Using the MEDiPORT humanoid robot to reduce procedural pain and distress in children with cancer: A pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Subcutaneous port needle insertions are painful and distressing for children with cancer. The interactive MEDiPORT robot has been programmed to implement psychological strategies to decrease pain and distress during this procedure. This study assessed the feasibility of a future MEDiPORT trial. The secondary aim was to determine the preliminary effectiveness of MEDiPORT in reducing child pain and distress during subcutaneous port accesses. METHODS: This 5-month pilot randomized controlled trial used a web-based service to randomize 4- to 9-year-olds with cancer to the MEDiPORT cognitive-behavioral arm (robot using evidence-based cognitive-behavioral interventions) or active distraction arm (robot dancing and singing) while a nurse conducted a needle insertion. We assessed accrual and retention; technical difficulties; outcome measure completion by children, parents, and nurses; time taken to complete the study and clinical procedure; and child-, parent-, and nurse-rated acceptability. Descriptive analyses, with exploratory inferential testing of child pain and distress data, were used to address study aims. RESULTS: Forty children were randomized across study arms. Most (85%) eligible children participated and no children withdrew. Technical difficulties were more common in the cognitive-behavioral arm. Completion times for the study and needle insertion were acceptable and >96% of outcome measure items were completed. Overall, MEDiPORT and the study were acceptable to participants. There was no difference in pain between arms, but distress during the procedure was less pronounced in the active distraction arm. CONCLUSION: The MEDiPORT study appears feasible to implement as an adequately-powered effectiveness-assessing trial following modifications to the intervention and study protocol. ClinicalTrials.gov NCT02611739.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".