Received 3 June 2016; accepted 30 July 2016; published 2 August 2016
Reduced physical function resulting from impairments associated with conditions such as stroke, brain injury, amputations and hip fracture is common. Engagement in therapeutic activities during rehabilitation can improve physical function if practice is task specific, repetitive and intensive   . Extrinsic augmented feedback about performance can improve physical function by enhancing motor learning   . Many technologies provide extrinsic feedback to users about their performance and practice completed. This feedback may facilitate engagement and increase the dose of repetitive exercise completed during rehabilitation. Feedback-based technologies are becoming more affordable and accessible, making them viable for use in rehabilitation settings to train physical function and promote physical activity. These technologies include virtual reality systems which provide users with feedback about movement in simulated or real life environments, and games (e.g. CAREN, Motekforce Link, Amsterdam, The Netherlands; Nintendo Wii, Nintendo, Kyoto, Japan), wearable devices which provide feedback about movement (e.g. step count from a Fitbit activity monitor, Fitbit Inc., San Francisco, California, USA), and biofeedback devices which provide feedback about unconscious physiological processes (e.g. centre of pressure/mass from a force platform).
A systematic review of qualitative studies exploring patient experiences of using feedback-based technology in rehabilitation is proposed. The primary aim of this review will be to identify and synthesise the findings of qualitative studies that explore the experience of adults who have used feedback-based technologies in physical rehabilitation. A secondary aim will be to build a new theory or theories to better understand and explain how technology can enhance skill acquisition and motivate patients to achieve the high dose of exercise associated with improved physical outcomes. This review also has the potential to assist with user-focused technology development. The review will explore characteristics of studies to identify any conditions and/or criteria that influence patient experiences, for example, the setting, diagnosis, age or types of technologies. In addition, the review aims to identify any gaps in knowledge and inform the direction of future qualitative research. The outcomes in this review will be restricted to physical function. A parallel review is being conducted by the authors on therapists’ experiences of using feedback-based technology in rehabilitation (Prospero Registration number: CRD42015020271).
The study design is a meta-synthesis of qualitative studies, comprising the following steps: 1) a systematic search of 10 electronic databases and grey literature, and hand searching of reference lists of included studies, 2) screening of search results and study selection, 3) data extraction, 4) quality appraisal of the included studies using the Critical Appraisal Skills Programme (CASP) checklist  , and 5) qualitative synthesis to identify common themes and concepts across studies. The review protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO) on 27 February 2015 and last updated on 7 December 2015 [Registration number: CRD42015017119]. Any protocol amendments will be tracked and include the date of each amendment, description of the change and the rationale. The Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) statement  will be used for reporting study methods and results.
2.2. Eligibility Criteria
The focus of the review is on the experience of adults who have used feedback-based technology to improve their physical function during rehabilitation. Studies will be judged for relevance according to the eligibility criteria outlined in Table 1. Studies will be excluded for the following reasons: 1) conference proceedings, 2) technology is used for other rehabilitative purposes, such as the provision of information/education, assessment, maintenance of records, as a medium to provide therapy (e.g. tele-health) or as an assistive device, 3) technology is used for improving other functions such as cognition, vision and pain and 4) report is on the experiences of caregivers, family members or therapists rather than the experiences of the adult/s participating in rehabilitation.
2.3. Study Identification
2.3.1. Information Sources
Ten electronic databases will be searched including: MEDLINE, CINAHL, Web of Science Core Collection, AMED, PsycINFO, EMBASE, OTseeker, PEDro, COMPENDEX and IEEEXplore. Grey literature sources will include theses and dissertations and will be searched using the following electronic sources: ProQuest Dissertation & Theses Full Text, British Library Electronic Digital Thesis Online Service (EThOS), and DART-Europe E-theses Portal. Studies will also be identified by searching the reference lists of included studies and contacting the first author of each identified study to ask if they are aware of any other published studies.
2.3.2. Search Strategy
A search strategy has been developed initially for Medline (Table 2) and will be adapted for each database in
Table 1. Eligibility criteria.
Table 2. Search strategy for medline.
