Aim. The aim of this study was to identify the impact of bedtime, wake time, sleep duration, sleep-onset latency, and sleep quality on depressive symptoms and suicidal ideation amongst Japanese freshmen. Methods. This cross-sectional data was derived from the baseline survey of the Enhancement of Q-University Students Intelligence (EQUSITE) study conducted from May to June, 2010. A total of 2,631 participants were recruited and completed the following self-reported questionnaires: the Pittsburgh Sleep Quality Index (PSQI), the Center for Epidemiologic Studies Depression Scale (CES-D), and the original Health Support Questionnaires developed by the EQUSITE study research team. Results. Of 1,992 participants eligible for analysis, 25.5% (n = 507) reported depressive symptoms (CES-D total score ≥ 16), and 5.8% (n = 115) reported suicidal ideation. The present study showed that late bedtime (later than 01:30), sleep-onset latency (≥30 minutes), and poor sleep quality showed a marginally significant association with depressive symptoms. Poor sleep quality was seen to predict suicidal ideation even after adjusting for depressive symptoms. Conclusion. The current study has important implications for the role of bedtime in the prevention of depressive symptoms. Improving sleep quality may prevent the development of depressive symptoms and reduce the likelihood of suicidal ideation.
Active religious practice is central to Muslim livelihood. Among Muslims, this religious engagement is rarely studied with regards to its association in coping with critical illnesses. This study investigated the association between Islamic religiosity with depression and anxiety in Muslim cancer patients. Fifty-nine cancer patients recruited from a Malaysian public hospital and a cancer support group completed the Muslim Religiosity and Personality Inventory, Beck Depression Inventory and Beck Anxiety Inventory in July and August 2010. Islamic religiosity score, obtained from the sum of subscale scores of Islamic worldview and religious personality represents a greater understanding and practice of Islam in a comprehensive manner. Results yielded a significant negative correlation between Islamic religiosity score with both depression and anxiety. Depression was also found to be negatively associated with religious personality subscale. Older patients scored significantly higher on both Islamic worldview and religious personality whereas patients with higher education scored higher on Islamic worldview. Married patients scored significantly higher scores on religious personality than the single patients. Results provided an insight into the significant role of religious intervention which has huge potentials to improve the psychological health of cancer patients particularly Muslims in Malaysia. Research implication includes the call for professionals to meet the spiritual needs of Muslim cancer patients and incorporating religious components in their treatment, especially in palliative care.
Early detection of depression allows rapid intervention and reduce the escalation of the disorder. Conventional method requires patient to seek diagnosis and treatment by visiting a trained clinician. Bio-sensors technology such as automatic depression detection using speech can be used to assist early diagnosis for detecting remotely those who are at risk. In this research, we focus on detecting depression using Bahasa Malaysia language using speech signals that are recorded remotely via subject’s personal mobile devices. Speech recordings from a total of 43 depressed subjects and 47 healthy subjects were gathered via online platform with diagnosis validation according to the Malay beck depression inventory II (Malay BDI-II), patient health questionnaire (PHQ-9) and subject’s declaration of major depressive disorder (MDD) diagnosis by a trained clinician. Classifier models were compared using time-based and spectrum-based microphone independent feature set with hyperparameter tuning. Random forest performed best for male reading speech with 73% accuracy while support vector machine performed best on both male spontaneous speech and female reading speech with 74% and 73% accuracy, respectively. Automatic depression detection on Bahasa Malaysia language has shown to be promising using machine learning and microphone independent features but larger database is necessary for further validation and improving performance.
Introduction: Currently, own individual perception is recognized as one of the important factors in the prevention of disease, including coronavirus disease, COVID-19. Given the massive impact of COVID-19 on all population's life, including nurses as one of the main health services providers in the country, this study aims to translate and validate the Malay Version 5-Items Brief Illness Perception Questionnaire, BIP-Q5 towards COVID-19 among Malaysian nurses. Materials and Methods: Forward and backward translations and pretesting of the BIP-Q5 to Malay were conducted among nurses, subject matter experts, and language professionals. The validations process was elicited through an online cross-sectional study involving 56 nurses based on a ~10:1 subject-to-items ratio sample size estimations. Results: The principal component analysis (PCA) revealed one best component with eigenvalues more than one, confirming the questionnaire's original version. There are five items within the single component, and all are with weightage of over 43%. The scree plot supported the findings, which showed that at least one factors are suitable to be retained. The overall Cronbach's α coefficient was 0.7 and the intraclass correlation coefficient was 0.659. The Kaiser-Meyer-Olkin was 0.655, and Bartlett's test of sphericity p-value was <0.001. Conclusion: This study showed that the translated Malay Version 5-Items Brief Illness Perception Questionnaire, BIP-Q5 has a good psychometric property,
Introduction: Depression risk has been significantly associated with sociodemographic aspects such as education levels and self-rated health. The aim was to investigate the relationship of socio-demographic characteristics particularly level of education, and self-rated health on depressive symptoms among Malaysian adults. Methods: This is a cross-sectional study among Malaysians who aged 16 to 52 years old. Respondents were recruited via social media, using convenience sampling. Sociodemographic questions include education levels and self-rated health among other questions. Depressive symptoms were measured using Beck Depression Inventory-II, Malay version. The data were analysed using Chi- Square Test. Two-Way of ANOVA was utilized to determine the association of education levels and self-rated health on depressive symptoms. Results: Chi-Square indicated that age, level of education, job categories and self-rated health had a significant relationship at p<0.05 with key variables used in this study, presence, and absence of depressive symptoms except for gender, race and marital status. Two-way of ANOVA results revealed a significant interaction between self-rated health, level of education and depressive symptoms (F = 2.711,df=5,p<0.05). Conclusion: Malaysian individuals with low education levels showed depressive symptoms and showed a significant association with low self-rated health, however some of them rated themselves as healthy. Therefore, the government needs to make health literacy a priority for everyone, particularly for those with low levels of education and individuals who perceived themselves as mentally healthy.
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