the high reliability MPQ well-being scale might not be the most suitable measure for happiness. Future research is needed to examine a comprehensive well-being scale to measure happiness as evidence suggests that the use of MPQ well-being scale could have been skewed more towards trait happiness. References Bartels, M., Boomsma, D. I. (2009). Born to be happy? The etiology of subjective well- being. Behavior Genetics, 39, 605-615. Braungart, J. M., Plomin, R., DeFries, J. C., Fulker, D. W. (1992). 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