METHODS: The AD8 was translated into Malay for Malay-speaking participants. A correlation analysis and a receiver operator characteristic curve were generated to establish the psychometric properties of the AD8 in relation to the MoCA.
RESULTS: One hundred fifty patients and their caretakers completed the AD8 and MoCA. Using a cutoff score of 1/8, the AD8 had 81% sensitivity and 59% specificity for the detection of cognitive impairment in PD. With a cutoff score of 2/8, the AD8 had 83% specificity and 64% sensitivity. The area under the receiver operator characteristic curve was 80%, indicating good-to-excellent discriminative ability.
DISCUSSION: These findings suggest that the AD8 can reliably differentiate between cognitively impaired and cognitively normal patients with PD and is a useful caregiver screening tool for PD.
METHODS: The English version of the KDQOL-36 was translated according to international guidelines to Malay. Content validity was verified by an expert panel and piloted in five patients. Our instrument was then administered to patients with chronic kidney disease stage 1-3A and patients on hemodialysis at baseline and 4 weeks later.
RESULTS: A total of 181/232 patients agreed to participate (response rate = 78.0%). The majority were male (69.6%) with a median age of 51.0 years. Exploratory factor analysis found that the KDQOL-36 had three domains. All three domains showed low to moderate correlation (Spearman's Rho = 0.297-0.610) with the Europe Quality of Life Five Dimension questionnaire. Patients on hemodialysis (physical component summary = 39.8; mental component summary = 53.1;burden of disease = 37.5; symptoms/burden list = 75.0; effects of kidney disease on daily life = 68.8) had significantly worse quality of life than patients with chronic kidney disease stage 1-3A (physical component summary = 49.9; mental component summary = 52.9; burden of disease = 75.0; symptoms/burden list = 85.4; effects of kidney disease on daily life = 93.8, p
METHODS: A cross sectional study on nationally representative sample deaths that occurred in Malaysia during 2013 was used. A VA questionnaire suitable for local use was developed. Trained field interviewers visited the family members of the deceased at their homes and conducted face to face interviews with the next of kin. Completed questionnaires were reviewed by trained physicians who assigned multiple and underlying causes. Reference diagnoses for validation were obtained from review of medical records (MR) available for a sample of the overall study deaths.
RESULTS: Corresponding MR diagnosis with matched sample of the VA diagnosis were available in 2172 cases for the validation study. Sensitivity scores were good (>75%) for transport accidents and certain cancers. Moderate sensitivity (50% - 75%) was obtained for ischaemic heart disease (64%) and cerebrovascular disease (72%). The validation sample for deaths due to major causes such as ischaemic heart disease, pneumonia, breast cancer and transport accidents show low cause-specific mortality fraction (CSMF) changes. The scores obtained for the top 10 leading site-specific cancers ranged from average to good.
CONCLUSION: We can conclude that VA is suitable for implementation for deaths outside the health facilities in Malaysia. This would reduce ill-defined mortality causes in vital registration data, and yield more accurate national mortality statistics.
DESIGN: We conducted a multi-country cross-sectional study.
METHODS: Following a literature review and patient focus groups, an expert panel generated questionnaire items. Following a pilot study, item numbers were reduced. The final questionnaire consisted of three sections: demographics, perceived QoC and one open-ended question. Data was collected from patients (n = 531) discharged from hospitals across seven countries in South East Europe (languages: Turkish, Greek, Portuguese, Romanian, Croatian, Macedonian and Bulgarian). Reliability and validity of the measure were assessed.
RESULTS: Confirmatory factor analysis was used to compare various factor models of patient-perceived QoC. Good model fit was demonstrated for a two-factor model: communication and interpersonal care, and hospital facilities.
CONCLUSIONS: The ORCAB (Improving quality and safety in the hospital: The link between organisational culture, burnout and quality of care) Patient QoC questionnaire has been collaboratively and exhaustively developed between healthcare professionals and patients. It enables patient QoC data to be assessed in the context of the IOM pillars of quality, considering both technical and interpersonal dimensions of care. It represents an important first step in including the patient perspective.
