Cultural adaptation and psychometric evaluation of the CHU9D in Hong Kong adolescents

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Methods A cross-sectional survey design was employed for data collection. Adolescents aged 13 to 17 years were recruited from diverse local community settings to complete a self-administered questionnaire that included the adapted CHU-9D, the Pediatric Quality of Life Inventory (PedsQL), and relevant demographic items. Psychometric evaluations encompassed assessments of ceiling and floor effects, factorial validity through confirmatory factor analysis, convergent validity via correlations with PedsQL scores, and known-group validity to examine differences across predefined risk groups. Results A total of 627 adolescents successfully completed the survey, providing a robust dataset for analysis. The unidimensionality of the CHU-9D was confirmed, demonstrating excellent model fit indices. A ceiling effect was observed, with 27% of participants reporting full health status on the CHU-9D descriptive system, indicating potential limitations in capturing variations at the upper end of health. Convergent validity was supported by significant correlations between CHU-9D utility scores and PedsQL items and subscales. The instrument exhibited strong known-group validity, effectively discriminating HRQoL differences across various risk groups with statistically significant results. Conclusion The culturally adapted Traditional Chinese version of the CHU-9D demonstrates sound psychometric properties in Hong Kong adolescents, establishing it as a valid tool for measuring and valuing HRQoL in this population and cultural context. CHU-9D adolescents Hong Kong psychometric properties preference-based measurement Figures Figure 1 Introduction The Child Health Utility 9D (CHU-9D) is a pediatric health-related quality of life (HRQoL) instrument designed specifically for children and adolescents aged 7–17 years. 1 It measures nine dimensions to estimate utility scores that support cost-utility analyses of health and social care interventions. 2 Because adolescence involves rapid physical, psychological, and social development, young people typically assign different weights to HRQoL dimensions compared with adults. 3 Consequently, economic evaluations of treatments and preventive program targeting adolescents must consider their preferences to ensure accurate estimation of benefits, informed resource allocation, and optimized health outcomes. When applying the CHU-9D in diverse populations, cultural and linguistic adaptation is essential to maintain conceptual and measurement equivalence. Although a Simplified Chinese version has been validated in mainland China, 4 and a Traditional Chinese version is available in Taiwan, these versions may not be directly applicable to the Hong Kong (HK) context. Beyond differences in written conventions, HK adolescents grow up in a different sociocultural environment characterized by a unique education system, intense academic competition, and specific cultural norms and expectations around achievement and family roles. 5 These contextual and cultural features may shape how health-related quality of life (HRQoL) is perceived and reported. Therefore, a HK-specific Traditional Chinese version of the CHU-9D is needed to ensure that items are culturally relevant, easily interpretable, and capable of capturing the lived experiences and priorities of HK adolescents. Rigorous psychometric evaluation in this group is also required to confirm that the adapted instrument performs robustly, preserves the strengths of the original, and sensitively reflects locally salient domains. Such validation enhances the instrument’s scientific credibility and practical utility for evaluating interventions targeting prevalent adolescent issues in HK, including rising mental health difficulties in a highly competitive environment. Thus, the present study aimed to adapt the CHU-9D into Traditional Chinese specifically for HK and then to assess its psychometric properties in a sample of local adolescents. Methods Participants and survey design This cross-sectional survey was conducted in Hong Kong from December 2025 to January 2026. Data collection was managed by a professional local survey company. Adolescents were eligible to participate if they were between 13 and 17 years old, able to read and write in Traditional Chinese, and if both they and their parent or legal guardian could provide informed consent and assent. Well-trained investigators visited 10 different public locations, including parks, markets, and shopping malls, across Hong Kong to recruit participants. At each site, investigators screened adolescents for eligibility and explained the study procedures. Those who met the inclusion criteria and agreed to participate, along with their parent or legal guardian, provided written informed consent and assent. Participants completed the survey using a tablet provided by the investigator, ensuring privacy and data accuracy. The questionnaire was programmed and administered via the Qualtrics platform. All data were collected anonymously and securely stored. The study protocol, including the consent and assent forms, was reviewed and approved by the Institutional Review Board of The Hong Kong Polytechnic University (Ref. ID: HSEARS20251105004). Measures CHU-9D and cultural adaption The CHU-9D is a preference-based, generic HRQoL instrument specifically designed for use with children and adolescents. The descriptive system of the CHU-9D consists of nine dimensions: worried, sad, pain, tired, annoyed, schoolwork/homework, sleep, daily routine, and activities. Each dimension has five response levels, allowing children to self-report their health status. The CHU-9D can be used to generate utility values for economic evaluations and is widely used in both clinical and population-based research to assess the impact of health conditions and interventions on young people’s quality of life. The Traditional Chinese version of the CHU-9D was provided by the University of Sheffield. However, this version was originally developed for use in Taiwan, and certain linguistic and cultural differences exist between Taiwan and Hong Kong. To ensure the instrument’s suitability for the Hong Kong context, a cultural adaptation process was undertaken. Cognitive debriefing interviews were conducted with six adolescents aged 15 to 17 years in Hong Kong. During these interviews, participants were asked to complete the CHU-9D and provide feedback on the clarity, relevance, and cultural appropriateness of each item and response option. Their comments were reviewed to identify any terms or phrases that might be unclear or not commonly used in Hong Kong. Based on the feedback, minor modifications were made to the wording of some items to enhance their comprehensibility and cultural relevance for Hong Kong adolescents. The adapted version was then reviewed by a panel of experts in child health and linguistics to ensure content validity. This process confirmed that the Hong Kong Traditional Chinese version of the CHU-9D is both linguistically accurate and culturally appropriate for use in local adolescent populations. The Pediatric Quality of Life Inventory (PedsQL, age:13–17 version) The PedsQL is a widely used instrument for measuring HRQoL in children and adolescents. The PedsQL 13–17 version is specifically designed for teenagers aged 13 to 17 years. 