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Open Access Publications from the University of California

Scholarly Works (9 results)

  • Article
  • Peer Reviewed
UC San Francisco Previously Published Works (2022)

Background

Individuals with a greater perceived risk of heart attack or type 2 diabetes tend to adopt recommended lifestyle changes to minimize their risks. Despite the rapidly growing Hispanic population in the United States, data regarding their perceived risks are lacking.

Objective

This study aimed to examine the perceived risk of suffering a heart attack and/or developing type 2 diabetes and to explore the factors associated with these risk perceptions in Hispanic adults with overweight/obesity.

Methods

We analyzed 69 Hispanic adults with overweight/obesity who participated in the screening/baseline visit for the Adelgaza study, a weight loss and diabetes prevention trial, using descriptive statistics and logistic regressions. Heart attack or type 2 diabetes risk perception was assessed using a single-item questionnaire.

Results

The mean (SD) values for age and body mass index (BMI) were 43.8 (11.2) years and 31.7 (4.5) kg/m 2 , respectively. Of all participants, 46.4% perceived a low risk for heart attack and 29.0% perceived a low risk for developing type 2 diabetes in their lifetime, whereas only 11.6% reported both risk perceptions. Older age, lower BMI, and longer walking duration (minutes) per day were significantly associated with a lower perceived risk of heart attack ( P < .05). Having no family history of heart attack, lower BMI, and lower fat intake were significant predictors of a lower diabetes-risk perception ( P < .05).

Conclusions

Hispanic adults with overweight/obesity seem to underestimate their risks of heart attack and type 2 diabetes.
    Cover page: Perceived Risk of Heart Attack and Type 2 Diabetes in Hispanic Adults With Overweight and Obesity
    • Article
    • Peer Reviewed
    UC San Francisco Previously Published Works (2022)
    We aimed to understand adults’ self-weighing behaviors and explore significant predictors of body mass index (BMI) accuracy based on self-reported height and weight in a diverse sample of community-dwelling adults. Methods: In this cross-sectional study, 531 adults participating in a physical activity program or a weight loss program were analyzed. Participants’ self-reported and objectively measured weight, height, weight scale ownership, self-weighing behaviors, and medical history were collected. Results: The mean age (standard deviation) was 50.0 (12.0) years with a range of 24 to 78 years. Out of 531 participants, 455 (85.7%) were women. The study population was diverse (58.9% non-White). In total, 409 (77.0%) participants had a weight scale at home, but only 222 (41.8%) weighed themselves at least once a week. The weight and BMI underestimation became much more significant as the participant’s weight increased (p ≤ 0.001). Employment status, high cholesterol, and low objectively measured weight were significant predictors of self-reported BMI accuracy after controlling for potential confounding factors (p < 0.05). Interestingly, ownership of a home weight scale and the frequency of self-weighing behavior were not significantly associated with the accuracy of self-reported BMI (p > 0.05). Conclusion: The accuracy of the participants’ BMI, based on self-reported height and weight, was significantly associated with employment status, high cholesterol, and low objectively measured weight, suggesting that BMI accuracy depends on multi factors.
      Cover page: Self-Weighing Behaviors of Diverse Community-Dwelling Adults Motivated for a Lifestyle Change
      • Article
      • Peer Reviewed
      UC San Francisco Previously Published Works (2022)

      Background

      Heart disease is the leading cause of death for women and men in the United States. Yet, little is known about the motivation for care-seeking behavior for heart attack and the perception of self-risk of a heart attack in individuals, especially those at high risk for developing type 2 diabetes.

      Objectives

      This study aimed to describe knowledge and awareness of heart attacks and perceived risk for future heart attacks and evaluate factors associated with a low perceived risk of a heart attack in adults with a high risk for type 2 diabetes.

      Methods

      In this secondary data, cross-sectional study, the screening/baseline data of 80 adults participating in the mobile phone-based diabetes prevention program trial were analyzed. Validated measures assessed knowledge, self-efficacy, and heart attack risk perception were used. Logistic regressions were performed.