METHODS: The English version of Catquest-9SF questionnaire was translated and back translated into Malay and Chinese languages. The Malay and Chinese translated versions were self-administered by 236 and 202 pre-operative patients drawn from a cataract surgery waiting list, respectively. The translated Catquest-9SF data and its four response options were assessed for fit to the Rasch model.
RESULTS: The Catquest-9SF performed well in the Malay and Chinese translated versions fulfilling all criteria for valid measurement, as demonstrated by Rasch analysis. Both versions of questionnaire had ordered response thresholds, with a good person separation (Malay 2.84; and Chinese 2.59) and patient separation reliability (Malay 0.89; Chinese 0.87). Targeting was 0.30 and -0.11 logits in Malay and Chinese versions respectively, indicating that the item difficulty was well suited to the visual abilities of the patients. All items fit a single overall construct (Malay infit range 0.85-1.26, outfit range 0.73-1.13; Chinese infit range 0.80-1.51, outfit range 0.71-1.36), unidimensional by principal components analysis, and was free of Differential Item Functioning (DIF).
CONCLUSIONS: These results support the good overall functioning of the Catquest-9SF in patients with cataract. The translated questionnaire to Malay and Chinese-language versions are reliable and valid in measuring visual disability outcomes in the Malaysian cataract population.
MATERIALS AND METHODS: The EQ- 5D was cross-culturally adapted and translated using an iterative process following standard guidelines. Consenting adult Malay- and Tamil-speaking subjects at a primary care facility in Singapore were interviewed using a questionnaire (including the EQ-5D, a single item assessing global health, the SF-8 and sociodemographic questions) in their respective language versions. Known-groups and convergent construct validity of the EQ-5D was investigated by testing 30 a priori hypotheses per language at attribute and overall levels.
RESULTS: Complete data were obtained for 94 Malay and 78 Indian patients (median age, 54 years and 51 years, respectively). At the attribute level, all 16 hypotheses were fulfilled with several reaching statistical significance (Malay: 4; Tamil: 5). At the overall level, 42 of 44 hypotheses related to the EQ-5D/ EQ-VAS were fulfilled (Malay: 22; Tamil: 20), with 21 reaching statistical significance (Malay: 9; Tamil: 12).
CONCLUSION: In this study among primary care patients, the Singapore Malay and Tamil EQ-5D demonstrated satisfactory known-groups and convergent validity.
METHOD: A cross-sectional survey was conducted among university undergraduate students in Nigeria. The study consisted of 300 participants in the EFA (males 55.7%, females 44.3%) and 430 participants in the CFA (males 54.0%, females 46.0%). Participants were selected using a convenience sampling approach to assess their perceptions regarding SDH. Content Validity Index (CVI), Face Validity Index (FVI), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Composite Reliability (CR), Average Variance Extracted (AVE), Cronbach's alpha, and Intraclass Correlation Coefficient (ICC) were computed to determine the psychometric properties of the newly developed SDH scale.
RESULTS: In the EFA, two factors were extracted (structural determinants of SDH and intermediary determinants of SDH), with all 20 items retained. The total variance explained by the EFA model was 61.8%, and the factor correlation was 0.178. The Cronbach's alpha values of the two factors were 0.917 and 0.939. In the CFA, the initial model did not fit the data well based on fit indices. After several re-specification of the model, the final re-specified measurement model demonstrated adequate fit factor structure of the SDH scale with two factors and 20 items (CFI = 0.943, TLI = 0.930, SRMR = 0.056, RMSEA = 0.053, RMSEA p-value = 0.220). The CR was 0.797 for structural determinants of SDH and 0.794 for intermediary determinants of SDH. The ICC was 0.938 for structural determinants of SDH and 0.941 for intermediary determinants of SDH.
CONCLUSION: The findings indicate that the SDH scale has adequate psychometric properties and can be used to assess the perceived level of SDH. We recommended that this tool be tested in other populations with diverse age groups and other demographic characteristics.