6 It assesses physical, emotional, social, and school functioning through a series of self-reported questions. The PedsQL provides a comprehensive overview of a young person’s well-being and is commonly used in both clinical practice and research to evaluate the impact of health conditions and treatments on adolescents’ quality of life. General health status A visual analogue scale item was employed to assess participants' self-reported health status on a continuum ranging from 0 to 100, where 0 represents the worst imaginable health state and 100 denotes the best imaginable health state. Data analysis Descriptive analyses were conducted to summarize participants’ background information. Categorical variables were presented as frequencies and proportions, while continuous variables were reported as means and standard deviations (SD). A significance level of p < 0.05 was used for all statistical tests. All data analyses were performed using R software. Ceiling and floor The ceiling effect was defined as the proportion of respondents who achieved the highest possible score on the CHU-9D, indicating optimal HRQoL. The floor effect was defined as the proportion of respondents who obtained the lowest possible score, reflecting the poorest health status. If more than 15% of participants scored at either extreme, this was considered indicative of a substantial ceiling or floor effect, which may limit the instrument’s ability to detect changes or differences in health status. The ceiling and floor for both item and scale level were calculated. Factorial validity Confirmatory factor analysis (CFA) was conducted to assess the factorial validity of the CHU-9D. Previous studies have supported a one-factor structure for this instrument. 7 – 9 CFA was performed to confirm this one-factor structure. Model fit was evaluated using the comparative fit index (CFI; acceptable > 0.90), Tucker-Lewis index (TLI; acceptable > 0.90), and root mean square error of approximation (RMSEA; acceptable < 0.08). Convergent validity Hypothesis testing was conducted at both the item and total score levels to assess the convergent validity of the CHU-9D. At the item level, Pearson’s correlation coefficients were calculated between individual CHU-9D dimensions and corresponding PedsQL subscales to evaluate the extent to which similar constructs were related. For example, the CHU-9D "pain" dimension was expected to show a moderate to strong correlation with the PedsQL item “I hurt or ache”, and the CHU-9D "sad" dimension was hypothesized to be moderate-to-strong correlated with the PedsQL item “I feel sad or blue.” At the scale level, correlations were assessed between the CHU-9D LSS and the PedsQL subscale scores. Correlation coefficients of 0.3 or higher were considered indicative of acceptable convergent validity. Known-group validity To assess the known-group validity of the CHU-9D, one-way ANOVA was used to evaluate its capacity to discriminate between subgroups anticipated to exhibit differences in HRQoL. Specifically, CHU-9D utility scores were compared across categories of self-reported sleep duration, weekly exercise frequency, general health status, and selected PedsQL items (e.g., "It is hard for me to run," "I feel sad or blue," "I have low energy," "I have trouble getting along with other teens," and "It is hard to pay attention in class"). These PedsQL items were chosen because they cover the instrument's core subscales while aligning with key CHU-9D dimensions. Effect sizes were calculated using Cohen’s d, with interpretations following conventional thresholds: small (≈ 0.2), medium (≈ 0.5), and large (≈ 0.8). 10 Results Participants A total of 627 adolescent participants completed the survey with a response rate of 26.5% (Table 1 ). The sample is nearly gender-balanced (50.1% male) and evenly distributed across ages 13–17 years. Educational levels range from Secondary Year 1 (1.7%) to Senior Secondary Year 6 (19.5%), with most in higher years. Half (50.7%) report fewer than 3 days of 30-minute moderate-to-vigorous physical activity per week, and 70% sleep 7 hours or less daily. Among responders, 37.3% perceive average income and 41.9% live with both parents. Table 1 Participant’s demographics (N = 627) Characteristics N % Sex Male 314 50.1 Female 313 49.9 Educational level Secondary (Year 1) 11 1.7 Secondary (Year 2) 124 19.7 Secondary (Year 3) 122 19.4 Senior secondary (Year 4) 125 19.9 Senior Secondary (Year 5) 123 19.6 Senior Secondary (Year 6) 122 19.5 Age (years) 13 123 19.6 14 126 20.1 15 127 20.2 16 124 19.8 17 127 20.2 30-min moderate-to-vigorous-intensity physical activity per week (day) 7 188 30.0 Perceived family income Lower than local averge 39 6.2 Equal to local average 234 37.3 Higher than local average 38 6.1 Reject to answer/don’t know 316 50.4 Living condition With parents 263 41.9 With either of the parents 45 7.2 Without parents 3 0.5 Reject to answer/don’t know 316 50.4 CHU-9D profile Most respondents report no problems (ceiling) on CHU-9D descriptive system, with proportions ranging from 40.3% (tired) to 98.2% (daily routine). Severe problems (levels 4–5) are extremely rare across all dimensions. Tiredness shows the greatest impairment, with only 40.3% reporting no tiredness. A notable ceiling effect is present, with 27.7% of respondents in full health. It indicates limited sensitivity to detect subtle variations in health-related quality of life among individuals with minimal or no impairment (Table 2 ). Table 2 CHU-9D Profile CHU-9D 1 2 3 4 5 Worried 79.6 15.5 4.7 0.2 0 Sad 96.3 3.3 0.4 0 0 Pain 92.3 6.4 1.3 0 0 Tired 40.3 40.2 17.7 1.8 0 Annoyed 86.9 12.4 0.3 0.3 0 School work/homework 71.6 22.6 5.3 0.5 0 Sleep 74.8 22.2 3.0 0 0 Able to join activities 80.7 17.5 1.4 0.2 0.2 Daily routine 98.2 1.8 0 0 0 Full health (111111111) 27.7 - - - - Factorial validity The results of CFA supported a unidimensional structure, with all nine items loading positively and significantly on a single factor (standardized loadings ranging from 0.538 for Pain to 0.844 for Sad). Model fit was good to excellent (CFI = 0.974, TLI = 0.965, RMSEA = 0.062), confirming that the one-factor model adequately represents the data. These findings support the common practice of deriving a single preference-based utility score from the CHU-9D, although the lower loadings for some items suggest that future research should also consider multidimensional and invariance testing in different populations (Fig. 1 ). Convergent validity At the item level, each CHU-9D dimension showed statistically significant positive correlations with conceptually matched PedsQL items, with coefficients in the low-to-moderate range (Table 3 ). The strongest associations were observed for Tired (r = 0.50 with “I have low energy”) and Sleep (r = 0.49 with “I have trouble sleeping”). At the scale level, the CHU-9D LSS was significantly and negatively correlated with PedsQL domain and summary scores. The largest correlation was with general health (r = − 0.56), followed by physical functioning (r = − 0.49) and emotional