Emil Coman

This study examined the convergent and predictive validity of objective and subjective food swamp measures within a Community-Based Participatory Research project conducted in six neighborhoods. Using resident survey data and geocoded audit data for 20 food store types, food swamps were measured using three indices: Food Swamp Index (FSI), modified Retail Food Environment Index (mRFEI), and Physical Food Environment Index (PFEI), calculated within a ½ mile buffer of respondents’ homes. Convergent validity was assessed using Spearman correlations. At the individual level, no significant correlations were found between objective and subjective measures (all rho < 0.06, p > .05). At the neighborhood level, results varied by measurement approach: as continuous variables, only mRFEI showed a significant but divergent correlation (rho = -0.81, p < .001); when dichotomized, mRFEI showed perfect convergent validity (rho = 1.00, p < .001), PFEI showed modest convergent validity (rho = 0.12, p = .039), while FSI showed divergent validity (rho = -0.28, p < .001). Subjective measures consistently predicted shopping frequency at unhealthy food stores (all p < .004), while objective measures showed null associations. These findings suggest subjective measures better capture the behaviorally relevant food environment and may be preferable for research examining dietary behaviors.

The study examined the relationship between food swamps and self-reported food shopping frequency and perceived food access, while considering transportation mode and travel time. This Community-Based Participatory Research study surveyed residents from six neighborhoods in Hartford. Individual-level food swamp exposure (the ratio of unhealthy to healthy food stores within a 0.5-mile radius of participants’ homes) was measured both objectively (using GIS-based methods) and subjectively (through self-reporting). Poisson regression models assessed the associations between food swamps and outcomes (shopping frequency by store types and perceived access to food), with transportation mode and travel time as moderators. Of 304 participants, 51% lived in subjective (n = 153) and 71% in objective (n = 198) food swamps. Food swamp exposure was associated with greater shopping frequency at unhealthy outlets (β = 0.12, p < 0.001), less access to healthier food (β = −0.13, p < 0.001), and increased access to unhealthy food (β = 0.08, p < 0.001). Transportation significantly moderates these relationships; bus riders reported the highest rates of unhealthy food purchasing (β = 0.17, p < 0.001). Longer travel times increased both healthy and unhealthy food access (β = 0.01, p < 0.001 for each). Food swamps interact with public transportation to contribute to food shopping and access, underscoring the need for integrated food and transportation policies to address structural barriers and promote health equity in underserved urban communities.

Background: Since COVID-19 rapidly made telemedicine a necessity, it is clear that virtual patient visits are going to be part of the new norm in continued outpatient care as we move into a postpandemic reality. However, we are still learning about patients’ experiences and preferences amid the rapid and widespread deployment of telemedicine. Objective: The aim of this paper is to determine patients’ satisfaction with and experiences of telehealth services during the COVID-19 pandemic among those seeking care at Community Health Center Association of Connecticut member clinics. Methods: Data were collected using a 24-question phone survey, which asked about telehealth use, frequency of telehealth visits, and barriers experienced. Participants were eligible if they aged 18 years or older, were English speaking, and were receiving care at 1 of 3 participating Community Health Center Association of Connecticut clinics. Results: A total of 383 participants completed the phone survey throughout July 2021. The median age grouping was between 55 and 59 years, and the majority (63%) were female. Since COVID-19, in total, 78% reported having one or more audio-only telehealth visits (from 31% before), and 53% had one or more video telehealth visit (from 13% before). Most reported being very satisfied with their visits (86%) and that they felt confident in their provider’s ability to address their needs (74%). Most did not experience technical problems or have difficulty understanding how to connect to their provider. Even among older participants (60 years and older), only 28% reported having difficulty understanding how to connect to their provider, compared with 23% of 40- to 59-year-old patients and 18% of 18- to 39-year-old patients. Moreover, 45% reported being very likely to continue using telehealth even after the pandemic. However, 52% would have liked the option of in-person visits if they had been available in the past year. Conclusions: These results suggest that most patients find telehealth visits an appropriate and accessible means of accessing health care, though some still like the option of seeing their provider in person. Future work should compare provider and patient experiences and identify optimal means of making the encounters mutually satisfying and beneficial. Conflicts of Interest: None declared.

