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Record W2153981350 · doi:10.1093/jpepsy/jsp104

Assessing the Quality of Randomized Controlled Trials Examining Psychological Interventions for Pediatric Procedural Pain: Recommendations for Quality Improvement

2009· article· en· W2153981350 on OpenAlexafffund
Lindsay S Uman, Christine T. Chambers, Patrick J. McGrath, Steve Kisely, Debora Matthews, K. Hayton

Bibliographic record

VenueJournal of Pediatric Psychology · 2009
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
FundersCanadian Institutes of Health Research
KeywordsPsychological interventionRandomized controlled trialPediatric psychologyPsychologyQuality (philosophy)Clinical psychologyPhysical therapyMEDLINEMedicinePsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Systematic reviews of randomized controlled trials (RCTs) support the efficacy of psychological interventions for procedural pain management. However, methodological limitations (e.g., inadequate randomization) have affected the quality of this research, thereby weakening RCT findings. METHODS: Detailed quality coding was conducted on 28 RCTs included in a systematic review of psychological interventions for pediatric procedural pain. RESULTS: The majority of RCTs were of poor to low quality (criteria reported in <50% of RCTs). Commonly reported criteria addressed study background, conditions, statistical analyses, and interpretation of results. Commonly nonreported criteria included treatment administration, evaluation of treatment efficacy (effect sizes, summary statistics, intention-to-treat analyses), caregiver demographics, follow-up, and participant flow. Quality was greater in more recent trials, and did not vary by journal type (psychology vs. medical). CONCLUSION: Despite poor quality ratings, quality reporting in psychological RCTs for pediatric procedural pain has improved over time. Recommendations for quality enhancement are provided.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.123
metaresearch head score (Gemma)0.082
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.653
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1230.082
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.322
GPT teacher head0.557
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2009
Admission routes2
Has abstractyes

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