Teachers' and students' perceptions on barriers and facilitators for eHealth education in the curriculum of functional exercise and physical therapy: a focus groups study.

BACKGROUND: Despite the growing importance of eHealth it is not consistently embedded in the curricula of functional exercise and physical therapy education. Insight in barriers and facilitators for embedding eHealth in education is required for the development of tailored strategies to implement eHealth in curricula. This study aims to identify barriers/facilitators perceived by teachers and students of functional exercise/physical therapy for uptake of eHealth in education. METHODS: A qualitative study including six focus groups (two with teachers/four with students) was conducted to identify barriers/facilitators. Focus groups were audiotaped and transcribed in full. Reported barriers and facilitators were identified, grouped and classified using a generally accepted framework for implementation including the following categories: innovation, individual teacher/student, social context, organizational context and political and economic factors. RESULTS: Teachers (n = 11) and students (n = 24) of functional exercise/physical therapy faculties of two universities of applied sciences in the Netherlands participated in the focus groups. A total of 109 barriers/facilitators were identified during the focus groups. Most related to the Innovation category (n = 26), followed by the individual teacher (n = 22) and the organization (n = 20). Teachers and students identified similar barriers/facilitators for uptake of eHealth in curricula: e.g. unclear concept of eHealth, lack of quality and evidence for eHealth, (lack of) capabilities of students/teachers on how to use eHealth, negative/positive attitude of students/teachers towards eHealth. CONCLUSION: The successful uptake of eHealth in the curriculum of functional exercise/physical therapists needs a systematic multi-facetted approach considering the barriers and facilitators for uptake identified from the perspective of teachers and students. A relatively large amount of the identified barriers and facilitators were overlapping between teachers and students. Starting points for developing effective implementation strategies can potentially be found in those overlapping barriers and facilitators. REGISTRATION: The study protocol was a non-medical research and no registration was required. Participants gave written informed consent.

Why the uptake of eRehabilitation programs in stroke care is so difficult-a focus group study in the Netherlands.

BACKGROUND: The uptake of eRehabilitation programs in stroke care is insufficient, despite the growing availability. The aim of this study was to explore which factors influence the uptake of eRehabilitation in stroke rehabilitation, among stroke patients, informal caregivers, and healthcare professionals. METHODS: A qualitative focus group study with eight focus groups (6-8 participants per group) was conducted: six with stroke patients/informal caregivers and two with healthcare professionals involved in stroke rehabilitation (rehabilitation physicians, physical therapists, occupational therapists, psychologists, managers). Focus group interviews were audiotaped, transcribed in full, and analyzed by direct content analysis using the implementation model of Grol. RESULTS: Thirty-two patients, 15 informal caregivers, and 13 healthcare professionals were included. A total of 14 influencing factors were found, grouped to 5 of the 6 levels of the implementation model of Grol (Innovation, Organizational context, Individual patient, Individual professional, and Economic and political context). Most quotes of patients, informal caregivers, and healthcare professionals were classified to factors at the level of the Innovation (e.g., content, attractiveness, and feasibility of eRehabilitation programs). In addition, for patients, relatively many quotes were classified to factors at the level of the individual patient (e.g., patients characteristics as fatigue and the inability to understand ICT-devices), and for healthcare professionals at the level of the organizational context (e.g., having sufficient time and the fit with existing processes of care). CONCLUSION: Although there was a considerable overlap in reported factors between patients/informal caregivers and healthcare professionals when it concerns eRehabilitation as innovation, its seems that patients/informal caregivers give more emphasis to factors related to the individual patient, whereas healthcare professionals emphasize the importance of factors related to the organizational context. This difference should be considered when developing an implementation strategy for patients and healthcare professionals separately.

Adherence of stroke patients with an online brain training program: the role of health professionals' support.

