Parental Assessment of Postsurgical Pain in Infants at Home Using Artificial Intelligence–Enabled and Observer-Based Tools: Construct Validity and Clinical Utility Evaluation Study
Bibliographic record
Abstract
Background Pain assessment in the infant population is challenging owing to their inability to verbalize and hence self-report pain. Currently, there is a paucity of data on how parents identify and manage this pain at home using standardized pain assessment tools. Objective This study aimed to explore parents’ assessment and intervention of pain in their infants at home following same-day surgery, using standardized pain assessment tools. Methods This prospective study initially recruited 109 infant boys undergoing circumcision (same-day surgery). To assess pain at home over 3 days after surgery, parents using iOS devices were assigned to use the PainChek Infant tool, which is a point-of-care artificial intelligence–enabled tool, while parents using Android devices were assigned to use the Observer-Administered Visual Analog Scale (ObsVAS) tool. Chi-square analysis compared the intervention undertaken and pain presence. Generalized estimating equations were used to evaluate outcomes related to construct validity and clinical utility. Receiver operating characteristic analysis assessed pain score cutoffs in relation to the intervention used. Results A total of 69 parents completed postsurgery pain assessments at home and returned their pain diaries. Of these 69 parents, 24 used ObsVAS and 45 used PainChek Infant. Feeding alone and feeding with medication were the most common pain interventions. Pain presence over time reduced. In the presence of pain, an intervention was likely to be administered (χ22=21.4; P<.001), with a medicinal intervention being 12.6 (95% CI 4.3-37.0; P<.001) times more likely and a nonmedicinal intervention being 5.2 (95% CI 1.8-14.6; P=.002) times more likely than no intervention. In the presence of intervention, score cutoff values were ≥2 for PainChek Infant and ≥20 for ObsVAS. A significant effect between the use of the pain instrument (χ21=7.2, P=.007) and intervention (χ22=43.4, P<.001) was found, supporting the construct validity of both instruments. Standardized pain scores were the highest when a medicinal intervention was undertaken (estimated marginal mean [EMM]=34.2%), followed by a nonmedicinal intervention (EMM=23.5%) and no intervention (EMM=11.2%). Similar trends were seen for both pain instruments. Pain was reduced in 94.5% (224/237) of assessments where parents undertook an intervention. In 75.1% (178/237) of assessments indicative of pain, the score changed from pain to no pain, with PainChek Infant assessments more likely to report this change (odds ratio 4.1, 95% CI 1.4-12.3) compared with ObsVAS assessments. Conclusions The use of standardized pain assessment instruments by parents at home to assess pain in their infants can inform their decision-making regarding pain identification and management, including determining the effectiveness of the chosen intervention. In addition to the construct validity and clinical utility of PainChek Infant and ObsVAS in this setting, feeding alone and a combination of feeding with medication use were the key pain intervention strategies used by parents.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".