“Population” search terms will include people participating as patients in aged-care or neurological rehabilitation as inpatients or non-inpatients. “Intervention” search terms will be separated into three concepts: “technology”, “physical therapies and modalities” and “physical rehabilitation interventions”. The three concepts will be combined with Boolean operators as follows: “technology” AND (“physical therapies and modalities” OR “physical rehabilitation interventions”).
The “technology” search terms will include a range of feedback-based technologies that patients may use to improve their physical function, including video and computer-based exercises and games, activity monitors, computer or phone devices and applications and biofeedback devices. “Physical therapies and modalities” search terms will include the main physical therapies and modalities that are used in rehabilitation, for example in physiotherapy, occupational therapy and exercise therapy. “Physical rehabilitation interventions” search terms will include the purpose of using technologies in rehabilitation, and use terms that are the focus of physical rehabilitation interventions such as exercise, physical activity, balance, strength, motor skills, walking, standing and reaching. The “outcomes of interest” search terms will include those used to describe or report on the experiences of using technology, for example experiences, perceptions, attitudes, beliefs, acceptance and adoption, barriers and facilitators.
2.4. Selection of Studies
Libraries will be created for search results retrieved from each database using Endnote, a reference management software package. Each library will be combined to form one master library in Endnote. Duplicate studies will be removed in Endnote as the libraries are combined. The selection of studies for the review will follow a three-stage process of initial exclusion, screening and final selection.
2.5. Risk of Bias (Quality) Assessment
Studies included in the review will be appraised for methodological quality and trustworthiness to determine their significance to the review question. Studies will be assessed using The Critical Appraisal Skills Programme toolkit for qualitative studies (CASP)  . Items on the checklist will be independently assessed for their presence in each of the studies by two reviewers (CH and ML). Any discrepancies in appraisal will be resolved through discussion between review team members.
2.6. Data Extraction
Data relevant to the aims of this review only will be extracted. For example, data reported in studies that relate to effectiveness of an intervention will not be extracted. Data extraction will be undertaken independently by two reviewers (CH and ML). Extracted data will be compared and discrepancies resolved through discussion with other team members (AM and LH).
A template will be used to extract variables of relevance. We will extract general information (year of publication, country, type of publication, type of study), participant characteristics (number, average age, gender, clinical diagnosis, eligibility criteria, time since injury/diagnosis, symptom/injury severity, ambulatory status, experience using technology prior to use in rehabilitation), details about the intervention (name of feedback- based technology, description of the technology and context of use, physical outcomes of interest, co-intervention (if applicable) and methods of the study (aim/s of the study, methodological approach, sampling method, data collection methods, data analysis). A pilot trial of data extraction will be undertaken using a template. Study authors will be contacted to provide any missing or additional data required.
Text data will be extracted about the experiences of using feedback-based technology, that is, experiences of learning, practicing, progressing, accepting and adopting, as well as barriers and facilitators to use. Relevant data including study participant quotes and the author’s interpretations provided in the findings, results, discussion or conclusion sections identified in the primary studies will be extracted. Text will be imported into NVivo10, a computer assisted qualitative data analysis software package, to assist data synthesis.
2.7. Data Synthesis
Data synthesis will take an inductive approach and be undertaken by at least two reviewers (CH and AM or ML). Data will be coded for content, then categorised into more focused themes based on our review question to identify patient experiences. Similarities and differences in the study findings will be compared, and links/relation- ships with the themes evident in patient experiences made in order to integrate the data and develop new insights. The heterogeneity of included studies based on theoretical or contextual differences will also be considered during this process.
Subgroup analysis will be undertaken if studies are sufficiently homogeneous. Sub-group analyses may explore differences in terms of clinical diagnosis (neurological compared to non-neurological), participant characteristics (age, gender), type of technology (commercially available virtual reality systems, customised virtual reality systems, wearable devices, biofeedback devices) and the context of technology use (hospital-based, home- based, community-based rehabilitation).
We would like to thank Elaine Tam, Academic Liaison Librarian at The University of Sydney for her assistance in the development of the search strategy.
CH is supported by a PhD scholarship from an Australian National Health and Medical Research Council Project Grant (APP1063751).