JMIR Publications

ABSTRACT

Background:

Asthma and COPD are long-term respiratory conditions that require active self-management to improve quality of life and reduce resource burdens on health systems. Self-management interventions are increasingly delivered via digital platforms, they offer strategies to support tailored behavior training, education, medication adherence, and symptom monitoring., and are increasingly delivered digitally. Developing an improved understanding of how patients use such digital tools is needed to support optimal management.

Objective:

This scoping review aims to understand how heterogeneous patient groups engage with digital interventions for the self-management of heterogenous asthma and COPD. This is accomplished by exploring how studies report demographic characteristics, outcome measures, and usage data. Additionally, the results identify how these types of data are combined in analysis.

Methods:

This study adopted a two-phase set of exclusion-inclusion criteria. This initially identified empirical research reporting three types of data: demographic characteristics, clinical outcome measures, and usage. Secondly, by identifying and reviewing the range of usage measures reported an informed decision was made to focus on studies reporting four meaningful measures. This review required usage measures to be comparable across interventions (i.e. numerical and without subjective user inputs). Additionally, thematic synthesis was used to develop themes using discussion and conclusion sections. Patient Public Involvement (PPI) sessions discussed the results to inform the discussion.

Results:

Twenty-four studies were included in final analysis, each reporting an average of two comparable usage measures. Eleven studies (45.8%) reported two or more types of outcome measures (i.e. asthma/COPD-specific self-reported, physiological, or other self-reported measure). Age, disease severity, and sex were reported in all studies. Most studies did not report ethnicity (17, 70.8%) or socio-economic status, including proxies (15, 62.5%). Sixteen studies (66.67%) did not combine these different types of data in analysis. Thematic synthesis extends our understanding of the identified gaps in reporting practices in three key areas: (1) a lack of discussion on patterns of engagement, (2) a superficial use of demographic characteristics that does not consider differences in outcome or usage, and (3) an underdeveloped understanding of how healthcare support affects engagement.

Conclusions:

Overall, to understand how people engage with digital tools (and improve intervention effectiveness) across subpopulations, researchers should consider digital usage and related outcome measures across well described groups. We highlight improvements that could be incorporated at each stage of the research process. We emphasize two priorities; (1) expanding the reporting of demographic characteristics to build a more comprehensive understanding that can complements existing knowledge; (2) conducting more comprehensive analysis that combines different types of data. Addressing these priorities in tandem should identify differences between subpopulations and explain how such differences develop, promoting opportunities for greater tailoring of interventions and improved clinical outcomes. Clinical Trial: N/A