Assessing the Validity and Reliability of the Indonesian Version of Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health

Assessing the Validity and Reliability of the Indonesian Version of Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing the Validity and Reliability of the Indonesian Version of Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Vitriana Biben, Farida Arisanti, Efi Fitriana, Erika Maklun, Vindy Margaretha Miguna, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3993154/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The assessment of Health-Related Quality of Life (HRQoL) is an essential clinical outcome, focusing on the subjective perception of individuals regarding their health status in the physical, mental, and social dimensions. However, HRQoL assessment in large-scale studies and mass inspections presents various challenges, necessitating the development of non-burdensome instrument. A promising instrument in this context is PROMIS Global Health, a widely used English tool, which requires translation, validation, and cross-cultural testing for non-English populations, such as Indonesia. Therefore, this study aimed to validate and assess the reliability of the Indonesian version of Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health for comprehensive HRQoL assessment. Methods The sample population comprised 343 participants, including patients, caregivers, and residents of Physical Medicine and Rehabilitation. PROMIS Global Health was subjected to translation and cultural adaptation using the Functional Assessment of Chronic Illness Therapy (FACIT) method. Subsequently, the content validity test was carried out using S-CVI assessment of 5 experts, and the internal validity was evaluated with Confirmatory Factor Analysis (CFA). The reliability test was performed with Cronbach's Alpha for internal consistency as well as the test-retest method for external consistency and item discrimination analysis. Results Questions or statements in the Indonesian version of PROMIS Global Health based on S-CVI/Universal Agreement (0.90), χ2/df (1.53), RMSEA (0.04), RMR (0.03), and CFI (0.99). The reliability results showed that Chronbach's Alpha score for Global Physical Health (GPH) and Global Mental Health (GMH) was 0.61 and 0.77, respectively. In addition, the test-retest method showed a good correlation (GPH r = 0.727, p < 0.05; GMH r = 0.701, p 0.3. Conclusion Based on the results, the validity and reliability tests showed that questions or statements in PROMIS Global Health were valid and reliable. Patient-reported outcomes Quality of life Questionnaire Validity Reliability Figures Figure 1 Figure 2 Background Health is an essential determinant that plays a major role in shaping quality of life of individuals. According to the World Health Organization (WHO), quality of life is defined as “individuals’ perception of their position in life in terms of culture and value system, goals, expectations, standards, and concerns.” [ 1 ] Several studies have also reported that it has a multifaceted nature, with aspects influenced by health being called Health-Related Quality of Life (HRQoL). In addition, HRQoL focuses on the subjective perception of health status, consisting of physical, mental, and social dimensions. HRQoL is also considered the best outcome of medical interventions due to its ability to comprehensively assess the subjective perception and expectations of patients. [ 2 , 3 ] This assessment typically includes levels of satisfaction and feelings of worth beyond physical well-being. [ 4 ] In recent years, several studies have been carried out to develop HRQoL measurement instrument that alleviates administrative burdens, particularly for large-scale reports and examinations. A promising instrument in this context is Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health questionnaire, developed by the National Institute of Health, which has been proven to provide comprehensive measurement. In addition, it consists of 10 questions covering various facets, such as health, general quality of life, physical and mental well-being, satisfaction with social activities, ability to engage in social activities, daily physical activity, emotions, fatigue, and pain [ 5 , 6 ]. The completion of this questionnaire typically requires 2 minutes, making it more time-efficient compared to the popular SF-36. [ 7 ] Several reports have shown that the use of PROMIS Global Health offers additional advantages by leveraging items response theory (IRT), where items are arranged on a scale (metric) based on the degree of 'difficulty'. [ 8 ] Consequently, this questionnaire has gained recognition as an assessment included in the standard set for adult general health by the International Consortium of Health Outcomes Measurement (ICHOM). [ 9 ] HRQoL instrument has been developed worldwide in the last decade, but a significant portion is predominantly available in the English language. For non-English speaking populations, the use of this instrument necessitates various processes, including translation, validation testing, and cross-cultural reliability. For example, PROMIS Global Health has been translated into Dutch, Norwegian, and Korean, with positive validity and reliability tests results. [ 10 – 12 ] Despite the availability of this questionnaire in different languages, it has not yet been translated into Indonesian. In the context of medical intervention and rehabilitation, an essential asset is a measurement tool that not only ensures validity and reliability but also alleviates administrative burdens. This necessity is amplified within Indonesia's diverse cultural and linguistic landscape. This indicates that to effectively assess and monitor the impact of medical interventions, there is a pressing need to develop culturally sensitive instrument tailored to the Indonesian context. Therefore, this study aimed to translate and validate PROMIS Global Health questionnaire, renowned for its comprehensive assessment of various facets of quality of life, into an Indonesian version. The results are expected to provide healthcare professionals with a robust and accessible tool to facilitate precise evaluation and monitoring, ultimately enhancing the quality of care and rehabilitation outcomes for individuals nationwide. Methods This study used a cross-sectional method to assess the validity and reliability of questionnaire items that had been translated and culturally adapted into Indonesian language using the Functional Assessment of Chronic Illness Therapy (FACIT) technique (Fig. 1 ). In addition, this technique was used in all translations of adult and pediatric PROMIS items and complied with the guidelines recommended by the International Society for Pharmacoeconomic and Outcomes Research (ISPOR) to translate PRO instrument. The validity and reliability testing started after ISPOR finalized the translation. The sample population comprised patients, caregivers who came to the Medical Rehabilitation outpatient clinic at Dr. Hasan Sadikin Hospital, and residents of Physical Medicine and Rehabilitation from January to December 2023 to fulfill the heterogeneity aspect. The participants were then selected with the consecutive sampling method using the predetermined criteria. In addition, the inclusion criteria were (1) medical rehabilitation outpatients, (2) caregivers, (3) residents of Physical Medicine and Rehabilitation, (4) aged > 18 years old, (5) able to understand instructions, (6) could speak, read, and write Indonesian well, (7) independent, (8) willing to take part in the procedures. Individuals who had a cognitive issue (MMSE < 24) and had uncorrected severe visual and hearing impairments were excluded from the procedures. Descriptive analysis was carried out by displaying the participants’ demographic data accompanied by an assessment of the mean, standard deviation, and subset scores. Comparative tests on GPH and GMH scores were performed based on the demographic factor categories of the samples. In addition, comparison of means with T-test for 2 categories and ANOVA for > 2 categories were carried out with a reference value of p < 0.05, indicating a significant difference from the mean assessed group. [ 13 ] The collection of validity evidence was carried out by: Evidence-based in test content , based on expert judgment by Physical Medicine and Rehabilitation Specialists and linguistic experts who mastered the theoretical basis