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Health and Quality of Life Outcomes





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Introduction: Clinician time and resources may be underutilised if the treatment they offer does not match patient expectations and attitudes. We developed a questionnaire (AxEL-Q) to guide clinicians toward elements of first-line care that are pertinent to their patients with low back pain. Methods: We used guidance from the COSMIN consortium to develop the questionnaire and evaluated it in a sample of people with low back pain of any duration. Participants were recruited from the community, were over 18 years and fluent in English. Statements that represented first-line care were identified. Semantic scales were used to measure attitude towards these statements. These items were combined to develop the questionnaire draft. Construct validity was evaluated with exploratory factor analysis and hypotheses testing, comparing to the Back Beliefs Questionnaire and modified Pain Self-Efficacy Questionnaire. Reliability was evaluated and floor and ceiling effects calculated. Results: We recruited 345 participants, and had complete data for analysis for 313 participants. The questionnaire draft was reduced to a 3-Factor questionnaire through exploratory factor analysis. Factor 1 comprised 9 items and evaluated Attitude toward staying active, Factor 2 comprised 4 items and evaluated Attitude toward low back pain being rarely caused by a serious health problem, Factor 3 comprised 4 items and evaluated Attitude toward not needing to know the cause of back pain to manage it effectively. There was a strong inverse association between each factor and the Back Beliefs Questionnaire and a moderate positive association with the modified Pain Self-Efficacy Questionnaire. Each independent factor demonstrated acceptable internal consistency; Cronbach α Factor 1 = 0.92, Factor 2 = 0.91, Factor 3 = 0.90 and adequate interclass correlation coefficients; Factor 1 = 0.71, Factor 2 = 0.73, Factor 3 = 0.79. Conclusion: This study demonstrates acceptable construct validity and reliability of the AxEL-Q, providing clinicians with an insight into the likelihood of patients following first-line care at the outset.