Depressive symptoms in youth before and during the COVID-19 pandemic: longitudinal investigation of patterns dependent on age, sex, and family history of mental illness.

BACKGROUND: Cross-sectional studies report high levels of depressive symptoms during the COVID-19 pandemic, especially in youth and females. However, longitudinal research comparing depressive symptoms before and during the pandemic is lacking. Little is known about how the pandemic affected individuals with familial history of mental illness. The present study examines the impact of the pandemic on youth depressive symptoms, including offspring of parents with major mood and psychotic disorders. METHODS: Between March 2018 and February 2020, we measured depressive symptoms in 412 youth aged 5-25 years. We measured depressive symptoms again in 371 (90%) of these youth between April 2020 and May 2022. Two thirds (249) participants had a biological parent with a major mood or psychotic disorder. We tested the effect of the pandemic by comparing depression symptoms before and after March 2020. We examined age, sex, and family history as potential moderators. RESULTS: We found an overall small increase in youth depressive symptoms (b = 0.07, 95% CI -0.01 to 0.15, p = 0.062). This was driven by an increase in female youth without familial history of mental illness (b = 0.35, 95% CI 0.14 to 0.56, p = 0.001). There was no change in depressive symptoms among offspring of parents with mental illness or males. CONCLUSIONS: Our results provide reassurance about the wellbeing of children of parents with mental illness during a period of restricted access to resources outside the family. Rather than increasing symptoms in established risk groups, the pandemic led to a redistribution of depression burden towards segments of the youth population that were previously considered to be low-risk.

Manifestation of depression in speech overlaps with characteristics used to represent and recognize speaker identity.

The sound of a person's voice is commonly used to identify the speaker. The sound of speech is also starting to be used to detect medical conditions, such as depression. It is not known whether the manifestations of depression in speech overlap with those used to identify the speaker. In this paper, we test the hypothesis that the representations of personal identity in speech, known as speaker embeddings, improve the detection of depression and estimation of depressive symptoms severity. We further examine whether changes in depression severity interfere with the recognition of speaker's identity. We extract speaker embeddings from models pre-trained on a large sample of speakers from the general population without information on depression diagnosis. We test these speaker embeddings for severity estimation in independent datasets consisting of clinical interviews (DAIC-WOZ), spontaneous speech (VocalMind), and longitudinal data (VocalMind). We also use the severity estimates to predict presence of depression. Speaker embeddings, combined with established acoustic features (OpenSMILE), predicted severity with root mean square error (RMSE) values of 6.01 and 6.28 in DAIC-WOZ and VocalMind datasets, respectively, lower than acoustic features alone or speaker embeddings alone. When used to detect depression, speaker embeddings showed higher balanced accuracy (BAc) and surpassed previous state-of-the-art performance in depression detection from speech, with BAc values of 66% and 64% in DAIC-WOZ and VocalMind datasets, respectively. Results from a subset of participants with repeated speech samples show that the speaker identification is affected by changes in depression severity. These results suggest that depression overlaps with personal identity in the acoustic space. While speaker embeddings improve depression detection and severity estimation, deterioration or improvement in mood may interfere with speaker verification.

Applications of Speech Analysis in Psychiatry.

ABSTRACT: The need for objective measurement in psychiatry has stimulated interest in alternative indicators of the presence and severity of illness. Speech may offer a source of information that bridges the subjective and objective in the assessment of mental disorders. We systematically reviewed the literature for articles exploring speech analysis for psychiatric applications. The utility of speech analysis depends on how accurately speech features represent clinical symptoms within and across disorders. We identified four domains of the application of speech analysis in the literature: diagnostic classification, assessment of illness severity, prediction of onset of illness, and prognosis and treatment outcomes. We discuss the findings in each of these domains, with a focus on how types of speech features characterize different aspects of psychopathology. Models that bring together multiple speech features can distinguish speakers with psychiatric disorders from healthy controls with high accuracy. Differentiating between types of mental disorders and symptom dimensions are more complex problems that expose the transdiagnostic nature of speech features. Convergent progress in speech research and computer sciences opens avenues for implementing speech analysis to enhance objectivity of assessment in clinical practice. Application of speech analysis will need to address issues of ethics and equity, including the potential to perpetuate discriminatory bias through models that learn from clinical assessment data. Methods that mitigate bias are available and should play a key role in the implementation of speech analysis.

Cognition in offspring of parents with psychotic and non-psychotic severe mental illness.

