Using the Consensus on Exercise Reporting Template (CERT) Checklist at the Exercise Level to Assess the Completeness of Exercise Reporting: A Methodological Review
Year: 2025
Type: article
Study design: Systematic Review
Abstract: OBJECTIVE: To evaluate exercise reporting completeness at the exercise level using the Consensus on Exercise Reporting Template (CERT) checklist (a guideline for reporting of exercise trials, consisting of 19 items), explore the partial-credit versus traditional full-credit models of scoring completeness, and assess the reliability of scoring methods. DESIGN: Methodological review of randomized clinical trials. LITERATURE SEARCH: Eight databases were searched for trials investigating exercise for subacromial pain syndrome, published between January 2021 and February 2024. STUDY SELECTION CRITERIA: Trials examining exercise in treatment and comparator arms for subacromial pain syndrome were included. Of 25 eligible studies, 10 were randomly selected for analysis. DATA SYNTHESIS: Each exercise was scored using a modified CERT, employing a partial-credit model. Exercise-level mean scores were calculated for each study and compared to traditional study-level scores. Proportions of completeness and interrater reliability were calculated for each CERT item. RESULTS: The mean CERT total score of 7.3/20 using a partial-credit model (0, 0.5, or 1 point) across all exercises demonstrates inadequate exercise reporting, with lower scores indicating incomplete reporting. Traditional scoring (0 or 1 point) applied at the exercise level (using recoding) resulted in a judgment of less complete reporting, with a mean CERT score of 3.7/20, while traditional study-level scoring suggested more complete reporting (8.7/19). Reliability (kappa) was improved with partial-credit (mean k = 0.54) versus traditional study-level scoring (mean k = 0.29). CONCLUSION: Exercise-level CERT scoring with a partial-credit model details gaps in reporting and limitations of the traditional study-level scoring. This somewhat labor-intensive approach provides a more accurate and reliable assessment of exercise reporting completeness. JOSPT Methods 2025;1(3):102-112. Epub 15 September 2025. doi:10.2519/josptmethods.2025.0004
Source: JOSPT Methods
Authors: Joshua A. Subialka, Ryan C. McConnell, Ethan Vosburgh, Derek Pyle, Mareli Klopper, C. Daniel Maddox, Tyler Miller, Anthony Mancini, Marcel P. Dijkers
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4414201007