Background:Children with asthma can decrease the impact of their disease by improving their physical activity (PA). However, health care providers lack interventions for children with asthma that effectively increase their PA levels and achieve behavior change. A technology-supported approach can positively influence PA and physical functioning in children.Objective:The aims of this study were to develop a technology-supported intervention that facilitates health care providers in promoting PA for children (aged 8 to 12 years) with asthma and to systematically describe this developmental process.Methods:Intervention mapping (IM) was applied to develop a blended and technology-supported intervention in cocreation with children with asthma, their parents, and health care providers. In accordance with the IM framework, the following steps were performed: conduct a needs assessment; define the intervention outcome, performance objectives, and change objectives; select theory-based intervention methods and strategies; create components of the intervention and conduct pilot tests; create an implementation plan; and create an evaluation plan.Results:We developed the blended intervention Foxfit that consists of an app with a PA monitor for children (aged 8 to 12 years) with asthma and a web-based dashboard for their health care provider. The intervention focuses on PA in everyday life to improve social participation. Foxfit contains components based on behavior change principles and gamification, including goal setting, rewards, action planning, monitoring, shaping knowledge, a gamified story, personal coaching and feedback, and a tailored approach. An evaluation plan was created to assess the intervention’s usability and feasibility for both children and health care providers.Conclusions:The IM framework was very useful for systematically developing a technology-supported intervention and for describing the translational process from scientific evidence, the needs and wishes of future users, and behavior change principles into this intervention. This has led to the technology-supported intervention Foxfit that facilitates health care providers in promoting PA in children with asthma. The structured description of the development process and functional components shows the way behavior change techniques are incorporated in the intervention.Trial Registration:International Clinical Trial Registry Platform NTR6658; https://tinyurl.com/3rxejksf
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This paper presents the results of an evaluation of a technology-supported leisure game for people with dementia in relation to the stimulation of social behavior.
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While traditional crime rates are decreasing, cybercrime is on the rise. As a result, the criminal justice system is increasingly dealing with criminals committing cyber-dependent crimes. However, to date there are no effective interventions to prevent recidivism in this type of offenders. Dutch authorities have developed an intervention program, called Hack_Right. Hack_Right is an alternative criminal justice program for young first-offenders of cyber-dependent crimes. In order to prevent recidivism, this program places participants in organizations where they are taught about ethical hacking, complete (technical) assignments and reflect on their offense. In this study, we have evaluated the Hack_Right program and the pilot interventions carried out thus far. By examining the program theory (program evaluation) and implementation of the intervention (process evaluation), the study adds to the scarce literature about cybercrime interventions. During the study, two qualitative research methods have been applied: 1) document analysis and 2) interviews with intervention developers, imposers, implementers and participants. In addition to the observation that the scientific basis for linking specific criminogenic factors to cybercriminals is still fragile, the article concludes that the theoretical base and program integrity of Hack_Right need to be further developed in order to adhere to principles of effective interventions.
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Abstract: Background: Chronic obstructive pulmonary disease (COPD) and asthma have a high prevalence and disease burden. Blended self-management interventions, which combine eHealth with face-to-face interventions, can help reduce the disease burden. Objective: This systematic review and meta-analysis aims to examine the effectiveness of blended self-management interventions on health-related effectiveness and process outcomes for people with COPD or asthma. Methods: PubMed, Web of Science, COCHRANE Library, Emcare, and Embase were searched in December 2018 and updated in November 2020. Study quality was assessed using the Cochrane risk of bias (ROB) 2 tool and the Grading of Recommendations, Assessment, Development, and Evaluation. Results: A total of 15 COPD and 7 asthma randomized controlled trials were included in this study. The meta-analysis of COPD studies found that the blended intervention showed a small improvement in exercise capacity (standardized mean difference [SMD] 0.48; 95% CI 0.10-0.85) and a significant improvement in the quality of life (QoL; SMD 0.81; 95% CI 0.11-1.51). Blended intervention also reduced the admission rate (relative ratio [RR] 0.61; 95% CI 0.38-0.97). In the COPD systematic review, regarding the exacerbation frequency, both studies found that the intervention reduced exacerbation frequency (RR 0.38; 95% CI 0.26-0.56). A large effect was found on BMI (d=0.81; 95% CI 0.25-1.34); however, the effect was inconclusive because only 1 study was included. Regarding medication adherence, 2 of 3 studies found a moderate effect (d=0.73; 95% CI 0.50-0.96), and 1 study reported a mixed effect. Regarding self-management ability, 1 study reported a large effect (d=1.15; 95% CI 0.66-1.62), and no effect was reported in that study. No effect was found on other process outcomes. The meta-analysis of asthma studies found