of the constructs used. The expert reviewers for this measuring instrument were 5 specialists in Physical Medicine and Rehabilitation at Dr. Hasan Sadikin Hospital who were from each division (Musculoskeletal, Neuromuscular, Cardiorespiratory, Geriatrics, and Pediatrics). The expert reviewer was asked to assess the accuracy of the items based on the item definitions proposed by PROMIS. The content validity index (CVI) value was then assessed using the relevance rating from the expert. For CVI item assessment (I-CVI), experts were asked to provide a relevance rating for each item using a scale of 1–4, where 1 = item is not relevant; 2 = item is somewhat relevant; 3 = item is quite relevant; and 4 = item is very relevant. Subsequently, each item was assessed for I-CVI, which was obtained by dividing the number of experts who gave a rating of 3–4 by the number of experts, also known as the proportion of agreement on the relevance. The next assessment was the CVI for the entire scale also known as S-CVI, which was calculated using universal agreement and conservative method. The universal agreement was assessed by experts (S-CVI/UA), namely by dividing the number of I-CVI worth 1 by the total items. A more conservative way was to average the I-CVI (S-CVI/Ave). A good S-CVI number was above 0.7, and for new measuring instrument, the recommended S-CVI was 0.8. [ 14 , 15 ] Evidence-based on internal structure , carried out using the confirmatory factor analysis (CFA) method to study the internal structure of PROMIS Global Health Indonesia construct. CFA was also used to determine whether the model met the goodness of fit criteria. In addition, the chi-square value showed the difference between the expected outcome and the observed covariance matrix. A chi-square value close to 0 indicated little difference. The probability level must be > 0.05 when the chi-square value approached 0. This study used a test-retest method for the reliability test using internal consistency tests, which were performed with Cronbach's Alpha (α). The results showed that the alpha coefficient values ​​ranged from 0 (no reliability) to 1 (perfect reliability). The measuring instrument had ideal internal consistency when the coefficient score was ≥ 0.7. [ 16 ] Item discrimination was used to determine the consistency between item scores and the overall score. This consistency could be seen from the large correlation coefficient between each item and the overall score. Item correlation of < 0.30 indicated poor discriminating power, while correlation ≥ 0.30 showed good discriminating power. [ 17 , 18 ] The item discrimination assessment was also accompanied by a Cronbach's alpha internal consistency reliability value when an item was removed from the measurement. When the alpha coefficient increased after an item was removed from the total count, then the item had less internal consistency. Meanwhile, a decreasing coefficient compared to the total indicated good internal consistency of an item. [ 19 ] The data obtained was processed through the Statistical Program for Social Science (SPSS) software version 26.0 for Windows. This study was carried out after approval by the Research Ethics Committee of Dr. Hasan Sadikin Hospital, number DP.04.03//X.2.2.1/3825/2023. All data supporting the findings are available within the paper and its supplementary information. Results The sample population comprised 343 participants who completed PROMIS-GH questionnaire, and their characteristics were presented in Table 1 . Table 1 Demographic data of research subjects Category Number (subject) Percentage (%) Gender Woman 226 65.89 Man 117 34.11 Age 18–24 years old 52 15,16 25–34 years old 93 27.11 35–44 years old 49 14.28 45–54 years old 74 21.57 55–64 years old 49 14.28 65–74 years old 21 6.12 ≥ 75 years 5 1.45 Education Basic education 27 7.90 Middle Education 173 50.60 Higher education 142 41.50 Marital status Not married yet 84 24.50 Marry 259 75.50 Health condition Healthy 96 28 Sick 247 72 Analysis of mean differences was carried out for several categories. The results showed the presence of significant mean differences in gender, age group, education level, and sick or healthy conditions. Meanwhile, marital status did not significantly influence the difference in mean GPH and GMH between the 2 groups (Table 2 ). Table 2 The GPH and GMH mean differences among groups Total score Category Number (subject) Average (Mean) Standard Deviation Equality of Means (significance, 2-tailed) Gender Total GPH Woman 226 12.54 2.56 0.01* Man 117 13.28 2.76 Total GMH Woman 226 11.93 2.60 0.00* Man 117 13.26 2.78 Age group Total GPH 18–24 52 12.94 2.32 0.00* 25–34 93 13.42 2.81 35–44 49 13.61 2.84 45–54 74 12.31 2.55 55–64 49 11.84 2.23 65–74 21 11.95 2.42 >=75 5 11.00 1.41 Total GMH 18–24 52 12.44 2.83 0.00* 25–34 93 12.49 2.99 35–44 49 13.80 2.62 45–54 74 11.65 2.52 55–64 49 12.18 2.38 65–74 21 11.38 2.04 >=75 5 12.60 1.14 Health condition Total GPH Healthy 96 14.83 2.24 0.00* Sick 247 11.99 2.35 Total GMH Healthy 96 12.88 3.09 0.05 Sick 247 12,19 2.56 Level of education Total GPH Base 27 11.52 2.01 0.00* Intermediate 174 12.50 2.44 High 142 13.37 2.85 Total GMH Base 27 11.63 1.82 0.00* Intermediate 174 11.80 2.61 High 142 13.23 2.80 Marital status Total GPH Marry 260 12.73 2.62 0.48 Not married yet 83 12.96 2.71 Total GMH Marry 260 12.38 2.64 0.98 Not married yet 83 12.37 3.01 * = significant (p < 0.05) The validity in the form of S-CVI from PROMIS Global Health was obtained in 2 ways. The first assessment was obtained by dividing the number of items with a relevance score of 3–4 from experts by the total number of items (S-CVI/UA = 0.90). The analysis showed that the content validity of PROMIS-GH was good (S-CVI > 0.8, Table 4 ). In addition, another way was to divide the total I-CVI by the total number of items (S-CVI/AVE = 0.98). The I-CVI calculation at the item level is presented in Table 3 . Table 3 The analysis of evidence based on text content Items Expert ratings Number in Agreement I-CVI Expert 1 Expert 2 Expert 3 Expert 4 Expert 5 Global03 4 4 3 4 4 5 1 Global06 4 4 4 4 4 5 1 Global07r 4 4 3 2 3 4 0.8 Global08r 4 4 3 4 3 5 1 Global02 4 4 3 4 4 5 1 Global04 4 4 4 4 4 5 1 Global05 4 4 4 4 4 5 1 Global10r 4 4 4 4 4 5 1 Global01 4 4 3 4 4 5 1 Global09r 4 4 4 3 4 5 1 Mean I-CVI 0.98 S-CVI/UA 0.90 Expert Proportion 1.00 1.00 1.00 0.90 1.00 Mean Expert Proportion 0.98 Proof of the validity of the internal structure was obtained using the Confirmatory Factor Analysis (CFA) method to determine the relationship between each question item and the GPH and GMH constructs (Table 4 ). Table 4 The validity of internal structure based on the CFA Method Measurement Two factors score Interpretation \({\chi }^{2}\) ( pdf ) 19.90 (13) Good fit p-value 0.10 RMSEA 0.04 Good fit RMR 0.03 Good fit NFI 0.98 Good fit CFI 0.99 Good fit Reliability testing was carried out using two methods, and the first was assessing internal consistency obtained from the Cronbach's Alpha score. The Cronbach's Alpha value for GPH was 0.61, while a value of 0.77 was obtained for GMH. Test-retest reliability was then gotten from the correlation results of the pre-test and post-test total scores (GPH r = 0.727, p < 0.05; GMH r = 0.701, p < 0.05). The item analysis carried out in this study found that all items in the measuring instrument had good discriminant items (correlation ≥ 0.30), as shown in Table 6 . Table 6 The results of item analysis on GPH and GMH Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted GPH Global03 0.46 0.49 Global06 0.43 0.51 Global07 recorded 0.42 0.51 Global08 0.30 0.61 GMH Global02 0.58 0.71 Global04 0.71 0.63 Global05 0.58 0.72 Global10 0.44 0.79 Discussion The majority of participants in this study were women, and this was due to their dominance as patients and caregivers. In addition, this was understandable considering caregivers throughout the world were dominated by women. [ 19 ] The difference in the mean GPH and GMH scores for women and men was found to be significant (p < 0.5) with the mean total score being lower in women (GPH lower 0.74, GMH lower 1.33). The gender differences had an impact on individuals’ perceived quality of life as reported in previous studies. Lower score could be due to the burden of taking care of children, lack of attention given to health conditions, lack of social support, depression, lower educational level, and the tendency not to work [ 20 ]. Based on the results, most of the