A case study of virtually delivered emotion‐focused family therapy
Bibliographic record
Abstract
Clinical psychologists and therapists are increasingly taking advantage of internet and mobile-based technologies to deliver mental health services for individuals and groups since the COVID-19 pandemic. However, there is a dearth of research evaluating the appropriateness of virtual platforms for family interventions. Further, no research has examined the effectiveness of weekly emotion-focused family therapy (EFFT). This case study presents a virtually delivered 8-week EFFT intervention, which supported caregivers to manage child symptoms of depression, anxiety, and anger, facilitate emotion processing, and strengthen relationships. Two parents from one family during a marital separation participated and completed brief measures of therapeutic alliance, family functioning, parental self-efficacy, and parental and child psychological distress at 12 time points as well as a posttreatment semistructured interview. A strong therapeutic alliance was formed, and general family functioning, parental self-efficacy, parent psychopathology, and child depression, anger, and anxiety symptoms improved over the course of therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".