Do we know when our clients get worse? an investigation of therapists' ability to detect negative client change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Routine clinical judgment is often relied upon to detect client deterioration. How reliable are therapists' judgments of deterioration? Two related studies were conducted to investigate therapist detection of client deterioration and therapist treatment decisions in situations of deterioration. The first study examined therapists' ability to detect client deterioration through the review of therapy progress notes. Therapist treatment decisions in cases of client deterioration were also explored. Therapists had considerable difficulty recognizing client deterioration, challenging the assumption that routine clinical judgment is sufficient when attempting to detect client deterioration. A second study was a survey of therapists asking how they detect client deterioration and what treatment decisions they make in response. Symptom worsening was the most commonly stated cue of deterioration. Copyright © 2009 John Wiley & Sons, Ltd. Key Practitioner Message: • Clinicians may have a difficult time detecting when their client's symptoms are worsening. • Outcome assessment strategies do exist to help clinicians detect client deterioration.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it