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Record W2945395858 · doi:10.2196/13446

Internet-Based Cognitive Therapy for Social Anxiety Disorder in Hong Kong: Therapist Training and Dissemination Case Series

2019· article· en· W2945395858 on OpenAlexvenueno aff
Graham R. Thew, Candice L. Y. M. Powell, Amy Kwok, Mandy H Lissillour Chan, Jennifer Wild, Emma Warnock‐Parkes, Patrick W. L. Leung, David M. Clark

Bibliographic record

VenueJMIR Formative Research · 2019
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersNational Institute for Health and Care ResearchWellcome Trust
KeywordsPsychological interventionCompetence (human resources)AnxietyThe InternetContext (archaeology)PsychologyCognitionMental healthSocial anxietyMedicineMedical educationPsychotherapistPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Guided internet-based psychological interventions show substantial promise for expanding access to evidence-based mental health care. However, this can only be achieved if results of tightly controlled studies from the treatment developers can also be achieved in other independent settings. This dissemination depends critically on developing efficient and effective ways to train professionals to deliver these interventions. Unfortunately, descriptions of therapist training and its evaluation are often limited or absent within dissemination studies. OBJECTIVE: This study aimed to describe and evaluate a program of therapist training to deliver internet-based Cognitive Therapy for social anxiety disorder (iCT-SAD). As this treatment was developed in the United Kingdom and this study was conducted in Hong Kong with local therapists, an additional objective was to examine the feasibility, acceptability, and initial efficacy of iCT-SAD in this cultural context, based on data from a pilot case series. METHODS: Training in iCT-SAD was provided to 3 therapists and included practice of the face-to-face format of therapy under clinical supervision, training workshops, and treating 6 patients with the iCT-SAD program. Training progress was evaluated using standardized and self-report measures and by reviewing patient outcomes. In addition, feedback from patients and therapists was sought regarding the feasibility and acceptability of the program. RESULTS: The training program was effective at increasing therapists' iCT-SAD knowledge and skills, resulting in levels of competence expected of a specialist Cognitive Behavioral Therapy practitioner. The 6 patients treated by the trainees all completed their treatment and achieved a mean pre- to posttreatment change of 53.8 points (SD 39.5) on the primary patient outcome measure, the Liebowitz Social Anxiety Scale. The within-group effect size (Cohen d) was 2.06 (95% CI 0.66-3.46). There was evidence to suggest that the patients' clinical outcomes were sustained at 3-month follow-up. These clinical results are comparable to those achieved by UK patients treated by the developers of the internet program. Patient and therapist feedback did not identify any major cultural barriers to implementing iCT-SAD in Hong Kong; some modest language suggestions were made to assist understanding. CONCLUSIONS: The therapist training implemented here facilitated the successful dissemination of an effective UK-developed internet intervention to Hong Kong. The treatment appeared feasible and acceptable in this setting and showed highly promising initial efficacy. A randomized controlled trial is now required to examine this more robustly. As therapist training is critical to the successful dissemination of internet interventions, further research to develop, describe, and evaluate therapist training procedures is recommended.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.118
GPT teacher head0.508
Teacher spread0.390 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2019
Admission routes1
Has abstractyes

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