An Evaluation of the Design of Multimedia Patient Education Materials in Musculoskeletal Health Care: Systematic Review.

Abstract

Background: Educational multimedia is a cost-effective and straightforward way to administer large-scale information interventions to patient populations in musculoskeletal health care. While an abundance of health research informs the content of these interventions, less guidance exists about optimizing their design.

Objective: This study aims to identify randomized controlled trials of patient populations with musculoskeletal conditions that used multimedia-based patient educational materials (PEMs) and examine how design was reported and impacted patients' knowledge and rehabilitation outcomes. Design was evaluated using principles from the cognitive theory of multimedia learning (CTML).

Methods: PubMed, CINAHL, PsycINFO, and Embase were searched from inception to September 2023 for studies examining adult patients with musculoskeletal conditions receiving multimedia PEMs compared to any other interventions. The primary outcome was knowledge retention measured via test scores. Secondary outcomes were any patient-reported measures. Retrievability was noted, and PEMs were sourced through search, purchase, and author communication.

Results: A total of 160 randomized controlled trials were eligible for inclusion: 13 (8.1%) included their educational materials and 31 (19.4%) required a web search, purchase, or direct requests for educational materials. Of these 44 (27.5%) studies, none fully optimized the design of their educational materials, particularly lacking in the CTML principles of coherence, redundancy, modality, and generative activities for the learner. Of the 160 studies, the remaining 116 (72.5%) contained interventions that could not be retrieved or appraised. Learning was evaluated in 5 (3.1%) studies.

Conclusions: Musculoskeletal studies should use open science principles and provide their PEMs wherever possible. The link between providing multimedia PEMs and patient learning is largely unexamined, but engagement potential may be maximized when considering design principles such as the CTML.