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Record W4391384205 · doi:10.3390/healthcare12030360

Innovative Program to Prevent Pediatric Chronic Postsurgical Pain: Patient Partner Feedback on Intervention Development

2024· article· en· W4391384205 on OpenAlexaff
Danielle Ruskin, Klaudia Szczech, Jennifer Tyrrell, Lisa Isaac

Bibliographic record

VenueHealthcare · 2024
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoYork University
Fundersnot available
KeywordsBiopsychosocial modelPsychological interventionThematic analysisChronic painIntervention (counseling)AnxietyMedicinePerioperativeMental healthPhysical therapyClinical psychologyPsychologyQualitative researchPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The risk of developing chronic postsurgical pain (CPSP) in youth is related to psychological factors, including preoperative anxiety, depression, patient/caregiver pain catastrophizing, and poor self-efficacy in managing pain. While interventions exist to address these factors, they are generally brief and educational in nature. The current paper details patient partner feedback on the development of a psychologist-delivered perioperative psychological program (PPP) designed to identify and target psychological risk factors for CPSP and improve self-efficacy in managing pain. METHODS: Qualitative interviews were conducted with two patients and their caregivers to discuss their surgical and pain management experience and to advise on components of the PPP. RESULTS: Reflexive thematic analysis of interviews generated the following themes, which were incorporated into the content and implementation of the PPP: caregiver involvement, psychological and physical strategies for pain management, biopsychosocial pain education, intervention structure, and supporting materials. CONCLUSIONS: The development of a novel psychologist-led PPP is a promising approach to mitigate mental health risks associated with pediatric CPSP and potentially boost postoperative outcomes and family wellbeing. Integrating patient partner feedback ensures that the PPP is relevant, acceptable, and aligned with the needs and preferences of the patients it is designed to serve.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.362
Teacher spread0.333 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations3
Published2024
Admission routes1
Has abstractyes

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