Methods: This study used a cross-sectional design with data from the Indonesian Demographic and Health Survey (IDHS) of 2017. The independent variables were age, employment status, education, marital status, wealth status, health insurance and parity. The dependent variable was the use of contraception. The statistical significance was set at p <0.05 using bivariate analysis and binary logistic regression.
Results: The study showed that the age group of 45-49 years (OR 0.199; 95% CI 0.149-0.266), secondary education (OR 2.227; 95% CI 2.060-2.514), women married/living with their partner (OR 43.752; 95% CI: 35.484-53.946), wealth status: middle (OR 1.492; 95% CI 1.400-1.589) and multipara (OR 2.524; 95% CI: 2.328-2.737) exhibited the increased use of contraception among women of childbearing age in rural Indonesia.
Conclusion: The variables proven to represent obstacles to contraceptive use among women of childbearing age in rural Indonesia include old age, no education, no husband/partner, poverty and already having one child.
Objective: The aim was to translate and adapt the English PFFS for use in Malaysian clinical settings.
Methods: The original English PFFS underwent forward and backward-translation by two bilingual translators to and from the Malay language. A finalized version, the PFFS-Malay (PFFS-M), was formed after expert reviewers' consensus and was pilot tested with 20 patients, 20 caregivers, 16 healthcare assistants, 17 nurses and 22 doctors. Score agreement between patients and their caregivers and among healthcare professionals were assessed. All participants rated their understanding of the scale using the feasibility survey forms.
Results: A total of 95 participants were included. There were high percentages of scoring agreements among all participants on the scale (66.7% to 98.9%). Overall feedback from all respondents were positive and supported the face validity of the PFFS-M.
Conclusion: The PFFS-M reflects an accurate translation for the Malaysian population. The scale is usable and feasible and has face validity. Reliability and predictive validity assessments of the PFFS-M are currently underway.
METHOD: A quantitative cross-sectional study was conducted using secondary data from the Indonesian Family Life Survey 2014. The sample included 3,603 adolescents aged 10-19 years. Data were analysed using logistic regression statistical tests.
RESULTS: Of the adolescents, 29.1% had depressive symptoms. The bivariate analysis showed that sex, region, economic status, chronic illness history, sleep quality, smoking habit, and personality type were associated with a higher probability of depressive symptoms among the adolescents.
CONCLUSION: A history of chronic diseases contributes the most to the occurrence of depressive symptoms among adolescents. To reduce the prevalence of chronic diseases associated with depression, the Indonesian government must make preventive efforts through early detection among young people.
MATERIALS AND METHODS: Two-hundred and eighty three (283) older people with type 2 diabetes were enrolled in this study. Mini-Cog and mini-mental state examination (MMSE) Thai 2002 were used to measure cognitive impairment while Thai geriatric screening test (TGDS) was used to measure depressive mood in all participants. Spearmen correlation was applied to determine the relationship between cognitive function and depressive mood.
RESULTS: There was a positive relationship between cognitive impairment and depressive mood in older people with type 2 diabetes. The scores from Mini-Cog and MMSE Thai 2002 were negatively correlated with TGDS scores while adjusting for the effects of age and years of education with rs = -0.1, p = 0.06 and rs = -0.2, p<0.01, respectively. Although it showed an inverse relationship of the scores between cognitive and depressive mood screening tests, the results between the tests were positive when interpreting the test scores. It means that the higher score in Mini-Cog and MMSE Thai 2002 (non-cognitive impairment) were associated with the lower score in TGDS (non-depressed mood).
CONCLUSION: The finding of this study showed that older people with type 2 diabetes who had cognitive impairment seemed to have depressive mood. Hence, these two co-morbidities should be considered in order to give an optimal care to older people with diabetes.