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Artigo em Inglês | MEDLINE | ID: mdl-38663576

RESUMO

OBJECTIVES: To identify the range of evidence for relationships between psychological factors using the Fear Avoidance Model (FAM) as a guiding framework and relevant clinical outcomes in adult patients with persisting symptoms after concussion (PSaC), develop a comprehensive understanding of psychological factors that have been identified as predictors of clinical outcomes for PSaC, and contribute to the theoretical framework of the FAM for PSaC. DATA SOURCES: Six databases (CINAHL, Embase, PsycINFO, PubMed, SportDiscus, and Web of Science) were searched by a librarian for empirical and theoretical publications and experimental and quasi-experimental study designs. The literature search was not limited by publication date restrictions. Gray literature, with the exception of doctoral dissertations, was excluded. STUDY SELECTION: We included studies in the English language consisting of human participants aged ≥18 years. Articles must have included both outcomes pertaining to PSaC (≥3mo after injury) and psychological constructs. DATA EXTRACTION: One reviewer extracted data from the resulting studies using a standardized data extraction form designed for this review. Two reviewers independently assessed risk of bias using the Quality in Prognosis Studies tool. DATA SYNTHESIS: This review found numerous psychological constructs, some directly linked to the FAM, that have potential prognostic relationships with PSaC. However, research remains limited and some psychological factors central to FAM were only identified in a small number of studies (catastrophizing, cogniphobia, and avoidance), whereas other psychological factors were studied more extensively (anxiety and depression). CONCLUSIONS: There is the need for additional evidence, and this integrative review provides an adaptation of the FAM for PSaC to be used as a guiding preliminary framework for future research. Future research should aim to include psychological factors proposed in this modified FAM to fully understand PSaC.

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