Publications

BACKGROUND: In residency programs, the availability of faculty mentors for traditional dyadic mentorship relationships may be limited. Few frameworks exist for mentorship programs with a combined faculty and peer mentorship approach. The authors developed the Mentorship Families Program (MFP), a faculty-resident group mentorship program within a psychiatry residency program to meet the need for mentorship for a large cohort of residents. A cross-sectional survey was used to evaluate the impact of the MFP after its first implementation year.

METHODS: Eleven mentorship families were created with 11 faculty members and 45 residents; each mentorship family consisted of one faculty member and 4-5 residents. A cross-sectional survey characterized the one-year perceived impact (2021-2022) of the MFP on resident and faculty mentoring experiences, with questions about the content, frequency, and quality of the MFP meetings and the strengths and areas of improvement for the MFP. Descriptive statistics were used to summarize quantitative feedback; directed content analysis was performed on open-ended feedback.

RESULTS: Twenty-seven residents (60%) and 8 faculty members (73%) responded to the survey. 70% of mentorship families met at least once. The MFP helped foster resident-faculty connections and provided an environment to gain career advice. However, residents and faculty reported challenges with scheduling meetings and a lack of meeting structure as barriers to effective engagement with the MFP. Most residents recommended that other training programs implement a program like the MFP as it offered multidimensional opportunities for connections between residents and faculty.

CONCLUSIONS: A faculty-resident group mentorship program like the MFP can be implemented in residency training programs when traditional one-to-one faculty mentorship is often limited.

BACKGROUND: Women may be vulnerable to elevated depressive symptoms during the menopause transition (MT). Studies generally have not considered premenopausal depressive symptom history or examined symptoms in relation to the final menstrual period (FMP).

OBJECTIVE: To identify specific time points in relation to the FMP when depressive symptoms increase or decrease.

METHODS: Participants were 1582 multiracial/ethnic women from the longitudinal Study of Women's Health Across the Nation (SWAN). Biological, psychosocial, and depressive symptom data were collected approximately annually. Depressive symptoms were measured by the Center for Epidemiological Studies-Depression (CESD) scale.

RESULTS: Women with high baseline depressive symptoms (CES-D ≥ 16) declined in symptoms (M = -1.04/yr., 95 % CI = -1.58, -0.50) until 4 years before the FMP, followed by a smaller decrease (M = -0.50/yr., 95 % CI = -0.72, -0.28) until 18 months after the FMP. Depressive symptoms increased (M = 0.21/yr., 95 % CI = 0.11, 0.30) in those with low baseline symptoms until 1 year before the FMP, and decreased (M = -0.06/yr., 95 % CI = -0.11, -0.008) going forward. Greater social support, higher levels of follicle stimulating hormone and estradiol, and less sleep disturbance contributed to greater decline in depressive symptoms among those with high baseline depressive symptoms. Anxiety, experiencing stressful life events, lower body mass index, and poor role-physical function contributed to an increase in depressive symptoms among those with low baseline symptoms.

LIMITATIONS: Excluded women had higher baseline CES-D scores. Lacked pre-MT depression for pre/early perimenopausal women at baseline.

CONCLUSION: Accounting for baseline depressive symptom level and focusing on the FMP more precisely characterize depressive symptom change over the MT.

Prenatal generalized anxiety disorder (GAD) is a common and underdiagnosed condition with negative health consequences to both the pregnant individual and child. Here we studied the relationship between diagnosis and treatment status of GAD during pregnancy (no GAD diagnosis, suspected but not diagnosed, diagnosed but not treated, diagnosed and treated) during the COVID-19 pandemic and postpartum mental health outcomes, while considering the potential influence of individual psychological factors such as distress tolerance and resilience and the role of COVID-19-related health worries. In this sample of predominantly highly educated and white birthing individuals, one in five respondents experienced GAD during pregnancy and another one in six suspected GAD but was not diagnosed. Amongst those with a GAD diagnosis, 30% did not receive treatment. We found that those with a GAD diagnosis during pregnancy who did not receive treatment showed the highest levels of postpartum anxiety and depressive symptoms in the postpartum, even after controlling for covariates, and experienced the most COVID-19-related health worries. In comparison, individuals with a GAD diagnosis during pregnancy who received treatment experienced significantly lower anxiety symptom burden and depressive symptom burden, with a symptom burden similar to those without a confirmed or suspected diagnosis after controlling for individual psychological factors. We conclude that clinicians should strongly consider screening for and treating prenatal anxiety to prevent suboptimal postpartum mental health outcomes.

