Quality of Life Research最新文献

Purpose: This study aimed to examine the association between the risk of obstructive sleep apnea (OSA) and health-related quality of life (HRQoL) using nationally representative data from the Korea National Health and Nutrition Examination Survey (KNHANES).

Methods: We analyzed data from the 2023 KNHANES, including 3968 adults aged 40 years and older. OSA risk was assessed using the STOP-BANG questionnaire, and HRQoL was measured with the HINT-8, a validated instrument developed in Korea. Complex sample linear regression analyses were performed to investigate the relationship between OSA risk categories and the HINT-8 utility index, adjusting for sociodemographic and health-related factors. Sensitivity analyses using multiple imputation and models with continuous variables were also conducted to assess robustness.

Results: Participants at moderate risk of OSA had significantly lower HINT-8 utility scores compared to those at low risk (β = -0.009; 95% CI = -0.017 to -0.001). The high-risk group showed a non-significant trend toward lower HRQoL. In a sensitivity analysis additionally adjusted for age and sex, the negative association remained consistent in both magnitude and direction. Overall, the results were robust across multiple analytical approaches.

Conclusion: Only the moderate-risk group showed a statistically significant reduction in HRQoL, whereas the high-risk group demonstrated a non-significant trend. The STOP-BANG questionnaire, owing to its simplicity and high sensitivity, may be useful for the early identification of individuals at moderate risk of impaired HRQoL. These findings support the value of integrating OSA risk screening into population-based health strategies to promote HRQoL. Obstructive sleep apnea (OSA) is a common sleep problem where breathing stops during sleep. Many people with OSA are not diagnosed, even though the condition can reduce energy, raise health risks, and lower quality of life. This study was done to find out how the risk of OSA affects how people feel and function in daily life.We used national data from South Korea to examine this. People were grouped by their risk for OSA using the STOP-BANG questionnaire, a simple screening tool. We measured their quality of life using the HINT-8, which looks at physical ability, pain, mental health, and daily functioning.The study found that people with a moderate risk of OSA had lower quality of life than those with low risk. These results remained even after adjusting for age, sex, income, and health conditions.Our findings suggest that people who are at risk for OSA already experience reduced well-being, even if they have not been diagnosed. Simple tools like STOP-BANG can help identify these individuals early so that they can receive care and improve their quality of life.

Purpose: Longitudinal patterns of patient-reported quality of life (QoL) remain poorly understood in patients with salivary gland cancer (SGC). This study aimed to identify distinct trajectories of QoL over 5 years following SGC treatment and to evaluate the baseline characteristics associated with adverse recovery patterns.

Methods: This prospective cohort study was conducted at a tertiary cancer center from 2016. Patients with histologically confirmed SGC were enrolled prior to treatment and followed longitudinally for up to 5 years. Repeated QoL assessments were conducted using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and Head and Neck Cancer-Specific Module 35 questionnaires at standardized intervals. The primary outcome was the global QoL trajectory over 5 years, modeled using group-based trajectory analysis.

Results: Among 252 participants, three QoL trajectories were identified: Stable Good (n = 132, 52.4%), Declining (n = 41, 16.2%), and Delayed Recovery (n = 79, 31.3%). Female sex, older age, worse baseline pain score, and recurrence were significantly associated with an unstable trajectory of QoL. Interestingly, treatment intensity was not a significant factor for QoL. The Delayed Recovery group showed improvements in nutritional status and pain burden. The Declining group experienced deterioration in role, cognitive, and social functioning, along with increased fatigue, pain, and head-and-neck-specific symptoms.

Conclusion: Long-term QoL changes following SGC treatment are heterogeneous, with nearly half of the patients experiencing either persistent or delayed impairment. Trajectory-based classifications may support the early identification of vulnerable survivors and inform risk-stratified supportive care strategies targeting pain, nutrition, and emotional function.

Purpose: The validity of inferences from patient-reported outcome measure (PROM) scores can be confounded by differential item functioning (DIF). DIF occurs when there is heterogeneity in how patients respond to and interpret questions about their health, despite having the same underlying health status. Ignoring the effects of DIF could lead to inaccurate interpretations and misinformed clinical decisions resulting in compromised healthcare delivery. Tree-based item response theory (IRT) models are recommended as an alternative class of methods for analyzing PROMs because they offer a robust approach for identifying DIF when covariates associated with DIF are unknown a priori.