that blended intervention had a small improvement in lung function (SMD 0.40; 95% CI 0.18-0.62) and QoL (SMD 0.36; 95% CI 0.21-0.50) and a moderate improvement in asthma control (SMD 0.67; 95% CI 0.40-0.93). A large effect was found on BMI (d=1.42; 95% CI 0.28-2.42) and exercise capacity (d=1.50; 95% CI 0.35-2.50); however, 1 study was included per outcome. There was no effect on other outcomes. Furthermore, the majority of the 22 studies showed some concerns about the ROB, and the quality of evidence varied. Conclusions: In patients with COPD, the blended self-management interventions had mixed effects on health-related outcomes, with the strongest evidence found for exercise capacity, QoL, and admission rate. Furthermore, the review suggested that the interventions resulted in small effects on lung function and QoL and a moderate effect on asthma control in patients with asthma. There is some evidence for the effectiveness of blended self-management interventions for patients with COPD and asthma; however, more research is needed. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42019119894; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=119894
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Objective: To describe the development of a goal-directed movement intervention in two medical wards, including recommendations for implementation and evaluation. Design: Implementation Research. Setting: Pulmonology and nephrology/gastroenterology wards of the University Medical Centre Utrecht, The Netherlands. Participants: Seven focus groups were executed including 28 nurses, 7 physical therapists and 15 medical specialists. Patients' perceptions were repeatedly assessed during the iterative steps of the intervention development. Intervention: Interventions were targeted to each ward's specific character, following an Intervention Mapping approach using literature and research meetings. Main measures: Intervention components were linked to Behavior Change Techniques and implementation strategies will be selected using the Expert Recommendation Implementing Change tool. Evaluation outcomes like number of patients using the movement intervention will be measured, based on the taxonomy of Proctor. Results: The developed intervention consists of: insight in patients movement behavior (monitoring & feedback), goal setting (goals & planning) and adjustments to the environment (associations & antecedents). The following implementation strategies are recommended: to conduct educational meetings, prepare & identify champions and audit & provide feedback. To measure service and client outcomes, the mean level of physical activity per ward can be evaluated and the Net Promoter Score can be used. Conclusion(s): This study shows the development of a goal-directed movement intervention aligned with the needs of healthcare professionals. This resulted in an intervention consisting of feedback & monitoring of movement behavior, goal setting and adjustments in the environment. Using a step-by-step iterative implementation model to guide development and implementation is recommended.
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This longitudinal, quantitative study contributes to the debate on technology-based professional development by examining the extent to which a learning (LinkedIn) intervention in a university setting affects an individual’s social media use for professional development, and the extent to which this relates to self-reported employability. In addition, we investigated how this relationship is moderated by an individual’s motivation to communicate through social media (LinkedIn). Based on social capital theory and the conservation of resources theory, we developed a set of hypotheses that were tested based on longitudinal data collected from university employees (N = 101) in middle- and high-level jobs. First, in line with our expectations, social media use for professional development was significantly higher after the learning intervention than before. Second, partially in line with our expectations, social media use for professional development was positively related with the employability dimension anticipation and optimization. Third, contrary to our expectations, motivation to communicate through social media (LinkedIn) did not have a moderating role in this relationship. We concluded that the learning intervention has the potential to foster social media use for professional development, and in turn, can contribute to individuals’ human capital in terms of their employability. Hence, the intervention that forms the core of this empirical research can be a sustainable and promising human resource management (HRM) practice that fits the human capital agenda.
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Objective: Self-management is a core theme within chronic care and several evidence-based interventions (EBIs) exist to promote self-management ability. However, these interventions cannot be adapted in a mere copy-paste manner. The current study describes and demonstrates a planned approach in adapting EBI’s in order to promote self-management in community-dwelling people with chronic conditions. Methods: We used Intervention Mapping (IM) to increase the intervention’s fit with a new context. IM helps researchers to take decisions about whether and what to adapt, while maintaining the working ingredients of existing EBI’s. Results: We present a case study in which we used IM to adapt EBI’s to the Flemish primary care context to promote self-management in people with one or more chronic disease. We present the reader with a contextual analysis, intervention aims, and content, sequence and scope of the resulting intervention. Conclusion: IM provides an excellent framework in providing detailed guidance on intervention adaption to a new context, while preserving the essential working ingredients of EBI’s. Practice Implications: The case study is exemplary for public health researchers and practitioners as a planned approach to seek and find EBI’s, and to make adaptations.
