The INternet ThERapy for deprESsion Trial (INTEREST): protocol for a patient-preference, randomised controlled feasibility trial comparing iACT, iCBT and attention control among individuals with comorbid chronic pain and depression
Bibliographic record
Abstract
INTRODUCTION: Approximately one-third of adults with chronic pain also report clinically relevant levels of depression. Internet-delivered psychological therapies such as Cognitive Behavioural Therapy (iCBT) and Acceptance and Commitment Therapy (iACT) have been developed to overcome barriers of access to services and ensure the timely delivery of care. The objective of this trial is to collect data on feasibility, acceptability and range of probable effect sizes for iCBT and iACT interventions tailored towards the treatment of depression and chronic pain using a randomised controlled patient-preference design. METHODS AND ANALYSIS: Community dwelling adults with chronic non-cancer pain (CNCP) and major depression will be recruited from pain clinics and primary care providers in Newfoundland and Labrador, Canada. The study is a randomised controlled patient-preference trial. Eligible patients will be randomly assigned to a 'preference' or 'no-preference' arm during the first step of randomisation and to intervention or control in the second step of randomisation. Two interventions (ie, iCBT or iACT) will be evaluated relative to attention control. iCBT and iACT involve the completion of 7-weekly online modules augmented with one session of motivational enhancement and weekly therapy sessions. Primary outcomes include (1) feasibility and acceptability parameters and (2) change in symptoms of depression. Secondary outcomes include pain, physical function, emotional function and quality of life. We will recruit 60 participants and examine the range of effect sizes obtained from the trial but will not conduct significance testing as per recommendations for behavioural trial development. ETHICS AND DISSEMINATION: Ethics was approved by the provincial Health Research Ethics Board. Dissemination of results will be published in a peer-reviewed academic journal and presented at scientific conferences. TRIAL REGISTRATION NUMBER: NCT04009135.
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 | 0.025 | 0.020 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.096 | 0.017 |
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".