使用 "我的积极健康"(MPH)和 "个人康复结果计数器"(I.ROC)对话工具测量积极健康:一项关于荷兰代表性普通人群测量特性的小组研究

Vera P. van Druten, Margot J. Metz, Jolanda J.P. Mathijssen, Dike van de Mheen, Marja van Vliet, Bridey Rudd, Esther de Vries, Lenny M.W. Nahar - van Venrooij
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引用次数: 0

摘要

导言:积极健康观点已在普通医疗保健领域出现。其概念与心理保健中的康复观点有相似之处。这两个概念都是多维的,都注重能力。我的积极健康(MPH)和个人康复结果计数器(I.ROC)工具是为对话而开发的。这些工具可能有助于量化测量积极健康的概念,从而达到监测和科学研究的目的。我们的目标是调查这一点。方法在具有代表性的荷兰普通人群(LISS 小组)中开展了一项观察性横断面研究,以调查 42 个项目的 MPH 和 12 个项目的 I.ROC 的因子结构和内部一致性。随机拆分数据集后,采用了探索性因子分析(EFA)和确认性因子分析(CFA)。结果 2 457 名参与者填写了问卷。MPH(PH42)提取出了六因子结构,I.ROC(I.ROC12)提取出了双因子结构。解释方差分别为 68.1%和 56.1%。CFA 的拟合指数良好。Cronbach 误差介于 0.74 至 0.97 之间(PH42)和 0.73 至 0.87 之间(I.ROC12)。总分之间的相关性为 0.77。结论 PH42 和 I.ROC12 都有助于定量测量积极的健康方面,这些方面可以用总分来概括普通人群。本研究发现的维度和相应的项目划分与原始对话工具的维度有所不同。建议进一步开展研究,重点关注 PH42 的项目削减、I.ROC 的因子结构以及(在普通人群中)更深入的构建有效性评估。
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Measuring positive health using the My Positive Health (MPH) and Individual Recovery Outcomes Counter (I.ROC) dialogue tools: a panel study on measurement properties in a representative general Dutch population
Introduction Using the positive health perspective has emerged in general healthcare. Conceptual similarities exist with the recovery perspective in mental healthcare. Both concepts are multidimensional and focus on capability. The My Positive Health (MPH) and Individual Recovery Outcomes Counter (I.ROC) tools were developed for dialogues. These tools might be useful for quantitively measuring the positive health construct for monitoring and scientific purposes as well. We aimed to investigate this. Method An observational cross-sectional study was conducted in a representative general Dutch population (the LISS panel) to investigate factor structures and internal consistency from the 42-items MPH and 12-items I.ROC. After randomly splitting the dataset, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied. Spearman correlation coefficient between both tools total scores was calculated. Results 2,457 participants completed the questionnaires. A six-factor structure was extracted for MPH (PH42) and a two-factor structure for I.ROC (I.ROC12). Explained variances were 68.1% and 56.1%, respectively. CFA resulted in good fit indices. Cronbach alphas were between 0.74 to 0.97 (PH42) and 0.73 to 0.87 (I.ROC12). Correlation between the total scores was 0.77. Conclusion Both PH42 and I.ROC12 are useful to quantitatively measure positive health aspects which can be summarised in sum scores in a general population. The dimensions found in this study and the corresponding item division differed from the dimensions of the original dialogue tools. Further research is recommended focussing on item reduction for PH42, factor structure of I.ROC and assessment of construct validity (in a general population) in more depth.
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