Postpartum mental health conditions are a public health concern, affecting a large number of reproductive-age women and their families. Postpartum depression alone affects at least 14% of new mothers and their families. However, very little has been written about how advances in digital mental health can benefit women in the postpartum period, or how those advances may poorly serve this vulnerable population. This manuscript takes a high-level view of the advances in different areas of digital mental health, including telehealth, apps, and digital phenotyping. In this comment, we explore ways in which digital interventions for postpartum mental health may help with connection to treatment, accessibility, agency, and ease of access. We also note particular concerns for how digital postpartum mental health may encounter issues of low-quality resources, ethical considerations, and equity considerations. We provide suggestions for how to leverage the promise and avoid the pitfalls of digital mental health for postpartum women.

OBJECTIVE: Understanding the impact of lifestyle on mental illness symptoms is important for informing psycho-education and developing interventions which target mental and physical comorbidities. Obsessive-compulsive and related disorders can have a significant impact on health-related quality of life and physical health. However, our understanding of the impact of lifestyle on obsessive-compulsive symptoms and broader compulsive and impulsive problematic repetitive behaviours is limited.

AIMS: We investigated whether lifestyle factors predicted change in obsessive-compulsive symptoms and problematic repetitive behaviours in a general population sample over a 3-month period.

METHODS: Eight hundred thirty-five participants completed an online questionnaire battery assessing lifestyle and mental health. Of these, 538 participants completed the same battery 3 months later. We conducted negative binomial regressions to analyse the association of lifestyle factors at baseline with future (1) obsessive-compulsive symptoms, (2) compulsive problematic repetitive behaviours and (3) impulsive problematic repetitive behaviours, adjusting for baseline obsessive-compulsive symptoms and problematic repetitive behaviours.

RESULTS: Lower vegetable (p = 0.020) and oily fish (p = 0.040) intake and lower moderate intensity physical activity (p = 0.008) predicted higher obsessive-compulsive symptoms at follow-up. Higher intake of high-fat foods (p < 0.001) predicted higher compulsive problematic repetitive behaviours at follow-up. No lifestyle factors significantly predicted impulsive problematic repetitive behaviours at follow-up.

CONCLUSION: Our results speak to the potential importance of lifestyle quality screening, education and lifestyle interventions (e.g. an anti-inflammatory diet) for individuals experiencing compulsivity-related behaviours and/or symptoms. Further research into potential mechanisms of action will allow for more targeted approaches to lifestyle interventions for transdiagnostic compulsive behaviours.

BACKGROUND: Many people with harmful addictive behaviors may not meet formal diagnostic thresholds for a disorder. A dimensional approach, by contrast, including clinical and community samples, is potentially key to early detection, prevention, and intervention. Importantly, while neurocognitive dysfunction underpins addictive behaviors, established assessment tools for neurocognitive assessment are lengthy and unengaging, difficult to administer at scale, and not suited to clinical or community needs. The BrainPark Assessment of Cognition (BrainPAC) Project sought to develop and validate an engaging and user-friendly digital assessment tool purpose-built to comprehensively assess the main consensus-driven constructs underpinning addictive behaviors.

OBJECTIVE: The purpose of this study was to psychometrically validate a gamified battery of consensus-based neurocognitive tasks against standard laboratory paradigms, ascertain test-retest reliability, and determine their sensitivity to addictive behaviors (eg, alcohol use) and other risk factors (eg, trait impulsivity).

METHODS: Gold standard laboratory paradigms were selected to measure key neurocognitive constructs (Balloon Analogue Risk Task [BART], Stop Signal Task [SST], Delay Discounting Task [DDT], Value-Modulated Attentional Capture [VMAC] Task, and Sequential Decision-Making Task [SDT]), as endorsed by an international panel of addiction experts; namely, response selection and inhibition, reward valuation, action selection, reward learning, expectancy and reward prediction error, habit, and compulsivity. Working with game developers, BrainPAC tasks were developed and validated in 3 successive cohorts (total N=600) and a separate test-retest cohort (N=50) via Mechanical Turk using a cross-sectional design.

RESULTS: BrainPAC tasks were significantly correlated with the original laboratory paradigms on most metrics (r=0.18-0.63, P<.05). With the exception of the DDT k function and VMAC total points, all other task metrics across the 5 tasks did not differ between the gamified and nongamified versions (P>.05). Out of 5 tasks, 4 demonstrated adequate to excellent test-retest reliability (intraclass correlation coefficient 0.72-0.91, P<.001; except SDT). Gamified metrics were significantly associated with addictive behaviors on behavioral inventories, though largely independent of trait-based scales known to predict addiction risk.

CONCLUSIONS: A purpose-built battery of digitally gamified tasks is sufficiently valid for the scalable assessment of key neurocognitive processes underpinning addictive behaviors. This validation provides evidence that a novel approach, purported to enhance task engagement, in the assessment of addiction-related neurocognition is feasible and empirically defensible. These findings have significant implications for risk detection and the successful deployment of next-generation assessment tools for substance use or misuse and other mental disorders characterized by neurocognitive anomalies related to motivation and self-regulation. Future development and validation of the BrainPAC tool should consider further enhancing convergence with established measures as well as collecting population-representative data to use clinically as normative comparisons.