      Results

      The mean (standard deviation) age of participants was 55.4 (9.0) years. 32.5% of the sample failed to identify any heart attack symptoms. Half of the sample did not perceive their risk of having a heart attack in their lifetime. Older age, lower body mass index, not having a family history of heart attack, and current smokers were significantly associated with a lower perceived risk of heart attack (P < .05).

      Conclusions

      Healthcare providers need to assess the discrepancies between the individual's risk perception and the presence of actual risk factors of a heart attack in adults with a high risk for type 2 diabetes.
        Cover page: Perceived Heart Attack Likelihood in Adults with a High Diabetes Risk
        • Thesis
        • Peer Reviewed
        UC Davis Electronic Theses and Dissertations (2023)

        Chatbots are dialogue systems designed to simulate human communication by means of text, speech or both. Developments in artificial intelligence, machine learning, and natural language processing has empowered chatbots to converse with human users in a more naturalistic and humanlike manner, transcending beyond basic task execution. Recent research underscores the potential of human-chatbot relationships, providing evidence that chatbots are capable of developing meaningful relationships with humans. The capability of chatbots to foster social connections with humans offers implications, especially in the health domain. This body of work consists of two comprehensive studies that examine the role of relational chatbots, specifically designed to cultivate relationships with human users, in influencing health behavior outcomes. The first study examines the underlying mechanisms and impacts of the human-chatbot relationship. The study employed the two fundamental dimensions of mind perception—warmth and competence—to evaluate the impact of chatbots’ relational behaviors on human-chatbot relationship and subsequently on physical activity behavior intention. The study then explored how the two affective processes, self-disclosure and empathy, contributed to the mind perception of the relational chatbots. Results indicated a significant indirect effect of chatbot’s relational behaviors on physical activity behavior intention mediated by warmth and human-chatbot relationship. It was also revealed that the presence of self-disclosure and empathy contributed to shaping perceptions of warmth and competence. The implications of these findings are discussed in detail. In the second study, the feasibility and initial efficacy of a relational chatbot-based intervention on physical activity behavior outcomes were evaluated. The study was conducted over a one-week period, during which objective physical activity data were collected using smartphone pedometers. The primary findings revealed that the control chatbot group experienced a significant decrease in steps on the final day, whereas the group interacting with the relational chatbot maintained their step counts and step goal achievements. Additionally, individuals who engaged with the relational chatbot reported a stronger social bond compared to those in the control chatbot condition. The study also observed a high retention rate and engagement, indicating good feasibility of the intervention. Overall, these studies illuminate the potential of relational chatbots to foster relationships with human users and improve physical activity outcomes. Leveraging the relationship-building capabilities of chatbots holds significant value in the development of cost-effective, accessible, and sustainable interventions. This approach proves particularly beneficial for individuals with limited access to conventional physical activity interventions. Theoretical contributions regarding the effects and mechanisms of human-chatbot relationships, as well as practical and ethical implications, are further explored and discussed.

          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2023)

          Background

          Despite the health benefits of engaging in regular physical activity (PA), the majority of American adults do not meet the PA guidelines for aerobic and muscle-strengthening activities. Self-efficacy, the belief that one can execute specific actions, has been suggested to be a strong determinant of PA behaviors. With the increasing availability of digital technologies, collecting longitudinal real-time self-efficacy and PA data has become feasible. However, evidence in longitudinal real-time assessment of self-efficacy in relation to objectively measured PA is scarce.

          Objective

          This study aimed to examine a novel approach to measure individuals' real-time weekly self-efficacy in response to their personalized PA goals and performance over the 12-week intervention period in community-dwelling women who were not meeting PA guidelines.

          Methods

          In this secondary data analysis, 140 women who received a 12-week PA intervention were asked to report their real-time weekly self-efficacy via a study mobile app. PA (daily step counts) was measured by an accelerometer every day for 12 weeks. Participants rated their self-efficacy on meeting PA goals (ranging from "not confident" to "very confident") at the end of each week via a mobile app. We used a logistic mixed model to examine the association between weekly self-efficacy and weekly step goal success, controlling for age, BMI, self-reported White race, having a college education or higher, being married, and being employed.

