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WHAT MAKES PEOPLE HAPPY?. Social Support & Emotional Intelligence as Predictors of Subjective Wellbeing Emma Gallagher & Dianne Vella-Brodrick. W hat we already know …. Happiness is operationalised by Subjective wellbeing (SWB).
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WHAT MAKES PEOPLE HAPPY? Social Support & Emotional Intelligence as Predictors of Subjective Wellbeing Emma Gallagher & Dianne Vella-Brodrick
What we already know… • Happiness is operationalised by Subjective wellbeing (SWB). • SWB studies highlight factors that foster optimal psychological functioning. • Three components of SWB: Positive Affect (PA), Negative Affect (NA), Satisfaction with Life (SWL).
Sociodemographic variables & personality factors • Sociodemographic variables 8-20% (Argyle, 2001; Diener et al., 1999). • Personality factors consistently large proportion of variance. • e.g. 34% of unique variance in a general community sample (Gannon & Ranzijn, 2005).
Social support • Social support (SS) relates positively to SWB. • Some believe SS is necessary for SWB (Baumeister & Leary, 1995; Diener & Oishi, 2005, Diener & Seligman, 2002). • SS – thought to promote well-being through the provision of resources from one person to another which influence emotions, cognitions, and behaviours that in turn help people cope and enjoy life.
Social support considerations • Need to measure SS and all three components of SWB. • Source of SS(significant other, family, friends)over type of support(material aid). • Perception of SS over number of supports and/or receipt of support. • SWB + source & perception of SS + sociodemographic variables + personality factors
Emotional intelligence • Linked to both SWB and SS (Bar-On, 2005; Salovey, Bedell, Detweiler, & Mayer, 1999). • Relatively ignored in SWB research. • Eminent SWB researchers have suggested EI is ‘worth investigating’ for variance in SWB. • Investigations of SWB/EI relationship are relatively new.
Emotional intelligence • EI was labelled and modelled by Salovery and Mayer (1990). • Popularised by Goleman (1995). • Broadly defined as: the cognitive ability toperceive, manage, and regulate emotions within one’s self,and others, in ways that maximise positive cognitive and behavioural outcomes that result in more beneficial life outcomes(Bar-On, 2005; Mayer & Salovey, 1997; Salovey et al., 1999; Salovey & Mayer, 1990).
Emotional intelligence • Emerging evidence that EI can be taught, opposed to other SWB predictors such as personality(Emmerling & Goleman, 2003; Reshmi, 2006; Slaski & Cartwright, 2002; Stys & Brown, 2004). • Utility of EI complicated as more than one model has been proposed. • Conjecture regarding the discriminant validity of EI – now sufficient evidence showing discriminant validity(Bar-On, 2005; Brackett & Mayer, 2003; Ciarrochi, Chan & Bajgar, 2001; Ciarrochi, Chan, Caputi, 2000; Ciarrochi, Deane & Anderson, 2002; Gannon & Ranzijn, 2005; Lopes et al, 2004; Schette et al., 1998; Tett, Fox & Wang, 2005).
Emotional intelligence • EI has been shown to relate positively to SWL and PA. • SWL influenced by how clearly people understand emotion. • Controlling for well-known predictors of SWB provide clearer results for EI. • Research need: use well–respected SWB measures; measure 3 x components of SWB; and control for well-established predictors of SWB.
SWB, SS & EI • Underlying processes of SS and EI seem similar. • The moderator question is: Does the relationship between SSand SWB depend on an individuals’ level of EI?
Hypotheses That where sociodemographic variables and personality factors are controlled, SS from Significant Other, Family and Friends would significantly predict SWL, PA and NA. It was also hypothesised that where sociodemographic variables and personality factors are controlled, EI would significantly predict SWL, PA and NA. It was further hypothesised that EI would significantly influence the relationship between SS and SWB as measured by sources of support and SWL, PA and NA respectively, where the interaction effects between SS and EI would add significant variance to the prediction of SWB beyond main effects.
Participants • 267 adults 196 females, 71 males. • general population: who volunteered after reading explanatory statement. • Age 18-80 (M=41.52 years, SD=14.28). • 52.8% in relationships. • 72.6% were tertiary educated. • Income range $80-$2699 (gross) per week, modal income $1000 per week.
