Manee Pinyopornpanish

Diagnosing delirium in elderly Thai patients: utilization of the CAM algorithm.

BackgroundDelirium is a common illness among elderly hospitalized patients. However, under-recognition of the condition by non-psychiatrically trained personnel is prevalent. This study investigated the performance of family physicians when detecting delirum in elderly hospitalized Thai patients using the Thai version of the Confusion Assessment Method (CAM) algorithm.MethodsA Thai version of the CAM algorithm was developed, and three experienced Thai family physicians were trained in its use. The diagnosis of delirium was also carried out by four fully qualified psychiatrists using DSM-IV TR criteria, which can be considered the gold standard. Sixty-six elderly patients were assessed with MMSE Thai 2002, in order to evaluate whether they had dementia upon admission. Within three days of admission, each patient was interviewed separately by a psychiatrist using DSM-IV TR, and a family physician using the Thai version of the CAM algorithm, with both sets of interviewers diagnosing for delirium.ResultsThe CAM algorithm tool, as used by family physicians, demonstrated a sensitivity of 91.9% and a specificity of 100.0%, with a PPV of 100.0% and an NPV of 90.6%. Interrater agreement between the family physicians and the psychiatrists was good (Cohens Kappa = 0.91, p < 0.0001). The mean of the time the family physicians spent using CAM algorithm was significantly briefer than that of the psychiatrists using DSM-IV TR.ConclusionsFamily physicians performed well when diagnosing delirium in elderly hospitalized Thai patients using the Thai version of the CAM algorithm, showing that this measurement tool is suitable for use by non-psychiatrically trained personnel, being short, quick, and easy to administer. However, proper training on use of the algorithm is required.

level of agreement between self-rated and clinician-rated instruments when measuring major depressive disorder in the Thai elderly: a 1-year assessment as part of the ThAIsAD study

Purpose Whether self-reporting and clinician-rated depression scales correlate well with one another when applied to older adults has not been well studied, particularly among Asian samples. This study aimed to compare the level of agreement among measurements used in assessing major depressive disorder (MDD) among the Thai elderly and the factors associated with the differences found. Patients and methods This was a prospective, follow-up study of elderly patients diagnosed with MDD and receiving treatment in Thailand. The Mini International Neuropsychiatric Inventory (MINI), 17-item Hamilton Depression Rating Scale (HAMD-17), 30-item Geriatric Depression Scale (GDS-30), 32-item Inventory of Interpersonal Problems scale, Revised Experience of Close Relationships scale, ten-item Perceived Stress Scale (PSS-10), and Multidimensional Scale of Perceived Social Support were used. Follow-up assessments were conducted after 3, 6, 9, and 12 months. Results Among the 74 patients, the mean age was 68±6.02 years, and 86% had MDD. Regarding the level of agreement found between GDS-30 and MINI, Kappa ranged between 0.17 and 0.55, while for Gwet’s AC1 the range was 0.49 to 0.91. The level of agreement was found to be lowest at baseline, and increased during follow-up visits. The correlation between HAMD-17 and GDS-30 scores was 0.17 (P=0.16) at baseline, then 0.36 to 0.41 in later visits (P<0.01). The PSS-10 score was found to be positively correlated with GDS-30 at baseline, and predicted the level of disagreement found between the clinicians and patients when reporting on MDD. Conclusion The level of agreement between the GDS, MINI, and HAMD was found to be different at baseline when compared to later assessments. Patients who produced a low GDS score were given a high rating by the clinicians. An additional self-reporting tool such as the PSS-10 could, therefore, be used in such under-reporting circumstances.

Baseline characteristics of depressive disorders in Thai outpatients: findings from the Thai Study of Affective Disorders

Background The Thai Study of Affective Disorders was a tertiary hospital-based cohort study developed to identify treatment outcomes among depressed patients and the variables involved. In this study, we examined the baseline characteristics of these depressed patients. Methods Patients were investigated at eleven psychiatric outpatient clinics at tertiary hospitals for the presence of unipolar depressive disorders, as diagnosed by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. The severity of any depression found was measured using the Clinical Global Impression and 17-item Hamilton Depression Rating Scale (HAMD) clinician-rated tools, with the Thai Depression Inventory (a self-rated instrument) administered alongside them. Sociodemographic and psychosocial variables were collected, and quality of life was also captured using the health-related quality of life (SF-36v2), EuroQoL (EQ-5D), and visual analog scale (EQ VAS) tools. Results A total of 371 outpatients suffering new or recurrent episodes were recruited. The mean age of the group was 45.7±15.9 (range 18–83) years, and 75% of the group was female. In terms of diagnosis, 88% had major depressive disorder, 12% had dysthymic disorder, and 50% had a combination of both major depressive disorder and dysthymic disorder. The mean (standard deviation) scores for the HAMD, Clinical Global Impression, and Thai Depression Inventory were 24.2±6.4, 4.47±1.1, and 51.51±0.2, respectively. Sixty-two percent had suicidal tendencies, while 11% had a family history of depression. Of the major depressive disorder cases, 61% had experienced a first episode. The SF-36v2 component scores ranged from 25 to 56, while the mean (standard deviation) of the EQ-5D was 0.50±0.22 and that of the EQ VAS was 53.79±21.3. Conclusion This study provides an overview of the sociodemographic and psychosocial characteristics of patients with new or recurrent episodes of unipolar depressive disorders.

Comorbid personality disorders among patients with depression.

