In‐person versus virtual therapy in outpatient eating‐disorder treatment: A <scp>COVID</scp>‐19 inspired study
Bibliographic record
Abstract
OBJECTIVE: Findings show virtual therapy (conducted using internet-based videoconferencing techniques) to be a viable alternative to in-person therapy for a variety of mental-health problems. COVID-19 social-distancing imperatives required us to substitute virtual interventions for in-person sessions routinely offered in our outpatient eating disorder (ED) program-and afforded us an opportunity to compare the two treatment formats for clinical efficacy. METHODS: Using self-report assessments, we compared outcomes in a historical sample of 49 adults with heterogeneous EDs (treated in-person over 10-14 weeks in individual and group therapies) to those of 76 patients receiving comparable virtual treatments, at distance, during the COVID-19 outbreak. Linear mixed models were used to study symptom changes over time and to test for differential effects of treatment modality. RESULTS: Participants in both groups showed similar improvements on eating symptoms, levels of weight gain (in individuals in whom gain was indicated), and satisfaction with services. DISCUSSION: Our results suggest that short-term clinical outcomes with virtual and in-person ED therapies are comparable, and point to potentials of virtual therapy for situations in which geographical distance or other barriers impede physical access to trained therapists or specialized treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".