Background: Broad health disparities (HDs) persist in Connecticut and the United States between minority and White patients, especially in access to and the utilization of behavioral telehealth services. Objective: We aimed to determine the geographic distribution of HDs in Connecticut between Black female and White female adults in Medicaid behavioral telehealth utilization in 2019 and 2020. Methods: We used the following spatial Connecticut data: (1) behavioral health utilization from Medicaid claims, from the Connecticut Department of Social Services, for the third quarters of 2019 and 2020; (2) mental health and drug and alcohol treatment facilities and ZCTA (ZIP Code Tabulation Area)-level descriptors from PolicyMap; and (3) Connecticut ZIP-to-ZCTA crosswalk data. Data were joined spatially, merged, and analyzed using spatial autoregressive models in Stata 17 (with outcome, predictors, and errors spatial lags). We computed ZCTA-level HDs comparing Black and White adult female Medicaid beneficiaries’ rates of face-to-face and telehealth behavioral services utilization. Spatial regressions were used to test spatial effects, which are extensions of classic regressions, that add neighbors’ effects to covariates. Results: Distances to nearest treatment facility vary quite widely in Connecticut by ZCTAs, from 0.06 mile to 13.4 miles—3.5 miles on average. The overall White female versus Black female HDs in behavioral health care utilization were impacted by the distance to the nearest facility, such that ZCTAs farther away from the nearest facility display larger Black versus White HDs—nearly statistically significant effect in 2019 and significant effect in 2020. In 2020, in ZCTAs situated farther away from treatment facilities, both White female and Black female Medicaid patients had higher telebehavioral health utilization (spatial effects +1.3% points and +2.0% points, respectively, for 1 more mile farther away). The differential Black versus White female HDs in telebehavioral health care utilization were not impacted by distance to nearest facility, according to the total effect (direct and indirect through neighboring ZCTAs; P=.26). Conclusions: Quantitative analyses indicate broad differences in Medicaid enrollment and the utilization of behavioral health services among Black and White female Medicaid recipients in Connecticut and that these differences were rather stable between 2019 and 2020. It appears that the expansion of telebehavioral health services in 2020 enhanced the access to treatment among residents who were located furthest away from providing facilities.

BACKGROUND Broad health disparities (HDs) persist in Connecticut and the United States between minority and White patients, especially in access to and the utilization of behavioral telehealth services. OBJECTIVE We aimed to determine the geographic distribution of HDs in Connecticut between Black female and White female adults in Medicaid behavioral telehealth utilization in 2019 and 2020. METHODS We used the following spatial Connecticut data: (1) behavioral health utilization from Medicaid claims, from the Connecticut Department of Social Services, for the third quarters of 2019 and 2020; (2) mental health and drug and alcohol treatment facilities and ZCTA (ZIP Code Tabulation Area)-level descriptors from PolicyMap; and (3) Connecticut ZIP-to-ZCTA crosswalk data. Data were joined spatially, merged, and analyzed using spatial autoregressive models in Stata 17 (with outcome, predictors, and errors spatial lags). We computed ZCTA-level HDs comparing Black and White adult female Medicaid beneficiaries’ rates of face-to-face and telehealth behavioral services utilization. Spatial regressions were used to test spatial effects, which are extensions of classic regressions, that add neighbors’ effects to covariates. RESULTS Distances to nearest treatment facility vary quite widely in Connecticut by ZCTAs, from 0.06 mile to 13.4 miles—3.5 miles on average. The overall White female versus Black female HDs in behavioral health care utilization were impacted by the distance to the nearest facility, such that ZCTAs farther away from the nearest facility display larger Black versus White HDs—nearly statistically significant effect in 2019 and significant effect in 2020. In 2020, in ZCTAs situated farther away from treatment facilities, both White female and Black female Medicaid patients had higher telebehavioral health utilization (spatial effects +1.3% points and +2.0% points, respectively, for 1 more mile farther away). The differential Black versus White female HDs in telebehavioral health care utilization were not impacted by distance to nearest facility, according to the total effect (direct and indirect through neighboring ZCTAs; P=.26). CONCLUSIONS Quantitative analyses indicate broad differences in Medicaid enrollment and the utilization of behavioral health services among Black and White female Medicaid recipients in Connecticut and that these differences were rather stable between 2019 and 2020. It appears that the expansion of telebehavioral health services in 2020 enhanced the access to treatment among residents who were located furthest away from providing facilities.

