Richter Kimber P, Hunt Jamie J, Cupertino A Paula, Gajewski Byron J, Jiang Yu, Marquis Janet, Friedmann Peter D
a Department of Preventive Medicine and Public Health , University of Kansas Medical School , Kansas City , Kansas , USA.
b School of Nursing and Health Studies, University of Missouri Kansas City , Kansas City , Missouri , USA.
Subst Abus. 2017 Jan-Mar;38(1):35-39. doi: 10.1080/08897077.2016.1265039. Epub 2016 Nov 29.
Although people with mental illness, including substance use disorders, consume 44% of cigarettes in the United States, few facilities provide tobacco treatment. This study assesses staff- and facility-level drivers of tobacco treatment in substance use treatment.
Surveys were administered to 405 clinic directors selected from a comprehensive inventory of 3800 US outpatient facilities. The main outcome was the validated 7-item Index of Tobacco Treatment Quality. Other measures included the validated Tobacco Treatment Commitment Scale and indicators of facility resources for providing tobacco treatment.
Stepwise model selection was used to determine the relationship between capacity/resources and treatment quality. The final model retained 7 items and had good fit (adjusted R = 0.43). Four capacities significantly predicted treatment quality. Structural equation modeling (SEM) was used to test the impact of staff commitment on treatment quality; the model had good fit and the relationship was significant (comparative fit index [CFI] = 0.951, root mean square error of approximation [RMSEA] = 0.054). Adding the 7 capacity/resources maintained similar model fit (CFI = 0.922, RMSEA = 0.053). Staff commitment was slightly strengthened in this model, with a rise in parameter estimate from 0.449 to 0.560. All resource/capacity items were also significant predictors of treatment quality; the strongest was receiving training in how to provide tobacco treatment (0.360), followed by dedicated staff time (0.279) and having a policy that requires staff to offer treatment (0.272).
Staff commitment to providing tobacco treatment was the strongest predictor of tobacco treatment quality, followed by resources for providing treatment. Interventions to change staff attitudes and improve resources for tobacco treatment have the strongest potential for improving quality of care.
在美国,包括物质使用障碍在内的精神疾病患者消耗了44%的香烟,但很少有机构提供烟草治疗。本研究评估了物质使用治疗中烟草治疗的工作人员和机构层面的驱动因素。
对从3800家美国门诊机构的综合清单中选出的405名诊所主任进行了调查。主要结果是经过验证的7项烟草治疗质量指数。其他指标包括经过验证的烟草治疗承诺量表以及提供烟草治疗的机构资源指标。
采用逐步模型选择法来确定能力/资源与治疗质量之间的关系。最终模型保留了7个项目,拟合度良好(调整R = 0.43)。四项能力显著预测了治疗质量。使用结构方程模型(SEM)来测试工作人员承诺对治疗质量的影响;该模型拟合度良好,关系显著(比较拟合指数[CFI] = 0.951,近似均方根误差[RMSEA] = 0.054)。加入这7项能力/资源后,模型拟合度保持相似(CFI = 0.922,RMSEA = 0.053)。在该模型中,工作人员承诺略有增强,参数估计值从0.449升至0.560。所有资源/能力项目也是治疗质量的显著预测因素;最强的是接受如何提供烟草治疗的培训(0.360),其次是专门的工作人员时间(0.279)以及有要求工作人员提供治疗的政策(0.272)。
工作人员提供烟草治疗的承诺是烟草治疗质量的最强预测因素,其次是提供治疗的资源。改变工作人员态度和改善烟草治疗资源的干预措施在提高护理质量方面具有最大潜力。