participants had secondary and higher education, as shown in Table 1 . High education influenced individuals’ quality of life through knowledge and behavioral dexterity, changes in preferences, and alterations in challenges and opportunities experienced. [ 21 ] The higher the level of education, the better the quality of life. [ 22 ] The finding was consistent with this study, where an increase in GPH and GMH scores was related to increasing education, with a significant mean difference (p < 0.5). The results showed that there were significant differences in HRQoL between the age groups, with the highest total GPH and GMH scores being obtained in the 25–34 and 35–44 years groups, respectively. The lowest GPH score was found at the age of > 75 years and the lowest age was 65–74 years. This could be caused by the decrease in HRQoL as aging occurred, with significant influences from the level of physical activity, chronic diseases, mental health conditions, smoking status, place of residence, employment, and education. [ 23 ] Marital status according to a study by Gondodiputro, et al. in Indonesia with elderly participants was known to affect quality of life. The married participants had better quality of life compared to those who were not married. [ 24 ] The finding was inconsistent with this study, where there was no significant difference in total mean GPH and GMH between the married and unmarried groups. The validity in the form of S-CVI from PROMIS Global Health showed that the content validity of PROMIS-GH was good (S-CVI > 0.8). In addition, S-CVI calculation showed that the items from the PROMIS Global Health could measure the constructs. Some input from experts was in the form of changes to sentence structure. The suggestion for item Global03 was to change the sentence to “How would you rate your general physical health?”. Changes were also suggested for items Global07r and Global08r with a change to “How would you rate your pain on average?” and “How to assess your average fatigue?”. In this study, there was an additional input for item Global07r, namely changing the word "pain" to "pain". Although there was some input from experts, the results of the evidence based on PROMIS Global Health's internal structure were classified as good, hence, no changes were made to the items. Evidence of the validity of the internal structure was obtained using the Confirmatory Factor Analysis (CFA) method to determine the relationship between each question item as well as the GPH and GMH constructs. Correlation tests between sub-dimensions were carried out to obtain the relationship between each sub-dimension (latent variable), as shown in Fig. 2 . The results showed that the GPH sub-dimension had a good correlation with GMH (r = 0.79). Factor loading, which could be seen from the number in the middle of the arrow, showed the correlation between items and sub-dimensions. A value of more than 0.30 indicated a moderate correlation between items and subdimensions. [ 26 ] All items had scores that correlated well with the GPH or GMH subdimensions. The CFA model showed that the GPH and GMH constructs could be measured well (valid) by PROMIS Global Health items. Fit calculations were carried out to determine the fit of a model using the chi-square ratio with degrees of freedom (𝜒2/𝑑𝑓), comparative fit index (CFI), root mean square residual (RMR), and root mean square error of approximation (RMSEA). Mark𝜒2/𝑑𝑓≤ 3, CFI close to 1, RMR, and RMSEA < 0.05 were indicators of an ideal model fit. The results showed 𝜒2/𝑑𝑓1.53, RMSEA 0.04, RMR, and CFI 0.99, which represented good fit. These findings were consistent with similar studies using the Hungarian population (GPH: RMSEA 0.008, SRMR 0.045, CFI 0.968, GMH: RMSEA 0.012, SRMR 0.031, CFI 0.990) and the Dutch population (GPH: SRMR 0.04, GMH SRMR 0.03). [ 25 , 27 ] A strong correlation between the sub-dimensions of GPH and GMH (r = 0.79) was also found in line with the initial PROMIS study in the United States population (r = 0.63). [ 28 ] Reliability testing was carried out using 2 methods, and the first was assessing internal consistency using Cronbach's Alpha score. The Cronbach's Alpha value for GPH and GMH was 0.61 and 0.77, respectively. Test-retest reliability was obtained from the correlation results of the pre-test and post-test total scores (GPH r = 0.727, p < 0.05; GMH r = 0.701, p 0.7 and Pearson correlation 𝑟 was ≥ 0.5 with the test-retest method. Chronbach's 𝛼 in this study was found for GMH 0.77 and GPH 0.61. In addition, Chronbach's coefficient 𝛼 of 0.60–0.70 was included in the satisfactory category. [69] This result was close to the reliability results of PROMIS Global Health development studies, namely 0.81 for GPH and 0.86 for GMH. [35] The findings were also in line with the psychometric assessment study of the Dutch PROMIS Global Health translation, which also showed good reliability (GPH 0.78, GMH 0.83). [ 29 ] The results showed that GPH and GMH had good external reliability (Pearson correlation, GPH r = 0.727, GMH r = 0.701), which illustrated the consistency of the instrument assessment outcomes when repeated measurements were carried out. [ 30 ] The correlation coefficient of the item score with the total score showed the effectiveness of the item in distinguishing individuals with good physical and mental quality of life from others. All PROMIS Global Health items met good discriminant item standards. Table 6 showed that the results of the discriminant item analysis on the Global08r item were the smallest with a value of 0.3. The Global08r item assessed the average feeling of fatigue, where physical fatigue could be interpreted as the participants feeling mentally tired. This indicated that it did not truly differentiate participants with good physical HRQoL from others. In addition, the value could be because items tended to be more difficult for individuals to understand or guess. [ 29 ] Chronbach's assessment 𝛼 when items were removed in GPH showed a decrease in correlation coefficients across all items, while the deletion of Global10 item in GMH caused a slight increase in correlation coefficients (0.77 to 0.79). This increase was also found in a previous study, but lower in the Dutch study, where Global10 item had variance that was not relevant to the construct (0.83 to 0.85). Global10 item assessed the presence of emotional problems and the extent of distress caused. Weakness of items could be caused by the emergence of 2 meanings of the score. A low score could indicate that the participants did not have emotional problems, or had emotional problems but did not feel disturbed. Based on the findings, there were some limitations in this current study. The validity measurements were not carried out based on their relationship with other HRQoL measuring instrument, such as SF-36 and SF-12. In addition, this study did not differentiate patients based on the diagnosis of the disease, which could lead to varying health perceptions related to specific illnesses. Conclusion In conclusion, the statements and questions in the Indonesian version of PROMIS Global Health were valid and reliable, making it a suitable measuring tool for assessing health-related quality of life (HRQoL) in the Indonesian context. Declarations Ethics approval and consent to participate All procedures comprising human participants were carried out in line with the ethical standards of the Research Ethics Committee of Dr. Hasan Sadikin Hospital, number DP.04.03//X.2.2.1/3825/2023 Consent for publication All participants gave their informed consent before inclusion in the study. Availability of data and materials The datasets generated and analyzed during the current study are not publicly available due to concerns that participants’ privacy may be compromised but are available from the corresponding author upon reasonable request. Competing interests The authors have no competing interests to declare relevant to this article's content. Funding This study was partially funded by Universitas Padjadjaran. Authors' contributions All authors contributed to the study conception design. Material preparation and data collection were performed by Vitriana Biben, Farida Arisanti, Erika Maklun, and Vindy Margaretha Miguna. Data were analyzed by Efi Fitriana. In addition, the first draft of the manuscript was written by Nabilla Fikria Alviani and all authors commented on previous versions and collaborated to revise the manuscript. All authors read and approved the final manuscript. Acknowledgments The authors have none to declare. References Cai T, Verze P, Bjerklund Johansen TE. The Quality of Life Definition: Where Are We Going? Uro. 2021;1(1):14–22. Karimi M, Brazier J. Health, Health-Related Quality of Life, and Quality of Life: What is the Difference? Pharmacoeconomics. 