          Results

          The mean age was 52.7 (SD 11.5, range 25-68) years. Descriptive analyses showed the dynamics of real-time weekly self-efficacy on meeting PA goals and weekly step goal success. The majority (74.4%) of participants reported being confident in the first week, whereas less than half of them (46.4%) reported confidence in the final week of the intervention. Participants who met weekly step goals were 4.41 times more likely to be confident about achieving the following week's step goals than those who did not meet weekly step goals (adjusted odds ratio 4.41; 95% CI 2.59-7.50; P<.001). Additional analysis revealed that participants who were confident about meeting the following week's step goals were 2.07 times more likely to meet their weekly step goals in the following week (adjusted odds ratio 2.07; 95% CI 1.16-3.70; P=.01). The significant bidirectional association between real-time self-efficacy and weekly step goal success was confirmed in a series of sensitivity analyses.

          Conclusions

          This study demonstrates the potential utility of a novel approach to examine self-efficacy in real time for analysis of self-efficacy in conjunction with objectively measured PA. Discovering the dynamic patterns and changes in weekly self-efficacy on meeting PA goals may aid in designing a personalized PA intervention. Evaluation of this novel approach in an RCT is warranted.
            Cover page: A Novel Approach to Assess Weekly Self-efficacy for Meeting Personalized Physical Activity Goals Via a Cellphone: 12-Week Longitudinal Study
            • Article
            • Peer Reviewed
            UC Davis Previously Published Works (2021)

            Background

            This systematic review aimed to evaluate AI chatbot characteristics, functions, and core conversational capacities and investigate whether AI chatbot interventions were effective in changing physical activity, healthy eating, weight management behaviors, and other related health outcomes.

            Methods

            In collaboration with a medical librarian, six electronic bibliographic databases (PubMed, EMBASE, ACM Digital Library, Web of Science, PsycINFO, and IEEE) were searched to identify relevant studies. Only randomized controlled trials or quasi-experimental studies were included. Studies were screened by two independent reviewers, and any discrepancy was resolved by a third reviewer. The National Institutes of Health quality assessment tools were used to assess risk of bias in individual studies. We applied the AI Chatbot Behavior Change Model to characterize components of chatbot interventions, including chatbot characteristics, persuasive and relational capacity, and evaluation of outcomes.

            Results

            The database search retrieved 1692 citations, and 9 studies met the inclusion criteria. Of the 9 studies, 4 were randomized controlled trials and 5 were quasi-experimental studies. Five out of the seven studies suggest chatbot interventions are promising strategies in increasing physical activity. In contrast, the number of studies focusing on changing diet and weight status was limited. Outcome assessments, however, were reported inconsistently across the studies. Eighty-nine and thirty-three percent of the studies specified a name and gender (i.e., woman) of the chatbot, respectively. Over half (56%) of the studies used a constrained chatbot (i.e., rule-based), while the remaining studies used unconstrained chatbots that resemble human-to-human communication.

            Conclusion

            Chatbots may improve physical activity, but we were not able to make definitive conclusions regarding the efficacy of chatbot interventions on physical activity, diet, and weight management/loss. Application of AI chatbots is an emerging field of research in lifestyle modification programs and is expected to grow exponentially. Thus, standardization of designing and reporting chatbot interventions is warranted in the near future.

            Systematic review registration

            International Prospective Register of Systematic Reviews (PROSPERO): CRD42020216761 .
              Cover page: A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss
              • Article
              • Peer Reviewed
              UC Davis Previously Published Works (2021)

              Background

              As of May 9, 2021, the United States had 32.7 million confirmed cases of COVID-19 (20.7% of confirmed cases worldwide) and 580,000 deaths (17.7% of deaths worldwide). Early on in the pandemic, widespread social, financial, and mental insecurities led to extreme and irrational coping behaviors, such as panic buying. However, despite the consistent spread of COVID-19 transmission, the public began to violate public safety measures as the pandemic got worse.

              Objective

              In this work, we examine the effect of fear-inducing news articles on people's expression of anxiety on Twitter. Additionally, we investigate desensitization to fear-inducing health news over time, despite the steadily rising COVID-19 death toll.

