eHealth Interventions to Support Self-Management in People With Musculoskeletal Disorders, "eHealth: It's TIME"-A Scoping Review

eHealth interventions to support self-management: Perceptions and experiences of people with musculoskeletal disorders and physiotherapists - 'eHealth: It's TIME': A qualitative study

BACKGROUND

There is increasing interest in the potential role of eHealth interventions to support self-management in people with musculoskeletal disorders (MSDs). The COVID-19 pandemic appears to have been a significant catalyst for the implementation of eHealth modalities into routine practice, providing a unique opportunity for real-world evaluation of this underutilized method of delivering physiotherapy.

OBJECTIVE

To explore the perceptions of eHealth-mediated supported self-management from the perspective of people with MSDs and physiotherapists who work in this clinical area.

METHODS

A qualitative interpretive descriptive approach was used. Semi-structured telephone interviews with 13 musculoskeletal physiotherapists and 13 people with musculoskeletal disorders were undertaken. Transcripts were analyzed using reflexive thematic analysis.

RESULTS

Three main themes were identified: 1) Flexibility within a blended care model; 2) eHealth as a facilitator of self-management support; and 3) Technology: Getting it right. Participants expressed concerns about assessment and diagnosis, establishing a therapeutic relationship and felt eHealth should be reserved for follow-up purposes. There was a consistent view expressed that eHealth could facilitate aspects of self-management support. A lack of resources and suboptimal user experience remains a challenge.

CONCLUSIONS

eHealth-mediated self-management support interventions were broadly acceptably, predominately as a follow-up option.

Shifting Responsibilities: Developing a Pan-European Service Model for an eHealth Technology Supporting Self-Management of People with Chronic Obstructive Pulmonary Disease and Comorbidities

Introduction

Active participation of patients in their care via self-management is an important pillar to manage chronic conditions. Self-management education and continuous support are needed to improve patients' confidence to take such active role. One way to do this is through eHealth technologies. However, those technologies can only be successful when actively used in daily practice and when integrated in overall care. Therefore, this study investigated how a self-management eHealth technology could be implemented that emphasises the active role of patients in their care.

Methods

The service modelling method was utilized as implementation strategy. The design process consisted of five phases with salient stakeholders and consortium members of a European project to develop the service model. Studies with salient stakeholders were carried out in three different countries (Italy, Estonia, the Netherlands). A combination between face-to-face and online methods facilitated the participatory design process.

Results

Due to the pan-European context, different stakeholders in the three countries were identified. Research nurses and case managers were not yet established in practice but once implemented, expected to contribute to optimal implementation. During service modelling, a crucial step was revealed: providing self-management training before technology use to let patient familiarise with the concept of taking an active role. As HCPs felt that they were not necessarily equipped to guide patients in terms of self-management, they also should have access to such self-management training.

Conclusion

By demonstrating a way for implementation while emphasising patients' active role, we also showed the complexity of the method in two ways. First, by demonstrating the fine line between the descriptive and prescriptive model. Thus, showcasing the need to recognize that prescriptive models may be hampered by the delay in changing work practices. Second, by highlighting the importance of identifying country-specific differences in the pan-European context, revealing that service modelling is not a one-size-fits-all approach.

The Association of Technology-Based Ageism with Using Digital Technology in Physical Therapy for Older Persons

Integrating digital technologies in healthcare for older adults can enhance their independence and quality of life. Nevertheless, ageism among healthcare professionals impacts treatment decisions and may deprive older patients of technology-based treatment. This study explores whether technology-specific ageism influenced physiotherapists' use of technology-based healthcare with older patients. Seventy-eight physiotherapists in Luxembourg filled out an online survey. Participants filled out the Attitudes Towards Older Adults Using Technology (ATOAUT-11) scale, Expectations Regarding Aging, attitudes towards technology use in the work environment, and whether they had not offered technology-based treatment in the past because of a patient's age. Using logistic regression, negative ATOAUT was found to predict not offering technology-based treatment, such that participants with more negative attitudes (1 standard deviation) were two times more likely not to offer treatment. Positive attitudes towards using technology in the work environment were also found to be a significant predictor. All other characteristics (gender, age, experience and percentage of patients over 50) were not predictive of not offering treatment. This study demonstrates that technology-specific ageism may lead to discrimination and deprive older persons of optimal treatment. More research is needed to identify the magnitude of ageism in using technology-based treatment and develop interventions to overcome it.

