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Gender differences in a clinical sample of 60+ year old patients receiving treatment for alcohol use disorder

INTRODUCTION: Gender differences have been found in treatment-seeking older adults with AUD, concerning areas such as quality of life, drinking patterns, and prevalence of AUD. However, little is known about how these gender differences may relate to treatment. OBJECTIVES: To investigate gender diff...

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Detalles Bibliográficos
Autores principales: Tryggedsson, J., Andersen, K., Bogenschutz, M., Nielsen, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568114/
http://dx.doi.org/10.1192/j.eurpsy.2022.2138
Descripción
Sumario:INTRODUCTION: Gender differences have been found in treatment-seeking older adults with AUD, concerning areas such as quality of life, drinking patterns, and prevalence of AUD. However, little is known about how these gender differences may relate to treatment. OBJECTIVES: To investigate gender differences in quality of life, problematic areas at treatment start, and subsequent choice of treatment, in a clinical sample of 60+ year old patients receiving treatment for AUD. METHODS: We will utilize data from the Elderly Study; a multi-national (USA, Germany, and Denmark), single-blind randomized controlled trial. Participants (n=693) were randomized to brief, outpatient treatment based on motivational enhancement therapy alone (4 sessions) or motivational enhancement therapy followed by a community reinforcement approach age-adapted to older adults (up to 8 sessions). The latter was a module-based treatment where participants chose which module(s) they deemed most relevant. Modules focused on coping with aging, building sober networks, mood management, etc. The gender differences at baseline will be described by means of descriptive statistics (e.g. one-way analysis of variance, χ2 statistics, etc.). Gender differences, including choice of modules, will be investigated by means of multivariate statistics, e.g. generalized linear models. Analyses will be controlled for relevant confounders such as age, country, education, work situation, marital status, family and friends, type of housing, etc. RESULTS: Will be presented at the EPA Congress. CONCLUSIONS: Will be presented at the EPA Congress. DISCLOSURE: No significant relationships.