functioning (r = − 0.41). Overall, these findings indicate satisfactory convergent validity for the CHU-9D, while the modest correlation magnitudes suggest that it also captures distinct aspects of functioning and well-being. Table 3 Convergent validity of the CHU-9D CHU-9D PedsQL Correlation coefficient Worried I worry about what will happen to me 0.36 *** Sad I feel sad or blue 0.39 *** Pain I hurt or ache 0.40 *** Tired I have low energy 0.50 *** Annoyed I feel angry 0.28 *** School work/ homework I have trouble keeping up with my schoolwork 0.33 *** Sleep I have trouble sleeping 0.49 *** Able to join activities It is hard for me to do sports activity or exercise 0.27 *** Daily routine It is hard for me to take a bath or shower by myself 0.29 *** CHU-9D LSS Physical functioning -0.49 *** CHU-9D LSS Emotional functioning -0.41 *** CHU-9D LSS Social functioning -0.24 *** CHU-9D LSS School functioning -0.34 *** CHU-9D LSS General health (0-100) -0.56 *** Known-group validity The CHU-9D exhibited strong known-groups validity in discriminating between adolescent subgroups expected to differ in HRQoL, with higher scores consistently indicating greater problems (Table 4 ). Energy and general health groups showed large effect sizes, while other grouping variables demonstrated small to medium effects. This suggests that the unweighted sum score is sensitive to global health and energy-related differences and may be most informative when used in studies or evaluations where physical health is central outcome. Table 4 Known-group validity Groups N Mean (SD) Sleep duration ≤ 7 hours per day 439 11.5(2.8) > 7 hours per day 188 10.4(1.7) Cohen’s d 0.42 P-value < 0.001 Exercise per week < 3 days 319 11.4(2.8) ≥ 3 days 308 11.0(2.0) Cohen’s d 0.19 P-value < 0.001 PedsQL It is hard for me to run Not at all 540 11.1(2.1) Some difficulty 87 12.0(3.5) Cohen’s d 0.39 P-value < 0.001 PedsQL I feel sad or blue No 273 10.8(1.7) Yes 354 11.5(2.7) Cohen’s d 0.29 P-value < 0.001 PedsQL I have low energy No 52 9.8(1.3) Yes 575 11.3(2.5) Cohen’s d 0.64 P-value < 0.001 PedsQL I have trouble getting along with other teens Not difficult 260 10.9(2.1) Difficult 367 11.4(2.6) Cohen’s d 0.21 P-value < 0.001 PedsQL It is hard to pay attention in class No 93 10.6 (2.0) Yes 534 11.3 (2.5) Cohen’s d 0.28 P-value median score 254 10.1 (1.4) Cohen’s d 0.78 P-value < 0.001 Discussion This study reports the first cultural adaptation and psychometric evaluation of the Traditional Chinese CHU-9D among adolescents in HK. The adapted CHU-9D demonstrated satisfactory psychometric performance, including strong factorial validity, acceptable convergent validity, and good known-groups validity. These findings support its use as a preference-based HRQoL measure in this setting, particularly for economic evaluations of adolescent health interventions. About 27.7% of respondents reported full health on the CHU-9D, consistent with previous validations in general adolescent populations, where ceiling effects are common due to generally good health in community samples. For example, studies in the UK, Australia, Sweden, and mainland China have reported full-health proportions between 9.8% and 34.8%, with tiredness and sleep often emerging as the most impaired dimensions. 11 – 14 Tiredness was the most frequently reported problem, which is consistent with the sample profile: 50.7% engaged in fewer than three days of moderate-to-vigorous physical activity per week, and 70% reported sleeping seven hours or less per night. These findings likely reflect broader contextual factors in HK, including intense academic pressure and lifestyle demands that contribute to fatigue and sleep deprivation among adolescents. The unidimensional structure of the CHU-9D supports the use of a single preference-based utility score, which is crucial for calculating quality-adjusted life years in cost-utility analyses of adolescent health interventions. It also strengthens the instrument’s suitability for population monitoring, economic evaluation, and brief screening. However, the variability in item loadings (e.g., lower for pain) suggests that unidimensionality may not hold equally well across all dimensions or subgroups. This indicates further work using multidimensional models, item response theory, and measurement invariance testing to examine whether the measure functions consistently in different populations and contexts. The convergent validity of the CHU-9D was satisfactory but modest, with item-level correlations in the low-to-moderate range. This is broadly in line with previous validation studies, which typically report moderate rather than strong correlations between the CHU-9D and non-preference-based HRQoL measures. Several factors may explain these findings. First, our data were collected from a healthy community sample with limited HRQoL variability, reducing the potential strength of correlations. This is an issue commonly observed in general adolescent populations. 15 Second, conceptual and methodological differences between instruments likely contribute: the PedsQL is a non-preference-based profile focused on functional health, whereas the CHU-9D is a preference-based utility measure designed for economic evaluation and may capture broader aspects of well-being. 16 Third, differences in recall periods or timeframe (e.g., “today” vs “past month”) can attenuate associations by tapping slightly different windows of experience. 17 These findings showed that the CHU-9D may not be viewed as interchangeable with profile measures like the PedsQL and might be best used alongside them when detailed functional domain information is needed. The strong known-group validity of the CHU-9D was supported in the present study, as it significantly discriminated between all predefined risk groups. These results align with and extend previous findings on the CHU-9D in Chinese pediatric populations, where the CHU-9D effectively differentiated children by self-reported general health status and presence of chronic conditions, demonstrating statistically significant differences with moderate to large effect sizes. 4 , 18 , 19 Compared to head-to-head evaluations with the PedsQL, prior evidence has been mixed: some studies reported similar known-group validity between the two instruments, 8 while others found the PedsQL to be superior in discriminating certain health states (e.g., overweight/obesity). 