Barriers and Facilitators to Resuming In-Person Psychotherapy with Perinatal Patients amid the COVID-19 Pandemic: A Multistakeholder Perspective
Bibliographic record
Abstract
During the COVID-19 pandemic, outpatient psychotherapy transitioned to telemedicine. This study aimed to examine barriers and facilitators to resuming in-person psychotherapy with perinatal patients as the pandemic abates. We conducted focus group and individual interviews with a sample of perinatal participants (n = 23), psychotherapy providers (n = 28), and stakeholders (n = 18) from Canada and the U.S. involved in the SUMMIT trial, which is aimed at improving access to mental healthcare for perinatal patients with depression and anxiety. Content analysis was used to examine perceived barriers and facilitators. Reported barriers included concerns about virus exposure in a hospital setting (77.8% stakeholders, 73.9% perinatal participants, 71.4% providers) or on public transportation (50.0% stakeholders, 26.1% perinatal participants, 25.0% providers), wearing a mask during sessions (50.0% stakeholders, 25.0% providers, 13.0% participants), lack of childcare (66.7% stakeholders, 46.4% providers, 43.5% perinatal participants), general transportation barriers (50.0% stakeholders, 47.8% perinatal participants, 25.0% providers), and the burden of planning and making time for in-person sessions (35.7% providers, 34.8% perinatal participants, 27.8% stakeholders). Reported facilitators included implementing and communicating safety protocols (72.2% stakeholders, 47.8% perinatal participants, 39.3% providers), conducting sessions at alternative or larger locations (44.4% stakeholders, 32.1% providers, 17.4% perinatal participants), providing incentives (34.8% perinatal participants, 21.4% providers, 11.1% stakeholders), and childcare and flexible scheduling options (31.1% perinatal participants, 16.7% stakeholders). This study identified a number of potential barriers and illustrated that COVID-19 has fostered and amplified barriers. Future interventions to facilitate resuming in-person sessions should focus on patient-centered strategies based on empathy regarding ongoing risk-aversion among perinatal patients despite existing safety protocols, and holistic thinking to make access to in-person psychotherapy easier and more accessible for perinatal patients.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".