2016;34(7):645–9. Katona M, Schmidt R, Schupp W, Graessel E. 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Eur J Heal Econ. 2023;(0123456789). Hays RD, Bjorner JB, Revicki DA, Spritzer KL, Cella D. Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items. Qual Life Res. 2009;18(7):873–80. Pellicciari L, Chiarotto A, Giusti E, Crins MHP, Roorda LD, Terwee CB. Psychometric properties of the patient-reported outcomes measurement information system scale v1.2: global health (PROMIS-GH) in a Dutch general population. Health Qual Life Outcomes. 2021;19(1):1–17. Heale R, Twycross A. Validity and reliability in quantitative studies. Evid Based Nurs. 2015;18(3):66–7. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3993154","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":285305107,"identity":"b2add5d5-930c-4cad-ac9b-896cffb3ce82","order_by":0,"name":"Vitriana Biben","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYDACZiBOAGJ+MI8NRDA2SODXwgzRItlAtBawNUBgcACuhYEBrxaD4/zHPjyouSNvfCP32IMfZQzy/A3MjTfwajnMzDwj4dgzw2038tINe84xGM44wNhsgU+LZDPQMwlshxm33cgxk+BtY2DcwMDYhtdhEC3/DttvnpFjJvm3jcGeoBZ+ZqCWxLbDiRskcsykgbYkEqPFmCGx73DyjDNvzI1lzkkkzzhMwC9s/AcfM/74dti2vz3H7OGbMhsgo/0h3hBD0c4AjhFmYtUzwONxFIyCUTAKRgEaAAB+zEKSuJTvUwAAAABJRU5ErkJggg==","orcid":"","institution":"Universitas Padjadjaran/dr.Hasan Sadikin General Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Vitriana","middleName":"","lastName":"Biben","suffix":""},{"id":285305108,"identity":"7cd96413-7849-40a5-8340-2f1d41003dab","order_by":1,"name":"Farida Arisanti","email":"","orcid":"","institution":"Universitas Padjadjaran/dr.Hasan Sadikin General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Farida","middleName":"","lastName":"Arisanti","suffix":""},{"id":285305109,"identity":"ffa994c0-86fe-4ea5-8fa7-ac8aac473cee","order_by":2,"name":"Efi Fitriana","email":"","orcid":"","institution":"Universitas Padjadjaran","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Efi","middleName":"","lastName":"Fitriana","suffix":""},{"id":285305110,"identity":"1f1b3379-ee94-448b-a9b1-b4cfd860efe5","order_by":3,"name":"Erika Maklun","email":"","orcid":"","institution":"Universitas Padjadjaran/dr.Hasan Sadikin General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Erika","middleName":"","lastName":"Maklun","suffix":""},{"id":285305111,"identity":"14e9b222-3acb-41ec-aea2-bc888dadaa1e","order_by":4,"name":"Vindy Margaretha Miguna","email":"","orcid":"","institution":"Universitas Padjadjaran/dr.Hasan Sadikin General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Vindy","middleName":"Margaretha","lastName":"Miguna","suffix":""},{"id":285305112,"identity":"16480832-2b34-4242-98e4-876c20204007","order_by":5,"name":"Nabilla Fikria Alviani","email":"","orcid":"","institution":"Universitas Padjadjaran/dr.Hasan Sadikin General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nabilla","middleName":"Fikria","lastName":"Alviani","suffix":""}],"badges":[],"createdAt":"2024-02-27 07:03:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3993154/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3993154/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53970232,"identity":"8162b3bc-86cc-42b1-9036-754a0529724c","added_by":"auto","created_at":"2024-04-02 20:40:46","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":250858,"visible":true,"origin":"","legend":"\u003cp\u003eThe FACIT translation method. [1-5]\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3993154/v1/cf44d55b02c3c8bcf47a9c74.jpeg"},{"id":53970231,"identity":"e2e83770-3410-4fd2-bc03-070c7094d7f0","added_by":"auto","created_at":"2024-04-02 20:40:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27653,"visible":true,"origin":"","legend":"\u003cp\u003eThe factor loading of GPH and GMH\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3993154/v1/fd8ce4bb876c064822908d58.png"},{"id":54411873,"identity":"50b312d2-efbe-48e6-ac08-cae599250549","added_by":"auto","created_at":"2024-04-10 05:46:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":446250,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3993154/v1/8d351bcf-09ab-4756-950c-4fdea7568914.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing the Validity and Reliability of the Indonesian Version of Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health","fulltext":[{"header":"Background","content":"\u003cp\u003eHealth is an essential determinant that plays a major role in shaping quality of life of individuals. According to the World Health Organization (WHO), quality of life is defined as \u0026ldquo;individuals\u0026rsquo; perception of their position in life in terms of culture and value system, goals, expectations, standards, and concerns.\u0026rdquo; [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Several studies have also reported that it has a multifaceted nature, with aspects influenced by health being called Health-Related Quality of Life (HRQoL). In addition, HRQoL focuses on the subjective perception of health status, consisting of physical, mental, and social dimensions. HRQoL is also considered the best outcome of medical interventions due to its ability to comprehensively assess the subjective perception and expectations of patients. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] This assessment typically includes levels of satisfaction and feelings of worth beyond physical well-being. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn recent years, several studies have been carried out to develop HRQoL measurement instrument that alleviates administrative burdens, particularly for large-scale reports and examinations. A promising instrument in this context is Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health questionnaire, developed by the National Institute of Health, which has been proven to provide comprehensive measurement. In addition, it consists of 10 questions covering various facets, such as health, general quality of life, physical and mental well-being, satisfaction with social activities, ability to engage in social activities, daily physical activity, emotions, fatigue, and pain [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The completion of this questionnaire typically requires 2 minutes, making it more time-efficient compared to the popular SF-36. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] Several reports have shown that the use of PROMIS Global Health offers additional advantages by leveraging items response theory (IRT), where items are arranged on a scale (metric) based on the degree of 'difficulty'. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] Consequently, this questionnaire has gained recognition as an assessment included in the standard set for adult general health by the International Consortium of Health Outcomes Measurement (ICHOM). [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHRQoL instrument has been developed worldwide in the last decade, but a significant portion is predominantly available in the English language. For non-English speaking populations, the use of this instrument necessitates various processes, including translation, validation testing, and cross-cultural reliability. For example, PROMIS Global Health has been translated into Dutch, Norwegian, and Korean, with positive validity and reliability tests results. [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Despite the availability of this questionnaire in different languages, it has not yet been translated into Indonesian.\u003c/p\u003e \u003cp\u003eIn the context of medical intervention and rehabilitation, an essential asset is a measurement tool that not only ensures validity and reliability but also alleviates administrative burdens. This necessity is amplified within Indonesia's diverse cultural and linguistic landscape. This indicates that to effectively assess and monitor the impact of medical interventions, there is a pressing need to develop culturally sensitive instrument tailored to the Indonesian context. Therefore, this study aimed to translate and validate PROMIS Global Health questionnaire, renowned for its comprehensive assessment of various facets of quality of life, into an Indonesian version. The results are expected to provide healthcare professionals with a robust and accessible tool to facilitate precise evaluation and monitoring, ultimately enhancing the quality of care and rehabilitation outcomes for individuals nationwide.