20 The current study's consistent discrimination across groups defined partly by individual PedsQL items provides evidence of the CHU-9D's construct validity in HK adolescents. Several limitations should be addressed. First, the response rate of 26.5% raises potential selection bias, as non-responders may differ in HRQoL. The convenience sampling approach limits generalizability, and the high ceiling effect may reduce discriminative power in healthy populations. Second, this cross-sectional design did not assess test-retest reliability, responsiveness to change, or measurement invariance across subgroups. Last, the use of an unweighted level sum score, rather than a HK-specific preference-based tariff, precludes direct utility estimation for cost-utility analyses. Conclusions In conclusion, the culturally adapted CHU-9D demonstrates good psychometric performance in Hong Kong adolescents, providing a valid tool for measuring and valuing HRQoL in this context. Future research should focus on developing a local preference-based scoring algorithm, testing the instrument in clinical populations to evaluate floor effects and responsiveness, and conducting longitudinal studies to assess reliability over time. These advancements will enhance its applicability in health economic evaluations and policy decisions targeting adolescent health in Hong Kong. Declarations Ethics approval and consent to participate The Institutional Review Board of Hong Kong Polytechnic University approved the research protocol (Ref: HSEARS20251105004). This study complied with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration. All the participants provided written informed consent. Consent for publication Not applicable. Competing interests None to declared. Funding No funding supports. Author Contribution RHX: Conceptualization; Methodology; Software; Validation; Formal analysis; Investigation; Resources; Data Curation; Writing - Original Draft; Writing - Review & Editing; Supervision.YSX: Methodology; Project administration; Writing - Review & Editing. 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 30 Mar, 2026 Reviews received at journal 30 Mar, 2026 Reviews received at journal 06 Mar, 2026 Reviewers agreed at journal 25 Feb, 2026 Reviewers agreed at journal 10 Feb, 2026 Reviewers invited by journal 26 Jan, 2026 Editor assigned by journal 21 Jan, 2026 Submission checks completed at journal 21 Jan, 2026 First submitted to journal 20 Jan, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-8646953","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":599329531,"identity":"99a45a29-194a-471b-8c8e-ece304a5c73d","order_by":0,"name":"Richard Huan Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYDACZgY2MAnEBxgYCsBiBgyMDQnEaGFLACkmQgsDXAuPAXFazNuZnz34uceaweBGzrcHHwwOJzawN2+TYNyRhlOLzGE2c8OeZ+kMkjNytxvOAGnhOVYmwXgmB6cWCWYeNgmeA4cZ+CVyt0nzgLRI5JhJMLZV4NUi+QeohU0i5xlEi/wbwlqkIbbksEFt4QFpwecwNjNpmQPpPJI9z8yBfkk3buNJK7ZIbMPtfQn+w88k3xywljM4nvzswYcKa9l+9sMbb3xsS8apBQZ4GCAR1AwmGRIIaoAAkOI6ItWOglEwCkbBSAIAwIpJCG1OQYwAAAAASUVORK5CYII=","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":true,"prefix":"","firstName":"Richard","middleName":"Huan","lastName":"Xu","suffix":""},{"id":599329532,"identity":"3645aa64-d783-4717-9a8c-bc665bbb13a6","order_by":1,"name":"Yuanshuo Xu","email":"","orcid":"","institution":"Hong Kong Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Yuanshuo","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-01-20 08:51:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8646953/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8646953/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104166596,"identity":"0db5dd13-aacc-491a-842b-9fa8d9cde4e1","added_by":"auto","created_at":"2026-03-08 14:18:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21631,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of factorial validity assessment (CFA)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"CFA.png","url":"https://assets-eu.researchsquare.com/files/rs-8646953/v1/0f83899f4e7b89ad7e512a59.png"},{"id":104779478,"identity":"ccc9259d-ae51-4005-a6cf-fd5e246e69bd","added_by":"auto","created_at":"2026-03-17 07:40:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":824939,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8646953/v1/28ca63f9-d1d2-4c67-8f12-6e514fb18911.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cultural adaptation and psychometric evaluation of the CHU9D in Hong Kong adolescents","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Child Health Utility 9D (CHU-9D) is a pediatric health-related quality of life (HRQoL) instrument designed specifically for children and adolescents aged 7\u0026ndash;17 years.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e It measures nine dimensions to estimate utility scores that support cost-utility analyses of health and social care interventions.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Because adolescence involves rapid physical, psychological, and social development, young people typically assign different weights to HRQoL dimensions compared with adults.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Consequently, economic evaluations of treatments and preventive program targeting adolescents must consider their preferences to ensure accurate estimation of benefits, informed resource allocation, and optimized health outcomes.\u003c/p\u003e \u003cp\u003eWhen applying the CHU-9D in diverse populations, cultural and linguistic adaptation is essential to maintain conceptual and measurement equivalence. Although a Simplified Chinese version has been validated in mainland China,\u003csup\u003e4\u003c/sup\u003e and a Traditional Chinese version is available in Taiwan, these versions may not be directly applicable to the Hong Kong (HK) context. Beyond differences in written conventions, HK adolescents grow up in a different sociocultural environment characterized by a unique education system, intense academic competition, and specific cultural norms and expectations around achievement and family roles.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e These contextual and cultural features may shape how health-related quality of life (HRQoL) is perceived and reported. Therefore, a HK-specific Traditional Chinese version of the CHU-9D is needed to ensure that items are culturally relevant, easily interpretable, and capable of capturing the lived experiences and priorities of HK adolescents. Rigorous psychometric evaluation in this group is also required to confirm that the adapted instrument performs robustly, preserves the strengths of the original, and sensitively reflects locally salient domains. Such validation enhances the instrument\u0026rsquo;s scientific credibility and practical utility for evaluating interventions targeting prevalent adolescent issues in HK, including rising mental health difficulties in a highly competitive environment. Thus, the present study aimed to adapt the CHU-9D into Traditional Chinese specifically for HK and then to assess its psychometric properties in a sample of local adolescents.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and survey design\u003c/h2\u003e \u003cp\u003eThis cross-sectional survey was conducted in Hong Kong from December 2025 to January 2026. Data collection was managed by a professional local survey company. Adolescents were eligible to participate if they were between 13 and 17 years old, able to read and write in Traditional Chinese, and if both they and their parent or legal guardian could provide informed consent and assent. Well-trained investigators visited 10 different public locations, including parks, markets, and shopping malls, across Hong Kong to recruit participants. At each site, investigators screened adolescents for eligibility and explained the study procedures. Those who met the inclusion criteria and agreed to participate, along with their parent or legal guardian, provided written informed consent and assent. Participants completed the survey using a tablet provided by the investigator, ensuring privacy and data accuracy. The questionnaire was programmed and administered via the Qualtrics platform. All data were collected anonymously and securely stored. The study protocol, including the consent and assent forms, was reviewed and approved by the Institutional Review Board of The Hong Kong Polytechnic University (Ref. ID: HSEARS20251105004).