METHOD: This study will comprehensively review full-text papers published between 2013 and 2023. We will search 3 databases, PubMed, SCOPUS, and Web of Science, using the keyword search strategy to find articles related to the issue. Preferred Reporting Items for Systematic Reviews and Meta-Analyses will be used to guide the selection of relevant studies. The results will then be assessed using the standard Cochrane Quality assessment method. The outcome is addressed in light of a narrative synthesis that utilizes a theme category and focuses on each component's main conclusions.
RESULT: This protocol describes the planned scope and methodology for the systematic review and meta-analysis that will provide current evidence on; The status of health literacy among the community in protected areas and; The effect of Protected Areas on health literacy according to their types and characteristics.
CONCLUSION: Meta-analysis of low-to-high health literacy status will benefit the development of policy recommendations for protected areas.
METHODS: Respondents were sampled with quotas for urbanicity, gender, age, and ethnicity to ensure representativeness of the Malaysian population. The study was conducted using a standardized protocol involving the EuroQol Valuation Technology (EQ-VT) computer-assisted interview system. Respondents were administered ten composite time trade-off (C-TTO) tasks and seven discrete choice experiment (DCE) tasks. Both linear main effects and constrained non-linear regression models of C-TTO-only data and hybrid models combining C-TTO and DCE data were explored to determine an efficient and informative model for value set prediction.
RESULTS: Data from 1125 respondents representative of the Malaysian population were included in the analysis. Logical consistency was present in all models tested. Using cross-validation, eight-parameter models for C-TTO only and C-TTO + DCE hybrid data displayed greater out-of-sample predictive accuracy than their 20-parameter, main-effect counterparts. The hybrid eight-parameter model was chosen to represent the Malaysian value set, as it displayed greater out-of-sample predictive accuracy over C-TTO data than the C-TTO-only model, and produced more precise estimates. The estimated value set ranged from - 0.442 to 1.
CONCLUSIONS: The constrained eight-parameter hybrid model demonstrated the best potential in representing the Malaysian value set. The presence of the Malaysian EQ-5D-5L value set will facilitate its application in research and health technology assessment activities.
DESIGN: Systematic review.
DATA SOURCES: EMBASE, MEDLINE, Scopus and Global Health databases.
ELIGIBILITY CRITERIA: Studies were eligible if they: (1) included Nepalese migrant workers aged 18 or older working in the GCC countries or Malaysia or returnee migrant workers from these countries; (2) were primary studies that investigated health and well-being status/issues; and (3) were published in English language before 8 May 2020.
STUDY APPRAISAL: All included studies were critically appraised using Joanna Briggs Institute study specific tools.
RESULTS: A total of 33 studies were eligible for inclusion; 12 studies were conducted in Qatar, 8 in Malaysia, 9 in Nepal, 2 in Saudi Arabia and 1 each in UAE and Kuwait. In majority of the studies, there was a lack of disaggregated data on demographic characteristics of Nepalese migrant workers. Nearly half of the studies (n=16) scored as 'high' quality and the rest (n=17) as 'moderate' quality. Five key health and well-being related issues were identified in this population: (1) occupational hazards; (2) sexual health; (3) mental health; (4) healthcare access and (5) infectious diseases.
CONCLUSION: To our knowledge, this is the most comprehensive review of the health and well-being of Nepalese migrant workers in the GCC countries and Malaysia. This review highlights an urgent need to identify and implement policies and practices across Nepal and destination countries to protect the health and well-being of migrant workers.
METHODS: A simulation-based approach contingent on all single-level transitions defined by the EQ-5D-5L descriptive system was used to estimate the MID for each algorithm.
RESULTS: The resulting mean (and standard deviation) instrument-defined MID estimates were Germany, 0.083 (0.022); Indonesia, 0.093 (0.012); Ireland, 0.098 (0.023); Malaysia, 0.072 (0.010); Poland, 0.080 (0.030); Portugal, 0.080 (0.018); Taiwan, 0.101 (0.010); and the United States, 0.078 (0.014).
CONCLUSIONS: These population preference-based MID estimates and accompanying evidence of how such values vary as a function of baseline index score can be used to aid interpretation of index score change. The marked consistency in the relationship between the calculated MID estimate and the range of the EQ-5D-5L index score, represented by a ratio of 1:20, might substantiate a rule of thumb allowing for MID approximation in EQ-5D-5L index score warranting further investigation.
METHODS: A multi-stage sampling design was adopted for the study and data collection took place in three phases in 2010, 2011, and 2012 in the Northern region of Malaysia. Face-to-face interviews involved respondents answering both 13 TTO and 15 VAS valuation tasks were carried out. Both additive and multiplicative model specifications were explored using the valuation data. Model performance was evaluated using out-of-sample predictive accuracy by applying the cross-validation technique. The distribution of the model values was also graphically compared on Bland-Altman plots and kernel density distribution curves.
RESULTS: Data from 630 and 611 respondents were included for analyses using TTO and VAS models, respectively. In terms of main-effects specifications, cross-validation results revealed a slight superiority of multiplicative models over its additive counterpart in modelling TTO values. However, both main-effects models had roughly equal predictive accuracy for VAS models. The non-linear multiplicative model with I32 term, MULT7_TTO, performed best for TTO models; while, the linear additive model with N3 term, ADD11_VAS, outperformed the other VAS models. Multiplicative modelling neither altered the dimensional rankings of importance nor did it change the distribution of values of the health states.
CONCLUSION: Using EQ-5D-3L valuation data, multiplicative modelling was shown to improve out-of-sample predictive accuracy of TTO models but not of VAS models.