Safety-critical systems are often equipped with warning mechanisms to alert users regarding imminent system failures. However, they can suffer from false alarms, and affect users emotions and trust in the system negatively. While providing feedback could be an effective way to calibrate trust under such scenarios, the effects of feedback and warning reliability on users emotions, trust, and compliance behavior is not clear. This paper investigates this by designing a 2 (feedback: present/absent) 2 (warning reliability: high/low) 4 (sessions) mixed design study where participants interacted with a simulated unmanned aerial vehicle (UAV) system to identify and neutralize enemy targets. Results indicated that feedback containing both correctness and affective components decreased users positive emotions and trust in the system, and increased loneliness and hostility (negative) emotions. Emotions were found to mediate the relationship between feedback and trust. Implications of our findings for designing feedback and calibration of trust are discussed in the paper.

Objective: This study examined how work and family demands affect depressive symptoms, and the mediating roles of work-to-family conflict and family-to-work conflict in a sample of correctional supervisors. Methods: Using a cross-sectional design, correctional supervisors working in a Northeastern state (n = 156) participated in an online survey. Structural equation modeling was used to examine direct and indirect effects between study variables. Results: Amount of overtime hours worked significantly predicted work-to-family conflict (β = 0.18, P < 0.05), and work-to-family conflict significantly predicted greater depressive symptoms (β = 0.61, P < 0.01). Overtime work also had an indirect effect on depressive symptoms through work-to-family conflict (β = 0.11 [95% CI 0.001–0.42]). No other statistically significant effects of relevance were found. Conclusions: Working overtime had an indirect effect on correctional supervisors’ depressive symptoms, mediated by work-to-family conflict.

We evaluate the outcomes and processes of a video and web-based worksite exercise intervention for sedentary office workers in China, in a 2-arm cluster-randomised wait-list control trial (n = 282: intervention (INT) n = 196 and wait-list control (WLC) n = 86). Eligible clusters were two sites of a major organisation in China randomly allocated to each group (INT: Guangzhou; WLC: Beijing); eligible participants were site employees (n = 690). A theoretically informed digital workplace intervention (Move-It) involving a 10 min Qigong exercise session (video demonstration via website) was delivered twice a day at set break times during the working day for 12 consecutive weeks. Individual-level outcomes were assessed. Participants’ physical activity increased significantly from baseline to post-intervention similarly in both the intervention and the control group. There was a significantly smaller increase in weekday sitting hours in intervention than controls (by 4.66 h/week), and work performance increased only in the control group. Process evaluation (including six focus groups) was conducted using the RE-AIM (reach, effectiveness, adoption, implementation and maintenance) framework. The intervention had wide reach and was successfully marketed to all employees with good uptake. The participatory approach increased perceived organisational support and enhanced adoption. The intervention was implemented broadly as planned. Qigong worksite exercise intervention can be successfully delivered to sedentary office workers in China using video and web-based platforms. It may increase physical activity and does not adversely affect perceived work performance. The study highlights the complexity of conducting health promotion research in real-world organisational settings.

Trust in automation has been largely studied through a cognitive lens, though theories suggest that emotions play an important role. Understanding the affective aspects of human-automation trust can inform the design of systems that garner appropriate trust calibration. Toward this, we designed 4 videos describing a hypothetical drone system: one control, and three with additional performance or process information, or both. Participants reported the intensity of 19 emotions they would anticipate as system operator, perceptions of the system’s trustworthiness, individual differences, and perceptions of the institution behind the system. Emotions factored into hostility, positive, anxiety, and loneliness components that were regressed on system information, individual differences, and institutional trust. We found that financial risk-taking, recreational risk-taking, and propensity to trust influenced the intensity of different emotion factors. Moreover, greater perceptions of the institution’s ability led to more intense hostility emotions, greater perceptions of the institution’s benevolence led to less intense hostility, and integrity perceptions decreased anxiety and increased positive emotions. Lastly, structural assurance led to less intense hostility and anxiety and more intense positive emotions. These results offer support for the relationship between human-automation trust and emotions, warranting future research on how operator emotions can be addressed to improve trust calibration.