Therapeutic Processes in Clinical Interventions : A View of Qualitative Methodological Approaches
Bibliographic record
Abstract
This article examines several qualitative methods to capture and analyze processes in therapeutic and clinical interventions. The study of therapeutic processes provides an understanding of what leads to changes in clinical interventions. This is a goal of any therapeutic intervention. This interest should allow us to try to identify what the therapists do and think they are doing, how they do it, how they think about their interventions, and what happens during the session that might explain changes. These types of studies require that researchers provide clarifications about their epistemological and methodological choices. To meet that requirement, we propose to review a range of issues, methodologies, and tools – which come from qualitative research - that guide us in conducting research in the psychotherapeutic and clinical field. The aim of our article is to put forward a methodological framework for researchers to better explore the patient’s or the therapist’s lived-experience and better reveal, moment-to-moment, the clinical practice.
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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 | 0.320 | 0.222 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.010 | 0.077 |
| Scholarly communication | 0.020 | 0.020 |
| Open science | 0.007 | 0.016 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".