Eikelenboom Nathalie, Smeele Ivo, Faber Marjan, Jacobs Annelies, Verhulst Frank, Lacroix Joyca, Wensing Michel, van Lieshout Jan
Radboud University Medical Centre, Radboud Institute for Health Sciences, IQ healthcare, P.O. Box 9101, 114, 6500, HB, Nijmegen, The Netherlands.
DOH care group, P.O. Box 704, , 5600, AS, Eindhoven, The Netherlands.
BMC Fam Pract. 2015 Nov 11;16:165. doi: 10.1186/s12875-015-0381-z.
A rising number of people with chronic conditions is offered interventions to enhance self-management. The responsiveness of individuals to these interventions depends on patient characteristics. We aimed to develop and validate a tool to facilitate personalised counselling and support for self-management in patients with chronic diseases in primary care.
We drafted a prototype of the tool for Self-Management Screening (SeMaS), comprising 27 questions that were mainly derived from validated questionnaires. To reach high content validity, we performed a literature review and held focus groups with patients and healthcare professionals as input for the tool. The characteristics self-efficacy, locus of control, depression, anxiety, coping, social support, and perceived burden of disease were incorporated into the tool. Three items were added to guide the type of support or intervention, being computer skills, functioning in groups, and willingness to perform self-monitoring. Subsequently, the construct and criterion validity of the tool were investigated in a sample of 204 chronic patients from two primary care practices. Patients filled in the SeMaS and a set of validated questionnaires for evaluation of SeMaS. The Patient Activation Measure (PAM-13), a generic instrument to measure patient health activation, was used to test the convergent construct validity.
Patients had a mean age of 66.8 years and 46.6 % was female. 5.9 % did not experience any barrier to self-management, 28.9 % experienced one minor or major barrier, and 30.4 % two minor or major barriers. Compared to the criterion measures, the positive predictive value of the SeMaS characteristics ranged from 41.5 to 77.8 % and the negative predictive value ranged from 53.3 to 99.4 %. Crohnbach's alpha for internal consistency ranged from 0.56 to 0.87, except for locus of control (α = 0.02). The regression model with PAM-13 as a dependent variable showed that the SeMaS explained 31.7 % (r(2) = 0.317) of the variance in the PAM-13 score.
SeMaS is a short validated tool that can signal potential barriers for self-management that need to be addressed in the dialogue with the patient. As such it can be used to facilitate personalised counselling and support to enhance self-management in patients with chronic conditions in primary care.
越来越多的慢性病患者接受旨在加强自我管理的干预措施。个体对这些干预措施的反应取决于患者特征。我们旨在开发并验证一种工具,以促进在初级保健中为慢性病患者提供个性化咨询和自我管理支持。
我们起草了自我管理筛查工具(SeMaS)的原型,包括27个主要源自经过验证的问卷的问题。为了实现高内容效度,我们进行了文献综述,并与患者和医疗保健专业人员举行了焦点小组讨论,以此作为该工具的输入。自我效能感、控制点、抑郁、焦虑、应对方式、社会支持和疾病感知负担等特征被纳入该工具。添加了三个项目以指导支持或干预的类型,即计算机技能、团队协作能力和自我监测意愿。随后,在来自两个初级保健机构的204名慢性病患者样本中对该工具的结构效度和效标效度进行了调查。患者填写了SeMaS以及一组用于评估SeMaS的经过验证的问卷。使用患者激活量表(PAM-13)(一种用于测量患者健康激活程度的通用工具)来测试聚合结构效度。
患者的平均年龄为66.8岁,46.6%为女性。5.9%的患者在自我管理方面没有遇到任何障碍,28.9%的患者遇到了一个轻微或重大障碍,30.4%的患者遇到了两个轻微或重大障碍。与效标测量相比,SeMaS特征的阳性预测值范围为41.5%至77.8%,阴性预测值范围为53.3%至99.4%。除控制点外(α = 0.02),内部一致性的Cronbach's α范围为0.56至0.87。以PAM-13为因变量的回归模型表明,SeMaS解释了PAM-13得分方差的31.7%(r² = 0.317)。
SeMaS是一种经过验证的简短工具,能够识别自我管理中可能需要在与患者的对话中解决的潜在障碍。因此,它可用于促进个性化咨询和支持,以加强初级保健中慢性病患者的自我管理。