Background: In recent years, the effectiveness and cost-effectiveness of digital health services for people with musculoskeletal conditions have increasingly been studied and show potential. Despite the potential of digital health services, their use in primary care is lagging. A thorough implementation is needed, including the development of implementation strategies that potentially improve the use of digital health services in primary care. The first step in designing implementation strategies that fit the local context is to gain insight into determinants that influence implementation for patients and health care professionals. Until now, no systematic overview has existed of barriers and facilitators influencing the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Objective: This systematic literature review aims to identify barriers and facilitators to the implementation of digital health services for people with musculoskeletal conditions in the primary health care setting. Methods: PubMed, Embase, and CINAHL were searched for eligible qualitative and mixed methods studies up to March 2024. Methodological quality of the qualitative component of the included studies was assessed with the Mixed Methods Appraisal Tool. A framework synthesis of barriers and facilitators to implementation was conducted using the Consolidated Framework for Implementation Research (CFIR). All identified CFIR constructs were given a reliability rating (high, medium, or low) to assess the consistency of reporting across each construct. Results: Overall, 35 studies were included in the qualitative synthesis. Methodological quality was high in 34 studies and medium in 1 study. Barriers (–) of and facilitators (+) to implementation were identified in all 5 CFIR domains: “digital health characteristics” (ie, commercial neutral [+], privacy and safety [–], specificity [+], and good usability [+]), “outer setting” (ie, acceptance by stakeholders [+], lack of health care guidelines [–], and external financial incentives [–]), “inner setting” (ie, change of treatment routines [+ and –], information incongruence (–), and support from colleagues [+]), “characteristics of the healthcare professionals” (ie, health care professionals’ acceptance [+ and –] and job satisfaction [+ and –]), and the “implementation process” (involvement [+] and justification and delegation [–]). All identified constructs and subconstructs of the CFIR had a high reliability rating. Some identified determinants that influence implementation may be facilitators in certain cases, whereas in others, they may be barriers. Conclusions: Barriers and facilitators were identified across all 5 CFIR domains, suggesting that the implementation process can be complex and requires implementation strategies across all CFIR domains. Stakeholders, including digital health intervention developers, health care professionals, health care organizations, health policy makers, health care funders, and researchers, can consider the identified barriers and facilitators to design tailored implementation strategies after prioritization has been carried out in their local context
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Purpose: To systematically review the literature on effectiveness of remote physiotherapeutic e-Health interventions on pain in patients with musculoskeletal disorders. Materials and methods: Using online data sources PubMed, Embase, and Cochrane in adults with musculoskeletal disorders with a pain-related complaint. Remote physiotherapeutic e-Health interventions were analysed. Control interventions were not specified. Outcomes on effect of remote e-Health interventions in terms of pain intensity. Results: From 11,811 studies identified, 27 studies were included. There is limited evidence for the effectiveness for remote e-Health for patients with back pain based on five articles. Twelve articles studied chronic pain and the effectiveness was dependent on the control group and involvement of healthcare providers. In patients with osteoarthritis (five articles), total knee surgery (two articles), and knee pain (three articles) no significant effects were found for remote e-Health compared to control groups. Conclusions: There is limited evidence for the effectiveness of remote physiotherapeutic e-Health interventions to decrease pain intensity in patients with back pain. There is some evidence for effectiveness of remote e-Health in patients with chronic pain. For patients with osteoarthritis, after total knee surgery and knee pain, there appears to be no effect of e-Health when solely looking at reduction of pain. Implications for rehabilitation This review shows that e-Health can be an effective way of reducing pain in some populations. Remote physiotherapeutic e-Health interventions may decrease pain intensity in patients with back pain. Autonomous e-Health is more effective than no treatment in patients with chronic pain. There is no effect of e-Health in reduction of pain for patients with osteoarthritis, after total knee surgery and knee pain.Implications for rehabilitation* This review shows that e-Health can be an effective way of reducing pain in some populations.* Remote physiotherapeutic e-Health interventions may decrease pain intensity in patients with back pain.* Autonomous e-Health is more effective than no treatment in patients with chronic pain.* There is no effect of e-Health in reduction of pain for patients with osteoarthritis, after total knee surgery and knee pain.
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Background: Healthcare practitioner beliefs influence patients’ beliefs and health outcomes in musculoskeletal (MSK) pain. A validated questionnaire based on modern pain neuroscience assessing Knowledge and Attitudes ofPain (KNAP) was unavailable.Objectives: The aim of this study was to develop and test measurement properties of KNAP.Design: Phase 1; Development of KNAP reflecting modern pain neuroscience and expert opinion. Phase 2; a crosssectional and longitudinal study among Dutch physiotherapy students.Method: In the cross-sectional study (n = 424), internal consistency, structural validity, hypotheses testing, and Rasch analysis were examined. Longitudinal designs were applied to analyse test-retest reliability (n = 156), responsiveness, and interpretability (n = 76).Results: A 30-item KNAP was developed in 4 stages. Test-retest reliability: ICC (2,1) 0.80. Internal consistency: Cronbach’s α 0.80. Smallest Detectable Difference 90%: 4.99 (4.31; 5.75). Structural validity: exploratory factor analysis showed 2 factors. Hypotheses testing: associations with the Pain Attitudes and Beliefs Scale for Physiotherapists biopsychosocial subscale r = 0.60, with biomedical subscale r = 0.58, with the Neurophysiology of Pain Questionnaire r = 0.52. Responsiveness: 93% improved on KNAP after studying pain education. MinimalImportant Change: 4.84 (95%CI: 2.77; 6.91).Conclusions: The KNAP has adequate measurement properties. This new questionnaire could be useful to evaluate physiotherapy students’ knowledge and attitudes of modern pain neuroscience that could help to create awareness and evaluate physiotherapy education programs, and ultimately provide better pain management.