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Background: Many intervention development projects fail to bridge the gap from basic research to clinical practice. Instead of theory-based approaches to intervention development, co-design prioritizes the end users’ perspective as well as continuous collaboration between stakeholders, designers, and researchers throughout the project. This alternative approach to the development of interventions is expected to promote the adaptation to existing treatment activities and to be responsive to the requirements of end users. Objective: The first objective was to provide an overview of all activities that were employed during the course of a research project to develop a relapse prevention intervention for interdisciplinary pain treatment programs. The second objective was to examine how co-design may contribute to stakeholder involvement, generation of relevant insights and ideas, and incorporation of stakeholder input into the intervention design. Methods: We performed an embedded single case study and used the double diamond model to describe the process of intervention development. Using all available data sources, we also performed deductive content analysis to reflect on this process. Results: By critically reviewing the value and function of a co-design project with respect to idea generation, stakeholder involvement, and incorporation of stakeholder input into the intervention design, we demonstrated how co-design shaped the transition from ideas, via concepts, to a prototype for a relapse prevention intervention. Conclusions: Structural use of co-design throughout the project resulted in many different participating stakeholders and stimulating design activities. As a consequence, the majority of the components of the final prototype can be traced back to the information that stakeholders provided during the project. Although this illustrates how co-design facilitates the integration of contextual information into the intervention design, further experimental testing is required to evaluate to what extent this approach ultimately leads to improved usability as well as patient outcomes in the context of clinical practice.
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Background: The environment affects children’s energy balance-related behaviors to a considerable extent. A context-based physical activity and nutrition school- and family-based intervention, named KEIGAAF, is being implemented in low socio-economic neighborhoods in Eindhoven, The Netherlands. The aim of this study was to investigate: 1) the effectiveness of the KEIGAAF intervention on BMI z-score, waist circumference, physical activity, sedentary behavior, nutrition behavior, and physical fitness of primary school children, and 2) the process related to the implementation of the intervention. Methods: A quasi-experimental, controlled study with eight intervention schools and three control schools was conducted. The KEIGAAF intervention consists of a combined top-down and bottom-up school intervention: a steering committee developed the general KEIGAAF principles (top-down), and in accordance with these principles, KEIGAAF working groups subsequently develop and implement the intervention in their local context (bottom-up). Parents are also invited to participate in a family-based parenting program, i.e., Triple P Lifestyle. Children aged 7 to 10 years old (grades 4 to 6 in the Netherlands) are included in the study. Effect evaluation data is collected at baseline, after one year, and after two years by using a child questionnaire, accelerometers, anthropometry, a physical fitness test, and a parent questionnaire. A mixed methods approach is applied for the process evaluation: quantitative (checklists, questionnaires) and qualitative methods (observations, interviews) are used. To analyze intervention effectiveness, multilevel regression analyses will be conducted. Content analyses will be conducted on the qualitative process data. Discussion: Two important environmental settings, the school environment and the family environment, are simultaneously targeted in the KEIGAAF intervention. The combined top-down and bottom-up approach is expected to make the intervention an effective and sustainable version of the Health Promoting Schools framework. An elaborate process evaluation will be conducted alongside an effect evaluation in which multiple data collection sources (both qualitative and quantitative) are used.
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Background: As populations age, maintaining physical activity (PA) is essential to reduce chronic disease risk and preserve functional independence in older adults. Technology-supported interventions, such as wearables, mobile applications, and web-based platforms, have emerged as effective tools to promote PA. However, engagement with technology alone is not sufficient. Effectiveness depends on whether digital tools foster sustained adherence to prescribed PA, since health benefits are dose-dependent on activity levels. In this sense, adherence matters not just for short-term participation but for embedding long-term behaviour change, an especially pressing challenge for older adults, who are typically less active and may experience greater barriers to digital engagement. This scoping review aimed to identify psychological and motivational factors that influence adherence to both the physical activity component and the supporting technology. Methods: A systematic search was conducted across three databases (PubMed, Web of Science, Scopus) for studies published between 2000 and March 2023. Fifty-three studies were included, encompassing qualitative, quantitative, and mixed-methods designs. Behaviour Change Techniques (BCTs) were identified and categorised using the BCT Taxonomy v1, distinguishing between techniques delivered via technology and those delivered through human interaction. Data were synthesised, distinguishing between adherence to physical activity and adherence to technology use. Results: Frequently used BCTs included self-monitoring, goal setting, action planning, feedback, prompts/cues, and social support, with different techniques emphasised in digital versus human-facilitated delivery modes. From the qualitative data, 417 psychological and motivational factors were identified and grouped into 25 thematic categories. These were structured into five domains: (1) user factors related to technology adherence, (2) technology-related factors influencing technology adherence, (3) context factors related to technology adherence, (4) user factors related to PA adherence, and (5) context factors related to PA adherence. Key facilitators included ease of use, personalised content, motivational feedback, and social support, while key barriers included low digital literacy, repetitive content, and lack of guidance. Quantitative findings revealed 19 associations between psychological/motivational variables and adherence outcomes, of which 12 were statistically significant. Conclusions: This review provides a comprehensive overview supporting the understanding of what determines adherence in technology-supported PA interventions for older adults from a psychological and motivational perspective. By differentiating between technology adherence and PA adherence, and considering the BCTs that are incorporated in the interventions, our findings offer actionable guidance for researchers and developers to design more inclusive, motivating, and sustainable interventions that promote active ageing.
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