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCHU-9D and cultural adaption\u003c/h2\u003e \u003cp\u003eThe CHU-9D is a preference-based, generic HRQoL instrument specifically designed for use with children and adolescents. The descriptive system of the CHU-9D consists of nine dimensions: worried, sad, pain, tired, annoyed, schoolwork/homework, sleep, daily routine, and activities. Each dimension has five response levels, allowing children to self-report their health status. The CHU-9D can be used to generate utility values for economic evaluations and is widely used in both clinical and population-based research to assess the impact of health conditions and interventions on young people\u0026rsquo;s quality of life.\u003c/p\u003e \u003cp\u003eThe Traditional Chinese version of the CHU-9D was provided by the University of Sheffield. However, this version was originally developed for use in Taiwan, and certain linguistic and cultural differences exist between Taiwan and Hong Kong. To ensure the instrument\u0026rsquo;s suitability for the Hong Kong context, a cultural adaptation process was undertaken. Cognitive debriefing interviews were conducted with six adolescents aged 15 to 17 years in Hong Kong. During these interviews, participants were asked to complete the CHU-9D and provide feedback on the clarity, relevance, and cultural appropriateness of each item and response option. Their comments were reviewed to identify any terms or phrases that might be unclear or not commonly used in Hong Kong. Based on the feedback, minor modifications were made to the wording of some items to enhance their comprehensibility and cultural relevance for Hong Kong adolescents. The adapted version was then reviewed by a panel of experts in child health and linguistics to ensure content validity. This process confirmed that the Hong Kong Traditional Chinese version of the CHU-9D is both linguistically accurate and culturally appropriate for use in local adolescent populations.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe Pediatric Quality of Life Inventory (PedsQL, age:13–17 version)\u003c/h3\u003e\n\u003cp\u003eThe PedsQL is a widely used instrument for measuring HRQoL in children and adolescents. The PedsQL 13\u0026ndash;17 version is specifically designed for teenagers aged 13 to 17 years.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e It assesses physical, emotional, social, and school functioning through a series of self-reported questions. The PedsQL provides a comprehensive overview of a young person\u0026rsquo;s well-being and is commonly used in both clinical practice and research to evaluate the impact of health conditions and treatments on adolescents\u0026rsquo; quality of life.\u003c/p\u003e\n\u003ch3\u003eGeneral health status\u003c/h3\u003e\n\u003cp\u003eA visual analogue scale item was employed to assess participants' self-reported health status on a continuum ranging from 0 to 100, where 0 represents the worst imaginable health state and 100 denotes the best imaginable health state.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eDescriptive analyses were conducted to summarize participants\u0026rsquo; background information. Categorical variables were presented as frequencies and proportions, while continuous variables were reported as means and standard deviations (SD). A significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was used for all statistical tests. All data analyses were performed using R software.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCeiling and floor\u003c/h3\u003e\n\u003cp\u003eThe ceiling effect was defined as the proportion of respondents who achieved the highest possible score on the CHU-9D, indicating optimal HRQoL. The floor effect was defined as the proportion of respondents who obtained the lowest possible score, reflecting the poorest health status. If more than 15% of participants scored at either extreme, this was considered indicative of a substantial ceiling or floor effect, which may limit the instrument\u0026rsquo;s ability to detect changes or differences in health status. The ceiling and floor for both item and scale level were calculated.\u003c/p\u003e\n\u003ch3\u003eFactorial validity\u003c/h3\u003e\n\u003cp\u003eConfirmatory factor analysis (CFA) was conducted to assess the factorial validity of the CHU-9D. Previous studies have supported a one-factor structure for this instrument.\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e CFA was performed to confirm this one-factor structure. Model fit was evaluated using the comparative fit index (CFI; acceptable\u0026thinsp;\u0026gt;\u0026thinsp;0.90), Tucker-Lewis index (TLI; acceptable\u0026thinsp;\u0026gt;\u0026thinsp;0.90), and root mean square error of approximation (RMSEA; acceptable\u0026thinsp;\u0026lt;\u0026thinsp;0.08).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eConvergent validity\u003c/h2\u003e \u003cp\u003eHypothesis testing was conducted at both the item and total score levels to assess the convergent validity of the CHU-9D. At the item level, Pearson\u0026rsquo;s correlation coefficients were calculated between individual CHU-9D dimensions and corresponding PedsQL subscales to evaluate the extent to which similar constructs were related. For example, the CHU-9D \"pain\" dimension was expected to show a moderate to strong correlation with the PedsQL item \u0026ldquo;I hurt or ache\u0026rdquo;, and the CHU-9D \"sad\" dimension was hypothesized to be moderate-to-strong correlated with the PedsQL item \u0026ldquo;I feel sad or blue.\u0026rdquo; At the scale level, correlations were assessed between the CHU-9D LSS and the PedsQL subscale scores. Correlation coefficients of 0.3 or higher were considered indicative of acceptable convergent validity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eKnown-group validity\u003c/h2\u003e \u003cp\u003eTo assess the known-group validity of the CHU-9D, one-way ANOVA was used to evaluate its capacity to discriminate between subgroups anticipated to exhibit differences in HRQoL. Specifically, CHU-9D utility scores were compared across categories of self-reported sleep duration, weekly exercise frequency, general health status, and selected PedsQL items (e.g., \"It is hard for me to run,\" \"I feel sad or blue,\" \"I have low energy,\" \"I have trouble getting along with other teens,\" and \"It is hard to pay attention in class\"). These PedsQL items were chosen because they cover the instrument's core subscales while aligning with key CHU-9D dimensions. Effect sizes were calculated using Cohen\u0026rsquo;s d, with interpretations following conventional thresholds: small (\u0026asymp;\u0026thinsp;0.2), medium (\u0026asymp;\u0026thinsp;0.5), and large (\u0026asymp;\u0026thinsp;0.8).