It is well-established that addiction is typically associated with a distinct pattern of neurocognitive functioning with a consensus that it is typified by impaired top-down executive control and aberrant risk-reward processing. Despite a consensus that neurocognition plays an important role in characterizing and maintaining addictive disorders, there is a lack of systematic, bottom-up synthesis of quantitative evidence showing that neurocognition predicts addictive behaviors, and which neurocognitive constructs have the best predictive validity. This systematic review aimed to assess whether cognitive control and risk-reward processes as defined by the Research Domain Criteria (RDoC) predict the development and maintenance of addictive behaviors specifically, consumption, severity, and relapse. The findings from this review expose the substantial lack of evidence for neurocognition predicting addiction outcomes. However, there is evidence that suggests reward-related neurocognitive processes may be important for the detection of early risk for addiction, as well as a potentially viable target for designing novel, more effective interventions.

BACKGROUND: Many people with harmful addictive behaviors may not meet formal diagnostic thresholds for a disorder. A dimensional approach, by contrast, including clinical and community samples, is potentially key to early detection, prevention, and intervention. Importantly, while neurocognitive dysfunction underpins addictive behaviors, established assessment tools for neurocognitive assessment are lengthy and unengaging, difficult to administer at scale, and not suited to clinical or community needs. The BrainPark Assessment of Cognition (BrainPAC) Project sought to develop and validate an engaging and user-friendly digital assessment tool purpose-built to comprehensively assess the main consensus-driven constructs underpinning addictive behaviors.

OBJECTIVE: The purpose of this study was to psychometrically validate a gamified battery of consensus-based neurocognitive tasks against standard laboratory paradigms, ascertain test-retest reliability, and determine their sensitivity to addictive behaviors (eg, alcohol use) and other risk factors (eg, trait impulsivity).

METHODS: Gold standard laboratory paradigms were selected to measure key neurocognitive constructs (Balloon Analogue Risk Task [BART], Stop Signal Task [SST], Delay Discounting Task [DDT], Value-Modulated Attentional Capture [VMAC] Task, and Sequential Decision-Making Task [SDT]), as endorsed by an international panel of addiction experts; namely, response selection and inhibition, reward valuation, action selection, reward learning, expectancy and reward prediction error, habit, and compulsivity. Working with game developers, BrainPAC tasks were developed and validated in 3 successive cohorts (total N=600) and a separate test-retest cohort (N=50) via Mechanical Turk using a cross-sectional design.

RESULTS: BrainPAC tasks were significantly correlated with the original laboratory paradigms on most metrics (r=0.18-0.63, P<.05). With the exception of the DDT k function and VMAC total points, all other task metrics across the 5 tasks did not differ between the gamified and nongamified versions (P>.05). Out of 5 tasks, 4 demonstrated adequate to excellent test-retest reliability (intraclass correlation coefficient 0.72-0.91, P<.001; except SDT). Gamified metrics were significantly associated with addictive behaviors on behavioral inventories, though largely independent of trait-based scales known to predict addiction risk.

CONCLUSIONS: A purpose-built battery of digitally gamified tasks is sufficiently valid for the scalable assessment of key neurocognitive processes underpinning addictive behaviors. This validation provides evidence that a novel approach, purported to enhance task engagement, in the assessment of addiction-related neurocognition is feasible and empirically defensible. These findings have significant implications for risk detection and the successful deployment of next-generation assessment tools for substance use or misuse and other mental disorders characterized by neurocognitive anomalies related to motivation and self-regulation. Future development and validation of the BrainPAC tool should consider further enhancing convergence with established measures as well as collecting population-representative data to use clinically as normative comparisons.

The ability of flatworms to regenerate entire brain structures, and indeed much of their body from mere fragments of the whole animal, presents the unique opportunity to observe the development of day-night rhythms in adult animals. In many animals, young are arrhythmic, and their species-specific timing of activity develops as the animal matures. In this study, we created two flatworm cohorts, housed in isolation, that were regenerating either (1) the brain in a decapitated animal, or (2) major body structures in a bisected, tailless animal. In this way, we observed how bisection influenced the level of activity and diel rhythmicity, and how these developed as each flatworm regenerated. Here, we demonstrate that intact flatworms were predominantly active at night, with peaks in activity seen in the hours after lights-off and before lights-on. While decapitated and tailless flatworms could still move, both were less active than the original animal, and both segments retained a nocturnal lifestyle. Furthermore, decapitated flatworms, once regenerated, again showed a U-shaped pattern of nocturnal activity reminiscent of the two night-time peaks seen in the original animal. These results could be used to further investigate how regeneration may affect motor control and motor output, or to further investigate the presence of a clock in the flatworm brain.