Janet K Spittlehouse1, Esther Vierck2, John F Pearson3, Peter R Joyce4. 1. Department of Psychological Medicine, University of Otago, Christchurch, PO Box 4345, Christchurch, New Zealand. Electronic address: janet.spittlehouse@otago.ac.nz. 2. Department of Psychological Medicine, University of Otago, Christchurch, PO Box 4345, Christchurch, New Zealand. Electronic address: Esther.vierck@otago.ac.nz. 3. Biostatistics and Computational Biology Unit, University of Otago, Christchurch, PO Box 4345, Christchurch, New Zealand. Electronic address: john.pearson@otago.ac.nz. 4. Department of Psychological Medicine, University of Otago, Christchurch, PO Box 4345, Christchurch, New Zealand. Electronic address: Peter.joyce@otago.ac.nz.
Abstract
OBJECTIVES: We aimed to evaluate the effects of Temperament and Character Inventory (TCI) personality measures on well-being scores in a sample of 49-51 year old New Zealanders. Previous research has linked high self-directedness (SD) and low harm avoidance (HA) with well-being. We hypothesised that SD and HA would have predictive power for Warwick-Edinburgh Mental Well-being Scale (WEMWBS) well-being. We anticipated that character profiles with high SD and cooperativeness (CO) would be associated with higher well-being scores while high self transcendence (ST) scores would have less of an influence on well-being in a secular population such as New Zealand. Additionally we aimed to describe and assess the performance of a well-being measure, the WEMWBS and we intended to clarify the factors that underlie the questionnaire. METHODS: A cohort of 404 randomly selected participants in a study of ageing had WEMWBS means calculated and with principal component analysis used to investigate the factors that underlie the WEMWBS. Multiple hierarchical regression was used to predict WEMWBS scores from socio-demographic and TCI personality variables. ANOVA were used to explore the non-linear effects of personality profiles on well-being. RESULTS: Principal components analysis revealed one significant factor which explained 54.34% of the variance. After initial univariate analysis current depression, marital status and standard of living were entered at the first step of the multivariate regression. They explained 20% of the variance. In step two the seven TCI personality variables were added to the model, explaining a total of 49% (R(2) change=0.29). Low HA, high SD and the absence of current depression were the main predictors of WEMWBS scores. Character profiles featuring high SD produced significantly higher scores on the WEMWBS. Total WEMWBS scores were normally distributed, and the mean was 52.83 (95% CI 51.96-53.70). CONCLUSIONS: The key determinants of well-being were absence of current depression and personality variables, especially low HA and high SD. The WEMWBS has face validity and the New Zealand results were very similar to the UK results.
OBJECTIVES: We aimed to evaluate the effects of Temperament and Character Inventory (TCI) personality measures on well-being scores in a sample of 49-51 year old New Zealanders. Previous research has linked high self-directedness (SD) and low harm avoidance (HA) with well-being. We hypothesised that SD and HA would have predictive power for Warwick-Edinburgh Mental Well-being Scale (WEMWBS) well-being. We anticipated that character profiles with high SD and cooperativeness (CO) would be associated with higher well-being scores while high self transcendence (ST) scores would have less of an influence on well-being in a secular population such as New Zealand. Additionally we aimed to describe and assess the performance of a well-being measure, the WEMWBS and we intended to clarify the factors that underlie the questionnaire. METHODS: A cohort of 404 randomly selected participants in a study of ageing had WEMWBS means calculated and with principal component analysis used to investigate the factors that underlie the WEMWBS. Multiple hierarchical regression was used to predict WEMWBS scores from socio-demographic and TCI personality variables. ANOVA were used to explore the non-linear effects of personality profiles on well-being. RESULTS: Principal components analysis revealed one significant factor which explained 54.34% of the variance. After initial univariate analysis current depression, marital status and standard of living were entered at the first step of the multivariate regression. They explained 20% of the variance. In step two the seven TCI personality variables were added to the model, explaining a total of 49% (R(2) change=0.29). Low HA, high SD and the absence of current depression were the main predictors of WEMWBS scores. Character profiles featuring high SD produced significantly higher scores on the WEMWBS. Total WEMWBS scores were normally distributed, and the mean was 52.83 (95% CI 51.96-53.70). CONCLUSIONS: The key determinants of well-being were absence of current depression and personality variables, especially low HA and high SD. The WEMWBS has face validity and the New Zealand results were very similar to the UK results.
Authors: Thomas Nilsson; Örjan Falk; Eva Billstedt; Nóra Kerekes; Henrik Anckarsäter; Märta Wallinius; Björn Hofvander Journal: Front Psychiatry Date: 2016-11-16 Impact factor: 4.157