\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA total of 627 adolescent participants completed the survey with a response rate of 26.5% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The sample is nearly gender-balanced (50.1% male) and evenly distributed across ages 13\u0026ndash;17 years. Educational levels range from Secondary Year 1 (1.7%) to Senior Secondary Year 6 (19.5%), with most in higher years. Half (50.7%) report fewer than 3 days of 30-minute moderate-to-vigorous physical activity per week, and 70% sleep 7 hours or less daily. Among responders, 37.3% perceive average income and 41.9% live with both parents.\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\u003eParticipant\u0026rsquo;s demographics (N\u0026thinsp;=\u0026thinsp;627)\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 \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\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\u003eSecondary (Year 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary (Year 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary (Year 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior secondary (Year 4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior Secondary (Year 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior Secondary (Year 6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\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\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30-min moderate-to-vigorous-intensity physical activity per week (day)\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\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep hours per day (hour)\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\u003e\u0026le;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived family income\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\u003eLower than local averge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEqual to local average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher than local average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReject to answer/don\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving condition\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\u003eWith parents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWith either of the parents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithout parents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReject to answer/don\u0026rsquo;t know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCHU-9D profile\u003c/h2\u003e \u003cp\u003eMost respondents report no problems (ceiling) on CHU-9D descriptive system, with proportions ranging from 40.3% (tired) to 98.2% (daily routine). Severe problems (levels 4\u0026ndash;5) are extremely rare across all dimensions. Tiredness shows the greatest impairment, with only 40.3% reporting no tiredness. A notable ceiling effect is present, with 27.7% of respondents in full health. It indicates limited sensitivity to detect subtle variations in health-related quality of life among individuals with minimal or no impairment (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\u003eCHU-9D Profile\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=\"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 \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\u003eCHU-9D\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnoyed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e86.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchool work/homework\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAble to join activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily routine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e98.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFull health (111111111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFactorial validity\u003c/h2\u003e \u003cp\u003eThe results of CFA supported a unidimensional structure, with all nine items loading positively and significantly on a single factor (standardized loadings ranging from 0.538 for Pain to 0.844 for Sad). Model fit was good to excellent (CFI\u0026thinsp;=\u0026thinsp;0.974, TLI\u0026thinsp;=\u0026thinsp;0.965, RMSEA\u0026thinsp;=\u0026thinsp;0.062), confirming that the one-factor model adequately represents the data. These findings support the common practice of deriving a single preference-based utility score from the CHU-9D, although the lower loadings for some items suggest that future research should also consider multidimensional and invariance testing in different populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eConvergent validity\u003c/h2\u003e \u003cp\u003eAt the item level, each CHU-9D dimension showed statistically significant positive correlations with conceptually matched PedsQL items, with coefficients in the low-to-moderate range (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The strongest associations were observed for Tired (r\u0026thinsp;=\u0026thinsp;0.50 with \u0026ldquo;I have low energy\u0026rdquo;) and Sleep (r\u0026thinsp;=\u0026thinsp;0.49 with \u0026ldquo;I have trouble sleeping\u0026rdquo;). At the scale level, the CHU-9D LSS was significantly and negatively correlated with PedsQL domain and summary scores. The largest correlation was with general health (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.56), followed by physical functioning (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.49) and emotional functioning (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.41). Overall, these findings indicate satisfactory convergent validity for the CHU-9D, while the modest correlation magnitudes suggest that it also captures distinct aspects of functioning and well-being.\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\u003eConvergent validity of the CHU-9D\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHU-9D\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePedsQL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorrelation coefficient\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI worry about what will happen to me\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.36\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI feel sad or blue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI hurt or ache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI have low energy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnoyed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI feel angry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchool work/ homework\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI have trouble keeping up with my schoolwork\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI have trouble sleeping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAble to join activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIt is hard for me to do sports activity or exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaily routine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIt is hard for me to take a bath or shower by myself\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHU-9D LSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.49\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHU-9D LSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmotional functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.41\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHU-9D LSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.24\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHU-9D LSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchool functioning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHU-9D LSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral health (0-100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.56\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eKnown-group validity\u003c/h2\u003e \u003cp\u003eThe CHU-9D exhibited strong known-groups validity in discriminating between adolescent subgroups expected to differ in HRQoL, with higher scores consistently indicating greater problems (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Energy and general health groups showed large effect sizes, while other grouping variables demonstrated small to medium effects. This suggests that the unweighted sum score is sensitive to global health and energy-related differences and may be most informative when used in studies or evaluations where physical health is central outcome.\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\u003eKnown-group validity\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 \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep duration\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\u003e\u0026le;\u0026thinsp;7 hours per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.5(2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;7 hours per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.4(1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise per week\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\u003e\u0026lt;\u0026thinsp;3 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.4(2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.0(2.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePedsQL It is hard for me to run\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\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.1(2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome difficulty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.0(3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePedsQL I feel sad or blue\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.8(1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.5(2.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePedsQL I have low energy\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.8(1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.3(2.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePedsQL I have trouble getting along with other teens\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\u003eNot difficult\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.9(2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifficult\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.4(2.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePedsQL It is hard to pay attention in class\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.3 (2.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral health status (0-100)\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\u003e\u0026le; median score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.9 (2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; median score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study reports the first cultural adaptation and psychometric evaluation of the Traditional Chinese CHU-9D among adolescents in HK. The adapted CHU-9D demonstrated satisfactory psychometric performance, including strong factorial validity, acceptable convergent validity, and good known-groups validity. These findings support its use as a preference-based HRQoL measure in this setting, particularly for economic evaluations of adolescent health interventions.\u003c/p\u003e \u003cp\u003eAbout 27.7% of respondents reported full health on the CHU-9D, consistent with previous validations in general adolescent populations, where ceiling effects are common due to generally good health in community samples. For example, studies in the UK, Australia, Sweden, and mainland China have reported full-health proportions between 9.8% and 34.8%, with tiredness and sleep often emerging as the most impaired dimensions.\u003csup\u003e\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Tiredness was the most frequently reported problem, which is consistent with the sample profile: 50.7% engaged in fewer than three days of moderate-to-vigorous physical activity per week, and 70% reported sleeping seven hours or less per night. These findings likely reflect broader contextual factors in HK, including intense academic pressure and lifestyle demands that contribute to fatigue and sleep deprivation among adolescents.\u003c/p\u003e \u003cp\u003eThe unidimensional structure of the CHU-9D supports the use of a single preference-based utility score, which is crucial for calculating quality-adjusted life years in cost-utility analyses of adolescent health interventions. It also strengthens the instrument\u0026rsquo;s suitability for population monitoring, economic evaluation, and brief screening. However, the variability in item loadings (e.g., lower for pain) suggests that unidimensionality may not hold equally well across all dimensions or subgroups. This indicates further work using multidimensional models, item response theory, and measurement invariance testing to examine whether the measure functions consistently in different populations and contexts.\u003c/p\u003e \u003cp\u003eThe convergent validity of the CHU-9D was satisfactory but modest, with item-level correlations in the low-to-moderate range. This is broadly in line with previous validation studies, which typically report moderate rather than strong correlations between the CHU-9D and non-preference-based HRQoL measures. Several factors may explain these findings. First, our data were collected from a healthy community sample with limited HRQoL variability, reducing the potential strength of correlations. This is an issue commonly observed in general adolescent populations.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Second, conceptual and methodological differences between instruments likely contribute: the PedsQL is a non-preference-based profile focused on functional health, whereas the CHU-9D is a preference-based utility measure designed for economic evaluation and may capture broader aspects of well-being.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Third, differences in recall periods or timeframe (e.g., \u0026ldquo;today\u0026rdquo; vs \u0026ldquo;past month\u0026rdquo;) can attenuate associations by tapping slightly different windows of experience.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e These findings showed that the CHU-9D may not be viewed as interchangeable with profile measures like the PedsQL and might be best used alongside them when detailed functional domain information is needed.\u003c/p\u003e \u003cp\u003eThe strong known-group validity of the CHU-9D was supported in the present study, as it significantly discriminated between all predefined risk groups. These results align with and extend previous findings on the CHU-9D in Chinese pediatric populations, where the CHU-9D effectively differentiated children by self-reported general health status and presence of chronic conditions, demonstrating statistically significant differences with moderate to large effect sizes.