Abstract:
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.
journal_name
BMJ Openjournal_title
BMJ openauthors
Picco L,Chang S,Abdin E,Chua BY,Yuan Q,Vaingankar JA,Ong S,Yow KL,Chua HC,Chong SA,Subramaniam Mdoi
10.1136/bmjopen-2018-028179subject
Has Abstractpub_date
2019-07-11 00:00:00pages
e028179issue
7issn
2044-6055pii
bmjopen-2018-028179journal_volume
9pub_type
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