Understanding citizens' attitudes within user-centered digital health ecosystems: A sequential mixed method methodology including a web-survey

Abstract

Objective: Transitioning from digital health applications to digital health ecosystems, leveraging the advances in technologies and informatics, could be the next revolution in digital health. This includes offering centralized access to various health services and improving citizens' well-being, delivery, clinical processes, and data management. However, a limited understanding of citizens may impede adaptation. Therefore, this study investigates citizens' attitudes within digital health ecosystems, differentiated by their characteristics, to support health service-providers and governmental policymakers in establishing user-centered solutions.

Methods: This study follows a three-step sequential mixed method methodology: (1) a literature review. (2) Qualitative thematic analyses based on semi-structured qualitative interviews. (3) Quantitative analyses based on a web-survey (descriptive statistics, one-way analysis of variances, Tukey-honestly, and Cohen's d tests).

Results: N = 15 citizens were interviewed and n = 1289 responded to the web-survey, to our knowledge the largest survey on this topic. Citizens desire a more convenient management of health services and data (M = 5.2, SD = 1.59). Services with peer-to-peer interactions (M = 3.7, SD = 1.81) and lower involvement of health professionals (M = 3.8, SD = 1.75) are less demanded. Data protection is critical (M = 6.2, SD = 1.23). Public payers are mandated as orchestrators (M = 4.3, SD = 1.99), while private companies receive lower acceptance (M = 3.0, SD = 1.42).

Conclusions: Health service-providers could follow a three-staged approach to establish digital health ecosystems: (1) Increasing the convenience for citizens by enabling online management of health services and data. (2) Extending the citizen-healthcare provider partnership through online interactions. (3) Fostering preventative behaviors and quicker recovery by personalizing health services and interactions. Governmental policymakers should integrate an electronic health record.

Keywords: Digital health; apps; health informatics; mixed methods; qualitative; quantitative; technology.

Figure 1.

Included studies form the literature review. Identification and screening process to include relevant literature guided by the PRISMA-approach for literature scoping reviews.^–

Figure 2.

Web-survey data sample cleaning criteria/rationale. Only responses from respondents who completed the entire web-survey and correctly answered the control question were considered. The data were filtered to exclude respondents who did not take a reasonable amount of time to answer the questions. “Reasonable time” was defined as taking more time to answer than the quickest 10% of respondents. This threshold in absolute terms was determined after reviewing the first 1000 complete responses with correct control question answers. Respondents who answered more quickly than this absolute threshold were excluded. The established threshold was then applied to all subsequent respondents for exclusion, resulting in the exclusion of 119 responses. Applying a similar rationale, 10% of respondents who most frequently chose the “no answer preferred” option were excluded based on an absolute threshold defined using the first 1000 complete responses with correct control question answers. The established threshold was then applied to all subsequent responses for exclusion, resulting in the exclusion of 18 further responses. Noteworthy, the respondents who answered the quickest significantly overlapped with those who most frequently chose the “no answer preferred” option. In the further cleaning process, zero responses were excluded to ensure a minimum anonymity level of k ≥ 5 and no outliers were identified.

Figure 3.

Personal characteristics of web-survey respondents by predictor variables (constructs). Based on primary data collected via a web-survey including n = 1289 German citizens. The final data sample shows diverse personal characteristics across the predictor variables (constructs). Respondents are evenly split across “age” and “gender” groups, with 45% having received academic education and 65% being either full-time-, part-time-, self-, or public sector-employed; 13% did not visit a healthcare provider within the last 12 months and 48% have some form of exposure to a permanent/chronic disease. On a one-to-five-point Likert scale, citizens rate their “health feeling” at M = 2.8 and their “health interest” at M = 3.6. On average, citizens express being “rather satisfied” with their personal healthcare provider experience and rate their “ATI” level with M = 3.9 on a one-to-six-point Likert scale.

Figure 4.

Three-stage approach to establish user-centered digital health ecosystems. Based on three-step sequential mixed method approach including a literature review as well as primary data from n = 15 semi-structured qualitative interview participants and n = 1289 web-survey respondents. Shifting from managing health, partnering with healthcare providers, to personalizing health toward a user-centered digital health ecosystem.