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Technology acceptance of the EXPERT tool for guideline-based exercise prescription is strongly influenced by the organizational context
No full textBackground
An impressive amount of evidence exists on the effectiveness of guideline-based exercise for cardiac rehabilitation and secondary prevention. Also, studies show that exercise prescriptions are sub-optimal and not compliant with ESC/EAPC exercise guidelines. Decision support systems (DSS) for guideline-based exercise prescription, such as the EAPC endorsed EXPERT tool, have the potential to implement the guidelines in daily practice in an accessible way. This follows the assumption that a DSS for exercise prescription is readily adopted in clinical practice.
Purpose
While the general usability of the EXPERT tool has iteratively been studied and improved, no former study investigated its associated technology acceptance. The current study hypothesized that the technology acceptance of a DSS is influenced by internal and external factors, and by perceived barriers.
Methods
The technology acceptance (TA) study was embedded in a study on exercise prescription compliance, and on the training effect of the EXPERT tool. The intervention in this prospective, non-randomized intervention study was a one-month training with the EXPERT tool. At baseline and post-intervention, prescription compliance for three fictive patient cases with different complexity, with the ESC/EAPC guidelines was assessed. At the same points in time, questionnaires on TA (a modified TAM questionnaire) including possible barriers for adoption of clinical DSS, were presented to the participants.
Results
The current data analysis focused on findings in 24 participants that completed the study with the EXPERT training tool, out of 122 initial participants. All of them were Belgian physiotherapists, with varying experience. 15 participants (62.5%) were female, and the majority (66.7%) was younger than 31. 15 participants (62.5%) worked in a hospital, 5 of them were also involved in a private practice. No significant differences were found in responses to the TA questionnaire before and after the intervention. Significant negative correlations were found between the employment in a hospital and the "Perceived usefulness" (p=0.001), "Perceived ease of use" (p=0.019), "Attitude" (p=0.002) and "Subjective norm" (p=0.007). "Technological infrastructure in the workplace" was ranked as the main external barrier to usage of a DSS for guideline-based exercise prescription. Next on the list were "Time", "Evidence on the effectiveness of the system", "Organizational structure" and "Compatibility with standards of practice". The highest ranked internal barrier was "Experience" followed by "Familiarity" and "Knowledge". 16 out of 24 participants (66.7%) indicated that they are not aware of existing clinical DSS.
Conclusion
The results reveal that organizational factors and barriers are more decisive to technology acceptance than individual beliefs or technological attributes of the DSS. Aligning organizational practices with ESC/EAPC guidelines is essential and should be ambitioned.Type of funding sources: Other. Main funding source(s): H2020 CoroPrevention, FWO ICA EXPERT Network
Exercise prescription to patients with cardiovascular disease is in greater agreement with ESC/EAPC recommendations after using the EXPERT Training tool
No full textExercise prescription by physiotherapists to patients with cardiovascular disease is in greater agreement with European recommendations after using the EXPERT training tool
No full textBACKGROUND: Exercise prescriptions by clinicians to patients with cardiovascular disease (CVD) often disagree with recommendations, thus requiring improvement. AIM: To assess whether exercise prescriptions by physiotherapists to patients with CVD are better in agreement with European (ESC/EAPC) recommendations when the EXPERT (EXercise Prescription in Everyday practice & Rehabilitative Training) Training tool is used for digital educational training. DESIGN: In a prospective non-randomized intervention study. METHODS: Twenty-three belgian physiotherapists first prescribed exercise intensity, frequency, session duration, program duration and exercise type (endurance or strength training) for the same three patient cases, from which the agreement with ESC/EAPC recommendations (based on a maximal score of 60/per case: agreement score) was assessed. Next, they completed a one-month digital training by using the EXPERT Training tool and completed 31 ± 13 training cases. The EXPERT tool is a training and decision support system that automatically