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis study used a cross-sectional method to assess the validity and reliability of questionnaire items that had been translated and culturally adapted into Indonesian language using the Functional Assessment of Chronic Illness Therapy (FACIT) technique (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition, this technique was used in all translations of adult and pediatric PROMIS items and complied with the guidelines recommended by the International Society for Pharmacoeconomic and Outcomes Research (ISPOR) to translate PRO instrument.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe validity and reliability testing started after ISPOR finalized the translation. The sample population comprised patients, caregivers who came to the Medical Rehabilitation outpatient clinic at Dr. Hasan Sadikin Hospital, and residents of Physical Medicine and Rehabilitation from January to December 2023 to fulfill the heterogeneity aspect. The participants were then selected with the consecutive sampling method using the predetermined criteria. In addition, the inclusion criteria were (1) medical rehabilitation outpatients, (2) caregivers, (3) residents of Physical Medicine and Rehabilitation, (4) aged\u0026thinsp;\u0026gt;\u0026thinsp;18 years old, (5) able to understand instructions, (6) could speak, read, and write Indonesian well, (7) independent, (8) willing to take part in the procedures. Individuals who had a cognitive issue (MMSE\u0026thinsp;\u0026lt;\u0026thinsp;24) and had uncorrected severe visual and hearing impairments were excluded from the procedures.\u003c/p\u003e \u003cp\u003eDescriptive analysis was carried out by displaying the participants\u0026rsquo; demographic data accompanied by an assessment of the mean, standard deviation, and subset scores. Comparative tests on GPH and GMH scores were performed based on the demographic factor categories of the samples. In addition, comparison of means with T-test for 2 categories and ANOVA for \u0026gt;\u0026thinsp;2 categories were carried out with a reference value of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, indicating a significant difference from the mean assessed group. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe collection of validity evidence was carried out by:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eEvidence-based in test content\u003c/em\u003e, based on expert judgment by Physical Medicine and Rehabilitation Specialists and linguistic experts who mastered the theoretical basis of the constructs used. The expert reviewers for this measuring instrument were 5 specialists in Physical Medicine and Rehabilitation at Dr. Hasan Sadikin Hospital who were from each division (Musculoskeletal, Neuromuscular, Cardiorespiratory, Geriatrics, and Pediatrics).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eThe expert reviewer\u003c/em\u003e was asked to assess the accuracy of the items based on the item definitions proposed by PROMIS. The content validity index (CVI) value was then assessed using the relevance rating from the expert. For CVI item assessment (I-CVI), experts were asked to provide a relevance rating for each item using a scale of 1\u0026ndash;4, where 1\u0026thinsp;=\u0026thinsp;item is not relevant; 2\u0026thinsp;=\u0026thinsp;item is somewhat relevant; 3\u0026thinsp;=\u0026thinsp;item is quite relevant; and 4\u0026thinsp;=\u0026thinsp;item is very relevant. Subsequently, each item was assessed for I-CVI, which was obtained by dividing the number of experts who gave a rating of 3\u0026ndash;4 by the number of experts, also known as the proportion of agreement on the relevance. The next assessment was the CVI for the entire scale also known as S-CVI, which was calculated using universal agreement and conservative method. The universal agreement was assessed by experts (S-CVI/UA), namely by dividing the number of I-CVI worth 1 by the total items. A more conservative way was to average the I-CVI (S-CVI/Ave). A good S-CVI number was above 0.7, and for new measuring instrument, the recommended S-CVI was 0.8. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eEvidence-based on internal structure\u003c/em\u003e, carried out using the confirmatory factor analysis (CFA) method to study the internal structure of PROMIS Global Health Indonesia construct. CFA was also used to determine whether the model met the goodness of fit criteria. In addition, the chi-square value showed the difference between the expected outcome and the observed covariance matrix. A chi-square value close to 0 indicated little difference. The probability level must be \u0026gt;\u0026thinsp;0.05 when the chi-square value approached 0.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThis study used a test-retest method for the reliability test using internal consistency tests, which were performed with Cronbach's Alpha (α). The results showed that the alpha coefficient values ​​ranged from 0 (no reliability) to 1 (perfect reliability). The measuring instrument had ideal internal consistency when the coefficient score was \u0026ge;\u0026thinsp;0.7. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Item discrimination was used to determine the consistency between item scores and the overall score. This consistency could be seen from the large correlation coefficient between each item and the overall score. Item correlation of \u0026lt;\u0026thinsp;0.30 indicated poor discriminating power, while correlation\u0026thinsp;\u0026ge;\u0026thinsp;0.30 showed good discriminating power. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] The item discrimination assessment was also accompanied by a Cronbach's alpha internal consistency reliability value when an item was removed from the measurement. When the alpha coefficient increased after an item was removed from the total count, then the item had less internal consistency. Meanwhile, a decreasing coefficient compared to the total indicated good internal consistency of an item. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003cp\u003e The data obtained was processed through the Statistical Program for Social Science (SPSS) software version 26.0 for Windows. This study was carried out after approval by the Research Ethics Committee of Dr. Hasan Sadikin Hospital, number DP.04.03//X.2.2.1/3825/2023. All data supporting the findings are available within the paper and its supplementary information.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe sample population comprised 343 participants who completed PROMIS-GH questionnaire, and their characteristics were presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic data of research subjects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber (subject)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;34 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;44 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;54 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u0026ndash;64 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;74 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;75 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasic education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot married yet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSick\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAnalysis of mean differences was carried out for several categories. The results showed the presence of significant mean differences in gender, age group, education level, and sick or healthy conditions. Meanwhile, marital status did not significantly influence the difference in mean GPH and GMH between the 2 groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe GPH and GMH mean differences among groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber (subject)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003cp\u003e\u003cem\u003e(Mean)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eEquality of Means\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(significance, 2-tailed)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal GPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal GMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eTotal GPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;=75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eTotal GMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;=75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHealth condition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal GPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSick\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal GMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSick\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal GPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal GMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal GPH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot married yet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal GMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot married yet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e* = significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe validity in the form of S-CVI from PROMIS Global Health was obtained in 2 ways. The first assessment was obtained by dividing the number of items with a relevance score of 3\u0026ndash;4 from experts by the total number of items (S-CVI/UA\u0026thinsp;=\u0026thinsp;0.90). The analysis showed that the content validity of PROMIS-GH was good (S-CVI\u0026thinsp;\u0026gt;\u0026thinsp;0.8, Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In addition, another way was to divide the total I-CVI by the total number of items (S-CVI/AVE\u0026thinsp;=\u0026thinsp;0.98). The I-CVI calculation at the item level is presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe analysis of evidence based on text content\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eItems\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eExpert ratings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eNumber in Agreement\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eI-CVI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eExpert 1\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eExpert 2\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eExpert 3\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eExpert 4\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eExpert 5\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal07r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal08r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal10r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal09r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean I-CVI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eS-CVI/UA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eExpert Proportion\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eMean Expert Proportion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eProof of the validity of the internal structure was obtained using the Confirmatory Factor Analysis (CFA) method to determine the relationship between each question item and the GPH and GMH constructs (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe validity of internal structure based on the CFA Method\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTwo factors score\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\chi }^{2}\\)\u003c/span\u003e\u003c/span\u003e(\u003cem\u003epdf\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.90 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGood fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood fit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e Reliability testing was carried out using two methods, and the first was assessing internal consistency obtained from the Cronbach's Alpha score. The Cronbach's Alpha value for GPH was 0.61, while a value of 0.77 was obtained for GMH. Test-retest reliability was then gotten from the correlation results of the pre-test and post-test total scores (GPH r\u0026thinsp;=\u0026thinsp;0.727, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; GMH r\u0026thinsp;=\u0026thinsp;0.701, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThe item analysis carried out in this study found that all items in the measuring instrument had good discriminant items (correlation\u0026thinsp;\u0026ge;\u0026thinsp;0.30), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe results of item analysis on GPH and GMH\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCorrected Item-Total Correlation\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCronbach's Alpha if Item Deleted\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGPH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal07 recorded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGMH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe majority of participants in this study were women, and this was due to their dominance as patients and caregivers. In addition, this was understandable considering caregivers throughout the world were dominated by women. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] The difference in the mean GPH and GMH scores for women and men was found to be significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.5) with the mean total score being lower in women (GPH lower 0.74, GMH lower 1.33). The gender differences had an impact on individuals\u0026rsquo; perceived quality of life as reported in previous studies. Lower score could be due to the burden of taking care of children, lack of attention given to health conditions, lack of social support, depression, lower educational level, and the tendency not to work [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on the results, most of the participants had secondary and higher education, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. High education influenced individuals\u0026rsquo; quality of life through knowledge and behavioral dexterity, changes in preferences, and alterations in challenges and opportunities experienced. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] The higher the level of education, the better the quality of life. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] The finding was consistent with this study, where an increase in GPH and GMH scores was related to increasing education, with a significant mean difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.5).\u003c/p\u003e \u003cp\u003eThe results showed that there were significant differences in HRQoL between the age groups, with the highest total GPH and GMH scores being obtained in the 25\u0026ndash;34 and 35\u0026ndash;44 years groups, respectively. The lowest GPH score was found at the age of \u0026gt;\u0026thinsp;75 years and the lowest age was 65\u0026ndash;74 years. This could be caused by the decrease in HRQoL as aging occurred, with significant influences from the level of physical activity, chronic diseases, mental health conditions, smoking status, place of residence, employment, and education. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eMarital status according to a study by Gondodiputro, et al. in Indonesia with elderly participants was known to affect quality of life. The married participants had better quality of life compared to those who were not married. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] The finding was inconsistent with this study, where there was no significant difference in total mean GPH and GMH between the married and unmarried groups.\u003c/p\u003e \u003cp\u003eThe validity in the form of S-CVI from PROMIS Global Health showed that the content validity of PROMIS-GH was good (S-CVI\u0026thinsp;\u0026gt;\u0026thinsp;0.8). In addition, S-CVI calculation showed that the items from the PROMIS Global Health could measure the constructs. Some input from experts was in the form of changes to sentence structure. The suggestion for item Global03 was to change the sentence to \u0026ldquo;How would you rate your general physical health?\u0026rdquo;. Changes were also suggested for items Global07r and Global08r with a change to \u0026ldquo;How would you rate your pain on average?\u0026rdquo; and \u0026ldquo;How to assess your average fatigue?\u0026rdquo;. In this study, there was an additional input for item Global07r, namely changing the word \"pain\" to \"pain\". Although there was some input from experts, the results of the evidence based on PROMIS Global Health's internal structure were classified as good, hence, no changes were made to the items.