Individual Difference in Self and Social Attributions of Facial Appearances: Behavioural Correlates of Depression

Electronic versions

Dogfennau

  • Shubha Sreenivas

Abstract

Human faces are naturally captivating and display a variety of facial cues that can be accurately identified as mood state or inherent traits. This process of giving meaning to behaviours or signals that we observe is called attribution. When this is directed to self, we make self-attributions and when directed at others, we make social-attributions. Previous research demonstrates that attributions are affected by mood and wellbeing states, and personality traits, and in the initial chapter I discuss how wellbeing state and neuroticism trait predict depressive mood-state. I further aimed to develop an attribution task using self and others’ face. Studies so far have used self-face to understand perceptions of attractiveness, self-esteem and depression, but not specifically to investigate self-attributions relating to changes in mood state, wellbeing and neuroticism. Measuring attributions of facial appearance using self and others’ face is a new approach. It was important that the self and social attributions were meaningfully measured and easily comparable. I piloted the stimuli and the novel task; the latter is discussed in this thesis. I compared three 19-point face scales created using face composites of neuroticism, depression and agreeableness. The Neurotic Face Scale was chosen for the self and social attribution tasks on the basis of the results from the pilot study. I also demonstrate the different positive and negative attributions that are systematically made to neurotic facial cues. In the main experimental chapters, I investigate the association of self and social attributions of facial appearances with individual’s mood, wellbeing and neuroticism. Participants’ own photograph is used for the self-attribution task, while selected portraits of ‘other’ individuals were used for the social-attribution task. I also compare the participant’s self and social attributions with independent observers’ attributions (of the participants). I demonstrate that participant’s increasing severity of depressive symptoms, decreasing hedonic wellbeing and increasing neuroticism relate to misattributions of self and others, but does not affect independent observers’ attributions. I discuss participants displaying classic social projection based on the similarities between their self and social attributions. Finally, I triangulate self, social and observer attributions to demonstrate that misattributions displayed by participants experiencing depression were specifically for positive attributions, whilst maintaining consistent negative attributions as the independent observers. Self-attributions, however, are more sensitive to mood, wellbeing and inherent traits than social attributions. I further calculate discrepancies between basic self-attributions to demonstrate increasing self-negativity with increasing severity of depressive symptoms, neuroticism and decreasing hedonic wellbeing, as well as increasing selfdiscrepancy with decreasing hedonic wellbeing. I further investigate the longitudinal changes (11 weeks) of self-attributions in participants who are clinically depressed. I demonstrate decreasing severity of depressive symptoms overlapping with decreasing self-negativity and selfdiscrepancy, and increasing self-positivity. I further demonstrate that an increase in self-positivity and decrease in self-negativity in the first week predicts depressive symptoms at week 11. Finally in a pilot study, I demonstrate increase in self-positivity after eight weeks of mindfulness practice; a practice that focuses on non-judgemental self-referential processing to increase self-positivity. This pilot study is included in the final chapter for general discussion, to demonstrate the future research potential for the self-attribution task.

Details

Iaith wreiddiolSaesneg
Sefydliad dyfarnu
Goruchwylydd / Goruchwylwyr / Cynghorydd
Noddwyr traethodau hir
  • Bangor University
Dyddiad dyfarnuIon 2016