Enhancing the hermeneutic single-case efficacy design: Bridging the research–practice gap
Bibliographic record
Abstract
Systematic case study designs are emerging as alternative paradigm strategies for psychotherapy and social science research. Through enhanced sensitivity to context, these designs examine idiographic profiles of causal processes. We specifically advocate the use of the hermeneutic single-case efficacy design (HSCED). HSCED has recently been used to investigate the efficacy of an existing therapy with a new population (Observed and Experiential Integration for athlete performance barriers) and an emerging therapy (Lifespan Integration Therapy). We describe innovations in HSCED that were implemented for these studies. These developments include (a) integrating psychotherapists as case developers, (b) incorporating multiple cases in one investigation, and (c) tailoring the repertoire of assessment tools. These extensions strategically incorporated principles of contextual paradigms in HSCED, thus complementing single-case designs that neglect idiographic contexts. We discuss recommendations for using HSCED in practice-based research, highlighting its potential as a bridge to address the research-practice gap.
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 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 | 0.616 | 0.576 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".