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Record W4290786366 · doi:10.1097/corr.0000000000002320

Phone Administration of the Western Ontario Shoulder Instability Index Is More Reliable Than Administration via Email

2022· article· en· W4290786366 on OpenAlexaffabout
Patrick Goetti, Jacquelina Achkar, Émilie Sandman, Frédéric Balg, Dominique M. Rouleau

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2022
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité de SherbrookeCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHôpital du Sacré-Cœur de MontréalUniversité de Montréal
Fundersnot available
KeywordsMedicineAdministration (probate law)Index (typography)PhoneWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: The Western Ontario Shoulder Instability (WOSI) questionnaire is a 21-item questionnaire to evaluate quality of life in patients with shoulder instability. Completing the questionnaire is time-consuming because each item is evaluated on a visual analog scale. Telephone or email versions of the score are appealing alternatives to administering it during the standard in-person patient visit; however, their validity and reliability remain unknown. QUESTIONS/PURPOSES: (1) Does the numerical scale (NS) version of the WOSI correlate with the original WOSI and Quick-DASH? (2) Do telephone and email administration of the NS-WOSI have good reliability and consistency? (3) Compared with the original WOSI form, does the NS form lead to faster completion for patients and quicker data extraction for researchers? METHODS: Between 2014 and 2019, 50 patients with a documented history of shoulder dislocation with persistent symptomatic shoulder instability, whether anterior, posterior, or multidirectional; patients scheduled for surgery; and patients with traumatic or nontraumatic injuries were prospectively recruited from the outpatient clinic of two university hospitals acting as Level 1 trauma centers and sports traumatology tertiary referral centers. The median (IQR) age was 28 years (24 to 36), and 80% (40 of 50) were men. Most (52% [26 of 50]) patients had two to five lifetime shoulder dislocations. Validity of the NS-WOSI was assessed using the Pearson correlation coefficient during an in-person visit; the original WOSI questionnaire (or its previously validated French-language version), NS-WOSI, and Quick-DASH questionnaires were administered in a random order. After a minimum 7-day interval, 78% (39 of 50) of patients completed the phone interview, and 74% (37 of 50) of patients completed the email version of the NS-WOSI score to evaluate NS-WOSI's reliability using the intraclass correlation coefficient (ICC), which was interpreted as poor (< 0.5), moderate (0.50-0.75), strong (0.75-0.90), and very strong (> 0.90). The standard error of measurement (SEM) was used to evaluate variability around the true score, with a low value indicating a high reliability. The 95% minimal detectable change (MDC 95% ) was calculated to evaluate the minimal change in score that was not related to measurement errors. Lastly, the Cronbach alpha was used to assess internal consistency (intercorrelation strength), where a value > 0.70 was considered good. The time needed for the patient to complete the various versions and for researchers to extract data was recorded. RESULTS: The NS-WOSI score was very strongly correlated with the original WOSI score (r = 0.96 [95% confidence interval (CI) 0.93 to 0.98]; p < 0.001). Although telephone-acquired and email-acquired data for the NS-WOSI questionnaires were correlated with the NS-WOSI (telephone r = 0.91 [95% CI 0.83 to 0.95]; p < 0.001; email r = 0.84 [95% CI 0.71 to 0.91]; p < 0.001), the ICC was higher for telephone interviews (0.92 [95% CI 0.86 to 0.96] versus email 0.80 [95% CI 0.64 to 0.89]), indicating that although both had good reliability, the phone interview was more suitable. The phone interview was also preferable to email regarding SEM (3% [52 of 2100 points] versus 6% [132 of 2100 points]) and the MDC 95% (7% [144 of 2100 points] versus 17% [366 of 2100 points]). The 95% CI of the MDC acquired by email was superior to the reported minimum clinically important difference for the original WOSI (7% [152 of 2100 points]), meaning that an error of measurement could wrongly be interpreted as a clinically significant change in score. Internal consistency was deemed good, with a Cronbach alpha of 0.96 (95% CI 0.92 to 98) and 0.89 (95% CI 0.79 to 0.94) for NS-WOSI telephone and email, respectively. The time to complete the NS-WOSI was reduced compared with the original WOSI (221 ± 153 seconds versus 266 ± 146 seconds, mean difference -45 seconds [95% CI -72 to -12]; p = 0.009). Lastly, data extraction was faster (62 ± 15 seconds versus 209 ± 52 seconds, mean difference -147 seconds [95% CI -164 to -130]; p < 0.001) with the NS-WOSI than with the original WOSI. CONCLUSION: The NS-WOSI in person, by telephone, or by email is a valid, reliable, and timesaving alternative to the original WOSI questionnaire. However, the reliability of data acquisition by telephone interviews was superior to that of email. CLINICAL RELEVANCE: Given that there were no important differences in performance for the NS-WOSI, regardless of whether it was administered in person or by phone, we suggest that physicians use both interchangeably based on patient convenience. However, we do not recommend using the email version, especially for research purposes, since it was not as reliable when compared with in-person administration. The responsiveness of the modified NS-WOSI, as well as factors influencing response rates to phone interview, are questions that remain to be explored.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.098
GPT teacher head0.430
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
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".

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Citations2
Published2022
Admission routes2
Has abstractyes

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