WHAT MAKES PEOPLE HAPPY - PowerPoint PPT Presentation

1 / 30
About This Presentation
Title:

WHAT MAKES PEOPLE HAPPY

Description:

Emma Gallagher & Dianne Vella-Brodrick. What we already know... Ref: Watson et al. (1988) I am satisfied with life. Ref: Diener et al. (1985) ... – PowerPoint PPT presentation

Number of Views:204
Avg rating:3.0/5.0
Slides: 31
Provided by: acqolDe
Category:
Tags: happy | makes | people | what | emma | watson

less

Transcript and Presenter's Notes

Title: WHAT MAKES PEOPLE HAPPY


1
WHAT MAKES PEOPLE HAPPY?
Social Support Emotional Intelligence as
Predictors of Subjective Wellbeing Emma
Gallagher Dianne Vella-Brodrick
2
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).

3
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).

4
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.

5
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

6
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.

7
Emotional intelligence
  • EI was labelled and modelled by Salovery and
    Mayer (1990).
  • Popularised by Goleman (1995).
  • Broadly defined as the cognitive ability to
    perceive, manage, and regulate emotions within
    ones 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).

8
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).

9
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 wellrespected SWB measures
    measure 3 x components of SWB and control for
    well-established predictors of SWB.

10
SWB, SS EI
  • Underlying processes of SS and EI seem similar.
  • The moderator question is
  • Does the relationship between SS and SWB depend
    on an individuals level of EI?

11
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.

12
Participants
  • 267 adults 196 females, 71 males.
  • general population who volunteered after
    reading explanatory statement.
  • Age 18-80 (M41.52 years, SD14.28).
  • 52.8 in relationships.
  • 72.6 were tertiary educated.
  • Income range 80-2699 (gross) per week, modal
    income 1000 per week.

13
Measures
Response Type all self report
Plus socio-dem questions
Alpha (Original) This Study
Item example
of Items
5 point Likert Scalevery slightly or not at all
to, extremely
Positive NegativeAffect Schedule 2 subscales
(PANAS)
20 10 e/s
Indicate how you feel eg. interested Ref Watson
et al. (1988)
PA, (.88) .88 NA, (.87) .89
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
There is a special personwhen I am in need Ref
Zimet et al. (1988)
7 point Likert Scale Very Strongly Disagree to,
Very Strongly Agree
SO (.91) .95 FAM (.87) .94 FRI (.85) .94
5 point Likert Scale Strongly Disagree to,
Strongly Agree
Schutte Emotional Intelligence Scale (EIS)
33
I have control over my emotions Ref Schutte et
al. (1998)
(.90) .90
International Personality Item Pool 5 subscales
(IPIP)
E (.87) .88 A (.82) .75 C (.79)
.84 ES (.86) .93 II (.84) .76
6 point Likert Scale Very inaccurate to, Very
accurate
50 10 e/s
Am the life of the party Ref Goldberg (1999)
Plus Ballards short social desirability
14
Procedure
  • Questionnaire kits with posters.
  • Public places.
  • Explanatory statement.
  • Anonymity and confidentiality.
  • 20 minutes.
  • Australia Post or returns box.

15
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

16
HMR steps
17
Satisfaction with Life
  • Model as a whole predicted 44.1 (40.7 adjusted)
    R.66, F(13, 216)13.09, p
  • 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

18
Positive Affect
  • Model as a whole predicted 47.7 (44.9
    adjusted) R.69, F(13, 239)16.78, p
  • 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

19
Negative Affect
  • Model as a whole predicted 50.3 (47.6 adjusted)
    R.71, F(13, 239)18.60, p
  • 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

20
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.

21
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
22
NASS Friends x EI
EI low, b -0.22 t -2.79 p .0028 EI
high, b .07 t .88 p 0.1896
23
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 terms significant.
  • Each model as a whole was significant.

24
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.

25
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.

26
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 .

27
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.

28
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.

29
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.

30
Thank you
Write a Comment
User Comments (0)
About PowerShow.com