Resuming In-person Psychological Treatment in the Era of COVID-19
Bibliographic record
Abstract
Background: Patient-centered research has emerged as a promising model to adequately address the needs and preferences of patient populations with mental disorders. The Scaling Up Maternal Mental healthcare by Increasing access to Treatment (SUMMIT) Trial aims to increase access to psychological treatment and implements a multi-stakeholder perspective to understand the needs/preferences of perinatal populations with symptoms of depression and anxiety. Specifically, this pragmatic, non-inferiority randomized effectiveness trial examines whether Behavioral Activation (BA) delivered via telemedicine is as effective as in-person treatment. However, due to COVID-19, the study suspended in-person BA sessions and completely shifted to telemedicine. To ensure BA remains widely accessible, the SUMMIT team strives to resume in-person treatment in the near future. Objective: To gain perspectives of key stakeholders on the potential barriers and facilitators for SUMMIT participants to resume in-person BA sessions in a COVID-19 context. Methods: A focus group discussion (1 hour) was conducted via Zoom with N=9 stakeholders, including patient advocates, nurses, clinicians, and researchers. Qualitative data was coded using NVivo and content analysis was performed to quantify frequently endorsed themes. Results: The majority of stakeholders considered resuming in-person BA sessions to be a challenge amidst COVID-19, with more barriers than facilitators mentioned overall. Most commonly endorsed barriers that participants may face when attending in-person treatment included arranging childcare (n=8; 89%) and discomfort/fear of coming to the hospital (n=6; 67%). The most widely endorsed facilitators for resuming in-person treatment during COVID-19 were clearly communicating hospital and transportation safety precautions to participants (n=7; 78%) and conducting in-person sessions at an off-site location (n=6; 67%). Conclusion: This study identified critical facilitators of resuming in-person BA sessions that can inform: (1) how to resume in-person BA sessions and (2) the development and implementation of strategies to make BA more patient-centered for perinatal populations during COVID-19. Objective: To gain perspectives of key stakeholders on the potential barriers and facilitators for SUMMIT participants to resume in-person BA sessions in a COVID-19 context. Methods: A focus group discussion (1 hour) was conducted via Zoom with N=9 stakeholders, including patient advocates, nurses, clinicians, and researchers. Qualitative data was coded using NVivo and a content analysis was performed to quantify frequently endorsed themes. Results: The majority of stakeholders considered resuming in-person BA sessions to be a challenge amidst COVID-19, with more barriers than facilitators mentioned overall. Most commonly endorsed barriers that participants may face when attending in-person treatment included arranging childcare (n=8; 89%) and discomfort/fear of coming to the hospital (n=6; 67%). The most widely endorsed facilitators for resuming in-person treatment during COVID-19 were clearly communicating hospital and transportation safety precautions to participants (n=7; 78%) and conducting in-person sessions at an off-site location (n=6; 67%). Conclusion: This study identified critical facilitators of resuming in-person BA sessions that can inform: (1) how to resume in-person BA sessions and (2) the development and implementation of strategies to make BA more patient-centered for perinatal populations during COVID-19.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".