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Associative stigma among mental health professionals in Singapore: a cross-sectional study
OBJECTIVES: (1) Investigate and explore whether different classes of associative stigma (the process by which a person experiences stigmatisation as a result of an association with another stigmatised person) could be identified using latent class analysis; (2) determine the sociodemographic and emp...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629392/ https://www.ncbi.nlm.nih.gov/pubmed/31300500 http://dx.doi.org/10.1136/bmjopen-2018-028179 |
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author | Picco, Louisa Chang, Sherilyn Abdin, Edimansyah Chua, Boon Yiang Yuan, Qi Vaingankar, Janhavi Ajit Ong, Samantha Yow, Kah Lai Chua, Hong Choon Chong, Siow Ann Subramaniam, Mythily |
author_facet | Picco, Louisa Chang, Sherilyn Abdin, Edimansyah Chua, Boon Yiang Yuan, Qi Vaingankar, Janhavi Ajit Ong, Samantha Yow, Kah Lai Chua, Hong Choon Chong, Siow Ann Subramaniam, Mythily |
author_sort | Picco, Louisa |
collection | PubMed |
description | OBJECTIVES: (1) Investigate and explore whether different classes of associative stigma (the process by which a person experiences stigmatisation as a result of an association with another stigmatised person) could be identified using latent class analysis; (2) determine the sociodemographic and employment-related correlates of associative stigma and (3) examine the relationship between associative stigma and job satisfaction, among mental health professionals. DESIGN: Cross-sectional online survey. PARTICIPANTS: Doctors, nurses and allied health staff, working in Singapore. METHODS: Staff (n=462) completed an online survey, which comprised 11 associative stigma items and also captured sociodemographic and job satisfaction-related information. Latent class analysis was used to classify associative stigma on patterns of observed categorical variables. Multinomial logistic regression was used to examine associations between sociodemographic and employment-related factors and the different classes, while multiple linear regression analyses were used to examine the relationship between associative stigma and job satisfaction. RESULTS: The latent class analysis revealed that items formed a three-class model where the classes were classified as ‘no/low associative stigma’, ‘moderate associative stigma’ and ‘high associative stigma’. 48.7%, 40.5% and 10.8% of the population comprised no/low, moderate and high associative stigma classes, respectively. Multinomial logistic regression showed that years of service and occupation were significantly associated with moderate associative stigma, while factors associated with high associative stigma were education, ethnicity and occupation. Multiple linear regression analyses revealed that high associative stigma was significantly associated with lower job satisfaction scores. CONCLUSION: Associative stigma was not uncommon among mental health professionals and was associated with sociodemographic factors and poorer job satisfaction. Associative stigma has received comparatively little attention from empirical researchers and continued efforts to address this understudied yet important construct in conjunction with future efforts to dispel misconceptions related to mental illnesses are needed. |
format | Online Article Text |
id | pubmed-6629392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-66293922019-07-30 Associative stigma among mental health professionals in Singapore: a cross-sectional study Picco, Louisa Chang, Sherilyn Abdin, Edimansyah Chua, Boon Yiang Yuan, Qi Vaingankar, Janhavi Ajit Ong, Samantha Yow, Kah Lai Chua, Hong Choon Chong, Siow Ann Subramaniam, Mythily BMJ Open Mental Health OBJECTIVES: (1) Investigate and explore whether different classes of associative stigma (the process by which a person experiences stigmatisation as a result of an association with another stigmatised person) could be identified using latent class analysis; (2) determine the sociodemographic and employment-related correlates of associative stigma and (3) examine the relationship between associative stigma and job satisfaction, among mental health professionals. DESIGN: Cross-sectional online survey. PARTICIPANTS: Doctors, nurses and allied health staff, working in Singapore. METHODS: Staff (n=462) completed an online survey, which comprised 11 associative stigma items and also captured sociodemographic and job satisfaction-related information. Latent class analysis was used to classify associative stigma on patterns of observed categorical variables. Multinomial logistic regression was used to examine associations between sociodemographic and employment-related factors and the different classes, while multiple linear regression analyses were used to examine the relationship between associative stigma and job satisfaction. RESULTS: The latent class analysis revealed that items formed a three-class model where the classes were classified as ‘no/low associative stigma’, ‘moderate associative stigma’ and ‘high associative stigma’. 48.7%, 40.5% and 10.8% of the population comprised no/low, moderate and high associative stigma classes, respectively. Multinomial logistic regression showed that years of service and occupation were significantly associated with moderate associative stigma, while factors associated with high associative stigma were education, ethnicity and occupation. Multiple linear regression analyses revealed that high associative stigma was significantly associated with lower job satisfaction scores. CONCLUSION: Associative stigma was not uncommon among mental health professionals and was associated with sociodemographic factors and poorer job satisfaction. Associative stigma has received comparatively little attention from empirical researchers and continued efforts to address this understudied yet important construct in conjunction with future efforts to dispel misconceptions related to mental illnesses are needed. BMJ Publishing Group 2019-07-11 /pmc/articles/PMC6629392/ /pubmed/31300500 http://dx.doi.org/10.1136/bmjopen-2018-028179 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Mental Health Picco, Louisa Chang, Sherilyn Abdin, Edimansyah Chua, Boon Yiang Yuan, Qi Vaingankar, Janhavi Ajit Ong, Samantha Yow, Kah Lai Chua, Hong Choon Chong, Siow Ann Subramaniam, Mythily Associative stigma among mental health professionals in Singapore: a cross-sectional study |
title | Associative stigma among mental health professionals in Singapore: a cross-sectional study |
title_full | Associative stigma among mental health professionals in Singapore: a cross-sectional study |
title_fullStr | Associative stigma among mental health professionals in Singapore: a cross-sectional study |
title_full_unstemmed | Associative stigma among mental health professionals in Singapore: a cross-sectional study |
title_short | Associative stigma among mental health professionals in Singapore: a cross-sectional study |
title_sort | associative stigma among mental health professionals in singapore: a cross-sectional study |
topic | Mental Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629392/ https://www.ncbi.nlm.nih.gov/pubmed/31300500 http://dx.doi.org/10.1136/bmjopen-2018-028179 |
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