Benefits of “Decentered and Influential” Practices During Telehealth: Establishing, Slipping, and Re-Establishing Position in a Therapeutic Conversation
Bibliographic record
Abstract
Telehealth therapy has become a common platform to provide therapeutic services during the COVID-19 pandemic and is expected to remain a viable option for services. Most mental health professionals had little prior experience in using this modality and have been experimenting with various ways of ensuring respectful, collaborative and effective ways of offering their services. A Decentered and Influential position offers numerous benefits that support anchoring therapists in a mindset that is conducive to optimized therapeutic conversations especially with people from socio-cultural and generational backgrounds different from their own. The value of this therapeutic position is illustrated by clinical work with a teenager struggling with violence towards family members during the quarantine. A description of clinical work where the therapist slipped to a centered position, and the re-engagement of a Decentered and Influential position, is exemplified by a discussion and preventive suggestions.
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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 | 0.038 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.041 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.004 | 0.024 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 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".