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1000
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Abstract/Summary
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Purpose: This study examines congruence between self-reported and device-measured physical activity data in women with early breast cancer and compares trajectories under different treatments. Methods: Women with non-metastatic breast cancer were recruited before primary therapy. In four weeks distributed over six months after treatment start, patients reported time spent on work, transport, chores and sports via diary and wore Garmin super R vivofit 3 accelerometers to assess steps taken. Associations between these measures and agreement regarding guideline adherence were tested with Spearman's Correlation Coefficient and Weighted Kappa statistic. Effects of time and treatment were evaluated using mixed analyses of variance. Results: Ninety-nine participants (median age = 50) were treated with adjuvant (N= 23), neoadjuvant (N= 21) or without chemotherapy (N= 55). Coherence between self-report and device data was strong (r = 0.566). Agreement about reaching recommendations was only 'fair' (kappa coefficient = 0.321 and 0.249, resp.). Neither treatment or week nor their interaction had effects on step counts (all p > 0.05). Self-reported activity time was lower for patients with chemotherapy than for those without (adjuvant: increment = 69min, p= 0.006, neoadjuvant: increment = 45min, p= 0.038) and lower in week 18 than in week 3 ( increment = 43min, p= 0.010). Conclusion: Results show that consumer-grade activity monitors and self-reports correlate but show different perspectives on physical activity in breast cancer patients. In general, patients perceive some decline regardless of primary treatment regimen. Those affected should be offered assistance to gain the benefits of activity. Accelerometers may help professionals to identify these individuals and patients to verify appraisal of their activity levels.
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1000
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Hinweis
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DeepGreen-ID: c63275356795454ca67b75312849c57d ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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