Matching Items (2)
Filtering by
- All Subjects: Pregnant women--Weight gain--Psychological aspects.
- Creators: Huberty, Jennifer L
Description
Excessive gestational weight gain (GWG) during pregnancy is a major public health concern. Studies have reported more than 70% of pregnant women gain excessive weight which may pose increased maternal and fetal risks. Little is known about the relationships of GWG to behavioral factors (i.e., physical activity, sleep, social support) and maternal mental health (i.e., stress, anxiety, depression) during pregnancy. This descriptive, cross-sectional study explored the relationships of GWG to behavioral factors and maternal mental health during pregnancy. Secondarily, this study described the preferences, uses of, and interests in alternative approaches as well as the mental health differences between users and non-users of alternative approaches during pregnancy. A national survey was administered to women ≥8 weeks pregnant, ≥18 years old, and residing in the United States (N=968). Bivariate correlations were used to determine relationships between GWG and variables of interest. Independent t-tests were used to observe mental health differences between users and non-users of alternative approaches. Data were analyzed throughout pregnancy and by trimester. Throughout pregnancy, significant relationships were found in GWG to stressful events (r=-.112, p<.01), depression (r=.066, p<.05), mindfulness (r=-.067, p<.05), and sleep (r=.089, p<.01). When GWG was assessed by trimester, stressful events were significant in the second (r=-.216, p<.01) and third trimesters (r=-.085, p<.05). Depression remained positively related to GWG in the first (r=.409, p<.01) and second trimesters (r=.162, p<.01). A positive relationship emerged between GWG and anxiety in the first trimester (r=.340, p<.01) and physical activity became significant in the second (r=-.136; p<.05) and third trimesters (r=-.100; p<.05). Mindfulness was the only variable significantly related to GWG throughout all time points. Mean anxiety (d=.236; p=.001) and depression (d=.265; p<.001) scores were significantly lower in users compared to non-users of alternative approaches throughout pregnancy and when assessed by trimester anxiety (d=.424; p=.001) and depression (d=.526; p<.001) were significant in the second trimester. This study provides a framework for future analyses in GWG and maternal mental health. The information presented here may inform future interventions to test the effectiveness of alternative approaches to simultaneously manage maternal mental health and GWG due to the integrative nature of alternative approaches.
ContributorsMatthews, Jennifer L. (Author) / Huberty, Jennifer L (Thesis advisor) / Leiferman, Jenn (Committee member) / Larkey, Linda (Committee member) / McClain, Darya (Committee member) / Arizona State University (Publisher)
Created2015
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