Attributes Underlying Non-surgical Treatment Choice for People With Low Back Pain: A Systematic Mixed Studies Review
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 141
فایل این مقاله در 10 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_HPM-10-4_004
تاریخ نمایه سازی: 18 مرداد 1403
چکیده مقاله:
Background The knowledge of patients’ preferences in the medical decision-making process is gaining in importance. In this article we aimed to provide an overview on the importance of attributes underlying the choice of non-surgical treatments in people with low back pain (LBP). Methods A systematic mixed studies review was conducted. Articles were retrieved from the search engines PubMed, ScienceDirect, and Scopus through June ۲۱, ۲۰۱۸. The Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of the study, and each step was performed by ۲ reviewers. Analysis From a total of ۳۹۰ articles, ۱۳ were included in the systematic review, all of which were considered to be of good quality. Up to ۴۰ attributes were found in studies using various methods. Effectiveness, ie, pain reduction, was the most important attribute considered by patients in their choice of treatment. This attribute was cited by ۷ studies and was systematically ranked first or second in each. Other important attributes included the capacity to realize daily life activities, fit to patient’s life, and the credibility of the treatment, among others. Discussion Pain reduction was the most important attribute underlying patients’ choice for treatment. However, this was not the only trait, and future research is needed to determine the relative importance of the attributes.
کلیدواژه ها:
نویسندگان
Thomas G. Poder
School of Public Health, University of Montreal, Montreal, QC, Canada
Marion Beffarat
CERDI, Université Clermont Auvergne, ClermontFerrand, France
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :