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Record W3012997654 · doi:10.2196/18216

Guided Internet-Based Cognitive Behavioral Therapy in Japanese Patients With Obsessive-Compulsive Disorder: Protocol for a Randomized Controlled Trial

2020· article· en· W3012997654 on OpenAlexvenueno aff
Kazuki Matsumoto, Sayo Hamatani, Takuya Makino, Taku Uemura, Futoshi Suzuki, Seina Shinno, Tomoki Ikai, Hiroyuki Hayashi, Chihiro Sutoh, Eiji Shimizu

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsRandomized controlled trialBeck Anxiety InventoryCognitive behavioral therapyCognitive therapyAnxietyClinical psychologyCognitionPsychiatryAnxiety disorderGeneralized anxiety disorderPsychologyMedicineBeck Depression InventoryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive behavioral therapy for obsessive-compulsive disorder has been established, but access to this therapy in Japan is limited. Internet-based cognitive behavioral therapy may improve treatment accessibility and sufficiently improve obsessive-compulsive symptoms. There are few randomized controlled trials examining the effectiveness of internet-based cognitive behavioral therapy in patients with obsessive-compulsive disorder. We designed a randomized controlled trial protocol to assess the effectiveness of guided internet-based cognitive behavioral therapy in Japanese patients with obsessive-compulsive disorder. OBJECTIVE: We aimed to develop a protocol for a randomized controlled trial of internet-based cognitive behavioral therapy in Japanese patients with obsessive-compulsive disorder. METHODS: The randomized controlled trial will compare internet-based cognitive behavioral therapy treatment and usual care groups, each consisting of 15 participants (n=30) diagnosed with obsessive-compulsive disorder. We will evaluate the effectiveness of a 12-week intervention. The primary outcome of symptom severity will be measured using the Yale-Brown Obsessive-Compulsive Scale. Secondary outcomes will be assessed with the Obsessive-Compulsive Inventory, Beck Anxiety Inventory, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Working Alliance Inventory-Short Form, and the Euro Qol - 5 Dimension. All measures will be assessed at weeks 0 (baseline) and 12 (follow-up). In the statistical analysis comparing treatment effects, the least-squares means and their 95% CIs will be estimated by analysis of covariance with the change in total outcomes scores at week 12. All comparisons are planned, and all P values will be two-sided, with values <.05 considered statistically significant. RESULTS: The study will be performed from January 2020 to March 2021, and results are expected to be available in mid-2021. CONCLUSIONS: The trial will demonstrate whether internet-based cognitive behavioral therapy improves access and is more effective than more usual care for patients with obsessive-compulsive disorder in Japan. TRIAL REGISTRATION: University Hospital Medical Information Network (UMIN) 000039375; https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000044422. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18216.

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 imitation

Not 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.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.064
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.034
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0140.006
Bibliometrics0.0040.004
Science and technology studies0.0040.004
Scholarly communication0.0040.004
Open science0.0040.002
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0640.008

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 head0.128
GPT teacher head0.509
Teacher spread0.381 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations7
Published2020
Admission routes1
Has abstractyes

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