Design and development of an eHealth intervention to support self-management in people with musculoskeletal disorders - 'eHealth: It's TIME': a study protocol

Background: Musculoskeletal disorders (MSDs) are a leading cause of global morbidity, with the burden expected to increase in the near future. Self-management, with the support of healthcare professionals, is recommended for many MSDs. However, frequent clinical contact is not feasible. Previous research has highlighted the need for a co-designed eHealth-mediated self-management follow-up support intervention which integrates remote monitoring and behavioural change. Thus, the current study aims to develop and design a user-centred, eHealth-mediated self-management support prototype for people with MSDs. Methods: A three-step, iterative system development cycle will be utilised to develop and design the "eHealth: It's TIME prototype". The three-step process will include creating website features and content using two sequential focus groups with people with MSDs (n = 6 - 8); heuristic testing using the 10 heuristic principles of Nielsen (n = 5); and usability testing through in-person 60-minute interviews with people with MSDs (n = 3 - 5) and musculoskeletal physiotherapists (n = 3 - 5). Conclusion: The eHealth: It's TIME prototype will be a systematically developed, follow-up self-management support intervention guided by behavioural change theory and the preferences of end users.

Psychologically Informed Practice: The Importance of Communication in Clinical Implementation

There has been increasing interest in the secondary prevention of chronic pain and pain-associated disability over the past 3 decades. In 2011, psychologically informed practice (PiP) was suggested as a framework for managing persistent and recurrent pain, and, since then, it has underpinned the development of stratified care linking risk identification (screening). Although PiP research trials have demonstrated clinical and economic advantage over usual care, pragmatic studies have been less successful, and qualitative studies have identified implementation difficulties in both system delivery and individual clinical management. Effort has been put into the development of screening tools, the development of training, and the assessment of outcomes; however, the nature of the consultation has remained relatively unexplored. In this Perspective, a review of the nature of clinical consultations and the clinician-patient relationship is followed by reflections on the nature of communication and the outcome of training courses. Consideration is given to the optimization of communication, including the use of standardized patient-reported measures and the role of the therapist in facilitating adaptive behavior change. Several challenges in implementing a PiP approach in day-to-day practice are then considered. Following brief consideration of the impact of recent developments in health care, the Perspective concludes with a brief introduction to the PiP Consultation Roadmap (the subject of a companion paper), the use of which is suggested as a way of structuring the consultation with the flexibility required for a patient-centered approach to guided self-management of chronic pain conditions.

What we know about fatigue self-management programs for people living with chronic conditions: A scoping review

OBJECTIVE

The significant impact of fatigue on the lives of patients with chronic conditions has demanded a response. One response has been the development and testing of self-management programs. Little is known about what these programs have in common or how they differ. This scoping review compared the key components of fatigue self-management programs.

METHODS

Scoping review methodology was employed. Databases of CINAHL, Academic Search Premier, PsycINFO, Cochrane and Medline were searched to identify relevant sources.

RESULTS

Included fatigue programs were compared using a three-component framework: 1) self-management strategies; 2) active patient participation; and 3) self-management support. Although all programs included some aspects of these components, the extent varied with only a few domains of these components found across all programs.

CONCLUSION

The three self-management components employed in this study showed potential benefits in identifying similarities and differences across fatigue programs with comparable and distinct underlying theories. This three-component framework could facilitate identification of domains associated with positive outcomes.

PRACTICE IMPLICATIONS

It is essential that authors of programs provide detailed descriptions to enable inter-program comparison. The three-component framework chosen for this review was capable of describing and comparing fatigue self-management programs, paving the way for more effective interventions.

Non-pharmacological interventions for self-management of fatigue in adults: An umbrella review of potential interventions to support patients recovering from critical illness

PURPOSE

Fatigue is a common symptom after critical illness. However, evidence-based interventions for fatigue after critical illness are lacking. We aimed to identify interventions to support self-management of fatigue caused by physical conditions and assess their effectiveness and suitability for adaptation for those with fatigue after critical illness.

MATERIALS AND METHODS

We conducted an umbrella review of systematic reviews. Databases included CINAHL, PubMed, Medline, PsycINFO, British Nursing Index (BNI), Web of Science, Cochrane Database of Systematic Reviews (CDSR), JBI Evidence Synthesis Database, and PROSPERO register. Included reviews were appraised using the JBI Checklist for Systematic Reviews and Research Syntheses. Results were summarised narratively.

RESULTS

Of the 672 abstracts identified, 10 met the inclusion criteria. Reviews focused on cancer (n = 8), post-viral fatigue (n = 1), and Systemic Lupus Erythematosus (SLE) (n = 1). Primary studies often did not address core elements of self-management. Positive outcomes were reported across all reviews, and interventions involving facilitator support appeared to be most effective.

CONCLUSIONS

Self-management can be effective at reducing fatigue symptoms and improving quality of life for physical conditions and has clear potential for supporting people with fatigue after critical illness, but more conclusive data on effectiveness and clearer definitions of self-management are required.

