Study protocol: perinatal mood treatment study.

Perinatal depression (PND) affects up to 20% of women and is associated with significant impairment and disability in affected women. In addition, perinatal depression is associated with broader public health and multigenerational consequences. Innovative approaches are needed to reduce the burden of perinatal depression through identification, tracking, and treatment of depressive symptoms during the perinatal period. This study is a randomized clinical trial comparing the relative efficacy of a multi-tiered system of care, Screening and Treatment of Anxiety and Depression (STAND) to perinatal care delivered by a reproductive psychiatrist in reducing symptoms of depression and anxiety. A sample of 167 individuals was randomized between week 28 of pregnancy and 6 months postpartum. A secondary aim compares the original online therapy intervention used in the first half of the study to a newer online therapy program used in the second half of the study for individuals assigned to the STAND treatment. The study measures, intervention groups, and analysis methods are described, as well as expected implications. The findings from this study may improve the methods for tracking symptom changes over time, monitoring treatment response, and providing personalized care for individuals with PND. As such, this study may improve the lives of patients with PND and their families and lower the related health care costs to society.Trial registration NCT: 9/24/2021NCT direct link: https://www.clinicaltrials.gov/study/NCT05056454?term=NCT05056454&rank=1&a=1 .

Personalized mood prediction from patterns of behavior collected with smartphones.

Over the last ten years, there has been considerable progress in using digital behavioral phenotypes, captured passively and continuously from smartphones and wearable devices, to infer depressive mood. However, most digital phenotype studies suffer from poor replicability, often fail to detect clinically relevant events, and use measures of depression that are not validated or suitable for collecting large and longitudinal data. Here, we report high-quality longitudinal validated assessments of depressive mood from computerized adaptive testing paired with continuous digital assessments of behavior from smartphone sensors for up to 40 weeks on 183 individuals experiencing mild to severe symptoms of depression. We apply a combination of cubic spline interpolation and idiographic models to generate individualized predictions of future mood from the digital behavioral phenotypes, achieving high prediction accuracy of depression severity up to three weeks in advance (R2 ≥ 80%) and a 65.7% reduction in the prediction error over a baseline model which predicts future mood based on past depression severity alone. Finally, our study verified the feasibility of obtaining high-quality longitudinal assessments of mood from a clinical population and predicting symptom severity weeks in advance using passively collected digital behavioral data. Our results indicate the possibility of expanding the repertoire of patient-specific behavioral measures to enable future psychiatric research.

Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders.

BACKGROUND: Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas. METHODS: We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters. RESULTS: We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients. CONCLUSIONS: Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots.

The frequencies of mental disorders vary by geographic region. Investigating such variations may lead to more equitable access to mental healthcare and to scientific discoveries that reveal specific localized factors that contribute to the causes of mental illness. This study examined the frequency of three disorders with a major impact on public health ­ schizophrenia, bipolar disorder, and major depressive disorder ­ by analyzing electronic health records from a hospital providing comprehensive mental health care for a large region in Colombia. We show that individuals receiving outpatient care mainly live relatively near the facility. Those receiving inpatient care live throughout the region, but cluster in a few scattered locations. Future research could lead to strategies for more equitable provision of mental healthcare in Colombia and identify environmental or genetic factors that affect the likelihood that someone will develop one of these disorders.

En busqueda de los genes bipolares / Looking for the bipolar genes

Objetivos: Caracterizar una muestra de familias y tríos de una población colombiana aislada para mapear loci involucrados en la vulnerabilidad al Transtorno Bipolar tipo I (TAB-I). Se evaluaron endofenotipos clínicos, neuropsicológicos y moleculares, para acortar el camino entre la identificación de genes y sus expressiones fenotípicas, y luego se realizaron estudios de ligamiento. Métodos: Se recolectaron tríos y genealogías utilizando las entrevistas FIGS-DIGS en miembros de familias y sus posibles afectados. El poder para detectar ligamiento (PDL) se estimó por simulación. Como endofenotipos clínicos comparamos casos de TAB-I con agregación familiar y controles sin agregación. Realizamos una evaluación neuropsicológica comparativa en casos eutímicos y controles sanos. Evaluamos el polimorfismo de longitud del gen del promotor del receptor de serotonina (5HTTLP) y la asociación con el TAB-I. Luego estudiamos el desequilibrio promedio en tríos y familias tamizando los cromosomas 12, 18 y 21.Resultados:Se identificaron 28 familias co TAB-I, asumiendo homogencidad genetica y la evidencia de mestizaje recientemente hallada por nosotros, las simulaciones mostraron PDL significativo de 100 por cento para un LOD-score menor 3. En la población con TAB-I familiar se encontró peor funcionamiento intercrítico, mayor gravedad en episodios depresivos, disfunción neuropsicológica en eutímia y posible evidencia de ligamiento al cromosoma 21 q 22.3. Conclusión : Tenemos un grupo significativo de familias y tríos pertenecientes a una población aislada con un poder para detectar ligamiento al Trastorno Anímico Bipolar. Las características de esta población y los hallazgos actuales en ella sugieren gran probabilidad de encontrar rasgos de expresión clínica y neuropsicológica y genes de susceptibilidad al TAB-I. En el barrido genómico que llevamos a cabo actualmente pretendemos profundizar estos hallazgos.