| Summary: | Background: Personality is associated with various mental disorders. The personality factor of neuroticism is a risk factor for developing depression; extraversion and conscientiousness can also have an impact on depression. Few studies have looked at the elderly population in relation to personality and depression. The aim of this study was to examine the association between the Big Five personality factors of neuroticism, extroversion and conscientiousness and symptoms of depression and depressive episodes of community living elderly. An additional aim was to investigate what differentiates responders from non-responders in Postal Survey Research. Method: In 2006, a random sample of 1,000 participants from the population-based AGES-Reykjavik Study received the NEO-Five Factor Inventory (NEO-FFI) by mail. Previously gathered data was also used in the study which made the comparison of responders versus non-responders possible. The Geriatric Depression scale (GDS) was used to assess depressive symptoms and the Mini-International Neuropsychiatric Interview (M.I.N.I.) determined a diagnosis of depression according to DSM-IV criteria. Response rate was 41%, usable data came from 38% of the total sample. Descriptive statistics, t-test, chi-square test, correlation, multiple regression and logistic regression were applied. Results: Neuroticism and subjective health had the biggest impact on depressive symptoms; extraversion and gender also contributed significantly to the regression model. Those who considered themselves with poor health were 3.12 times likelier to experience a depressive episode, than those in good health. Higher neuroticism was related to greater odds of experiencing a depressive episode while higher extroversion and being older decreased the odds of depressive episodes. Non-responders had less education, reported worse health, were likelier to use anti-depressants and were older than responders. Strengths and Limitations: Due to the cross-sectional design, no causal inferences can be drawn. ...
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