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- All Subjects: Participatory Platforms
- Creators: Johnston, Erik W., 1977-
One approach to support such personalization is via self-experimentation using single-case designs. ‘Hack Your Health’ is a tool that guides individuals through an 18-day self-experiment to test if an intervention they choose (e.g., meditation, gratitude journaling) improves their own psychological well-being (e.g., stress, happiness), whether it fits in their routine, and whether they enjoy it.
The purpose of this work was to conduct a formative evaluation of Hack Your Health to examine user burden, adherence, and to evaluate its usefulness in supporting decision-making about a health intervention. A mixed-methods approach was used, and two versions of the tool were tested via two waves of participants (Wave 1, N=20; Wave 2, N=8). Participants completed their self-experiments and provided feedback via follow-up surveys (n=26) and interviews (n=20).
Findings indicated that the tool had high usability and low burden overall. Average survey completion rate was 91%, and compliance to protocol was 72%. Overall, participants found the experience useful to test if their chosen intervention helped them. However, there were discrepancies between participants’ intuition about intervention effect and results from analyses. Participants often relied on intuition/lived experience over results for decision-making. This suggested that the usefulness of Hack Your Health in its current form might be through the structure, accountability, and means for self-reflection it provided rather than the specific experimental design/results. Additionally, situations where performing interventions within a rigorous/restrictive experimental set-up may not be appropriate (e.g., when goal is to assess intervention enjoyment) were uncovered. Plausible design implications include: longer experimental and phase durations, accounting for non-compliance, missingness, and proximal/acute effects, and exploring strategies to complement quantitative data with participants’ lived experiences with interventions to effectively support decision-making. Future work should explore ways to balance scientific rigor with participants’ needs for such decision-making.
Public organizations have been interested in tapping into the creativity and passion of the public through the use of open innovation, which emphasizes bottom-up ideation and collaboration. A challenge for organizational adoption of open innovation is that the quick-start, bottom-up, iterative nature of open innovation does not integrate easily into the hierarchical, stability-oriented structure of most organizations. In order to realize the potential of open innovation, organizations must be willing to change the way they operate. This dissertation is a case study of how Arizona State University (ASU), has adapted its organizational structure and created unique programming to incorporate open innovation. ASU has made innovation, inclusion, access, and real world impact organizational priorities in its mission to be the New American University. The primarily focus of the case study is the experiential knowledge of administrative leaders and administrative intermediaries who have managed open innovation programming at the university over the past five years. Using theoretical pattern matching, administrator insights on open innovation adoption are illustrated in terms of design stages, teamwork, and ASU's culture of innovation. It is found that administrators view iterative experimentation with goals of impact as organizational priorities. Institutional support for iterative, experimental programming, along with the assumption that not every effort will be successful, empowers administrators to push to be bolder in their implementation of open innovation. Theoretical pattern matching also enabled a detailed study of administrator alignment regarding one particular open innovation program, the hybrid participatory platform 10,000 Solutions. Creating a successful and meaningful hybrid platform is much more complex than administrators anticipated at the outset. This chapter provides administrator insights in the design, management, and evaluation of participatory platforms. Next, demographic assessment of student participation in open innovation programming is presented. Demographics are found to be reflective of the university population and provide indicators for how to improve existing programming. This dissertation expands understanding of the task facing administrators in an organization seeking to integrate open innovation into their work.