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e Compared to head-to-head evaluations with the PedsQL, prior evidence has been mixed: some studies reported similar known-group validity between the two instruments,\u003csup\u003e8\u003c/sup\u003e while others found the PedsQL to be superior in discriminating certain health states (e.g., overweight/obesity).\u003csup\u003e20\u003c/sup\u003e The current study's consistent discrimination across groups defined partly by individual PedsQL items provides evidence of the CHU-9D's construct validity in HK adolescents.\u003c/p\u003e \u003cp\u003eSeveral limitations should be addressed. First, the response rate of 26.5% raises potential selection bias, as non-responders may differ in HRQoL. The convenience sampling approach limits generalizability, and the high ceiling effect may reduce discriminative power in healthy populations. Second, this cross-sectional design did not assess test-retest reliability, responsiveness to change, or measurement invariance across subgroups. Last, the use of an unweighted level sum score, rather than a HK-specific preference-based tariff, precludes direct utility estimation for cost-utility analyses.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, the culturally adapted CHU-9D demonstrates good psychometric performance in Hong Kong adolescents, providing a valid tool for measuring and valuing HRQoL in this context. Future research should focus on developing a local preference-based scoring algorithm, testing the instrument in clinical populations to evaluate floor effects and responsiveness, and conducting longitudinal studies to assess reliability over time. These advancements will enhance its applicability in health economic evaluations and policy decisions targeting adolescent health in Hong Kong.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The Institutional Review Board of Hong Kong Polytechnic University approved the research protocol (Ref: HSEARS20251105004). This study complied with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration. All the participants provided written informed consent.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eNone to declared.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funding supports.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eRHX: Conceptualization; Methodology; Software; Validation; Formal analysis; Investigation; Resources; Data Curation; Writing - Original Draft; Writing - Review \u0026amp; Editing; Supervision.YSX: Methodology; Project administration; Writing - Review \u0026amp; Editing.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStevens K. Developing a descriptive system for a new preference-based measure of health-related quality of life for children. Qual Life Res. 2009;18(8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11136-009-9524-9\u003c/span\u003e\u003cspan address=\"10.1007/s11136-009-9524-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStevens K. Valuation of the child health utility 9D index. PharmacoEconomics. 2012;30(8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2165/11599120-000000000-00000\u003c/span\u003e\u003cspan address=\"10.2165/11599120-000000000-00000\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProsser LA, Hammitt JK, Keren R. 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Int J Obes. 2023;47(7). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41366-023-01305-5\u003c/span\u003e\u003cspan address=\"10.1038/s41366-023-01305-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CHU-9D, adolescents, Hong Kong, psychometric properties, preference-based measurement","lastPublishedDoi":"10.21203/rs.3.rs-8646953/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8646953/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to perform a cultural adaptation of the Child Health Utility 9D (CHU-9D) instrument into Traditional Chinese specifically for use in Hong Kong, and evaluating its psychometric properties among a representative sample of local adolescents.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional survey design was employed for data collection. Adolescents aged 13 to 17 years were recruited from diverse local community settings to complete a self-administered questionnaire that included the adapted CHU-9D, the Pediatric Quality of Life Inventory (PedsQL), and relevant demographic items. Psychometric evaluations encompassed assessments of ceiling and floor effects, factorial validity through confirmatory factor analysis, convergent validity via correlations with PedsQL scores, and known-group validity to examine differences across predefined risk groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 627 adolescents successfully completed the survey, providing a robust dataset for analysis. The unidimensionality of the CHU-9D was confirmed, demonstrating excellent model fit indices. A ceiling effect was observed, with 27% of participants reporting full health status on the CHU-9D descriptive system, indicating potential limitations in capturing variations at the upper end of health. Convergent validity was supported by significant correlations between CHU-9D utility scores and PedsQL items and subscales. The instrument exhibited strong known-group validity, effectively discriminating HRQoL differences across various risk groups with statistically significant results.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe culturally adapted Traditional Chinese version of the CHU-9D demonstrates sound psychometric properties in Hong Kong adolescents, establishing it as a valid tool for measuring and valuing HRQoL in this population and cultural context.\u003c/p\u003e","manuscriptTitle":"Cultural adaptation and psychometric evaluation of the CHU9D in Hong Kong adolescents","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 14:18:22","doi":"10.21203/rs.3.rs-8646953/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-30T17:58:32+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-30T13:50:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-06T08:07:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233575191419490318760199085651756609889","date":"2026-02-25T09:24:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331632246338267472976373881122065055477","date":"2026-02-11T00:36:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-26T07:39:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-21T08:46:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-21T08:43:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Health and Quality of Life Outcomes","date":"2026-01-20T08:27:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6220781e-d13f-4842-8d8e-dc669a24d60c","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T07:41:05+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 14:18:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8646953","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8646953","identity":"rs-8646953","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}