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OBJECTIVES: Therapeutic response in depression is a major challenge since more than one third of patients are not in remission after two attempts of antidepressant treatment and will present a treatment-resistant depression. In order to better adapt therapeutic strategies for treatment-resistant patients, predictive indicators and markers of therapeutic response still need to be identified. In parallel, patients with depression exhibit disturbances in cognitive functioning. This study aims to describe and compare cognitive performances collected at inclusion of patients presenting treatment-resistant depression who will be responders at 6 months to those of non-responders, and to evaluate the predictive value of cognitive indicators on clinical therapeutic response at 6 months after a therapeutic modification. METHODS: Observational study. Patients were evaluated at the clinical (HDRS and BDI-II) and cognitive levels using standardized tools assessing memory, executive functions, attention, and social cognition, prior to a change in antidepressant treatment. Six months after inclusion, they were reassessed and classified into two groups based on the presence or absence of therapeutic response, defined by a 50% improvement on HDRS and BDI-II. The cognitive scores collected at inclusion were then compared. Additionally, univariate logistic regression models were used. RESULTS: Thirty patients were included in this study. Only 13 could be evaluated at 6 months. Among these patients, four had responded to the new treatment while nine were non-responders. Both groups of patients presented deviant cognitive performances compared to norms on tests evaluating executive functions and attention. Statistical analyses did not reveal any difference between the cognitive performances of responders and non-responders at 6 months. Regression analyses showed no association between cognitive scores and therapeutic response at 6 months. CONCLUSION: Executive functioning plays a significant role in treatment-resistant depression. In order to improve the understanding and identification of subtypes of depression, cognitive indicators should be systematically integrated into future research.
RESUMEN
BACKGROUND: During the COVID-19 pandemic, health professionals have been directly confronted with the suffering of patients and their families. By making them main actors in the management of this health crisis, they have been exposed to various psychosocial risks (stress, trauma, fatigue, etc). Paradoxically, stress-related symptoms are often underreported in this vulnerable population but are potentially detectable through passive monitoring of changes in speech behavior. OBJECTIVE: This study aims to investigate the use of rapid and remote measures of stress levels in health professionals working during the COVID-19 outbreak. This was done through the analysis of participants' speech behavior during a short phone call conversation and, in particular, via positive, negative, and neutral storytelling tasks. METHODS: Speech samples from 89 health care professionals were collected over the phone during positive, negative, and neutral storytelling tasks; various voice features were extracted and compared with classical stress measures via standard questionnaires. Additionally, a regression analysis was performed. RESULTS: Certain speech characteristics correlated with stress levels in both genders; mainly, spectral (ie, formant) features, such as the mel-frequency cepstral coefficient, and prosodic characteristics, such as the fundamental frequency, appeared to be sensitive to stress. Overall, for both male and female participants, using vocal features from the positive tasks for regression yielded the most accurate prediction results of stress scores (mean absolute error 5.31). CONCLUSIONS: Automatic speech analysis could help with early detection of subtle signs of stress in vulnerable populations over the phone. By combining the use of this technology with timely intervention strategies, it could contribute to the prevention of burnout and the development of comorbidities, such as depression or anxiety.