A systematic review of <scp>in‐person</scp> versus remotely delivered interventions for youth with chronic pain
Bibliographic record
Abstract
The COVID-19 pandemic prompted a rapid shift from in-person to virtually-delivered care. Many youth with chronic pain have the ability to access care virtually; however, little is known about the efficacy of pain care for youth with chronic pain delivered virtually when compared to in-person. Such evidence is essential to guide youth in making decisions about their care, but also to inform what options health professionals present to youth. The purpose of this systematic review and meta-analysis was to examine the efficacy of interventions that are delivered in-person versus virtually for youth with chronic pain. Five databases (i.e., CINAHL, EMBASE, MEDLINE, APA PsycINFO, and Web of Science) were searched in October 2022 to identify randomized controlled trials that compare single/multimodal interventions for pediatric chronic pain delivered in-person versus virtually. A total 3638 unique studies were identified through database and other searching, two of which satisfied established criteria for inclusion in this review. Both studies compared psychological interventions delivered virtually versus in-person for youth with chronic pain and showed comparable efficacy across modalities. The planned meta-analyses could not be conducted due to different outcomes within each study that could not be combined. This systematic review highlights a critical gap in the evidence regarding the efficacy of virtually delivered interventions for youth with chronic pain. This evidence is necessary to inform treatment decisions for youth, and further research is required to develop the evidence to inform clinical interventions, especially as virtual treatments continue to be offered.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".