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FACETS Can Understanding Facets of Personality lead to a Better Understanding of Behaviour.

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Presentation on theme: "FACETS Can Understanding Facets of Personality lead to a Better Understanding of Behaviour."— Presentation transcript:

1 FACETS Can Understanding Facets of Personality lead to a Better Understanding of Behaviour

2 Five Factor Model of Personality and its Facets Openness to Experience Fantasy/imagination Artistic Interests Emotions & Feelings Adventurousness Intellect Liberalism Conscientiousness Competency Orderliness Dutifulness Achievement Striving Self-Discipline Cautiousness Extraversion Friendliness Gregariousness Assertiveness Activity Level Excitement-Seeking Cheerfulness Agreeableness Trust Sincerity Altruism Compliance Modesty Sympathy Neuroticism Anxiety Anger Depression Self-Consciousness Impulsiveness Vulnerability

3 Impulsiveness One of the facets of Neuroticism Strong cravings and urges which are difficult to resist Short term pleasure rather than long term consequences

4 Whiteside and Lynam, 2001 Explored the relationship between the FFM and the multi-faceted Impulsivity 4 distinct factors linked to N,C,E – Urgency – experience strong impulses under negative conditions – Lack of Premeditation –Spur of the moment – Lack of Perseverance – difficulty staying focussed – Sensation seeking- enjoy and pursue risky experiences.

5 Psychopathology Substance use – Hypothesis that impulsivity is a risk factor for substance use (Acton, 2003), Antisocial Behaviour and ADHD – (Nigg et al, 2002).

6 Why use facets? Paunonen and Ashton (2001)

7 Big Five Factors and Facets and the Prediction of Behaviour Hierarchy: Big Five Factors ↓ narrower traits ↓ even narrower behaviours

8 Behaviour variation Independent of the Big Five Some other variables not covered by Big Five? – Some traits independent of the 5FM? – Other personality variables that might contribute to the prediction and understanding of behaviour beyond that achieved by the 5FM Debate about utility to the measurement of the narrow constituent facets of BF factors

9 Research Purpose Further evaluate the relative contributions of personality factors and personality facets to the prediction of behaviour.

10 Paunonen (1998) “aggregating personality traits into their underlying personality factors could result in decreased predictive accuracy due to the loss of trait-specific but criterion-valid variance” Criticism: lower level trait > higher level factor Differences between the present study and Paunonen’s

11 Method 141 students (46M, 95F) 2 sessions separated by a week – 1 st session: a battery of self-report measures – 2 nd session: additional self-report measures & peer-rating form

12 Personality Measures – PRF-JPI & NEO-PI-R – (self-report; both lower level traits and higher level factors) Criterion Measures: – Behaviour Report Form (self-rated & peer-rated); pencil-paper task; experimenter rating; university record; other records. Rater Judgments – Personality-Criterion Association

13 Results Overview Reliability of Rater Judgments: – PRF-JPI mean 0.39 0.72 mean reliability for combined panel of 5 judges – NEO-PI-R mean 0.50 0.81 mean reliability for 5-member panel. Reliability of Personality Measures – Internal consistency and reliability of self-reports on PRF-JPI trait scales and NEO-PI-R facets scales.

14 Criterion Validity of Personality Predictors 4 separate multiple regression: 1.PRF-JPI factor scales 2.PRE-JPI trait scales 3.NEO-PI-R domain scales 4.NEO-PI-R facet scales

15 Incremental Validity of Personality Predictors PRF-JPI trait scales over NEO-PI-R domain scales NEO-PI-R facet scales over PRF-JPI factor scales

16 Result of Comparisons A few carefully selected personality facet scales can predict as well as or better than can all of the Big Five factors scales combined A substantial part of the criterion variance predicted by the facet scales is variance not predicted by the factor scales

17 Discussion Generalizability of the Present Results Expected Prediction Results? Unidimensional vs. Multidimensional Criteria Beyond the Big Five

18 Conclusion Measures of Big Five factors can help to predict and understand behaviour. Also reliable personality-based variation in behaviour not accounted for by Big Five. Sources of non-Big Five personality variance can and should be used for the purposes of reducing error in behaviour prediction and increasing accuracy in behaviour explanation.

19 Female student‘s disordered eating and the Big 5 facets MacLaren & Best, 2009; Eating behaviours

20 Lit review + Intro 2.8% of women and 0.5% of men reported significant symptoms of eating disorders (Gadalla & Piran, 2007) Eating disorders relatively rare, but unhealthy preoccupations with weight common (Hautala et al., 2008) – 25% of normal white US girls perceive themselves as fat – 50% report controlling their weight in unhealthy manner Eating disorders and Personality disorder – N most consistently associated with eating disorder diagnosis and correlated with eating disorder symptoms in non-clinical samples – Specifically, combination of high N and low E risk factor (Miller et al, 2006)

21 Purpose of study To characterise individual dispositions that may increase vulnerability to disordered eating at factor and facet level

22 Method N = 378 nonclinical female university students All completed NEO-PI-R and Eating attitudes test-26 (EAT) – EAT measures atypical behaviours and attitudes about eating; Ps indicate frequency of eating-related thoughts, feelings and behaviours; 3 subscales: 1. Dieting, 2. Bulimia and food preoccupation,3. oral control EAT used to assign participants into 2 groups: - Sympomatic group (N = 43) - Nonsymptomatic groups (N= 335) Nonsymptomatic group‘s trait/facet scores were compared with symptomatic groups‘ scores Symptomatic group‘s scores were correlated with their EAT-subscale scores

23 Results –group comparisons Symptomatic group: Domains – Higher N, lower E N – Higher on all facets, except impulsiveness A – Higher on tender-mindedness E – Lower on assertiveness and excitement-seeking

24 Results- Subscale correlates.. Dieting: High dieting scores associated with – Low impulsiveness (r = -.34) – High self-discipline (r =.34) Oral control: High oral control associated with – Low overall N (esp. Impulsiveness and angry-hostility) – High overall A (esp. Compliance and Modesty) – High self-discipline (r=.43); impulsiveness (r = -.62); angry- hostility (r = -.37), Compliance (r =.46), Modesty (r =.36), Bulimia: high bulimia score associated with – high impulsivity (r =.35)

25 Discussion Study revealed some robust relationships between personality and disordered eating Some facets correlated differently with subscales, e.g. Impulsivity – negative correlation with dieting and oral control, pos correlated with bulimia (maybe difference differentiates between Anorexic and Bulimic tendencies) Robust correlates indicate we can to some extent predict behavioural tendencies, – i.e. make out people at risk, and maybe even use e.g. anorexia vs bulemia)


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