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- All Subjects: Behavioral Sciences
- All Subjects: Vitamin C
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
Among its many roles in the body, ascorbic acid functions as a cofactor in carnitine and catecholamine synthesis, metabolites involved in fat oxidation and mood regulation, respectively. Given that fat oxidation and mood affect one's feelings of vigor, I hypothesized that those with lower levels of plasma ascorbic acid would be less likely to exercise at high levels than individuals with adequate or high levels of vitamin C. To test this, I conducted a double-blind, placebo-controlled intervention. A group of healthy, non-smoking males between the ages of 18 and 40 were put on a vitamin C-restricted diet for two weeks and then randomized to a control group that received placebo capsules for six weeks or an intervention group that received 500 mg of vitamin C daily for six weeks. The men were restricted from eating foods high in vitamin C, instructed to wear a pedometer daily and to record their step counts, and to take a pill daily (either the placebo or vitamin C supplement). Unexpectedly, the subjects receiving the intervention had lower step counts than the control group; the control group, rather than the vitamin C group, significantly (p=0.017) increased their steps at week 8 compared to week 2. However, I also estimated daily Metabolic Equivalent Tasks (METs), and subjects receiving the placebo had lower MET outputs than subjects receiving vitamin C at the end of the trial, in spite of having higher step counts. This means the intensity of their activity was higher, based on METs expenditure. Additionally, depression scores (POMS-D) as measured by the Profile of Mood States (POMS) questionnaire were significantly higher (p=0.041) among subjects receiving the placebo at the end of the study. These latter results are consistent with my expectations that subjects with higher levels of plasma vitamin C would have improved mood and higher energy output than subjects with low levels of vitamin C.
ContributorsNetland, Heidi (Author) / Johnston, Carol S (Thesis advisor) / Swan, Pamela D (Committee member) / Hampl, Jeffery S (Committee member) / Arizona State University (Publisher)
Created2011