Journal of Evaluation in Clinical Practice

Portuguese version of the Medication Adherence Report Scale (MARS‐9): Validation in a population of chronic pain patients

Early View

  • Author(s): Rute Sampaio, Luís Filipe Azevedo, Cláudia Camila Dias, Rob Horne, José M. Castro Lopes
  • Article first published online: 16 Jan 2019
  • DOI: 10.1111/jep.13098
  • Read on Online Library
  • Subscribe to Journal

Abstract Aim The aim of present study was to perform the translation, cultural adaptation, and validation of the Medication Adherence Report Scale (MARS‐P9) for the European Portuguese language in a sample of chronic pain patients. Methods A Portuguese version of the nine‐item MARS (©Professor Rob Horne) scale (MARS‐P9) was constructed through a process of translation, back translation, and experts' panel evaluation. A total of 141 chronic pain patients were subsequently evaluated at four time assessments during a 1‐year pain medication treatment. The protocol interview included the assessment of pain intensity and interference (BPI), clinical outcomes and quality of life (S‐TOPS), and MARS‐P9. Results The internal consistency coefficient was acceptable for the total scale (α = 0.84). Exploratory factor analysis revealed a two‐factor structure (intentional and unintentional nonadherence) that explained 61% of the variance. Convergent and discriminant validity were demonstrated by correlations between MARS scores and pain interference (r = 0.180, P ≤ 0.01) and S‐TOPS (r = 0.242, P ≤ 0.05). Conclusion MARS‐P9 has been shown to be an adequate instrument for Portuguese researchers and clinicians to assess the pattern of adherence during the management of chronic pain.

Related Topics

Related Publications

Related Content

Site Footer

Biostatistics

Topics:

Business & Economics

Topics:

Engineering

Topics:

Environmental

Topics:

Methods

Topics:

Social Sciences

Topics:

Tools

Address:

This website is provided by John Wiley & Sons Limited, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ (Company No: 00641132, VAT No: 376766987)

Published features on StatisticsViews.com are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and StatisticsViews.com express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.