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Bone & Joint Open
Vol. 3, Issue 10 | Pages 786 - 794
12 Oct 2022
Harrison CJ Plummer OR Dawson J Jenkinson C Hunt A Rodrigues JN

Aims

The aim of this study was to develop and evaluate machine-learning-based computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and its subscales.

Methods

We developed CAT algorithms for the OHS, OKS, OSS, overall OES, and each of the OES subscales, using responses to the full-length questionnaires and a machine-learning technique called regression tree learning. The algorithms were evaluated through a series of simulation studies, in which they aimed to predict respondents’ full-length questionnaire scores from only a selection of their item responses. In each case, the total number of items used by the CAT algorithm was recorded and CAT scores were compared to full-length questionnaire scores by mean, SD, score distribution plots, Pearson’s correlation coefficient, intraclass correlation (ICC), and the Bland-Altman method. Differences between CAT scores and full-length questionnaire scores were contextualized through comparison to the instruments’ minimal clinically important difference (MCID).


Bone & Joint Open
Vol. 1, Issue 4 | Pages 47 - 54
2 Apr 2020
Al-Mohrej OA Elshaer AK Al-Dakhil SS Sayed AI Aljohar S AlFattani AA Alhussainan TS

Introduction

Studies have addressed the issue of increasing prevalence of work-related musculoskeletal (MSK) pain among different occupations. However, contributing factors to MSK pain have not been fully investigated among orthopaedic surgeons. Thus, this study aimed to approximate the prevalence and predictors of MSK pain among Saudi orthopaedic surgeons working in Riyadh, Saudi Arabia.

Methods

A cross-sectional study using an electronic survey was conducted in Riyadh. The questionnaire was distributed through email among orthopaedic surgeons in Riyadh hospitals. Standardized Nordic questionnaires for the analysis of musculoskeletal symptoms were used. Descriptive measures for categorical and numerical variables were presented. Student’s t-test and Pearson’s χ2 test were used. The level of statistical significance was set at p ≤ 0.05.