Methods: This paper introduces a web application developed using R Shiny, which enables users to implement tree-based IRT models for DIF assessment in potentially heterogeneous populations. The app provides flexible model specifications, visualization tools, and customizable settings to accommodate various data types and research needs. A practical tutorial is included, guiding users through the application interface, data preparation, model selection, and interpretation of results.

Results: The web application (https://ucalgary-pcma-lab.shinyapps.io/tree_based_dif_analysis/) offers interactive data upload in .CSV and .XLSX data formats. Recommendations are provided for selecting model parameters within the app based on the results of previous simulation studies. The web app tests for DIF on dichotomous- and polytomous-scored items. The coefficients, item parameters, and plots provide insights into potential sources of DIF.

Conclusion: This web application provides a user-friendly, interactive, innovative, easily accessible, and valuable tool for clinicians, applied health researchers, and analysts seeking to understand sample heterogeneity due to DIF in PROM data.

Objective: Examine the psychometric properties of the PROMIS Depression Short From 2.0 (PROMIS-D-SF), Caregiver and Youth Report in comparison with a legacy measure of depression, the Short Mood and Feelings Questionnaire, using a clinical sample.

Methods: Participants were 233 youth and caregivers referred to a behavioral health clinic by their pediatrician. Participants and their caregivers completed PROMIS-D-SF (youth and caregiver proxy), Short Mood and Feelings (SMFQ) (youth and caregiver proxy), and Semi-structured Interview. Descriptive, correlational, psychometric, receiver operating characteristic (ROC), and exploratory factor analysis were conducted for both measures.

Results: PROMISD-SF youth and caregiver correlations with the youth and caregiver SMFQ were 0.73 and 0.68 and had Area Under the Curve (AUCs) values ranging from 0.7 to 0.77 for the detection of a depression diagnosis. The PROMIS-D-SF youth measure had favorable test re-test reliability and the factor structure of the PROMIS measure correlated with each factor of the legacy SMFQ measure.

Implications: The PROMIS-D-SF demonstrated strong psychometric properties, correlated significantly with the SMFQ, and showed acceptable diagnostic accuracy for depression. This measure appears to be favorable for use in evidence-based assessment, including depression screening and progress monitoring.

Purpose: Little is known about the effectiveness of health behaviour intervention in improving health-related quality of life (HRQOL) despite HRQOL being an important outcome in Type 2 diabetes (T2DM) management. This study examined the effectiveness of a culturally appropriate health behavioural intervention in improving HRQOL of people with T2DM in Nepal.

Methods: A cluster randomized controlled trial was conducted among 481 people with T2DM from 30 randomly selected healthcare facilities in Kavrepalanchok and Nuwakot districts. The intervention group received 12 culturally tailored and group-based intervention sessions for six months whereas, the control group received usual care. The primary outcomes of this study were changes in the EuroQOL (EQ5D-3L) index score and EuroQOL visual analogue scale (EQVAS) score between baseline and six-month post-intervention. The intervention effect was assessed using generalized estimating equation models.

Results: At six-months post-intervention, there was a positive and statistically significant effect on EQVAS (β₁ = 3.61, 95%CI: 0.05, 7.17) in the intervention group compared to control group. No statistically significant effect was observed in EQ5D-3L index score. A statistically significant increase in EQVAS score of 0.5 was observed per session attended by the study participants (β₁ = 0.49, 95%CI: 0.01, 0.98).

Conclusion: The health behaviour intervention led to improved HRQOL. An increase in the number of intervention sessions attended was significantly associated with higher EQVAS scores, emphasizing the need for longer-term and engaging interventions that are well adhered to. Longer term assessment of change in HRQOL outcomes are needed when actual changes in HRQOL are more likely to be observed.

Trial registration: Australia and New Zealand Clinical Trial Registry (ACTRN12621000531819).