              Methods

              This study examined the anxiety levels in news articles (n=1465) and corresponding user tweets containing "COVID," "COVID-19," "pandemic," and "coronavirus" over 11 months, then correlated that information with the death toll of COVID-19 in the United States.

              Results

              Overall, tweets that shared links to anxious articles were more likely to be anxious (odds ratio [OR] 2.65, 95% CI 1.58-4.43, P<.001). These odds decreased (OR 0.41, 95% CI 0.2-0.83, P=.01) when the death toll reached the third quartile and fourth quartile (OR 0.42, 95% CI 0.21-0.85, P=.01). However, user tweet anxiety rose rapidly with articles when the death toll was low and then decreased in the third quartile of deaths (OR 0.61, 95% CI 0.37-1.01, P=.06). As predicted, in addition to the increasing death toll being matched by a lower level of article anxiety, the extent to which article anxiety elicited user tweet anxiety decreased when the death count reached the second quartile.

              Conclusions

              The level of anxiety in users' tweets increased sharply in response to article anxiety early on in the COVID-19 pandemic, but as the casualty count climbed, news articles seemingly lost their ability to elicit anxiety among readers. Desensitization offers an explanation for why the increased threat is not eliciting widespread behavioral compliance with guidance from public health officials. This work investigated how individuals' emotional reactions to news of the COVID-19 pandemic manifest as the death toll increases. Findings suggest individuals became desensitized to the increased COVID-19 threat and their emotional responses were blunted over time.
                Cover page: Desensitization to Fear-Inducing COVID-19 Health News on Twitter: Observational Study
                • Article
                • Peer Reviewed
                UC Davis Previously Published Works (2021)
                [This corrects the article DOI: 10.2196/26876.].
                  Cover page: Metadata Correction: “Desensitization to Fear-Inducing COVID-19 Health News on Twitter: Observational Study”
                  • Article
                  • Peer Reviewed
                  UC Davis Previously Published Works (2022)

                  Background

                  Approximately 30% to 40% of older adults have hyperkyphosis, defined as excessive curvature of the thoracic spine. Hyperkyphosis is associated with increased morbidity and mortality. This study aimed to determine whether hyperkyphosis (Cobb's angle) and upper extremity tasks were independently associated with the 6-min walk test (6MWT) in community-dwelling older adults with hyperkyphosis.

                  Methods

                  In this cross-sectional study, we studied 71 women and 28 men aged 60-87 from the study of hyperkyphosis, exercise, and function trial (SHEAF) who had kyphosis, 3 timed upper extremity tasks and the 6MWT assessed at their baseline visit. We used standing lateral spine radiographs and a standardized protocol for thoracic kyphosis (T4-T12) to measure Cobb angle of kyphosis. In addition, 3 activity of daily living (ADL) extremity tests (putting on and removing a laboratory coat, picking up a penny from the floor, and lifting a 7-lb. book to a shelf) were used.

                  Results

                  The mean ± SD age was 70.1 ± 6.1 years. The mean ± SD Cobb angle of kyphosis was 57.4 ± 12.5 degrees. On average ± SD, the participants walked 504.8 ± 84.2 m in 6 min and took 2.4 ± 2.2 prescription medications. The mean ± SD height was 164.7 ± 8.5 cm, weight was 68.7 ± 13.1 kg, and BMI was 25.2 ± 4.0 kg/m2. Multivariate regression revealed that age, height, upper extremity book lift task, and the number of prescribed medications were significant predictors of performance on the 6MWT (p < 0.05).

                  Conclusions

                  While kyphosis was not associated with the 6MWT, timed tests of upper extremity function indicated that upper body dynamics can affect walking performance. In addition, sociodemographic factors and the number of prescribed medications were significant contributing factors to the 6MWT in older adults with mild to moderate hyperkyphosis. These results illustrate multifactorial influences on physical performance and the need for an integrated and targeted approach in helping older hyperkyphotic adults maintain healthy physical functioning as they age.
                    Cover page: Slower upper extremity function in older adults with hyperkyphosis negatively impacts the 6-min walk test
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