Design and development of an eHealth intervention to support self-Management in people with musculoskeletal Disorders - ‘eHealth: It’s TIME’: a study protocol

Background: Musculoskeletal disorders (MSDs) are a leading cause of global morbidity, with the burden expected to increase in the near future. Self-management, with the support of healthcare professionals, is recommended for many MSDs. However, frequent clinical contact is not feasible. Previous research has highlighted the need for a co-designed eHealth-mediated self-management follow-up support intervention which integrates remote monitoring and behavioural change. Thus, the current study aims to develop and design a user-centred, eHealth-mediated self-management support prototype for people with MSDs. Methods: A three-step, iterative system development cycle will be utilised to develop and design the “eHealth: It’s TIME prototype”. The three-step process will include creating website features and content using two sequential focus groups with people with MSDs (n = 6 – 8); heuristic testing using the 10 heuristic principles of Nielsen (n = 5); and usability testing through in-person 60-minute interviews with people with MSDs (n = 3 – 5) and musculoskeletal physiotherapists (n = 3 – 5). Conclusion: The eHealth: It’s TIME prototype will be a systematically developed, follow-up self-management support intervention guided by behavioural change theory and the preferences of end users.

The effectiveness of eHealth self-management interventions in patients with chronic heart failure: Protocol for a systematic review and meta-analysis

Purpose

The objective of this paper is to design a protocol for a systematic review and meta-analysis on the effectiveness of self-management interventions in patients with chronic heart failure.

Methods

The protocol is developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol has been registered in PROSPERO (CRD42021246973). Base on the population, intervention, comparator, and outcome (PICO) framework, our research questions are: 1) What are the effects of eHealth self-management interventions on patients with chronic heart failure? 2) What factors of interventions might affect outcomes? The process includes: 1) search strategy and inclusion criteria; 2) data extraction; 3) risk of bias assessment and 4) data analysis. Searching process and data extraction will be guided by Cochrane Handbook for Systematic Reviews of Interventions. We will use Cochrane Risk of Bias tool to assess the risk of bias. The data analysis will be performed using Metafor package in R.

Conclusions

This systemic review will synthesize the current evidence and identify gaps. Findings in the meta-analysis will provide guidance for designing a more effective self-management intervention for patients with chronic heart failure in future.

Consumers’ Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis

Background

Despite the great potential of eHealth, substantial costs are involved in its implementation, and it is essential to know whether these costs can be justified by its benefits. Such needs have led to an increased interest in measuring the benefits of eHealth, especially using the willingness to pay (WTP) metric as an accurate proxy for consumers’ perceived benefits of eHealth. This offered us an opportunity to systematically review and synthesize evidence from the literature to better understand WTP for eHealth and its influencing factors.

Objective

This study aimed to provide a systematic review of WTP for eHealth and its influencing factors.

Methods

This study was performed and reported as per the Cochrane Collaboration and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, CINAHL Plus, Cochrane Library, EconLit, and PsycINFO databases were searched from their inception to April 19, 2022. We conducted random-effects meta-analyses to calculate WTP values for eHealth (at 2021 US dollar rates) and meta-regression analyses to examine the factors affecting WTP.

Results

A total of 30 articles representing 35 studies were included in the review. We found that WTP for eHealth varied across studies; when expressed as a 1-time payment, it ranged from US $0.88 to US $191.84, and when expressed as a monthly payment, it ranged from US $5.25 to US $45.64. Meta-regression analyses showed that WTP for eHealth was negatively associated with the percentages of women (β=−.76; P<.001) and positively associated with the percentages of college-educated respondents (β=.63; P<.001) and a country’s gross domestic product per capita (multiples of US $1000; β=.03; P<.001). Compared with eHealth provided through websites, people reported a lower WTP for eHealth provided through asynchronous communication (β=−1.43; P<.001) and a higher WTP for eHealth provided through medical devices (β=.66; P<.001), health apps (β=.25; P=.01), and synchronous communication (β=.58; P<.001). As for the methods used to measure WTP, single-bounded dichotomous choice (β=2.13; P<.001), double-bounded dichotomous choice (β=2.20; P<.001), and payment scale (β=1.11; P<.001) were shown to obtain higher WTP values than the open-ended format. Compared with ex ante evaluations, ex post evaluations were shown to obtain lower WTP values (β=−.37; P<.001).

Conclusions

WTP for eHealth varied significantly depending on the study population, modality used to provide eHealth, and methods used to measure it. WTP for eHealth was lower among certain population segments, suggesting that these segments may be at a disadvantage in terms of accessing and benefiting from eHealth. We also identified the modalities of eHealth that were highly valued by consumers and offered suggestions for the design of eHealth interventions. In addition, we found that different methods of measuring WTP led to significantly different WTP estimates, highlighting the need to undertake further methodological explorations of approaches to elicit WTP values.