Response Type – all self report Plus: socio-dem questions Alpha (Original) This Study Item example # of Items Measures 5 point Likert Scale:very slightly or not at all to, extremely Positive & NegativeAffect Schedule– 2 subscales (PANAS) 20 10 e/s PA, (.88) .88 NA, (.87) .89 Indicate how you feel eg. interested Ref: Watson et al. (1988) 7 point Likert Scale: Strongly Disagree to, Strongly Agree I am satisfied with life Ref: Diener et al. (1985) Satisfaction With Life Scale (SWLS) 5 (.87) .89 Multidimensional Scale of Perceived Social Support - 3 subscales (MSPSS) 12 4 e/s 7 point Likert Scale: Very Strongly Disagree to, Very Strongly Agree There is a special person…when I am in need Ref: Zimet et al. (1988) SO: (.91) .95 FAM: (.87) .94 FRI: (.85) .94 5 point Likert Scale: Strongly Disagree to, Strongly Agree Schutte Emotional Intelligence Scale (EIS) 33 (.90) .90 I have control over my emotions Ref: Schutte et al. (1998) International Personality Item Pool – 5 subscales (IPIP) E: (.87) .88 A: (.82) .75 C: (.79) .84 ES: (.86) .93 II: (.84) .76 50 10 e/s 6 point Likert Scale: Very inaccurate to, Very accurate Am the life of the party Ref: Goldberg (1999) Plus: Ballard’s short social desirability
Procedure • Questionnaire kits with posters. • Public places. • Explanatory statement. • Anonymity and confidentiality. • 20 minutes. • Australia Post or returns box.
Analyses • Missing values and violations of the assumptions of multivariate analysis • 8 univariate outliers truncated • Mean replacement where missing values were less than 5% • N 267-234 on pairwise analyses • No order effects • Main and interaction effects = Hierarchical Multiple Regression in SPSS
Satisfaction with Life • Model as a whole predicted 44.1% (40.7% adjusted) R=.66, F(13, 216)=13.09, p<.001 1 Sociodem & Personality 34%* 2 SS + 2.9%* 3 EI + 2.6%* 4 SS x EI (interaction) + 2.7%* - EI, and SSso x EI were significant at the last step *significant at .05
Positive Affect • Model as a whole predicted 47.7% (44.9% adjusted) R=.69, F(13, 239)=16.78, p<.001 1 Sociodem, Personality & Sdes 41.3%* 2 SS + (2%) 3 EI + 3.3%* 4 SS x EI (interaction) + (1%) - EI significant in last step *significant at .05
Negative Affect • Model as a whole predicted 50.3% (47.6% adjusted) R=.71, F(13, 239)=18.60, p<.001 1 Sociodem, Personality & Sdes 45%* 2 SS + 2.1%* 3 EI + (1%) 4 SS x EI (interaction) + (1%) - SS Friends x EI was significant at the last step *significant at .05
Interactions • SWL: SS Significant Other x EI • NA: SS Friends x EI • Interactions indicate that the relationship between SS and SWB is dependent on the level of EI reported.
SWLSS Significant Other x EI EI low, b = 0.27 t = 3.18 p = .0008 EI high, b = -0.05 t = -0.56 p = 0.2896
NASS Friends x EI EI low, b = -0.22 t = -2.79 p = .0028 EI high, b = .07 t = .88 p = 0.1896
Discussion • The results partially support the hypotheses. • SS predicted SWL and NA, but not PA. • EI predicted SWL and PA, but not NA. • 2/9 interaction termssignificant. • Each model as a whole was significant.
Discussion • Small amount of variance accounted for by SS, inconsistent with previous research. • Possible explanation is stringent controls; however can be seen to provide clearer results for unique value of SS. • Differential weights of SS sources across DVs; important consideration.
Discussion • Adds support to the discriminant validity of EI. • Predictive value of EI in SWB exciting, as EI thought to be subject to change. • Significant interaction terms support suggestions that EI is important to SWB and SS.
Discussion • SS x EI interaction re: SWB not previously published. • Where EI is high the level of perceived SS is inconsequential to the level of SWB reported. However, where EI is low the level of perceived SS and level of EI interact to produce a differential level of SWB, with higher reported SS having a relationship with higher SWB .
Discussion • SS may not be necessary for everyone, specifically those with high EI. • EI training could be considered as an alternative to formal SS. • Mindful that these are ‘new’ results – with some limitations: gender and education split.
Discussion • Valuable insight into SS and EI as predictors of SWB. • Addressed limitations of earlier studies. • Shows that continuous investigations into apparently robust relationships are warranted.
Discussion • Professionals concerned with SWB need to consider main and interactions effects of known variables. • This study shows that the relationship between SS and EI on SWB goes beyond main effects, and that it is important to explore the three components of SWB.