mHealth and Engagement Concerning Persons With Chronic Somatic Health Conditions: Integrative Literature Review

Designing mHealth Apps to Incorporate Evidence-Based Techniques for Prolonging User Engagement

Maintaining user engagement with mobile health (mHealth) apps can be a challenge. Previously, we developed a conceptual model to optimize patient engagement in mHealth apps by incorporating multiple evidence-based methods, including increasing health literacy, enhancing technical competence, and improving feelings about participation in clinical trials. This viewpoint aims to report on a series of exploratory mini-experiments demonstrating the feasibility of testing our previously published engagement conceptual model. We collected data from 6 participants using an app that showed a series of educational videos and obtained additional data via questionnaires to illustrate and pilot the approach. The videos addressed 3 elements shown to relate to engagement in health care app use: increasing health literacy, enhancing technical competence, and improving positive feelings about participation in clinical trials. We measured changes in participants' knowledge and feelings, collected feedback on the videos and content, made revisions based on this feedback, and conducted participant reassessments. The findings support the feasibility of an iterative approach to creating and refining engagement enhancements in mHealth apps. Systematically identifying the key evidence-based elements intended to be included in an app's design and then systematically testing the implantation of each element separately until a satisfactory level of positive impact is achieved is feasible and should be incorporated into standard app design. While mHealth apps have shown promise, participants are more likely to drop out than to be retained. This viewpoint highlights the potential for mHealth researchers to test and refine mHealth apps using approaches to better engage users.

Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review

BACKGROUND

Microrandomized trials (MRTs) have emerged as the gold standard for the development and evaluation of multicomponent, adaptive mobile health (mHealth) interventions. However, not much is known about the state of participant engagement measurement in MRTs of mHealth interventions.

OBJECTIVE

In this scoping review, we aimed to quantify the proportion of existing or planned MRTs of mHealth interventions to date that have assessed (or have planned to assess) engagement. In addition, for the trials that have explicitly assessed (or have planned to assess) engagement, we aimed to investigate how engagement has been operationalized and to identify the factors that have been studied as determinants of engagement in MRTs of mHealth interventions.

METHODS

We conducted a broad search for MRTs of mHealth interventions in 5 databases and manually searched preprint servers and trial registries. Study characteristics of each included evidence source were extracted. We coded and categorized these data to identify how engagement has been operationalized and which determinants, moderators, and covariates have been assessed in existing MRTs.

RESULTS

Our database and manual search yielded 22 eligible evidence sources. Most of these studies (14/22, 64%) were designed to evaluate the effects of intervention components. The median sample size of the included MRTs was 110.5. At least 1 explicit measure of engagement was included in 91% (20/22) of the included MRTs. We found that objective measures such as system usage data (16/20, 80%) and sensor data (7/20, 35%) are the most common methods of measuring engagement. All studies included at least 1 measure of the physical facet of engagement, but the affective and cognitive facets of engagement have largely been neglected (only measured by 1 study each). Most studies measured engagement with the mHealth intervention (Little e) and not with the health behavior of interest (Big E). Only 6 (30%) of the 20 studies that measured engagement assessed the determinants of engagement in MRTs of mHealth interventions; notification-related variables were the most common determinants of engagement assessed (4/6, 67% studies). Of the 6 studies, 3 (50%) examined the moderators of participant engagement-2 studies investigated time-related moderators exclusively, and 1 study planned to investigate a comprehensive set of physiological and psychosocial moderators in addition to time-related moderators.

CONCLUSIONS

Although the measurement of participant engagement in MRTs of mHealth interventions is prevalent, there is a need for future trials to diversify the measurement of engagement. There is also a need for researchers to address the lack of attention to how engagement is determined and moderated. We hope that by mapping the state of engagement measurement in existing MRTs of mHealth interventions, this review will encourage researchers to pay more attention to these issues when planning for engagement measurement in future trials.

A Health App for Post-Pandemic Years (HAPPY) for people with physiological and psychosocial distress during the post-pandemic era: Protocol for a randomized controlled trial

Objective

This article describes a protocol for a randomized controlled trial to evaluate the effects of a three-level Health App for Post-Pandemic Years (HAPPY) on alleviating post-pandemic physiological and psychosocial distress.

Methods

Convenience and snowball sampling methods will be used to recruit 814 people aged 18+ with physiological and/or psychosocial distress. The experimental group will receive a 24-week intervention consisting of an 8-week regular supervision phase and a 16-week self-help phase. Based on their assessment results, they will be assigned to receive interventions on mindfulness, energy conservation techniques, or physical activity training. The waitlist control group will receive the same intervention in Week 25. The primary outcome will be changes in psychosocial distress, measured using the Kessler Psychological Distress Scale (K10). Secondary outcomes will include changes in levels of fatigue (Chinese version of the Brief Fatigue Inventory), sleep quality (Chinese version of the Pittsburgh Sleep Quality Index), pain intensity (Numeric Rating Scale), positive appraisal (Short version of the 18-item Cognitive Emotion Regulation Questionnaire), self-efficacy (Chinese version of the General Self-efficacy Scale), depression and anxiety (Chinese version of the 21-item Depression Anxiety Stress Scale), and event impact (Chinese version of the 22-item Impact of Event Scale-Revised). All measures will be administered at baseline (T0), Week 8 after the supervision phase (T1), and 24 weeks post-intervention (T2). A generalized estimating equations model will be used to examine the group, time, and interaction (Time × Group) effect of the interventions on the outcome assessments (intention-to-treat analysis) across the three time points, and to compute a within-group comparison of objective physiological parameters and adherence to the assigned interventions in the experimental group.

Conclusions

The innovative, three-level mobile HAPPY app will promote beneficial behavioral strategies to alleviate post-pandemic physiological and psychosocial distress.

