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
{"title":"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","authors":"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","doi":"10.1101/2024.02.21.24301090","DOIUrl":null,"url":null,"abstract":"Introduction\nUsing 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.\nMethod\nAn 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.\nResults\n2,457 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.\nConclusion\nBoth 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.","PeriodicalId":501386,"journal":{"name":"medRxiv - Health Policy","volume":"119 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"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\",\"authors\":\"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\",\"doi\":\"10.1101/2024.02.21.24301090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Introduction\\nUsing 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.\\nMethod\\nAn 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.\\nResults\\n2,457 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.\\nConclusion\\nBoth 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.\",\"PeriodicalId\":501386,\"journal\":{\"name\":\"medRxiv - Health Policy\",\"volume\":\"119 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Health Policy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.02.21.24301090\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Health Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.02.21.24301090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.