scholarly journals Statistical methods used in the development of a health measurement scale

2012 ◽  
Vol 38 (3) ◽  
pp. 179-181 ◽  
Author(s):  
Pamela Warner
1999 ◽  
Vol 52 (2) ◽  
pp. 105-111 ◽  
Author(s):  
Robert G. Marx ◽  
Claire Bombardier ◽  
Sheila Hogg-Johnson ◽  
James G. Wright

2021 ◽  
Author(s):  
Xiangzhi Jing ◽  
Hongling Meng ◽  
Yuping Li ◽  
Lingeng Lu ◽  
yongcheng yao

Abstract Objective To explore the relationship between the self-reported health status, emotional coping style, emotional intelligence and positive psychological state of college students during the COVID-19 pandemic. Methods The questionnaires of Self-rated Health Measurement Scale (SRHMS), Emotional Intelligence Scale (EIS), Psychological Capital Questionnaire (PCQ), Simplified Coping Style Questionnaire (SCSQ)were used for online survey. The study included 367 undergraduates. Results Male undergraduates had significantly higher psychological capital scores than female (P < 0.05), and those without siblings had significantly higher emotional intelligence and psychological capital scores than those with (P < 0.05). The students from urban had significantly higher emotional intelligence scores than those from rural (P < 0.05). Students who spent less than 3 hours online per day had significantly higher self-rated health scores than those spending 6 hours online per day (P < 0.05), and those who spent 3–6 hours online per day was significantly higher psychological capital scores than those who spent more than 6 hours online per day (P < 0.05). The interaction between emotional intelligence, psychological capital and coping styles was statistically significant (β=-0.045,P < 0.05) in health status with coping style ranking the top (β = 21.277). Conclusion: Sex, having siblings or not, birth place and online time per day affected health status, emotional intelligence, and psychological capital in undergraduate students. Coping style is a main positive factor that affects health, which was modified by emotional intelligence and psychological capital. In this pandemic emergency, positive coping style with optimistic emotional perception and understanding is an important measure against the pandemic-induced health problem.


2020 ◽  
Author(s):  
Yanqi Liao ◽  
Ming-Ming Li ◽  
Wan-Xian Lu ◽  
Yan-Bin Pan ◽  
Jian-Rong Gong ◽  
...  

Abstract Background: Sub-health status (SHS) is an intermediate status between health and disease. We aimed to investigate the prevalence of sub-health status among college students during the coronavirus disease (COVID-19) pandemic and analyze its influencing factors in order to provide basic information to increase the health level of college students. Methods: College students were selected as subjects from Guangzhou Baiyun Technician College Business using convenience sampling. The inclusion criteria was informed consent, current college students who voluntarily participated in this survey. Exclusion criteria were students with chronic diseases or mental disorders. General data questionnaire, daily lifestyle questionnaire, and SHS measurement scale were used to survey college students. The SHS measurement scale consists of three subscales covering the physiological (1-14 items), psychological (16-27 items), and social (29-37 items) dimensions, with 39 items in total. The items 15, 28, 38 and 39 were used for the overall evaluation of the health status within each dimension and would not be taken into account for the score rating. A commonly used 5-point Likert scale was developed to incorporate the positive items, including questions 1-3, 13-19, and 26-39 with a scaled score equal to the raw score at 1-5; while negative items including questions 4-12 and 20-25 with a scaled score equal to 6 minus the raw score. For each subscale, the sum of all item scores was the raw score. The total raw score was calculated as the sum of raw scores derived from all 3 sub-scales. For any individual dimension, a lower score indicated higher severity of SHS. For sub-scales and the whole scale, raw scores were converted into percentile scores for statistical analysis. Converted score = (raw score - minimum theoretical score) / (maximum theoretical score – minimum theoretical score) × 100. The highest and lowest converted scores of the three subscales were 0 and 100 respectively. In this study, analysis of sub-health was performed using converted scores for all subscales and the whole scale. Based on the sub-health measurement scale, the health condition of subjects would be assessed as disease status (scored < 54), SHS (scored 54 to 79) and health status. From March 6 to 16, 2020, an online survey was conducted via wjx.cn (an online platform available for questionnaire sources). A total of 16,163 students filled out the questionnaire. Results: During the COVID-19 pandemic, the detected prevalence of sub-health among college students was 64.4%.the total SHS score was 73.356 ± 11.115 points, the physiological SHS score was 81.284 ± 11.034 points, the psychological SHS score was 68.691 ± 12.559 points, and the social SHS score was 67.242 ± 17.112 points. Multiple linear regression analysis showed that eating irregular meals, exercising fewer times per week, sleeping fewer hours per night, sleeping after 11 PM more often, spending more time on electronic devices, exercising for fewer minutes each time, and skipping breakfast had the significant negative impact on the SHS scores of college students during the COVID-19 pandemic (P<0.05), while being the only child had a significant positive impact on the SHS scores of college students during the COVID-19 pandemic (P<0.05). Conclusions: During the COVID-19 pandemic, the detected prevalence of sub-health was high among college students. Society and schools should pay more attention to the health of college students during the COVID-19 pandemic and take pertinence action to solve the problem base on influencing factors.


