Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data
Background: Carers of people with psychosis are at a greater risk of physical and mental health problems compared to the general population. Yet, not all carers will experience a decline in health. This predicament has provided the rationale for research studies exploring what factors predict poor w...
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sg-ntu-dr.10356-1452662023-03-05T16:48:30Z Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data Hazell, Cassie M. Hayward, Mark Lobban, Fiona Pandey, Aparajita Pinfold, Vanessa Smith, Helen Elizabeth Jones, Christina J. Lee Kong Chian School of Medicine (LKCMedicine) Social sciences::Psychology Carer Psychosis Background: Carers of people with psychosis are at a greater risk of physical and mental health problems compared to the general population. Yet, not all carers will experience a decline in health. This predicament has provided the rationale for research studies exploring what factors predict poor wellbeing in carers of people with psychosis. Our study builds on previous research by testing the predictive value of demographic variables on carer wellbeing within a single regression model. Methods: To achieve this aim, we conducted secondary analysis on two trial data sets that were merged and recoded for the purposes of this study. Results: Contrary to our hypotheses, only carer gender and age predicted carer wellbeing; with lower levels of carer wellbeing being associated with being female or younger (aged under 50). However, the final regression model explained only 11% of the total variance. Conclusions: Suggestions for future research are discussed in light of the limitations inherent in secondary analysis studies. Further research is needed where sample sizes are sufficient to explore the interactive and additive impact of other predictor variables. Published version 2020-12-16T04:12:57Z 2020-12-16T04:12:57Z 2020 Journal Article Hazell, C. M., Hayward, M., Lobban, F., Pandey, A., Pinfold, V., Smith, H. E., & Jones, C. J. (2020). Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data. BMC Psychiatry, 20(1), 269-. doi:10.1186/s12888-020-02691-0 1471-244X https://hdl.handle.net/10356/145266 10.1186/s12888-020-02691-0 32487127 1 20 en BMC Psychiatry © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. application/pdf |
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Social sciences::Psychology Carer Psychosis Hazell, Cassie M. Hayward, Mark Lobban, Fiona Pandey, Aparajita Pinfold, Vanessa Smith, Helen Elizabeth Jones, Christina J. Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data |
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Background: Carers of people with psychosis are at a greater risk of physical and mental health problems compared to the general population. Yet, not all carers will experience a decline in health. This predicament has provided the rationale for research studies exploring what factors predict poor wellbeing in carers of people with psychosis. Our study builds on previous research by testing the predictive value of demographic variables on carer wellbeing within a single regression model. Methods: To achieve this aim, we conducted secondary analysis on two trial data sets that were merged and recoded for the purposes of this study. Results: Contrary to our hypotheses, only carer gender and age predicted carer wellbeing; with lower levels of carer wellbeing being associated with being female or younger (aged under 50). However, the final regression model explained only 11% of the total variance. Conclusions: Suggestions for future research are discussed in light of the limitations inherent in secondary analysis studies. Further research is needed where sample sizes are sufficient to explore the interactive and additive impact of other predictor variables. |
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Lee Kong Chian School of Medicine (LKCMedicine) |
author_facet |
Lee Kong Chian School of Medicine (LKCMedicine) Hazell, Cassie M. Hayward, Mark Lobban, Fiona Pandey, Aparajita Pinfold, Vanessa Smith, Helen Elizabeth Jones, Christina J. |
format |
Article |
author |
Hazell, Cassie M. Hayward, Mark Lobban, Fiona Pandey, Aparajita Pinfold, Vanessa Smith, Helen Elizabeth Jones, Christina J. |
author_sort |
Hazell, Cassie M. |
title |
Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data |
title_short |
Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data |
title_full |
Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data |
title_fullStr |
Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data |
title_full_unstemmed |
Demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data |
title_sort |
demographic predictors of wellbeing in carers of people with psychosis : secondary analysis of trial data |
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2020 |
url |
https://hdl.handle.net/10356/145266 |
_version_ |
1759853171573784576 |