Matching Items (3)
Description
Many individual-level behavioral interventions improve health and well-being. However, most interventions exhibit considerable heterogeneity in response. Put differently, what might be effective on average might not be effective for specific individuals. From an individual’s perspective, many healthy behaviors exist that seem to have a positive impact. However, few existing tools support people in identifying interventions that work for them, personally.
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.
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.
ContributorsPhatak, Sayali Shekhar (Author) / Buman, Matthew P (Thesis advisor) / Hekler, Eric B. (Committee member) / Huberty, Jennifer L (Committee member) / Johnston, Erik W., 1977- (Committee member) / Swan, Pamela D (Committee member) / Arizona State University (Publisher)
Created2019
Description
Learning how to manage time efficiently is something that many people struggle with, college students in particular. The purpose of this study was to examine if personalization via self-experimentation of strategies to improve time management skills is a useful strategy for achieving this goal. This study used a multiple baseline approach with three phases: phase one, the baseline, phase two, which included individuals receiving examples of plausible strategies to improve time management skills, and phase three, which involved the self-experimentation component. Results of this study suggest no significant changes in time management based on self-reported completion of tasks but do indicate a trend towards improved time management skills overall based on the time management questionnaire taken at the beginning and end of the study. These results suggest that further exploration in the use of self-experimentation strategies for improving time management is likely warranted but that current strategies likely require additional research. Results from the interviews indicate that the self-experimentation strategy, as delivered via PACO does increase awareness and thinking about time management.
ContributorsCope, Breanna (Author) / Hekler, Eric (Thesis director) / Buman, Matthew (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
A study was undertaken to examine and test the effectiveness of a self-experimentation model, guided by a mobile app called PACO, in helping college students improve behaviors associated with sleep. Thirteen participants were enrolled in this study and their nightly sleep quality and sleep duration were measured via PACO as they underwent three conditions: a baseline non-intervention phase, an expert-developed intervention phase, in which pre-made intervention examples were provided and used in PACO, and a self-experimentation phase, during which users were invited to develop their own sleep-behavior interventions using PACO. The participants were randomly placed into three groups, and the points of transition between phases was staggered across five weeks according to a multiple baseline design. The goal and hypothesis was to determine if sleep duration and sleep quality (sleep satisfaction) were improved in the final self-experimentation phase compared to the expert-developed experimentation phase and baseline phase, as well as in the expert-developed experimentation phase compared to the baseline phase. The results show little change, and nearly no improvement in the outcome measures between phases, leaving us unable to support the hypothesis. However, the existence of several limitations considered in retrospect, such as the small sample size, the short study time period, and technical difficulties with the PACO application means that no concrete conclusions should be made regarding the effectiveness of the self-experimentation model, nor the usability of PACO. Additional research should be made toward user motivation and modes of teaching the underlying behavioral science principles to casual users to increase effectiveness.
ContributorsNazareno, Alexandra Nicole (Author) / Hekler, Eric (Thesis director) / Walker, Erin (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05