No abstract

Background Major depressive disorder (MDD) is a global public health concern that is notably underdiagnosed and undertreated due to its complexity and subjective diagnostic methods. A holistic diagnostic procedure, which sufficiently considers all possible contributors to MDD symptoms, would improve MDD diagnosis and treatment. This study aims to explore whether personality and coping styles can predict MDD status and differentiate between depressed patients and healthy individuals. Methods Seventy healthy controls (N = 54 females) were matched to 70 MDD patients for age, sex, ethnicity, and years of education. MDD severity was measured using the Hamilton Depression Rating Scale, while personality traits and coping styles were measured by the Ten-Item Personality (TIPI) and Brief COPE questionnaires, respectively. Logistic regression analyses were conducted to investigate the diagnostic and predictive potential of personality and coping styles. Receiver operating characteristic (ROC) analyses were also conducted to examine their discriminative ability to distinguish between depressed and healthy individuals. Results Introversion, lack of organisation skills, and neuroticism were statistically significant in predicting MDD status. Dysfunctional coping strategies, such as denial and self-blame, were also shown to significantly predict MDD status. ROC analyses found both the TIPI questionnaire (AUC = 0.90), and dysfunctional coping (as measured by Brief COPE) (AUC = 0.90) to be excellent predictors of MDD. Conclusions Our findings demonstrate the diagnostic and predictive potential of personality and coping styles for MDD in the clinical setting. They also demonstrate the remarkable ability of personality and coping styles to differentiate between depressed patients and healthy controls.

Introduction: Suicide is a pressing psychiatric concern worldwide with no established biomarker. While there is some evidence of the clinical utility of functional near-infrared spectroscopy (fNIRS) in assessing and predicting suicidality, no systematic review of such evidence has been conducted to date. Therefore, this review aimed to systematically review and gather evidence from existing studies that used fNIRS signals to assess suicidality and its associated changes in the brain, and those that examined how such signals correlated with suicide symptomatology.Methods: PubMed, EMBASE, and Cochrane Library databases were used in a systematic literature search for English-language articles published between 2000 and December 19, 2020 that focused on the utility of fNIRS for (i) assessing suicidality and its associated changes in the brain, and (ii) correlating with suicide symptomatology. Studies were included if they utilised fNIRS to evaluate variations in fNIRS-measured cerebral hemodynamic responses in patients with different mental disorders (e.g., major depressive disorder, schizophrenia), as well as in healthy controls, of any age group. Quality of evidence was assessed using the Newcastle-Ottawa quality assessment scale.Results: A total of 7 cross-sectional studies were included in this review, all of which had acceptable quality. Across all studies, fNIRS demonstrated reduced cerebral hemodynamic changes in suicidal individuals when compared to non-suicidal individuals. One study also demonstrated the potential of fNIRS signals in correlating with the severity of suicidality.Conclusions: This review provides a comprehensive, updated review of evidence supporting the clinical utility of fNIRS in the assessment and prediction of suicidality. Further studies involving larger sample sizes, standardised methodology, and longitudinal follow-ups are needed.