Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2011
Clinical correlates of health-related quality of life among opioid-dependent patients.
Клиническое исследованиеСтатьяМногоцентровое исследованиеПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Heslin Kevin C, Stein Judith A, Heinzerling Keith G, Pan Deyu, Magladry Christine, Hays Ron D
Аннотация
PURPOSE: Previous work suggests that opioid users have lower health-related quality of life (HRQOL) than patients with more prevalent chronic illnesses such as hypertension or diabetes. Although comparisons with population norms are informative, studies of the correlates of HRQOL for opioid users are needed to plan clinical services.
METHODS: We tested a conceptual model of the pathways between physiologic factors and symptoms in relation to HRQOL among 344 opioid users in a clinical trial. Physical and mental HRQOL were measured by the Short-Form (SF)-36; withdrawal signs, symptoms, and functioning were also measured with validated instruments. Using structural equation modeling, we tested hypotheses that medical history directly predicts withdrawal signs and symptoms, and that medical history, withdrawal signs and symptoms, and functioning predict the physical and mental HRQOL latent variables of the SF-36.
RESULTS: Most hypothesized relationships were significant, and model fit was good. The model explained 36% of the variance in mental HRQOL and 34% of the variance in physical HRQOL.
CONCLUSIONS: The conceptual framework appears valid for explaining variation in the physical and mental HRQOL of opioid users undergoing medically managed withdrawal. Analysis of longitudinal data would help to evaluate more rigorously the adequacy of the model for explaining HRQOL in opioid withdrawal.
METHODS: We tested a conceptual model of the pathways between physiologic factors and symptoms in relation to HRQOL among 344 opioid users in a clinical trial. Physical and mental HRQOL were measured by the Short-Form (SF)-36; withdrawal signs, symptoms, and functioning were also measured with validated instruments. Using structural equation modeling, we tested hypotheses that medical history directly predicts withdrawal signs and symptoms, and that medical history, withdrawal signs and symptoms, and functioning predict the physical and mental HRQOL latent variables of the SF-36.
RESULTS: Most hypothesized relationships were significant, and model fit was good. The model explained 36% of the variance in mental HRQOL and 34% of the variance in physical HRQOL.
CONCLUSIONS: The conceptual framework appears valid for explaining variation in the physical and mental HRQOL of opioid users undergoing medically managed withdrawal. Analysis of longitudinal data would help to evaluate more rigorously the adequacy of the model for explaining HRQOL in opioid withdrawal.