2020 ◽  
Vol 30 (3) ◽  
pp. 510-516 ◽  
Author(s):  
Josefien J F Breedvelt ◽  
Victoria Zamperoni ◽  
Emily South ◽  
Eleonora P Uphoff ◽  
Simon Gilbody ◽  
...  

Abstract Background Consistent and appropriate measurement is needed in order to improve understanding and evaluation of preventative interventions. This review aims to identify individual-level measurement tools used to evaluate mental health prevention interventions to inform harmonization of outcome measurement in this area. Methods Searches were conducted in PubMed, PsychInfo, CINAHL, Cochrane and OpenGrey for studies published between 2008 and 2018 that aimed to evaluate prevention interventions for common mental health problems in adults and used at least one measurement scale (PROSPERO CRD42018095519). For each study, mental health measurement tools were identified and reviewed for reliability, validity, ease-of-use and cultural sensitivity. Results A total of 127 studies were identified that used 65 mental health measurement tools. Most were used by a single study (57%, N = 37) and measured depression (N = 20) or overall mental health (N = 18). The most commonly used questionnaire (15%) was the Centre for Epidemiological Studies Depression Scale. A further 125 tools were identified which measured non-mental health-specific outcomes. Conclusions There was little agreement in measurement tools used across mental health prevention studies, which may hinder comparison across studies. Future research on measurement properties and acceptability of measurements in applied and scientific settings could be explored. Further work on supporting researchers to decide on appropriate outcome measurement for prevention would be beneficial for the field.


2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Jiangping Li ◽  
Honghui Li ◽  
Shulan He ◽  
Min Xue ◽  
Danian Tian ◽  
...  

Objective. The current study was aimed at using a latent profile analysis (LPA) model to classify greenhouse farmers into a potential cluster according to their exposure to pesticide residuals. Further, the association between self-rated health (SRH) and the cluster exposed to pesticide residual was explored. Methods. Four hundred sixty-four farmers from vegetable greenhouses were selected, their SRH information was gathered through questionnaires from the “Self-Rated Health Measurement Scale (SRHMS)” Version 1.0, and the corresponding pesticide residuals were detected in a laboratory. The linear mixed regression model was employed for association assessment. Results. Two latent clusters were extracted as samples, and the results showed that a high amount of pesticide residual accounted for poor physical health, but did not show statistical significance. In addition, an inverse significant association was observed between psychosocial symptoms and negative emotion and pesticide residual level. Furthermore, a diversity of significant relationship was observed in social health and its corresponding dimensions with latent cluster. Conclusions. LPA offers a holistic and parsimonious method to identify high-risk health clusters of greenhouse workers in various health aspects and allows for a personality-targeted intervention by a local health department.


BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e039701
Author(s):  
Yunlian Xue ◽  
Guihao Liu ◽  
Yefang Feng ◽  
Mengyao Xu ◽  
Lijie Jiang ◽  
...  

ObjectiveSuboptimal health status (SHS), a third state between good health and disease, can easily develop into chronic diseases, and can be influenced by lifestyle and health consciousness. No study has surveyed the intermediation of health consciousness on the relationship between lifestyle and SHS. This study aimed to analyse the association of lifestyle and SHS, and intermediation of health consciousness in Chinese urban residents.DesignA cross-sectional face-to-face survey using a four-stage stratified sampling method.ParticipantsWe investigated 5803 Chinese urban residents aged 18 years and over. We measured SHS using the Sub-Health Measurement Scale V1.0. We adopted a structural equation model to analyse relationships among lifestyle, health consciousness and SHS. We applied a bootstrapping method to estimate the mediation effect of health consciousness.ResultsLifestyle had stronger indirect associations with physical (β −0.185, 95% CI −0.228 to −0.149), mental (β −0.224, 95% CI −0.265 to −0.186) and social SHS (β −0.216, 95% CI −0.257 to −0.179) via health consciousness than direct associations of physical (β −0.144, 95% CI −0.209 to −0.081), mental (β −0.146, 95% CI −0.201 to −0.094) and social SHS (β −0.130, 95% CI −0.181 to −0.077). Health consciousness has a strong direct association with physical (β 0.360, 95% CI 0.295 to 0.427), mental (β 0.452, 95% CI 0.392 to 0.510) and social SHS (β 0.434, 95% CI 0.376 to 0.490). Ratio of mediating effect of health consciousness to direct effect of lifestyle with physical, mental and social SHS was 1.28, 1.53 and 1.66, respectively.ConclusionsHealth consciousness was more important in preventing physical, mental and social SHS than lifestyle. Therefore, it might be useful in changing unhealthy lifestyle and reducing the influence of poor lifestyle on physical, mental and social SHS.


BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e040816
Author(s):  
Marja Van Vliet ◽  
Brian M Doornenbal ◽  
Simone Boerema ◽  
Elske M van den Akker-van Marle

ObjectivesThe 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.DesignA cross-sectional study design.Participants and settingsA 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.MethodsThe 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.ResultsSimilar 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.ConclusionThe 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.


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