generates a (personalised) exercise prescription according to the patient's characteristics, thus integrating the exercise prescriptions for different CVDs and risk factors, all based on ESC/EAPC recommendations. Thereafter, the same three patient cases as at entry of study were filled out again, with re-assessment of level of agreement with ESC/EAPC recommendations. RESULTS: After using the EXPERT Training tool, the physiotherapists prescribed significantly greater exercise frequencies, program durations and total exercise volumes in all three patient cases (p < 0.05). In cases 1, 2 and 3, the agreement score increased from 29 ± 9 (out of 60), 28 ± 9, and 34 ± 7 to 41 ± 9, 41 ± 10, and 45 ± 8, respectively (p < 0.001). Hence, the total agreement score increased from 91 ± 17 (out of 180) to 127 ± 19 (p < 0.001, +44 ± 32%). A lower starting agreement score and younger age correlated with a greater improvement in total agreement score (p < 0.05). CONCLUSIONS: Exercise prescriptions to patients with CVD, generated by physiotherapists, are significantly better in agreement with European recommendations when the EXPERT Training tool is used, indicating its educational potential.sponsorship: This work was supported by the Flemish Research Fund (FWO, FWO-ICA: G0F4220N). (Flemish Research Fund (FWO)|FWO-ICA: G0F4220N)status: Publishe
Exercise prescription to patients with cardiovascular disease is in greater agreement with ESC/EAPC recommendations after using the EXPERT Training tool
No full textDesign and Initial Evaluation of Technology-Supported Shared Decision Making for Secondary Prevention in Cardiac Patients in the CoroPrevention Project
No full textSecondary prevention is recommended after a cardiac event to stimulate recovery and reduce the risk of recurrent events. To optimize the results and support the patients to actively play a part in the prevention programme, the Euro-pean guidelines and EAPC position statements on prevention of cardiovascular diseases suggest a holistic approach and shared decision making (SDM). Up till now, no eHealth solution that offers a holistic approach for secondary prevention that includes SDM has been described. The H2020 project CoroPrevention takes this challenge as one of its research goals, and strives for a technology-supported shared decision making approach for a comprehensive secondary prevention programme for cardiac patients. In this article, we report on the design and initial evaluation of the CoroPrevention-SDM approach. We highlight the stakeholder needs that underpin the design of the technology-supported shared decision making approach, and illustrate the three applications of the CoroPrevention Tool Suite that help patients and the medical staff to bring SDM into practice. How the CoroPrevention-SDM approach and applications underwrite the behavioural goal Medication Adherence, is elaborated as an example. While the overall medical and user experience related benefits can only be assessed in the large scale CoroPrevention randomized clinical trial (RCT), we share the methods and partial results of the initial usability studies and SDM evaluation in this article. In particular , the studies revealed that both patients and caregivers are inclined to use the CoroPrevention-SDM approach to collaboratively set behavioural goals during SDM encounters, and they appreciate the designed supporting applications
A Digitally-Supported Shared Decision Making Approach for Patients during Cardiac Rehabilitation: Protocol for a Randomized Controlled Trial.
No full textBackground: Physical activity is a key component of cardiac rehabilitation. However, EUROASPIRE V concluded that intending 48% of coronary artery disease (CAD) patients do not intend to do physical activity in the next six months. Patient involvement improves patient satisfaction, adherence, and health outcomes and is a prerequisite for good clinical practice. Unfortunately, patients currently have only limited input in their exercise prescription. We developed SharedHeart, a digitally-supported shared decision making (SDM) approach that assists patients with heart disease and their caregivers in collaboratively setting up exercise goals and creating an exercise plan for the patient.
Objective: The aim of the study is to determine the effectiveness and cost-effectiveness of the combination of center-based CR and shared decision making based telerehabilitation. The study investigates the influence of a SDM approach supported by digital applications on the patient’s quality of life, exercise capacity, motivation to exercise, perception of rehabilitation and engagement in the shared decision making process.