\u003c/p\u003e \u003cp\u003eEvidence of the validity of the internal structure was obtained using the Confirmatory Factor Analysis (CFA) method to determine the relationship between each question item as well as the GPH and GMH constructs. Correlation tests between sub-dimensions were carried out to obtain the relationship between each sub-dimension (latent variable), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The results showed that the GPH sub-dimension had a good correlation with GMH (r\u0026thinsp;=\u0026thinsp;0.79). Factor loading, which could be seen from the number in the middle of the arrow, showed the correlation between items and sub-dimensions. A value of more than 0.30 indicated a moderate correlation between items and subdimensions. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] All items had scores that correlated well with the GPH or GMH subdimensions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe CFA model showed that the GPH and GMH constructs could be measured well (valid) by PROMIS Global Health items. Fit calculations were carried out to determine the fit of a model using the chi-square ratio with degrees of freedom (\u0026#120594;2/\u0026#119889;\u0026#119891;), comparative fit index (CFI), root mean square residual (RMR), and root mean square error of approximation (RMSEA). Mark\u0026#120594;2/\u0026#119889;\u0026#119891;\u0026le; 3, CFI close to 1, RMR, and RMSEA\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were indicators of an ideal model fit. The results showed \u0026#120594;2/\u0026#119889;\u0026#119891;1.53, RMSEA 0.04, RMR, and CFI 0.99, which represented good fit. These findings were consistent with similar studies using the Hungarian population (GPH: RMSEA 0.008, SRMR 0.045, CFI 0.968, GMH: RMSEA 0.012, SRMR 0.031, CFI 0.990) and the Dutch population (GPH: SRMR 0.04, GMH SRMR 0.03). [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] A strong correlation between the sub-dimensions of GPH and GMH (r\u0026thinsp;=\u0026thinsp;0.79) was also found in line with the initial PROMIS study in the United States population (r\u0026thinsp;=\u0026thinsp;0.63). [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eReliability testing was carried out using 2 methods, and the first was assessing internal consistency using Cronbach's Alpha score. The Cronbach's Alpha value for GPH and GMH was 0.61 and 0.77, respectively. Test-retest reliability was obtained from the correlation results of the pre-test and post-test total scores (GPH r\u0026thinsp;=\u0026thinsp;0.727, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; GMH r\u0026thinsp;=\u0026thinsp;0.701, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A measuring instrument was considered to have ideal reliability when the Cronbach's value \u0026#120572; was \u0026gt;\u0026thinsp;0.7 and Pearson correlation \u0026#119903; was \u0026ge;\u0026thinsp;0.5 with the test-retest method. Chronbach's \u0026#120572; in this study was found for GMH 0.77 and GPH 0.61. In addition, Chronbach's coefficient \u0026#120572; of 0.60\u0026ndash;0.70 was included in the satisfactory category. \u003cb\u003e[69]\u003c/b\u003e This result was close to the reliability results of PROMIS Global Health development studies, namely 0.81 for GPH and 0.86 for GMH. \u003cb\u003e[35]\u003c/b\u003e The findings were also in line with the psychometric assessment study of the Dutch PROMIS Global Health translation, which also showed good reliability (GPH 0.78, GMH 0.83). [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] The results showed that GPH and GMH had good external reliability (Pearson correlation, GPH r\u0026thinsp;=\u0026thinsp;0.727, GMH r\u0026thinsp;=\u0026thinsp;0.701), which illustrated the consistency of the instrument assessment outcomes when repeated measurements were carried out. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe correlation coefficient of the item score with the total score showed the effectiveness of the item in distinguishing individuals with good physical and mental quality of life from others. All PROMIS Global Health items met good discriminant item standards. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e6\u003c/span\u003e showed that the results of the discriminant item analysis on the Global08r item were the smallest with a value of 0.3. The Global08r item assessed the average feeling of fatigue, where physical fatigue could be interpreted as the participants feeling mentally tired. This indicated that it did not truly differentiate participants with good physical HRQoL from others. In addition, the value could be because items tended to be more difficult for individuals to understand or guess. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eChronbach's assessment \u0026#120572; when items were removed in GPH showed a decrease in correlation coefficients across all items, while the deletion of Global10 item in GMH caused a slight increase in correlation coefficients (0.77 to 0.79). This increase was also found in a previous study, but lower in the Dutch study, where Global10 item had variance that was not relevant to the construct (0.83 to 0.85). Global10 item assessed the presence of emotional problems and the extent of distress caused. Weakness of items could be caused by the emergence of 2 meanings of the score. A low score could indicate that the participants did not have emotional problems, or had emotional problems but did not feel disturbed.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBased on the findings, there were some limitations in this current study. The validity measurements were not carried out based on their relationship with other HRQoL measuring instrument, such as SF-36 and SF-12. In addition, this study did not differentiate patients based on the diagnosis of the disease, which could lead to varying health perceptions related to specific illnesses.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the statements and questions in the Indonesian version of PROMIS Global Health were valid and reliable, making it a suitable measuring tool for assessing health-related quality of life (HRQoL) in the Indonesian context.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures comprising human participants were carried out in line with the ethical standards of the Research Ethics Committee of Dr. Hasan Sadikin Hospital, number DP.04.03//X.2.2.1/3825/2023\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAll participants gave their informed consent before inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAvailability of data and materials\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to concerns that participants\u0026rsquo; privacy may be compromised but are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare relevant to this article\u0026apos;s content.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFunding\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis study was partially funded by Universitas Padjadjaran.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAuthors\u0026apos; contributions\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception design. Material preparation and data collection were performed by Vitriana Biben, Farida Arisanti, Erika Maklun, and\u0026nbsp;Vindy Margaretha Miguna.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eData were analyzed by Efi Fitriana.\u0026nbsp;In addition, the first draft of the manuscript was written by Nabilla Fikria Alviani and all authors commented on previous versions and collaborated to revise the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAcknowledgments\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; The authors have none to declare.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCai T, Verze P, Bjerklund Johansen TE. The Quality of Life Definition: Where Are We Going? Uro. 2021;1(1):14\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eKarimi M, Brazier J. Health, Health-Related Quality of Life, and Quality of Life: What is the Difference? Pharmacoeconomics. 2016;34(7):645\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eKatona M, Schmidt R, Schupp W, Graessel E. Predictors of health-related quality of life in stroke patients after neurological inpatient rehabilitation: A prospective study. Health Qual Life Outcomes. 2015;13(1):1\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eFranchignoni F, Salaffi F. Quality of life assessment in rehabilitation medicine. Eura Medicophys. 