Purpose To investigate the personality disorders (PDs) diagnosed in patients with depressive disorders. Material and methods This study included a cross-sectional analysis, and was an extension of the Thai Study of Affective Disorder (THAISAD) project. Eighty-five outpatients with depressive disorders were interviewed using the Mini International Neuropsychiatric Inventory to assess for depression, in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision and using the Thai version of the Structured Clinical Interview for PDs to assess for PD. Results Seventy-seven percent of the patients had at least one PD, 40% had one PD and 60% had two or more PDs (mixed cluster). The most common PDs found were borderline PD (20%) and obsessive–compulsive PD (10.6%), while the occurrence of avoidant PD was low when compared to the findings of previous, related studies. Among the mixed cluster, cluster A combined with cluster C was the common mix. Both dysthymic disorder and double depression were found to have a higher proportion of PDs than major depressive disorder (85.7% versus 76.1%). Dependent PD was found to be less common in this study than in previous studies, including those carried out in Asia. Conclusion The prevalence of PDs among those with depressive disorder varied, and only borderline PD seems to be consistently high within and across cultures. Mixed cluster plays a prominent role in depression, so more attention should be paid to patients in this category.

The influence of comorbid personality disorders on recovery from depression

Purpose The impact of personality disorders on the treatment of and recovery from depression is still a controversial topic. The aim of this paper is to provide more information on what has led to this disagreement. Materials and methods Clinician-rated Hamilton Depression Rating Scale (HAMD) scores were assessed among 82 depressed outpatients who were receiving a routine treatment combination of antidepressant medication and psychosocial intervention. The participants were followed up over five visits at 3-month intervals: at the baseline, at 3, 6, 9 and 12 months. Personality disorders were assessed after the last visit in accordance with Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision. These repeated measures were used to explore the impact of personality disorders on HAMD scores by using a linear mixed model. Results Among the four personality clusters that were used (A, B, C, and mixed), only those in cluster B and in the mixed cluster were found to take significantly longer than those without personality disorders, for reduction in HAMD scores over the course of treatment. Conclusion In this study, the impact of personality disorders on treatment outcomes varied with the way that the personality disorder variables were described and used as independent predictors. This is because the outcomes were influenced by the impact weight of each personality disorder, even within the same cluster.

The impact of residual symptoms on relapse and quality of life among Thai depressive patients

Purpose Residual 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 methods Data 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. Results A 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). Conclusion Residual 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.

Depression and pain: testing of serial multiple mediators

Purpose Despite the fact that pain is related to depression, few studies have been conducted to investigate the variables that mediate between the two conditions. In this study, the authors explored the following mediators: cognitive function, self-sacrificing interpersonal problems, and perception of stress, and the effects they had on pain symptoms among patients with depressive disorders. Participants and methods An analysis was performed on the data of 346 participants with unipolar depressive disorders. The 17-item Hamilton Depression Rating Scale, Mini-Mental State Examination, the pain subscale of the health-related quality of life (SF-36), the self-sacrificing subscale of the Inventory of Interpersonal Problems, and the Perceived Stress Scale were used. Parallel multiple mediator and serial multiple mediator models were used. An alternative model regarding the effect of self-sacrificing on pain was also proposed. Results Perceived stress, self-sacrificing interpersonal style, and cognitive function were found to significantly mediate the relationship between depression and pain, while controlling for demographic variables. The total effect of depression on pain was significant. This model, with an additional three mediators, accounted for 15% of the explained variance in pain compared to 9% without mediators. For the alternative model, after controlling for the mediators, a nonsignificant total direct effect level of self-sacrificing was found, suggesting that the effect of self-sacrificing on pain was based only on an indirect effect and that perceived stress was found to be the strongest mediator. Conclusion Serial mediation may help us to see how depression and pain are linked and what the fundamental mediators are in the chain. No significant, indirect effect of self-sacrificing on pain was observed, if perceived stress was not part of the depression and/or cognitive function mediational chain. The results shown here have implications for future research, both in terms of testing the model and in clinical application.

Psychometric properties of a Thai version internet addiction test

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.

Prevalence, associated factors and impact of loneliness and interpersonal problems on internet addiction: A study in Chiang Mai medical students

INTRODUCTION Internet addiction is common among medical students, and the prevalence is higher than the general population. Identifying and creating solutions for this problem is important. The aim of this study was to examine the prevalence and associated factors, particularly loneliness and interpersonal problems among Chiang Mai medical students. MATERIALS AND METHODS Of 324 first to sixth year medical students, 56.8% comprised females with a mean age of 20.88 (SD 1.8). All completed questionnaires related to the objectives and activities of internet use, the Young Internet Addiction Test, the UCLA loneliness scale, and the Interpersonal Problems Inventory were employed to identify internet addiction. RESULTS In all, 36.7% of the subjects exhibited internet addiction, mostly at mild level. Amount of time used daily, loneliness and interpersonal problems were strong predictors (beta = 0.441, p < 0.05, beta = 0.219, p < 0.001 and beta = 0.203 p < 0.001, respectively), whereas age and sex were not. All objectives of using internet contributed to the variance of internet addiction score. For internet activities, only non-academic or studying contributed. The final model accounted for 42.8% of total variance of the internet addiction score. CONCLUSION Even though most addiction was at a mild level, careful strategies should be applied to better understand the situation. Along with a screening for potential internet addiction among medical students, attention should be paid to identifying those who experience loneliness and interpersonal problems, because both are strong predictors that can be improved by a variety of appropriate intervention.