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Achtergrond: Chronische pijn is een veelvoorkomend probleem. Hulpverleners hebben behoefte aan handvatten om de hulp aan mensen met chronische pjjn te verbeteren. Huidige behandelingen sorteren beperkt effect en de waardering van mensen over de ontvangen zorg is matig. Het faciliteren van betrokkenheid en eigen regie zijn voorwaardelijk voor effectieve hulp. EHealth toepassingen inclusief het monitoren van objectieve biomarkers voor pijn kunnen hierbij behulpzaam zijn. Een bestaande EHealth toepassing gericht op het informeren van mensen met een chronische aandoening en het faciliteren van zelfmanagement is beschikbaar. Doelstelling: 1)Het doorontwikkelen van een bestaande EHealth toepassing specifiek voor mensen met chronische pijn en het evalueren van biomarkers. 2)De ontwikkelde EHealth toepassing inclusief biomarkeranalyse te implementeren bij een beperkte groep van mensen met chronische musculoskeletale pijn om eerste effecten te evalueren en gebruikerservaringen te inventariseren en 3)op basis van de verkregen resultaten een vervolg onderzoeksaanvraag te schrijven om de effecten van deze nieuwe behandelwijze te onderzoeken en nieuwe biomarker-testen te ontwikkelen. Vraagstellingen: 1)Hoe ziet de doorontwikkeling (op basis van co-creatie) van de EHealth toepassing er concreet uit? 2)Is de biomarker α-amylase een objectieve maat voor pijnintensiteit? 3)Wat zijn de eerste effecten van deze EHealth applicatie? (uitkomstmaten zijn pijn, α-amylase concentratie, dagelijks functioneren en kwaliteit van leven) 4)Wat zijn de ervaringen van gebruikers (patiënten en hulpverleners)? Aanpak: Het onderzoek wordt uitgevoerd door een consortium van deskundigen op het gebied van niet-farmaceutische behandeling van mensen met chronische pijn en zelfmanagement, de ontwikkeling en het gebruik van biomarkers voor chronische pijn, een EHealth ontwikkelaar en behandelaren van mensen met chronische pijn en patiënten. Een EHealth toepassing wordt ontwikkeld, biomarkers waaronder α-amylase worden geëvalueerd en de eerste effecten en gebruikerservaringen van deze interventie inclusief biomarkerbepaling worden gemonitord in een populatie van mensen met chronische lage rug en/of nekpijn.
De fysiotherapie staat onder toenemende druk, daarom is er een noodzaak om de zorg effectiever en efficienter in te richten. Dit project onderzoekt of de toepassing van technologieën als augmented videoconferencing (integratie van sensoren in videoconsulten) de fysiotherapiebehandeling effectiever en efficiënter kan maken.
Movebite aims to combat the issue of sedentary behavior prevalent among office workers. A recent report of the Nederlandse Sportraad reveal a concerning trend of increased sitting time among Dutch employees, leading to a myriad of musculoskeletal discomforts and significant health costs for employers due to increased sick leave. Recognizing the critical importance of addressing prolonged sitting in the workplace, Movebite has developed an innovative concept leveraging cutting-edge technology to provide a solution. The Movebite app seamlessly integrates into workplace platforms such as Microsoft Teams and Slack, offering a user-friendly interface to incorporate movement into their daily routines. Through scalable AI coaching and real-time movement feedback, Movebite assists individuals in scheduling and implementing active micro-breaks throughout the workday, thereby mitigating the adverse effects of sedentary behavior. In collaboration with the Avans research group Equal Chance on Healthy Choices, Movebite conducts user-centered testing to refine its offerings and ensure maximum efficacy. This includes testing initiatives at sports events, where the diverse crowd provides invaluable feedback to fine-tune the app's features and user experience. The testing process encompasses both quantitative and qualitative approaches based on the Health Belief Model. Through digital questionnaires, Movebite aims to gauge users' perceptions of sitting as a health threat and the potential benefits of using the app to alleviate associated risks. Additionally, semi-structured interviews delve deeper into user experiences, providing qualitative insights into the app's usability, look, and feel. By this, Movebite aims to not only understand the factors influencing adoption but also to tailor its interventions effectively. Ultimately, the goal is to create an environment encouraging individuals to embrace physical activity in small, manageable increments, thereby fostering long-term engagement promoting overall well-being.Through continuous innovation and collaboration with research partners, Movebite remains committed to empowering individuals to lead healthier, more active lifestyles, one micro-break at a time.
