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Record W3005373331 · doi:10.1016/j.invent.2020.100309

Audit and feedback of therapist-assisted internet-delivered cognitive behaviour therapy within routine care: A quality improvement case study

2020· article· en· W3005373331 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternet Interventions · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsSaskatchewan Health AuthoritySaskatchewan HealthUniversity of Regina
FundersCanadian Institutes of Health ResearchAustralian Government
KeywordsAuditQuality (philosophy)MedicinePsychologyClinical auditQuality management

Abstract

fetched live from OpenAlex

With the growing use of ICBT in routine care clinics there is a need for literature on how to monitor and improve the quality of therapist behaviours in clinical practice. In this paper, we first provide background literature on Audit and Feedback (A&F), a common quality improvement technique, and then present a case study regarding the use of A&F to improve quality of therapist behaviours in emails sent to patients provided with ICBT in routine care. The A&F measure used was derived from previous research on therapist's email behaviours in ICBT. Fifteen undesirable therapist behaviours (e.g., Did Not Message, Unresponsive to Symptom Increase, Does Not Address Patient Concern) were audited in 1840 emails sent from eight therapists to 198 randomly selected patients, representing 18% of 1114 patients who started between one and five lessons of ICBT in the previous year and did not formally withdraw from treatment (n = 31 patients). The therapists who were audited were provided feedback four times over a one-year period from October 2018 to September 2019. Overall, in all audit periods, we found a low percentage of undesirable therapist behaviours (i.e., therapists displayed the behaviour in 12% or less of the total emails sent). For most therapist behaviours, we saw a trend towards improvement across the four audit cycles. Three therapist behaviours (i.e., Failure to Ask One Question to the Patient, Poor Instructions, Not Linking Email to Course Content) did not follow this pattern and were flagged for clinical discussion to determine why behaviours were elevated and whether these behaviours represented unrealistic expectations. The process was valuable for monitoring and improving therapist behaviours and highlights the need for future research on standards for therapist behaviours (e.g., which behaviours to focus on, setting acceptable levels of undesirable behaviour).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.137
GPT teacher head0.438
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it