Methods: The study is a prospective double-arm, randomized controlled trial that includes a usability study of the applications. In the usability study, instantaneous user friendliness and patients’ motivation will be investigated by testing the designed applications with 10 CAD patients and 5 physiotherapists. In the RCT, 80 patients will be randomized 1:1 between an intervention group and a control group. The intervention group will follow the SharedHeart approach, consisting of SDM encounters with caregivers and using the digital tools during phase II cardiac rehabilitation (i.e. 3 months). The primary outcome measure is patients’ quality of life, assessed with the HeartQoL questionnaire. Secondary outcomes are related to patients’ exercise capacity, motivation to exercise, perception of rehabilitation and engagement in the shared decision-making process.
All methods were performed in accordance with the relevant guidelines and regulations by including a statement in the Ethics approval and consent to participate section to this effect.
Discussion: This will be one of the first study to investigate the effects of a digitally-supported shared decision making approach. If the SharedHeart approach and supporting applications are found to be effective in increasing patients’ quality of life, exercise capacity, motivation to exercise, perception of rehabilitation and/or engagement in the shared decision making process, this can be a cost-effective and accessible solution to increase patient outcomes and patient involvement during cardiac rehabilitation.Funding: PD, HK, KC, WR and SEK received funding through the Horizons 2020 CoroPrevention project, project number 848056. MF received funding through the Flanders Research Foundation FWO, file number 1SE1222N.
Acknowledgements: The design of the the SharedHeart concept and the experimental design for the RCT, as well as the initial software development and usability evaluation were supported by UHasselt special research fonds (BOF PhD BOF18DOC26). Next steps in the study and the RCT are supported by H2020 CoroPrevention (grant 848056) and FWO (grant number 1SE1222N). An International Coordination Action “the EXPERT Network” (FWO-ICA G0F4220N) supports maintenance of the exercise prescription algorithm in the EXPERT tool
Integrating data-driven methods and expert knowledge to develop personas: Balancing automation and multi-disciplinary validation
No full textData-driven personas are increasingly used to inform design decisions. Various methods are published to produce personas based on data collected from projects of different types and scales, each with a specific focus. This study aims to create a set of personas using data collected from a prior randomised controlled trial (RCT), which will be instrumental in designing future eHealth applications to support individuals with cardiovascular disease (CVD). Our method followed five phases for designing personas: (Phase I) expert analysis and variable selection, (Phase II) clustering, (Phase III) expert validation, (Phase IV) persona optimisation, and (Phase V) final check. To ensure that personas accurately reflected the patients, we employed the k-prototype algorithm to cluster mixed data and we focused on validation with colleagues, including medical colleagues, physiotherapists, a psychologist and Human-Computer Interaction (HCI) experts. Seven different personas resulted from the clustering. A validation step involved a multidisciplinary team that assessed the personas' realism, giving an average rating of 8.0 out of 10. Based on their feedback, three of the personas were slightly updated. The final descriptions of all seven personas incorporated the clustered data and the proposed changes after the validation. We concluded that data-driven approaches and expert-based refinement to develop personas is an effective method for understanding the target population. This study highlighted the importance of validation, revealing that creating personas cannot be fully automated, as this may result in losing essential characteristics that only experts can identify. Future research includes demonstrating the practical use of personas.Funding
This research and the SharedHeart study were supported by H2020 CoroPrevention (grant 848056). The design and development of the SharedHeart applications were supported by UHasselt Special Research Fund (grant BOF18DOC26).
Acknowledgements
The authors would like to thank all validators, including Kim Bonné and Frank Vandereyt, in addition to the co-authors, for their valuable contribution to this work, in particular for insightful discussions and valuable feedback during the validation process
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A digitally-supported shared decision making approach for patients during cardiac rehabilitation: a randomised controlled trial.
No full textPhysical activity is a key component of cardiac rehabilitation. However, inclusion rates in cardiac rehabilitation programs remain low and patients currently have only limited input in their exercise prescription. SharedHeart is a digitally-supported shared decision making approach that assists patients with heart disease and their caregivers in collaboratively setting up exercise goals and creating an exercise plan for the patient.Type of funding sources: Public grant(s)– EU funding. Main funding source(s): Horizons 2020 CoroPrevention project
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