Objective. The UCLA Loneliness Scale, containing 20 items, is one of the commonly used loneliness scales. Some shorter versions have been developed using factor analysis. The study aimed to shorten the UCLA Loneliness Scale using Rasch and factor analysis methods and test the psychometric properties of the new scale.Methods. The full sample of the study included 719 respondents, divided into three subsamples (205, 324, and 190 for samples 1-3, respectively). The original, 20-item Revised UCLA Loneliness Scale (R-ULS) was shortened using 205 students (sample 1); the shortened scale was then validated for construct and concurrent validity with 324 students (sample 2) and 190 clinical participants (sample 3). Confirmatory factor analysis and Rasch analysis were used for construct validity. Convergent, discriminant, and concurrent validity were assessed by exploring the correlation with other psychological measurements.Results. In sample 1, the R-ULS was shortened to a 6-item scale (RULS-6) that fits the Rasch model. The RULS-6 met the criteria of unidimensionality and local independence without differential item functioning due to age and sex, and good targeting the clinical sample. Person Separation Index (PSI) reflected that reliability from the Rasch perspective was acceptable. However, collapsing categories 2 (sometime) and 3 (rarely) may be required in a clinical sample. When tested in samples 2 and 3, the RULS-6 fits the Rasch measurement model. Convergent and discriminant validity were demonstrated with interpersonal problems and attachment scales. As expected, a positive correlation was found between RULS-6 and anxiety, depression subscale, interpersonal difficulties, and somatization subscales denoting concurrent validity. Cronbach's alpha of the RULS-6 was good (.83).Conclusion. Using Rasch analysis, the proposed RULS-6 constituted a 70% reduction of the number of original items, yet preserved the psychometric properties in independent samples of students and psychiatric outpatients.

No abstract

Background Caregiver burden affects the caregiver’s health and is related to the quality of care received by patients. This study aimed to determine the extent to which caregivers feel burdened when caring for patients with Alzheimer’s Disease (AD) and to investigate the predictors for caregiving burden. Methods A cross-sectional study was conducted. One hundred two caregivers of patients with AD at Maharaj Nakorn Chiang Mai Hospital, a tertiary care hospital, were recruited. Assessment tools included the perceived stress scale (stress), PHQ-9 (depressive symptoms), Zarit Burden Interview-12 (burden), Clinical Dementia Rating (disease severity), Neuropsychiatric Inventory Questionnaires (neuropsychiatric symptoms), and Barthel Activities Daily Living Index (dependency). The mediation analysis model was used to determine any associations. Results A higher level of severity of neuropsychiatric symptoms (r = 0.37, p < 0.01), higher level of perceived stress (r = 0.57, p < 0.01), and higher level of depressive symptoms (r = 0.54, p < 0.01) were related to a higher level of caregiver burden. The direct effect of neuropsychiatric symptoms on caregiver burden was fully mediated by perceived stress and depressive symptoms (r = 0.13, p = 0.177), rendering an increase of 46% of variance in caregiver burden by this parallel mediation model. The significant indirect effect of neuropsychiatric symptoms by these two mediators was (r = 0.21, p = 0.001). Conclusion Caregiver burden is associated with patients’ neuropsychiatric symptoms indirectly through the caregiver’s depressive symptoms and perception of stress. Early detection and provision of appropriate interventions and skills to manage stress and depression could be useful in reducing and preventing caregiver burden.

ObjectiveThe aim was to assess the reliability and validity of a Thai version internet addiction test.ResultsCronbach’s alpha for the Thai version of the internet addiction test was 0.89. A three-factor model showed the best fit with the data for the whole sample, whereas the hypothesized six-factor model, as well as a unidimensional model of the internet addiction test, failed to demonstrate acceptable fit with the data. Three factors, namely functional impairment, withdrawal symptoms and loss of control, exhibited Cronbach’s alphas of 0.81, 0.81, and 0.70, respectively. Item 4, ‘to form new relationships with online users’, yielded the lowest loading coefficient of all items. Positive correlations between the internet addiction test and UCLA loneliness scores were found. The Thai version of the internet addiction test was considered reliable and valid, and has sufficient unidimensionality to calculate for total score in screening for excessive internet use.Electronic supplementary materialThe online version of this article (10.1186/s13104-018-3187-y) contains supplementary material, which is available to authorized users.

PurposeResidual symptoms of depressive disorder are major predictors of relapse of depression and lower quality of life. This study aims to investigate the prevalence of residual symptoms, relapse rates, and quality of life among patients with depressive disorder.Patients and methodsData were collected during the Thai Study of Affective Disorder (THAISAD) project. The Hamilton Rating Scale for Depression (HAMD) was used to measure the severity and residual symptoms of depression, and EQ-5D instrument was used to measure the quality of life. Demographic and clinical data at the baseline were described by mean ± standard deviation (SD). Prevalence of residual symptoms of depression was determined and presented as percentage. Regression analysis was utilized to predict relapse and patients’ quality of life at 6 months postbaseline.ResultsA total of 224 depressive disorder patients were recruited. Most of the patients (93.3%) had at least one residual symptom, and the most common was anxiety symptoms (76.3%; 95% confidence interval [CI], 0.71–0.82). After 3 months postbaseline, 114 patients (50.9%) were in remission and within 6 months, 44 of them (38.6%) relapsed. Regression analysis showed that residual insomnia symptoms were significantly associated with these relapse cases (odds ratio [OR] =5.290, 95% CI, 1.42–19.76). Regarding quality of life, residual core mood and insomnia significantly predicted the EQ-5D scores at 6 months postbaseline (B =−2.670, 95% CI, −0.181 to −0.027 and B =−3.109, 95% CI, −0.172 to −0.038, respectively).ConclusionResidual symptoms are common in patients receiving treatment for depressive disorder and were found to be associated with relapses and quality of life. Clinicians need to be aware of these residual symptoms when carrying out follow-up treatment in patients with depressive disorder, so that prompt action can be taken to mitigate the risk of relapse.