Dataset on comprehensive assessment & classification of upper & lower limb pain in athletes.

Data were charted as part of a scoping review which followed the Joanna Briggs Institute (JBI) evidence synthesis guidelines and the Preferred Reporting Items for Systematic Reviews and Meta Analysis Scoping Review extension (PRISMA-SCr) guidelines. Data was extracted from 470 articles that met the inclusion criteria for the scoping review; primary research articles of athletes where upper and/or lower limb pain since database inception. A draft data charting tool was developed by the research team and piloted for feasibility, accuracy and agreement. The charting tool was updated accordingly before being applied to the entire data set. Data collected included citation details, research context, participant information and pain assessment and classification tools, categories, and additional relevant information. The raw data set was filtered, and descriptive analysis of frequencies and counts were conducted. Researchers and clinicians interested in the range and applications of different pain assessment practices in athletes may reuse this data set. Data charting was comprehensive including aspects beyond the scope of the original research that offer clinical and research potential. These include information around recommended practice, (International Olympic Committee guidance) pain classifications and definitions and the use of multi-domain pain assessment tools.

Comprehensive assessment and classification of upper and lower limb pain in athletes: a scoping review.

BACKGROUND: Upper and lower limb (peripheral) pain is prevalent in athletes. Contemporary research prioritises multidimensional pain assessment and classification. This study aims to review comprehensive athlete pain assessment practices against the reference standard (International Olympic Committee, IOC Athlete Pain framework), identifying trends and highlighting gaps. METHODS AND ANALYSIS: Six databases were searched using a comprehensive search strategy. This review followed the Joanna Briggs Institute standardised methodology for scoping reviews and is reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Title and abstract, full-text screening and data charting were completed by two independent reviewers. INCLUSION CRITERIA: Original research, systematic reviews and clinical practice guidelines reporting assessment or classification of pain in athletes of any age with chronic or acute peripheral pain in English on human participants from database inception. RESULTS: 470 studies with 175 different pain assessment tools were mapped against the IOC Athlete Pain Framework. Papers included tools from neurophysiological (470/100%), biomechanical (425/90%), affective (103/22%), cognitive (59/13%) and socioenvironmental (182/39%) domains. Pain classification was included in 108 studies (23%). 4 studies (0.85%) defined pain. Athletes with physical disability were included in 13 (3%) studies and no studies included athletes with intellectual disabilities. Socioeconomic factors were addressed in 29 (6%) studies. DISCUSSION: Neurophysiological and biomechanical domains are frequently addressed. Affective, socioenvironmental and cognitive tools are under-represented. Potential tools for use by researchers and clinicians are highlighted. Defining and classifying pain and determining predominant pain mechanisms is needed in both research and clinical practice. More work on underrepresented populations is needed. CONCLUSION: This review informs researchers and clinicians working with athletes in pain how pain assessment and classification is currently conducted and highlights future priorities.

mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis.

BACKGROUND: The number of mobile health (mHealth) apps released for musculoskeletal (MSK) injury treatment and self-management with home exercise programs (HEPs) has risen rapidly in recent years as digital health interventions are explored and researched in more detail. As this number grows, it is becoming increasingly difficult for users to navigate the market and select the most appropriate app for their use case. It is also unclear what features the developers of these apps are harnessing to support patient self-management and how they fit into clinical care pathways. OBJECTIVE: The objective of this study was to scope the current market of mHealth apps for MSK rehabilitation and to report on their features, claims, evidence base, and functionalities. METHODS: A cross-sectional study of apps for MSK rehabilitation was performed across the iTunes App Store and Google Play Store. Four search terms were used, namely, physiotherapy rehabilitation, physical therapy rehabilitation, rehabilitation exercise, and therapeutic exercise to identify apps, which were then cross-referenced against set selection criteria by 4 reviewers. Each reviewer, where possible, downloaded the app and accessed supplementary literature available on the product to assist in data extraction. RESULTS: A total of 1322 apps were identified. After applying the inclusion and exclusion criteria and removing duplicates, 144 apps were included in the study. Over half (n=81, 56.3%) of the included apps had been released within the past 3 years. Three quarters (n=107, 74.3%) of the apps made no reference to evidence supporting the design or efficacy of the app, with only 11.1% (n=16) providing direct citations to research. Most of the apps did utilize exercise pictures (n=138, 95.8%) or videos (n=97, 67.4%); however, comparatively few harnessed additional features to encourage engagement and support self-management, such as an adherence log (n=66, 45.8%), communication portal (n=32, 22.2%), patient-reported outcome capture (n=36, 25%), or direct feedback (n=57, 39.6%). Of note and concern, many of these apps prescribed generic exercises (n=93, 64.6%) in the absence of individualized input to the user, with few providing specific patient education (n=43, 34%) and safety advice or disclaimers (n=38, 26.4%). CONCLUSIONS: The cohort of apps included in this study contained a large heterogeneity of features, so it is difficult for users to identify the most appropriate or effective app. Many apps are missing the opportunity to offer key features that could promote exercise adherence and encourage self-management in MSK rehabilitation. Furthermore, very few developers currently offering products on the market are providing evidence to support the design and efficacy of their technologies.