The Validity of Skin Conductance For Assessing Acute Pain in Infants
Bibliographic record
Abstract
OBJECTIVES: Measuring pain in infants is important but challenging, as there is no "gold standard." The measurement of skin conductance (SC) is considered to be a measure of stress and as a surrogate indicator of pain. The objectives of this study were to identify the extent of research conducted and to synthesize the validity evidence of SC for assessing acute pain in infants. METHODS: The Arksey and O'Malley framework for scoping reviews was followed, and 9 electronic databases were searched. Data were analyzed thematically and presented descriptively including the following main categories: study information/details, sampling information, characteristics of participants and settings, SC outcome measures, and validity evidence. RESULTS: Twenty-eight studies with 1061 infants were included, including 23 cross-sectional observation studies and 5 interventional studies. The most studied infants were those with mild severity of illness (n=13) or healthy infants (n=12). The validity evidence of SC was tested in relation to referent pain measures (13 variables), stimuli (13 variables), age (2 variables), and other contextual variables (11 variables). SC was not significantly correlated with vital signs, except for heart rate in 2 of the 8 studies. SC was significantly correlated with the unidimensional behavioral pain assessment scales and crying time rather than with multidimensional measurements. Fourteen of 15 studies (93.3%) showed that SC increased significantly during painful procedures. CONCLUSIONS: Inconsistent findings on validity of SC exist. Future research should aim to identify the diagnostic test accuracy of SC compared with well-accepted referent pain measures in infants, study the validity evidence of SC in critically ill infants, and utilize rigorous research design and transparent reporting.
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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 | 0.101 | 0.359 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".