Methods: This study used five series of National Health and Morbidity Survey data from 1986 to 2015. Healthcare utilisation for inpatient, outpatient and dental care were analysed. SES was grouped based on household expenditure variables accounting for total number of adults and children in the household using consumption per adult equivalents approach. The determination of healthcare utilisation across the SES segments was measured using concentration index.
Results: The overall distribution of inpatient utilisation tended towards the pro-poor, although only data from 1996 (P-value = 0.017) and 2006 (P-value = 0.021) were statistically significant (P < 0.05). Out-patient care showed changing trends from initially being pro-rich in 1986 (P < 0.05), then gradually switching to pro-poor in 2015 (P < 0.05). Dental care utilisation was significantly pro-rich throughout the survey period (P < 0.05). Public providers mostly showed significantly pro-poor trends for both in- and out-patient care (P < 0.05). Private providers, meanwhile, constantly showed a significantly pro-rich (P < 0.05) trend of utilisation.
Conclusion: Total health utilisation was close to being equal across SES throughout the years. However, this overall effect exhibited inequities as the effect of pro-rich utilisation in the private sector negated the pro-poor utilisation in the public sector. Strategies to improve equity should be consistent by increasing accessibility to the private sectors, which has been primarily dominated by the richest population.
Methods: A multi-center cross sectional study was conducted for a month in out-patient wards of hospitals in Khobar, Dammam, Makkah, and Madinah, Saudi Arabia. Patients were randomly selected from a registered patient pools at hospitals and the item-subject ratio was kept at 1:20. The tool was assessed for factorial, construct, convergent, known group and predictive validities as well as, reliability and internal consistency of scale were also evaluated. Sensitivity, specificity, and accuracy were also evaluated. Data were analyzed using SPSS v24 and MedCalc v19.2. The study was approved by concerned ethics committees (IRB-129-25/6/1439) and (IRB-2019-05-002).
Results: A total of 282 responses were received. The values for normed fit index (NFI), comparative fit index (CFI), Tucker Lewis index (TLI) and incremental fit index (IFI) were 0.960, 0.979, 0.954 and 0.980. All values were >0.95. The value for root mean square error of approximation (RMSEA) was 0.059, i.e., <0.06. Hence, factorial validity was established. The average factor loading of the scale was 0.725, i.e., >0.7, that established convergent validity. Known group validity was established by obtaining significant p-value <0.05, for the associations based on hypotheses. Cronbach's α was 0.865, i.e., >0.7. Predictive validity was established by evaluating odds ratios (OR) of demographic factors with adherence score using logistic regression. Sensitivity was 78.16%, specificity was 76.85% and, accuracy of the tool was 77.66%, i.e., >70%.
Conclusion: The Arabic version of GMAS achieved all required statistical parameters and was validated in Saudi patients with chronic diseases.
METHOD: A convenience sample of 102 patients was recruited from four Cure and Care Service Centres in Malaysia.
RESULTS: Principal component analysis with varimax rotation supported two-factor solutions for each subscale: problem recognition, desire for help and treatment readiness, which accounted for 63.5%, 62.7% and 49.1% of the variances, respectively. The Cronbach's alpha coefficients were acceptable for the overall measures (24 items: ∝ = 0.89), the problem recognition scale (10 items; ∝ = 0.89), desire for help (6 items; ∝ = 0.64) and treatment readiness scale (8 items; ∝ = 0.60). The results also indicated significant motivational differences for different modalities, with inpatients having significantly higher motivational scores in each scale compared to outpatients.
CONCLUSION: The present study pointed towards the favourable psychometric properties of a motivation for treatment scale, which can be a useful instrument for clinical applications of drug use changes and treatment.