OBJECTIVES: This study was aimed to explore the occurrence of anxiety, depression and to identify the factors associated with hospital readmission among older patients after AECOPD discharge.
METHODS: A multicentre prospective study was conducted in Malaysia (from 1st September 2012 till 31st September 2013) among older patients (≥60 years) hospitalised for AECOPD. Anxiety and depression were assessed on discharge using previously validated questionnaires, Generalized Anxiety Disorder-7 (GAD-7 and Geriatric Depression Scale (GDS-15), respectively. Patients were followed up for a period of 3 months after discharge.
RESULTS: A total of 81 patients with a median age of 72 years (IQR 66.40-78.00) were recruited. Anxiety was observed in 34.57% while 38.27% had depression. Both anxiety and depression were detected in 25.93% of the patients. A history of frequent AECOPD admissions was found to be associated with developing depressive symptoms, while anxiety scores were associated with severe dyspnoea. Severe depression was more commonly identified among patients aged 60-75 and in those with a history of tuberculosis. A high readmission rate (40.74%) during the 3-month period was noticed. History of frequent AECOPD admissions (OR = 2.87; 95% CI 1.05-7.85, P = 0.040) and ischemic heart disease (IHD) (OR = 4.04; 95% CI 1.1-14.6, P = 0.032) were identified as the factors associated with the risk of hospital readmission.
CONCLUSIONS: Anxiety and depression were found to be relatively common among older patients with AECOPD. IHD and history of frequent COPD hospitalisation were associated with short-term readmission among the elderly.
METHOD: This research was carried out on a sample of 263 participants (age range 12-24 years old), from Klang Valley, Selangor. The survey package comprises demographic information, a measure of reasons for living, social support, depression, anxiety and stress. To analyse the data, correlation analysis and a series of linear multiple regression analysis were carried out.
RESULTS: Findings showed that there were low negative relationships between all subdomains and the total score of reasons for living and depression. There were also low negative relationships between domain-specific of social support (family and friends) and total social support and depression. In terms of the family alliance, self-acceptance and total score of reasons for living, they were negatively associated with anxiety, whereas family social support was negatively associated with stress. The linear regression analysis showed that only future optimism and family social support found to be the significant predictors for depression. Family alliance and total reasons for living were significant in predicting anxiety, whereas family social support was significant in predicting stress.
CONCLUSION: These findings have the potential to promote awareness related to depression, anxiety, and stress among youth in Malaysia.
MATERIALS AND METHODS: This cross-sectional study was conducted among vitiligo patients aged 18 years and older in Hospital Klang, Selangor between October 2021 and June 2022. Assessment instruments used were Vitiligo Area Scoring Index (VASI) and Hospital Anxiety and Depression Scale (HADS). Demographic data and clinical characteristics of vitiligo patients were recorded.
RESULTS: Of the 100 participants, 12 (12%) and 21 (21%) had depression and anxiety, respectively. The mean depression score (HADS-depression component) was 3.4 (SD 3.4) and mean anxiety score (HADS-anxiety component) was 4.7 (SD 3.9). There were significantly higher number of patients with abnormal HADS-D score in the age group of 35-51 years (p=0.029), single status (p=0.001), with employment (p=0.014) and disease duration <2 years (p=0.004). Patients in the divorced/widowed group had a significant association with anxiety (p=0.011).
CONCLUSION: The prevalence of depression was 12% while anxiety was 21% in our cohort. Vitiligo has a significant psychosocial impact, thus clinicians should actively evaluate the mental health of these patients with the use of screening tools such as HADS and provide appropriate referrals and management.
MATERIALS AND METHODS: The data came from the larger COMET-G study. The study sample includes 12,792 health professionals from 40 countries (62.40% women aged 39.76 ± 11.70; 36.81% men aged 35.91 ± 11.00 and 0.78% non-binary gender aged 35.15 ± 13.03). Distress and clinical depression were identified with the use of a previously developed cut-off and algorithm, respectively.
STATISTICAL ANALYSIS: Descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses, and Factorial Analysis of Variance (ANOVA) tested relations among variables.
RESULTS: Clinical depression was detected in 13.16% with male doctors and 'non-binary genders' having the lowest rates (7.89 and 5.88% respectively) and 'non-binary gender' nurses and administrative staff had the highest (37.50%); distress was present in 15.19%. A significant percentage reported a deterioration in mental state, family dynamics, and everyday lifestyle. Persons with a history of mental disorders had higher rates of current depression (24.64% vs. 9.62%; p
METHOD: This is a cross-sectional, survey-based study in which participants responded to questionnairesregarding perceived burden (ZBI), quality of life (IEQoL), psychological distress (DASS-21), family functioning (FAD) and perceived social support (MSPSS). Additional measures include socio-demographics and clinical characteristics of the care-recipient.
RESULTS: A total of 111 caregivers participated, of whom 72.1% were females, 55% parents, 59.5% Chinese, 51.4% unemployed and 46.0% with tertiary education.Approximately half (42.3%) reported mild-to-moderate levels of burden (mean ZBI score 29.93, SD 16.09).Furthermore, multiple regression analysisidentified10 predictors of caregiver burden, namely family functioning, weekly caregiving hours, number of caregivers per family, attitude towards epilepsy, family support, caregivers' gender, personal income and as well as care-recipients' age of onset, seizure frequency and ADL dependency (F(10, 85) = 11.37, p