2003;39(4):191\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eSalinas J, Sprinkhuizen SM, Ackerson T, Bernhardt J, Davie C, George MG, et al. An international standard set of patient-centered outcome measures after stroke. Strokes. 2016;47(1):180\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eKatzan IL, Lapin B. PROMIS GH (Patient-reported outcomes measurement information system global health) scale in stroke a validation study. Strokes. 2018;49(1):147\u0026ndash;54.\u003c/li\u003e\n\u003cli\u003eBusija L, Ackerman IN, Haas R, Wallis J, Nolte S, Bentley S, et al. Adult Measures of General Health and Health-Related Quality of Life. Arthritis Care Res. 2020;72(S10):522\u0026ndash;64.\u003c/li\u003e\n\u003cli\u003eElsman EBM, Roorda LD, Crins MHP, Boers M, Terwee CB. Dutch reference values for the Patient-Reported Outcomes Measurement Information System Scale v1. 2-Global Health (PROMIS-GH). J Patient-Reported Outcomes. 2021;5(1):1\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eTerwee CB, Zuidgeest M, Vonkeman HE, Cella D, Haverman L, Roorda LD. Common patient-reported outcomes across ICHOM Standard Sets: the potential contribution of PROMIS\u0026reg;. BMC Med Inform Decis Mak. 2021;21(1):1\u0026ndash;13.\u003c/li\u003e\n\u003cli\u003eKang D, Kim Y, Lim J, Yoon J, Kim S, Kang E, et al. 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Ann Card Anaesth. 2019;22(4):407\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eZamanzadeh V, Ghahramanian A, Rassouli M, Abbaszadeh A, Alavi-Majd H, Nikanfar AR. Design and Implementation Content Validity Study: Development of an instrument for measuring Patient-CenteredCommunications. J Caring Sci. 2015 Jun;4(2):165\u0026ndash;78.\u003c/li\u003e\n\u003cli\u003ePolit DF, Beck CT, Owen S V. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health. 2007;30(4):459\u0026ndash;67.\u003c/li\u003e\n\u003cli\u003eSupratiknya A. Psychological Measurement. Sanata Sharma University; 2014. 127\u0026ndash;130 p.\u003c/li\u003e\n\u003cli\u003eFriedenberg L. Psychological Testing: Design, Analysis, and Use. Allyn and Bacon; 1995.\u003c/li\u003e\n\u003cli\u003eGliem JA, Gliem RR. Calculating, interpreting, and reporting Cronbach\u0026apos;s alpha reliability coefficient for Likert-type scales. In Midwest Research-to-Practice Conference in Adulthood, Continuing, and Community; 2003.\u003c/li\u003e\n\u003cli\u003eSharma N, Chakrabarti S, Grover S. Gender differences in caregiving among family - caregivers of people with mental illnesses. World J Psychiatry. 2016;6(1):7.\u003c/li\u003e\n\u003cli\u003eGebremichael DY, Hadush KT, Kebede EM, Zegeye RT. Gender differences in health-related quality of life and associated factors among people living with HIV/AIDS attending anti-retroviral therapy at public health facilities, western Ethiopia: Comparative cross-sectional study. BMC Public Health. 2018;18(1):1\u0026ndash;11.\u003c/li\u003e\n\u003cli\u003eEdgerton JD, Roberts LW, von Below S. Education and Quality of Life BT - Handbook of Social Indicators and Quality of Life Research. In: Land KC, Michalos AC, Sirgy MJ, editors. Dordrecht: Springer Netherlands; 2012. p. 265\u0026ndash;96.\u003c/li\u003e\n\u003cli\u003eSarah Javed, Salma Javed, Arfa Khan. Effect of Education on Quality of Life and Well-Being. Int J Indian Psychol. 2016;3(4):1\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eKrawczyk-Suszek M, Kleinrok A. Health-Related Quality of Life (HRQoL) of People over 65 Years of Age. Int J Environ Res Public Health. 2022 Jan;19(2).\u003c/li\u003e\n\u003cli\u003eGondodiputro S, Rizki Hidayati A, Rahmiati L. Gender, Age, Marital Status, and Education as Predictors to Quality of Life in Elderly: WHOQOL-BREF Indonesian Version. Int J Integr Heal Sci. 2018;6(1):36\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eZamanzadeh V, Ghahramanian A, Rassouli M, Abbaszadeh A, Alavi-Majd H, Nikanfar AR. Design and Implementation Content Validity Study: Development of an instrument for measuring Patient-Centered Communication. J Caring Sci. 2015 Jun;4(2):165\u0026ndash;78.\u003c/li\u003e\n\u003cli\u003eTavakol M, Wetzel A. Factor Analysis: a means for theory and instrument development in support of construct validity. Vol. 11, International journal of medical education. England; 2020. p. 245\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eBat\u0026oacute; A, Brodsky V, Zolt\u0026aacute;n A, Bal\u0026aacute;zs M, Fanni J. Psychometric properties and general population reference values for PROMIS Global Health in Hungary. Eur J Heal Econ. 2023;(0123456789).\u003c/li\u003e\n\u003cli\u003eHays RD, Bjorner JB, Revicki DA, Spritzer KL, Cella D. Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items. Qual Life Res. 2009;18(7):873\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003ePellicciari L, Chiarotto A, Giusti E, Crins MHP, Roorda LD, Terwee CB. Psychometric properties of the patient-reported outcomes measurement information system scale v1.2: global health (PROMIS-GH) in a Dutch general population. Health Qual Life Outcomes. 2021;19(1):1\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eHeale R, Twycross A. Validity and reliability in quantitative studies. Evid Based Nurs. 2015;18(3):66\u0026ndash;7. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Patient-reported outcomes, Quality of life, Questionnaire, Validity, Reliability","lastPublishedDoi":"10.21203/rs.3.rs-3993154/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3993154/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe assessment of Health-Related Quality of Life (HRQoL) is an essential clinical outcome, focusing on the subjective perception of individuals regarding their health status in the physical, mental, and social dimensions. However, HRQoL assessment in large-scale studies and mass inspections presents various challenges, necessitating the development of non-burdensome instrument. A promising instrument in this context is PROMIS Global Health, a widely used English tool, which requires translation, validation, and cross-cultural testing for non-English populations, such as Indonesia. Therefore, this study aimed to validate and assess the reliability of the Indonesian version of Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health for comprehensive HRQoL assessment.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe sample population comprised 343 participants, including patients, caregivers, and residents of Physical Medicine and Rehabilitation. PROMIS Global Health was subjected to translation and cultural adaptation using the Functional Assessment of Chronic Illness Therapy (FACIT) method. Subsequently, the content validity test was carried out using S-CVI assessment of 5 experts, and the internal validity was evaluated with Confirmatory Factor Analysis (CFA). The reliability test was performed with Cronbach's Alpha for internal consistency as well as the test-retest method for external consistency and item discrimination analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e Questions or statements in the Indonesian version of PROMIS Global Health based on S-CVI/Universal Agreement (0.90), χ2/df (1.53), RMSEA (0.04), RMR (0.03), and CFI (0.99). The reliability results showed that Chronbach's Alpha score for Global Physical Health (GPH) and Global Mental Health (GMH) was 0.61 and 0.77, respectively. In addition, the test-retest method showed a good correlation (GPH r\u0026thinsp;=\u0026thinsp;0.727, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; GMH r\u0026thinsp;=\u0026thinsp;0.701, p\u0026thinsp;\u0026lt;\u0026thinsp;05) with item analysis factor loading of \u0026gt;\u0026thinsp;0.3.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBased on the results, the validity and reliability tests showed that questions or statements in PROMIS Global Health were valid and reliable.\u003c/p\u003e","manuscriptTitle":"Assessing the Validity and Reliability of the Indonesian Version of Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-02 20:40:41","doi":"10.21203/rs.3.rs-3993154/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eca98a49-935f-4814-9f92-7dbc9561df18","owner":[],"postedDate":"April 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-19T10:09:04+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-02 20:40:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3993154","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3993154","identity":"rs-3993154","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}