Background: Methods for collecting self-reported health status measures in population health surveys vary significantly across countries, presenting challenges to comparability. The EuroQol Data for Assessment of Population Health Needs and Instrument Evaluation (EQ-DAPHNIE) project aims to address this issue by developing infrastructure to generate representative datasets across multiple countries. This initiative aims to standardize data collection methodologies and to evaluate the performance of various health status measures, providing a foundation for reliable population health assessments. This paper describes the rationale, design and data collection methods for the EQ-DAPHNIE project.

Methods/design: EQ-DAPHNIE employs a cross-sectional online survey design targeting the general adult population across various countries. Participants were recruited through an online panel provider. Each country had a target sample of 4500 responses, with quota sampling to ensure representativeness based on age, sex, income, region, and language. The survey collected comprehensive data on social determinants of health at both individual and neighbourhood levels. Participation was voluntary, and measures were taken to maintain data anonymity and ensure data quality through pre-testing and various quality assurance approaches.

Discussion: The EQ-DAPHNIE project represents a significant advancement in generating large, representative, and comparable population health datasets across multiple countries. By employing precise sampling strategies, robust recruitment and data collection methods, and rigorous quality control measures, the project aims to provide a valuable resource for assessing and understanding population health and evaluating various health-related quality of life (HRQoL) and wellbeing instruments.

Purpose: This study aims to develop a mapping model from the EORTC QLQ-C30 and QLQ-STO22 to the EQ-5D-5L.

Methods: Data were collected from 1059 gastric cancer patients in mainland China. The conceptual overlap between the EORTC QLQ-C30/QLQ-STO22 and EQ-5D-5L was assessed using the Pearson correlation coefficient. Four regression models were applied to estimate the algorithm: ordinary least squares (OLS), Tobit regression (Tobit), ordered probit regression (Oprobit), and beta mixture regression (Betamix). The independent variables in the models comprised the scale dimension scores of the EORTC QLQ-C30 and QLQ-STO22, squared terms of relevant dimension scores, age, and gender. The generalizability of the models was assessed using random sample validation and five-fold cross-validation. Model performance was evaluated using four primary metrics: root mean squared error (RMSE), mean absolute error (MAE), intraclass correlation coefficient (ICC), and absolute error (AE).

Results: The mean health utility value of the EQ-5D-5L was 0.853 (SD = 0.240). The Oprobit3 demonstrated the best performance among all evaluated models, with RMSE = 0.197, MAE = 0.111, AE > 0.05 (%) = 56.84, AE > 0.1 (%) = 28.61, and ICC = 0.703. The predictors included all dimensions of the EORTC QLQ-C30 and QLQ-STO22 questionnaires, as well as age and gender.

Conclusions: The developed algorithm enables researchers to estimate EQ-5D-5L health utilities based on EORTC QLQ-C30 and QLQ-STO22 scores. This approach facilitates cost-utility analyses in gastric cancer patients when EQ-5D-5L data are unavailable.

Background: Unemployment is a recognized risk factor for impaired physical and mental health, and numerous studies have shown that unemployed people often report a reduced health-related quality of life (HRQoL). The concurrent effects of having a mental illness and being unemployed reinforce one another, leading to chronic symptoms and reduced employability. This study examined the relationships between unemployment, HRQoL and other work- and health-related factors in unemployed individuals with mental illnesses.

Methods: We analyzed cross-sectional data from unemployed adults participating in the "Leipzig-Individual Placement and Support for people with mental illnesses" (LIPSY) project. All participants met ICD-10 criteria for at least one mental disorder. HRQoL was assessed with the 12-Item Short-Form Survey (SF-12), yielding a Physical Component Summary (PCS) and Mental Component Summary (MCS). Two multiple regression analyses (outcomes: PCS, MCS) included age, gender, education, partnership status, social network size, unemployment duration (≤ 24 vs 24 months), work ability score (WAS), and depression, anxiety, and somatization (Mini-Symptom Checklist, Mini-SCL) as predictors.

Results: Our sample included 452 unemployed participants with mental illnesses with an average age of 35.5 years, 50.4% were female. Higher age and somatization were negatively associated with PCS, while female gender, work ability, and anxiety showed positive associations. MCS was negatively associated with higher education, depression, and anxiety, and positively with work ability.

Conclusion: Our findings highlight the complex associations between demographic, psychological, and work-related factors and HRQoL. Supportive measures for unemployed individuals could have a dual impact by improving both HRQoL and employability.