Background Computer-based cognitive rehabilitation is used to improve cognitive functioning after stroke. However, knowledge on adherence rates of stroke patients is limited. Objective To describe stroke patients' adherence with a brain training program using two frequencies of health professionals' supervision. Methods This study is part of a randomized controlled trial comparing the effect of the brain training program (600 min playtime with weekly supervision) with a passive intervention in patients with self-perceived cognitive impairments after stroke. Patients randomized to the control condition were offered the brain training after the trial and received supervision twice (vs weekly in intervention group). Adherence was determined using data from the study website. Logistic regression analyses were used to examine the impact of supervision on adherence. Results 53 patients allocated to the intervention group (group S8; 64% male, mean age 59) and 52 patients who were offered the intervention after the trial (group S2; 59% male, mean age 59) started the brain training. The median playtime was 562 min (range 63-1264) in group S8 vs. 193 min (range 27-2162) in group S2 (p < 0.001, Mann Whitney U). Conclusions The overall adherence of stroke patients with a brain training was low and there are some implications that systematic, regular interaction with a supervisor can increase training adherence of stroke patients with a restitution-focused intervention performed at home.

The patient perspective on the use of information and communication technologies and e-health in rehabilitation.

INTRODUCTION: Success of e-health relies on the extent to which the related technology, such as the electronic device, is accepted by its users. However, there has been limited research on the patients' perspective on use of e-health-related technology in rehabilitation care. OBJECTIVE: To explore the usage of common electronic devices among rehabilitation patients with access to email and investigate their preferences regarding their usage in rehabilitation. METHODS: Adult patients who were admitted for inpatient and/or outpatient rehabilitation and were registered with an email address were invited to complete an electronic questionnaire regarding current and preferred use of information and communication technologies in rehabilitation care. RESULTS: 190 out of 714 invited patients completed the questionnaire, 94 (49%) female, mean age 49 years (SD 16). 149 patients (78%) used one or more devices every day, with the most frequently used devices were: PC/laptop (93%), smartphone (57%) and tablet (47%). Patients mostly preferred to use technology for contact with health professionals (mean 3.15, SD 0.79), followed by access to their personal record (mean 3.09, SD 0.78) and scheduling appointments with health professionals (mean 3.07, SD 0.85). CONCLUSION: Most patients in rehabilitation used one or more devices almost every day and wish to use these devices in rehabilitation. Implications for Rehabilitation In a sample of 190 patients in rehabilitation with access to email, almost all patients used one or more electronic devices almost every day of the week, with the most frequently used devices were: a PC/laptop, smartphone and tablet. Most of the patients wish to incorporate electronic devices in their rehabilitation process and prefer to use those devices to have insight in their health record, communication with peers and scheduling appointments with health professionals. To better assist patients with e-health in rehabilitation care in the future, preferences could be implemented in rehabilitation care by using the most commonly used devices.

The effects of an 8-week computer-based brain training programme on cognitive functioning, QoL and self-efficacy after stroke.

Cognitive impairment after stroke has a direct impact on daily functioning and quality of life (QoL) of patients and is associated with higher mortality and healthcare costs. The aim of this study was to determine the effect of a computer-based brain training programme on cognitive functioning, QoL and self-efficacy compared to a control condition in stroke patients. Stroke patients with self-perceived cognitive impairment were randomly allocated to the intervention or control group. The intervention consisted of an 8-week brain training programme (Lumosity Inc.®). The control group received general information about the brain weekly. Assessments consisted of a set of neuropsychological tests and questionnaires. In addition, adherence with trained computer tasks was recorded. No effect of the training was found on cognitive functioning, QoL or self-efficacy when compared to the control condition, except for very limited effects on working memory and speed. This study found very limited effects on neuropsychological tests that were closely related to trained computer tasks, but no transfers to other tests or self-perceived cognitive failures, QoL or self-efficacy. These findings warrant the need for further research into the value of computer-based brain training to improve cognitive functioning in the chronic phase after stroke.