BACKGROUND: Cognitive impairment is a feature of severe mental illness (SMI; schizophrenia, bipolar disorder, major depressive disorder). Psychotic forms of SMI may be associated with greater cognitive impairment, but it is unclear if this differential impairment pre-dates illness onset or whether it reflects a consequence of the disorder. To establish if there is a developmental impairment related to familial risk of psychotic SMI, we investigated cognition in offspring of parents with psychotic and non-psychotic SMI. METHOD: Participants included 360 children and youth (mean age 11.10, SD 4.03, range 6-24), including 68 offspring of parents with psychotic SMI, 193 offspring of parents with non-psychotic SMI, and 99 offspring of control parents. The cognitive battery assessed a range of functions using standardized tests and executive function tasks from the Cambridge Automated Neuropsychological Test Battery. RESULTS: Compared to controls, offspring of parents with psychotic SMI performed worse on overall cognition (ß = -0.32; p < 0.001) and 6 of 15 cognitive domains, including verbal intelligence, verbal working memory, processing speed, verbal learning and memory, verbal fluency, and sustained attention. Offspring of parents with non-psychotic SMI performed worse than controls on 3 of the 15 domain specific cognitive tests, including verbal intelligence, visual memory and decision-making. CONCLUSIONS: Widespread mild-to-moderate cognitive impairments are present in young offspring at familial risk for transdiagnostic psychotic SMI. Offspring at familial risk for non-psychotic SMI showed fewer and more specific impairments in the domains of verbal intelligence, visual memory and decision-making.

Visual memory and psychotic symptoms in youth.

BACKGROUND: Psychotic symptoms are common during childhood and adolescence and may indicate transdiagnostic risk of future psychiatric disorders. Lower visual memory ability has been suggested as a potential indicator of future risk of mental illness. The relationship between visual memory and clinician-confirmed definite psychotic symptoms in youth has not yet been explored. METHODS: We examined visual memory and psychotic symptoms among 205 participants aged 7-27 years in a cohort enriched for parental mood and psychotic disorders. We assessed visual memory using the Rey Complex Figure Test (RCFT) and psychotic symptoms using validated semi-structured interview measures. We tested the relationship between visual memory and psychotic symptoms using mixed-effects logistic regression. RESULTS: After accounting for age, sex, and family clustering, we found that psychotic symptoms were significantly associated with lower visual memory (OR = 1.80, 95% CI 1.06-3.06, p = 0.030). This result was unchanged after accounting for general cognitive ability. CONCLUSION: Lower visual memory performance is associated with psychotic symptoms among youth, regardless of general cognitive ability. This finding may inform future targeted early interventions.

Visual memory in offspring of parents with mental illness.

Severe mental illness (SMI) refers to impairing and frequently chronic disorders that are difficult to treat. Lower cognitive performance early in life may be a manifestation of risk for SMI. Visual memory has been highlighted as a potential cognitive predictor of future risk of developing bipolar disorder and schizophrenia. We examined visual memory in 214 participants (mean age = 12.62, SD = 4.49) using the Rey Complex Figure Test (RCFT). Our sample included 37 offspring with no parental history of mental illness, 103 offspring with parental history of non-severe mental illness (NSMI), and 74 offspring with parental history of SMI. We tested the effects of family history of mental illness on visual memory using mixed-effects linear regression. After accounting for age, sex, and family clustering, we found that as severity of parental mental illness increases, offspring visual memory performance decreases significantly (b = -3.58, 95% CI -6.79 to -0.37, p = 0.029). We found that severity of parental mental illness predicts visual memory ability. This finding may help identify youth most at risk of developing mental illness and thus inform future interventions.

Active behaviors and screen time in offspring of parents with major depressive disorder, bipolar disorder and schizophrenia.

Activities may be modifiable factors that moderate the risk and resilience in the development of mental health and illness. Youth who spend more time using screens are more likely to have poor mental health. Conversely, time spent engaged in active behaviors (i.e., physical activity, socializing and reading) is associated with better mental health. The choice of activities may be important in offspring of parents with mental illness, who are at increased risk for developing mental disorders. Among 357 youth of the FORBOW (Families Overcoming Risks and Building Opportunities for Well-being) cohort aged 6-21, we examined whether parental diagnosis of mental illness (i.e., major depressive disorder, schizophrenia and bipolar disorder) and current levels of depression influenced the amount of time their offspring spent using screens and engaging in active behaviors. Parental history of mental illness and higher levels of current depression in mothers were associated with less time spent engaged in active behaviors and more time spent using screens. Creating opportunities and incentives for active behaviors may redress the balance between youth with and without a familial history of mental illness.