Internet-Delivered Cognitive Behavioral Treatment for Chronic Pain in Adolescent Survivors of Childhood Cancer: Protocol for a Single-Group Feasibility Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND There are over 500,000 survivors of childhood cancer in North America alone. One in 4 survivors experiences chronic pain after treatment has been completed. Youths with chronic pain report increased anxiety, depression, activity limitations, and sleep disturbances. An 8-week web-based cognitive behavioral treatment for chronic pain (Web-Based Management of Adolescent Pain [WebMAP]) has demonstrated a reduction in pain in youths but has not yet been explored in survivors. OBJECTIVE The objectives of this study are to (1) test the feasibility and acceptability of WebMAP for a sample of survivors with chronic pain and their parents; (2) assess the acceptability of WebMAP using qualitative interviews; (3) assess WebMAP’s effect on activity limitations, pain intensity, depression and anxiety symptoms, and sleep disturbances; and (4) assess WebMAP’s effect on parent pain catastrophizing and parental response to their child’s pain. METHODS A single-arm mixed methods pre-post intervention study design will be used. Participants will be 34 survivors and at least one of their parents or caregivers. Inclusion criteria are (1) a cancer history, (2) current age of 10-17 years, (3) >2 years post treatment or >5 years post diagnosis, (4) pain present over prior 3 months impairing >1 area of daily life and occurring >1 time per month, and (5) computer access with broadband internet. Survivors will complete a pretreatment questionnaire, which will include the following: the Child Activity Limitations Interview, the pain intensity Numerical Rating Scale, Patient-Reported Outcomes Measurement Information System (PROMIS)–Pain Interference, Anxiety, Depression, Insomnia Severity Index, and Adolescent Sleep Wake Scale. Parents will complete the Pain Catastrophizing Scale–Parent Version and the Adult Responses to Child Symptoms. Upon completion of pretreatment questionnaires (T0), survivors will begin WebMAP. After the 8-week intervention, survivors will complete the same measures (T1), and at 3-month follow-up (T2). Posttreatment interviews will be conducted to determine acceptability. Feasibility will be assessed via recruitment and retention rates. Treatment engagement will be measured by number of modules completed. Pre-post outcome data will be assessed using linear mixed models. Qualitative data will be analyzed using thematic analysis. Patient partners will be involved in study design, recruitment, interpretation of results, and knowledge translation. RESULTS This study has been funded in January 2022. Data collection started in May 2022 and is projected to end in August 2023. We have enrolled 10 participants as of December 2022. CONCLUSIONS Investigating whether WebMAP is useful to survivors will be an important step in improving pain management in this population. CLINICALTRIAL ClinicalTrials.gov NCT05241717; https://clinicaltrials.gov/ct2/show/NCT05241717 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/45804
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Non-randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Non-randomized trial | high |
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 | 0.021 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.117 | 0.020 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".