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Objectives: Test a method of identifying, recruiting and collecting data from children and adolescents who consult their general practitioner about a musculoskeletal condition. Design: Prospective cohort feasibility study. Setting: 13 general practices in West Midlands of England. Participants: Patients aged 8–19 years who consult their general practice about a musculoskeletal condition. Patients were identified via a relevant musculoskeletal Read code entered at the point of consultation. Outcome measures: Feasibility was assessed in terms of study processes (recruitment rates), data collection procedures (duration, response variability), resource utilisation (mail-outs) and ethical considerations (acceptability). Results: From October 2016 to February 2017, an eligible musculoskeletal Read code was entered on 343 occasions, 202 patients were excluded (declined, n=153; screened not suitable, n=49) at the point of consultation. The remaining 141 patients were mailed an invitation to participate (41.1%); 46 patients responded to the invitation (response rate: 32.6%), of which 27 patients consented (consent rate: 19.1%). Participants mean age was 13.7 years (SD 2.7) and current pain intensity was 2.8 (SD 2.7). All participants completed the 6-week follow-up questionnaire. All participants found the interview questions to be acceptable and would consider participating in a similar study in the future. The majority of general practitioners/nurse practitioners, and all of the research nurses reported to be adequately informed about the study and found the study processes acceptable. Conclusion: The expected number of participants were identified and invited, but consent rate was low (<20%) indicating that this method is not feasible (eg, for use in a large prospective study). Recruiting children and adolescents with musculoskeletal conditions in a primary care setting currently presents a challenge for researchers. Further work is needed to identify alternative ways to conduct studies in this population in order to address the current knowledge gap in this field.

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Project No. 252 PI: Kate Dunn