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Record W3114181871 · doi:10.2196/23090

Swedish Web Version of the Quality of Recovery Scale Adapted for Patients Undergoing Local Anesthesia and Peripheral Nerve Blockade (SwQoR-LA): Prospective Psychometric Evaluation Study

2020· article· en· W3114181871 on OpenAlexvenueno aff
Ulrica Nilsson, Karuna Dahlberg, Maria Jaensson

Bibliographic record

VenueJMIR Perioperative Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicNausea and vomiting management
Canadian institutionsnot available
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdVetenskapsrådet
KeywordsMedicineAnesthesiaNerve blockCeiling effectConstruct validityPhysical therapyPatient satisfactionNeuraxial blockadeSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The frequency and timing of assessing patient symptoms and discomfort during postoperative recovery are goals. Therefore, real-time recovery evaluation has been suggested to identify specific deficits in patient recovery. OBJECTIVE: This study aimed to psychometrically evaluate the Swedish Web Version of the Quality of Recovery (SwQoR) Scale adapted for patients undergoing local and peripheral nerve block (SwQoR-LA). METHODS: This was a secondary analysis of a psychometric evaluation of 107 patients aged ≥18 years undergoing day surgery under local or peripheral nerve block anesthesia at 4 different day surgery departments in Sweden. The SwQoR-LA, available through a mobile app called Recovery Assessment by Phone Points (RAPP), was completed daily on postoperative days 1-7. RESULTS: Some evidence of construct validity was supported, and discriminant validity was found in 7 of 8 items related to general anesthesia. The internal consistency was acceptable (.87-.89), and the split-half reliability was 0.80-0.86. Cohen d effect size was 0.98, and the percentage of change from baseline was 43.4%. No floor nor ceiling effects were found. CONCLUSIONS: The SwQoR-LA is valid, reliable, responsive, and clinically feasible for digital real-time recovery assessment of patient recovery to identify specific deficits in patient recovery and detect those patients who might benefit from a timely intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT02492191; https://clinicaltrials.gov/ct2/show/NCT02492191. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2015-009901.

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)0.001
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 score0.018
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.045
GPT teacher head0.351
Teacher spread0.305 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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