Trial registration

ClinicalTrials.gov, NCT05459896. Registered on 15 July 2022.

Engaging patients and citizens in digital health technology development through the virtual space

Digital technologies are increasingly empowering individuals to take charge of their health and improve their well-being. However, there are disparities in access related to demographic, economic, and sociocultural factors that result in exclusion from the use of digital technologies for different groups of the population. The development of digital technology in health is a powerful lever for improving care and services, but also brings risks for certain users in vulnerable situations. Increased digital health inequalities are associated with limited digital literacy, lack of interest, and low levels of self-efficacy in using technology. In the context of the COVID-19 pandemic and post-pandemic healthcare systems, the leap to digital is essential. To foster responsible innovation and optimal use of digital health by all, including vulnerable groups, we propose that patient and citizen engagement must be an essential component of the research strategy. Patient partners will define expectations and establish research priorities using their experiential knowledge, while benefiting from rich exposure to the research process to increase their self-efficacy and digital literacy. We will support this proposition with an operationalised example aiming to implement a Virtual Community of Patients and Citizens Partners (COMVIP), a digital tool co-created with patients and public experts, as active team members in research. Founded on the principles of equity, diversity and inclusion, this base of citizen expertise will assemble individuals from different backgrounds and literacy levels living in vulnerable situations to acquire knowledge, and share their experiences, while contributing actively in the co-development of innovative strategies and health technology assessment.

Effect of cognitive behavioral intervention on anxiety, depression, and quality of life in patients with epilepsy

OBJECTIVE

This study aimed to investigate the effect of cognitive behavioral therapy (CBT) on quality of life, anxiety, and depression in patients with epilepsy.

METHODS

Each study subject was randomly assigned to a CBT (n=46) or control (n=49) group (1:1 ratio), and the first group underwent an 8-week CBT treatment. Anxiety, depression, and quality of life (QOLIE-31) were assessed at both baseline and endpoint using the Self-Rating Anxiety Scale (SAS), Hamilton Depression Scale (HDMA) and quality of life in Epilepsy-31 (QOLIE-31) scales. The statistical analyses included between-and within-group comparisons of the effects of CBT on these measures and associations with demographic and clinical variables.

RESULTS

No differences were found between variables at baseline (P>0.05). The repeated-measures analyses found that CBT group had greater improvement in depression score compared to the control group (P<0.05). The analysis of anxiety score showed that compared to the control group, CBT intervention had no statistical significance in the total anxiety population. However, the CBT intervention decreased anxiety in women and Combined-drug group (P<0.05). The CBT group had greater improvement in overall score, medication effect, and seizure worry score than the control group (P<0.05). Stratified analysis found total and medication effects score of CBT intervention group for the combined-drug group were higher than those of the single drug group (P<0.05).

CONCLUSION

Increases in overall scores, seizure worry, cognitive functioning, and medication effect were better in the CBT group. CBT can improve anxiety, depression, and quality of life in patients with epilepsy. Women and combined-drug patients with epilepsy benefit most from CBT.

Still engaged – healthcare staff’s engagement when introducing a new eHealth solution for wound management: a qualitative study

Background

eHealth solutions have often been considered favourable for improved effectiveness and quality in healthcare services for wound management. Staff engagement related to organisational changes is a key factor for successful development and implementation of a new eHealth solution, like a digital decision support systems (DDSS). It is essential to understand the engagement process in terms of sustainability, wellbeing in staff and efficiency in a long-term perspective. The aim of this study was to describe healthcare staff’s engagement during a 6-month test of an eHealth solution (DDSS) for wound management.

Methods

A qualitative design, including interviews conducted with healthcare staff working with wound management within primary, community and specialist care (n = 11) on two occasions: at the introduction of the solution and after 6 months, when the test period was over. Data were interpreted with qualitative content analysis.

Results

Healthcare staff’s descriptions from a 6-month test of an eHealth solution for wound management can be summarised as Engaging through meaning, but draining. The analysis revealed a result with three subcategories: Having a shared interest is stimulating, Good but not perfect and Exciting, but sometimes exhausting. The staff described their engagement as sustained through feelings of meaningfulness when using the eHealth solution, but limited by feelings of exhaustion due to heavy workload and lack of support and understanding from others.

Conclusions

The results indicate that the healthcare staff who tested the eHealth solution described themselves as individuals who easily become engaged when an idea and efforts felt meaningful. The staff needed resources to nourish engagement in their new role when implementing eHealth in the clinical everyday work of wound management. Allocating time and support are important to consider when planning for sustainable implementation of eHealth solutions in healthcare organisations.

Mobile Health, Disease Knowledge, and Self-Care Behavior in Chronic Kidney Disease: A Prospective Cohort Study

Mobile health (mHealth) management is an emerging strategy of care for patients with chronic diseases. However, the effect of mHealth management on clinical outcomes of patients with chronic kidney disease (CKD) has not been well-studied. The aim of this study was to investigate the additional influence of mHealth on disease knowledge and self-care behavior in CKD patients who had received traditional education. We designed and developed a new healthcare mobile application, called iCKD, which has several major features, including home-based physiological signal monitoring, disease health education, nutrition analysis, medication reminder, and alarms and a warning system. Trained nurses interviewed patients with CKD using structured questionnaires of disease knowledge and self-care behavior. After propensity score matching, we analyzed 107 patients who used iCKD and traditional education, and 107 who received traditional education. The patients who used iCKD had higher disease knowledge scores than those who received traditional education. In multivariate analysis, iCKD was significantly and positively associated with disease knowledge scores. Patients with high education levels could have greater disease knowledge through using mHealth. There was no significant difference in total scores of self-care behavior between the two groups. In conclusion, mHealth can significantly increase disease knowledge in patients with CKD.