Development and validation of a Context-sensitive Positive Health Questionnaire (CPHQ): A factor analysis and multivariate regression study.

BACKGROUND: The concept of Positive Health (PH) has gained increasing attention as a way of measuring individuals' ability to adapt in the face of contextual challenges. However, a suitable measurement instrument for PH that encompasses contextual factors has not yet been developed. This paper responds to this need by developing a Context-specific Positive Health (CPH) measurement instrument that aligns with the Capability Approach (CA). METHODS: The measurement instrument was developed and tested among a representative sample of 1002 Dutch internet survey panel members with diverse sociodemographic backgrounds. The instrument was developed in two stages: a preparation phase consisting of focus groups and expert consultations, and a validation among a representative panel of Dutch citizens. The goal of the preparation phase, was to pilot test and refine previously proposed Positive Health questionnaires into an initial version of the CPHQ. The validation phase aimed to examine the initial CPHQ's factorial validity using Factor Analysis, and its concurrent validity using Multivariate Regression Analysis. RESULTS: The developed questionnaire demonstrated adequate factorial and concurrent validity. Furthermore, it explicitly includes an assessment of resilience, this being a key component of PH. CONCLUSIONS: The introduced measurement tool, the CPHQ, comprises 11 dimensions that we have labeled as follows: relaxation, autonomy, fitness, perceived environmental safety, exclusion, social support, financial resources, political representation, health literacy, resilience, and enjoyment. In this article, we present four major contributions. Firstly, we embedded the measurement in a theoretical framework. Secondly, we focused the questionnaire on a key concept of Positive Health - the "ability to adapt." Thirdly, we addressed issues of health inequality by considering contextual factors. Finally, we facilitated the development of more understandable measurement items.

Measuring positive health: Concurrent and factorial validity based on a representative Dutch sample.

The definition of health has been shifting from disease absence to physical, emotional and social well-being. To demedicalise societal problems, the term Positive Health (PH) was introduced-a concept focused on the ability to adapt and to self-manage, in the face of physical, emotional and social challenges. The concept of PH receives broad attention, among others because a PH dialogue tool is intensively being used as a communication instrument while reflecting on patients' health, but a PH measurement instrument is not yet fully established. Recently, however, a 17-item PH measurement model was proposed. In this paper, a factor analysis and regression analyses were performed to test the factorial validity and concurrent validity of this PH measurement model based on a representative sample of the Dutch population (n = 1016, 50.0% women; age: from 15 until 39 = 29.8%, from 40 until 65 = 43.0%, older than 65 = 27.2%; education levels: low = 28.7%, medium = 42.6%, high = 28.7%). These tests are crucial to understand how well the PH measurement model is suitable as a measurement instrument. The factor analysis provided support for the factorial validity of the proposed PH measurement model. When comparing the proposed PH measurement model with domains of other measurements of health (i.e. BRS, HR-SWB, ICECAP, and EQ5D), to test the concurrent validity, the model explained more than half of the variance in measurements of the domains happiness (R2  = 0.60) and overall self-rated health (R2  = 0.57), but explained less than a quarter of the variance in measurements of autonomy (R2  = 0.17 / R2  = 0.13), personal growth (R2  = 0.21), stability (R2  = 0.20), self-care (R2  = 0.15), and resilience (R2  = 0.24). Two of the six domains of the PH measurement model-mental functioning and daily functioning-were weakly related to the other measurements of health. The results of this study imply that the PH measurement model is suitable to measure multiple dimensions of health. They also suggest that the PH measurement model may not be an encompassing measure for the concepts measured through other health measurements and might explain variance in health beyond these other measurements.

Self-rated health trajectories: A dynamic time warp analysis.

Self-rated health (SRH), individuals' overall perception of their health, is a key predictor of health events. To target disease prevention efforts, it is important to understand how SRH develops over time. The goal of this short communication is to find prototypic SRH trajectories by applying dynamic time warping, a time series comparison technique initially developed for speech recognition. Revealing prototypic SRH trajectories can help direct disease prevention efforts towards trajectories that are more likely to result in adverse health events. Based on data from a Dutch representative sample of 2,154 individuals, our dynamic time warp analysis suggests that Dutch individuals do not typically show a steady growth or decline in SRH. Instead, we identified four relatively stable SRH trajectories that differed in average SRH. One of these trajectories is a path of consistent low SRH.

Development and psychometric evaluation of a Positive Health measurement scale: a factor analysis study based on a Dutch population.

OBJECTIVES: The My Positive Health (MPH) dialogue tool is increasingly adopted by healthcare professionals in the Netherlands as well as abroad to support people in their health. Given this trend, the need arises to measure effects of interventions on the Positive Health dimensions. However, the dialogue tool was not developed for this purpose. Therefore, this study aims to work towards a suitable measurement scale using the MPH dialogue tool as starting point. DESIGN: A cross-sectional study design. PARTICIPANTS AND SETTINGS: A total of 708 respondents, who were all members of the municipal health service panel in the eastern part of the Netherlands, completed the MPH dialogue tool. METHODS: The factor structure of the MPH dialogue tool was explored through exploratory factor analysis using maximum likelihood extraction. Next, the fit of the extracted factor structure was tested through confirmatory factor analysis. Reliability and discriminant validity of both a new model and the MPH scales were assessed through Cronbach's alpha tests. RESULTS: Similar to the MPH dialogue tool, the extracted 17-item model has a six-factor structure but named differently, comprising the factors physical fitness, mental functions, future perspectives, contentment, social relations and health management. The reliability tests suggest good to very good reliability of the aimed measurement tool and MPH model (Cronbach's alpha values ranging from, respectively, 0.820 to 0.920 and 0.882 to 0.933). The measurement model shows acceptable discriminant validity, whereas the MPH model suggests overlap between domains. CONCLUSION: The results suggest that the current MPH dialogue tool seems reliable as a dialogue, but it is not suitable as a measurement scale. We therefore propose a 17-item model with improved, acceptable psychometric properties which can serve as a basis for further development of a measurement scale.

Big Five personality as a predictor of health: shortening the questionnaire through the elastic net.

BACKGROUND: The Big Five personality attributes (i.e. openness, conscientiousness, extraversion, agreeableness, and neuroticism) help to predict health. To predict health, researchers may prefer to use a short version of the Big Five Inventory. Although the psychometric properties of the shortened scales can be highly satisfactory, their use can lead researchers to substantially underestimate the role of personality. The aim of this paper is to demonstrate a method appropriate for shortening the Big Five Inventory without losing predictive performance. PARTICIPANTS AND PROCEDURE: The sample comprised 4,678 panel members. The personality traits were measured in 2017 using the Five Factor Model International Personality Item Pool and subjective health was measured in 2018 using the item "How would you describe your health, generally speaking?" While studying the personality-health relationship, the elastic net was compared to a more conventional regression method. RESULTS: While predicting health based on personality, using 14 Big Five Inventory items (R2 = .19) resulted in a similar predictive performance as using 50 Big Five Inventory items (R2 = .18). Controlled for gender and age, participants experienced lower levels of health when they "often feel blue", are not "relaxed most of the time", and "worry about things." These aspects of neuroticism relate to the lower-order facets anxiety and depression. CONCLUSIONS: When the primary goal of personality assessment is predictive performance, researchers should consider shortening their questionnaire using the method demonstrated in this paper. Shortening of the questionnaire does not have to result in a lower predictive performance.