Development and validation of a screening instrument for bipolar spectrum disorder: The Mood Disorder Questionnaire Thai version

Awareness of COVID-19 influences on the wellness of Thai health professional students: An ambulatory assessment during the early "new normal" informing policy

The COVID-19 global pandemic has had a socioeconomic effect, including many people suffering from stress and mental disorders. Health professional students are at risk of health issues as well when compared to their age-matched counterpart in the population. The present study aimed to find out the impact of COVID-19 awareness on the wellness of Thai health professional students. The awareness of COVID-19 and wellness among Thai health professional students, such as medical, physical therapy, nursing, pharmacy, and medical technology students were surveyed during the early “new normal” informing policy. The participants included 1,001 students, aged 17 to 25 years old, who responded to a Google form questionnaire set by request. The results showed that the prominent health risks among the Thai health professional students included sedentary behavior, obesity, and mental symptoms. A positive rating in attitude towards the COVID-19 epidemic was mostly observed. There was a negative influence on anxiety symptoms (standardized coefficient beta = -0.079, p-value = 0.012), but a positive impact on social well-being (standardized coefficient beta = 0.158, p-value < 0.001) and quality of life (standardized coefficient beta = 0.136, p-value < 0.001) among the students even when the situation was improving. To relieve the domino effect of the COVID-19 pandemic on students’ wellness, an updated policy for enhancing awareness and providing updated information is continuously required. Improvements on self and situational awareness may help prevent health risk behaviors and promote health among Thai health professional students.

The Influence of Current Mood States on Screening Accuracy of the Mood Disorder Questionnaire

Objective

In this study we investigated whether current mood states of patients with bipolar disorder have an influence on the screening accuracy of the Mood Disorder Questionnaire (MDQ).

Methods

A total of 452 patients with mood disorder (including 192 with major depressive disorder and 260 with bipolar disorder completed the Korean version of the MDQ. Patients with bipolar disorder were subdivided into three groups (bipolar depressed only, bipolar euthymic only, bipolar manic/hypomanic only) according to current mood states. The screening accuracy of the MDQ including sensitivity, specificity and area under the curve (AUC) of receiver operating characteristic (ROC) curves were evaluated according to current mood states.

Results

The optimal cutoff of MDQ was 5 in this study sample. Sensitivity and specificity were not significantly different according to current mood states. Significant differences in AUCs of four independent ROC curves were not found (ROC 1st curve included all bipolar patients; ROC 2nd curve included only bipolar depressed patients; ROC 3rd curve included only bipolar manic/hypomanic patients; ROC 4th curve included only bipolar euthymic patients).

Conclusion

The study results showed that current mood states (either euthymic state, depressed or manic/hypomanic) did not significantly influence the screening accuracy of the MDQ suggesting that the MDQ could be a useful screening instrument for detecting bipolar disorder in clinical practice regardless of the current mood symptoms of subjects.

Screening bipolar disorders in a general hospital: Psychometric findings for the Persian version of mood disorder questionnaire and bipolar spectrum diagnostic scale

Background: Mood Disorder Questionnaire (MDQ) and Bipolar Spectrum Diagnostic Scale (BSDS) are used to screen patients with bipolar disorders and have been examined in some psychiatric settings. The present study aimed to assess the validity and reliability of these 2 tools on inpatients in a general hospital.

Methods: In a cross-sectional study in 2011, a total of 207 inpatients admitted to different wards of Rasoul Akram hospital, Tehran, were selected by systematic random sampling. Demographic questionnaire, MDQ, and BSDS were completed. Also, Structured Clinical Interview for DSM-IV axis I disorders (SCID-I) was performed for all participants within 72 hours. The SCID-I was used as the gold standard of psychiatric diagnoses to identify the predictive validity of the 2 screening tests. Sensitivity and specificity indices were identified using Roc curve. The 2 screening tools were recompleted by 20% of the patients (n=43) after 3-7 days to measure test-retest reliability using paired t test and correlation between measures in 2 separate occasions.

Results: In this study, 101 female and 106 male (m=36.9±15.5 yrs.) patients were entered the study, of them 56 (32 males) had bipolar disorder according to SCID-I. The most common bipolar disorder was bipolar disorder type II (9.7%). Pearson’s test showed a high test-retest reliability for both MDQ (r=0.72, p<0.001) and BSDS (r=0.77, p<0.001). For MDQ, the scores 5 (sensitivity=0.60; specificity=0.73) and 6 (sensitivity=0.56; specificity=0.77) were the best cutoff points. Positive and negative predictive values for the mentioned cutoff points were 0.45 and 0.83 (for the score 5) and 0.48 and 0.82 (for the score 6), respectively. The best cutoff point for BSDS was 11 with the sensitivity, specificity, and positive and negative predictive values of 0.74, 0.69, 0.47, and 0.87.

Conclusion: The Persian versions of MDQ and BSDS have acceptable validity and reliability to screen Persian patients with bipolar spectrum disorders in a general hospital.

A Review on the General Stability of Mood Disorder Diagnoses Along the Lifetime

PURPOSE OF REVIEW

The purpose of this review is to review the most recent literature regarding diagnostic stability of mood disorders, focusing on epidemiological, clinical-psychopathological, and neurobiological data for unipolar and bipolar affective disorders.

RECENT FINDINGS

Unipolar depression follows a chronic course in at least half of all cases and presents a considerable diagnostic stability across all age ranges. Studies using latent class analysis are allowing improved profiling of depressive subtypes and assessment of their prevalence. Advances have been made in our understanding of the neurobiological underpinnings of depression, with data highlighting the roles of amyloid deposits, the ApoE4 allele, and atrophy of the anterior hippocampus or frontal cortex. The diagnostic instability of bipolar disorder is manifest in the early years, seen in both the extent of diagnostic delay and the high rate of diagnostic conversion from unipolar depression. Regarding disruptive mood dysregulation disorder, we have little data to date, but those which exist indicate a high rate of comorbidity and minimal diagnostic stability for this disorder. Diagnostic stability varies substantially among mood disorders, which would be related to the validity of current diagnostic categories and our diagnostic accuracy.

Person misfit on the Inventory of Depressive Symptomatology: Low quality self-report or true atypical symptom profile?

Person misfit on a self-report measure refers to a response pattern that is unlikely given a theoretical measurement model. Person misfit may reflect low quality self-report data, for example due to random responding or misunderstanding of items. However, recent research in the context of psychopathology suggests that person misfit may reflect atypical symptom profiles that have implications for diagnosis or treatment. We followed-up on Wanders et al. (Journal of Affective Disorders, 180, 36-43, 2015) who investigated person misfit on the Inventory of Depressive Symptomatology (IDS) in the Netherlands Study of Depression and Anxiety (n = 2,981). Our goal was to investigate the extent to which misfit on the IDS reflects low-quality self-report patterns and the extent to which it reflects true atypical symptom profiles. Regression analysis showed that person misfit related more strongly to self-report quality indicators than to variables quantifying theoretically-derived atypical symptom profiles. A data-driven atypical symptom profile explained most variance in person misfit, suggesting that person misfit on the IDS mainly reflects a sample- and questionnaire-specific atypical symptom profile. We concluded that person-fit statistics are useful for detecting IDS scores that may not be valid. Further research is necessary to support the interpretation of person misfit as reflecting a meaningful atypical symptom combination.