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Record W2656219854 · doi:10.1177/0844562117714704

A Pain Education Intervention for Patients Undergoing Ambulatory Inguinal Hernia Repair

2017· article· en· W2656219854 on OpenAlexaffvenue
Monakshi Sawhney, Judy Watt‐Watson, Michael McGillion

Bibliographic record

VenueCanadian Journal of Nursing Research · 2017
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsMcMaster UniversityUniversity of TorontoQueen's University
Fundersnot available
KeywordsMedicineInguinal herniaAmbulatoryRandomized controlled trialIntervention (counseling)Hernia repairPhysical therapyPsychological interventionHerniaSurgeryAnesthesiaNursing

Abstract

fetched live from OpenAlex

Background Inguinal hernia repair is a common ambulatory surgery after which many patients experience moderate to severe post-operative pain. Limited research has examined the effect of education interventions to reduce pain after ambulatory surgery. Purpose This trial evaluated the effectiveness of an individualized Hernia Repair Education Intervention (HREI) for patients following inguinal hernia repair. Method Pre-operatively, participants (N = 82) were randomized to either the intervention (HREI) or the usual care group. The HREI included written and verbal information regarding managing pain and two telephone support calls (before and after surgery). The primary outcome was WORST 24-h pain intensity on movement on post-operative day 2. Secondary outcomes included pain intensity at rest and movement, pain-related interference with activities, pain quality, analgesics consumed, and adverse effects at post-operative days 2 and 7. Results At day 2, the intervention group reported significantly lower scores across pain intensity outcomes, including WORST 24-h pain on movement and at rest (p < 0.001), and pain NOW on movement and at rest (p = 0.001). Conclusion These findings suggest that the HREI may improve patients' pain and function following ambulatory inguinal hernia repair. Further research should examine the effectiveness of an education intervention over a longer period of time.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.081
GPT teacher head0.418
Teacher spread0.336 · 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 designObservational
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

Citations20
Published2017
Admission routes2
Has abstractyes

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