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Objectives: Patient-level factors that influence compliance with a recommendation for CBT in nursing home residents diagnosed with depression were identified.
Methods: Within a cluster-randomized trial on stepped care for depression in nursing homes (DAVOS-study, Trial registration: DRKS00015686), participants received an intake interview administered by a licensed psychotherapist. If psychotherapy was required, patients were offered a referral for CBT. Sociodemographic characteristics, severity of depression, loneliness, physical health, antidepressant medication, prior experience with psychotherapy, and attitudes towards own aging were assessed. A binary regression determined predictors of compliance with referral.
Results: Of 123 residents receiving an intake interview, 80 were recommended a CBT. Forty-seven patients (58.8 %) followed the recommendation. The binary logistic regression model on compliance with recommended CBT was significant, χ2(9) = 21.64, p = .010. Significant predictors were age (Odds Ratio (OR) = 0.9; 95 % Confidence Interval (CI) = 0.82, 0.99; p = .024) and depression (OR = 1.33; 95 % CI = 1.08, 1.65; p = .008).
Conclusion: Within the implemented setting compliance rate was comparable to other age groups. Future interventions should include detailed psychoeducation on the benefits of psychotherapy on mild depressive symptoms in older age and evidence-based interventions to address the stigma of depression. Interventions such as reminiscence-based methods or problem-solving could be useful to increase compliance with referral, especially in very old patients (80+). Language barriers and a culturally sensitive approach should be considered when screening residents.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).