BMC Public Health

The literature on therapeutic landscapes highlights that the university campus landscape has restorative effects on students. This deserves more scholarly attention since mental health has become an important issue among university students. However, existing empirical studies have revealed mixed evidence with little attention to the heterogeneity across the design and, therefore, the potential therapeutic effects across different landscapes. This research examined how 13 landscape sites on a university campus might be differentially related to student well-being. These sites were identified from a variety of sources (campus design documents, photos used in the university’s social media posts, and interviews with a small group of students) to represent a comprehensive list of places that students might visit. The data was collected in a large online survey of a Chinese university (n = 2,528). We asked about students’ use of individual landscape sites and the associated motivations for visits, and measured well-being using a perceived stress scale and overall evaluation of the happiness level. Bivariate analysis was used to explore the zero-order associations between landscape use and well-being. OLS (for stress) and logistic regressions (for happiness) were conducted to further evaluate the associations after controlling the student background variables and potential correlations of uses across different landscapes. Among 13 landscape sites, four sites had significant positive associations with either or both measures of well-being after controlling for the student characteristics and use of the other landscape sites. There was also an additive benefit of visiting more landscapes. Compared to those who did not frequently visit any of the sites, well-being had a significant stepwise increase among those who frequently visited one or two and more sites. One site that was significantly related to both measures of well-being only offered distant views of landscapes, but it was right next to the study areas. This study demonstrates the heterogeneity of restorative effects across different landscapes on campus. The findings suggest that effective landscape design that aims to promote student well-being should be placed close to stressors (i.e., where they study), and between where they study and live to offer students opportunities to break from the common routines and to relax. The findings hold greater relevance for universities in China and institutions with similar student campus lifestyles, occupancies, and behavior patterns worldwide.

In India and other low- and middle-income countries, multiple family and community members are influential in caregivers’ perceptions of vaccination. Existing literature indicates the primary caregiver, typically the mother, is instrumental in vaccine decision-making, but this may vary in contexts. We investigated the role of stakeholders in India who influence caregivers’ vaccination perceptions, as this is essential to developing strategies to promote vaccine acceptance and improve uptake. This research was conducted in 2019 in Mewat District in Haryana, an area in India with extremely low vaccination coverage. We conducted six focus group discussions with 60 participants in the following categories: fathers of children under-5 years old, expectant mothers, mothers-in-law, community health workers, and community influencers such as locally elected officials and religious leaders. Our results highlighted four themes that influence vaccine uptake. First, while caregivers associated vaccination with reductions in specific diseases, they also noted that vaccination services brought broad health gains, including improved nutrition, antenatal guidance, and social support. Second, community health workers critically influenced, positively or negatively, caregivers’ vaccination perceptions. Third, community health workers faced gaps in their education such as limited training on vaccine side-effects, placing them at a disadvantage when dealing with families. Finally, we found that mothers-in-law, fathers, and religious leaders influence caregivers’ perceptions of vaccination. Communication of broader benefits of vaccines and vaccination services by community health workers could be impactful in increasing vaccine acceptance. Vaccine uptake could potentially be improved by facilitating community health workers’ ownership over vaccine acceptance and uptake by involving them in the design and implementation of interventions to target mothers and mothers-in-law. A ‘bottom-up’ approach, leveraging community health workers’ knowledge to design interventions, and giving a voice to key members of the household and society beyond mothers alone, may sustain health improvement in low vaccine coverage areas.

Countdown to 2015 was a multi-institution consortium tracking progress towards Millennium Development Goals (MDGs) 4 and 5. Case studies to explore factors contributing to progress (or lack of progress) in reproductive, maternal, newborn and child health (RMNCH) were undertaken in: Afghanistan, Bangladesh, China, Ethiopia, Kenya, Malawi, Niger, Pakistan, Peru, and Tanzania. This paper aims to identify cross-cutting themes on how and why these countries achieved or did not achieve MDG progress. Applying a standard evaluation framework, analyses of impact, coverage and equity were undertaken, including a mixed methods analysis of how these were influenced by national context and coverage determinants (including health systems, policies and financing). The majority (7/10) of case study countries met MDG-4 with over two-thirds reduction in child mortality, but none met MDG-5a for 75 % reduction in maternal mortality, although six countries achieved >75 % of this target. None achieved MDG-5b regarding reproductive health. Rates of reduction in neonatal mortality were half or less that for post-neonatal child mortality. Coverage increased most for interventions administered at lower levels of the health system (e.g., immunisation, insecticide treated nets), and these experienced substantial political and financial support. These interventions were associated with ~30–40 % of child lives saved in 2012 compared to 2000, in Ethiopia, Malawi, Peru and Tanzania. Intrapartum care for mothers and newborns -- which require higher-level health workers, more infrastructure, and increased community engagement -- showed variable increases in coverage, and persistent equity gaps. Countries have explored different approaches to address these problems, including shifting interventions to the community setting and tasks to lower-level health workers. These Countdown case studies underline the importance of consistent national investment and global attention for achieving improvements in RMNCH. Interventions with major global investments achieved higher levels of coverage, reduced equity gaps and improvements in associated health outcomes. Given many competing priorities for the Sustainable Development Goals era, it is essential to maintain attention to the unfinished RMNCH agenda, particularly health systems improvements for maternal and neonatal outcomes where progress has been slower, and to invest in data collection for monitoring progress and for rigorous analyses of how progress is achieved in different contexts.

Gender dynamics influence household-level decision-making about health behaviors and subsequent outcomes. Health and development programs in Niger are addressing gender norms through social and behavior change (SBC) approaches, yet not enough is known about how health care decisions are made and if gender-sensitive programs influence the decision-making process. We qualitatively explored how households make decisions about family planning, child health, and nutrition in the Maradi and Zinder regions, Niger, within the context of a multi-sectoral integrated SBC program. We conducted 40 in-depth interviews with married women (n = 20) and men (n = 20) between 18 and 61 years of age. Male heads of household were central in health decisions, yet women were also involved and expressed the ability to discuss health issues with their husbands. Participants described three health decision-making pathways: (1st pathway) wife informs husband of health issue and husband solely decides on the solution; (2nd pathway) wife informs husband of health issue, proposes the solution, husband decides; and (3rd pathway) wife identifies the health issue and both spouses discuss and jointly identify a solution. Additionally, the role of spouses, family members, and others varied depending on the health topic: family planning was generally discussed between spouses, whereas couples sought advice from others to address common childhood illnesses. Many participants expressed feelings of shame when asked about child malnutrition. Participants said that they discussed health more frequently with their spouses’ following participation in health activities, and some men who participated in husbands’ schools (a group-based social and behavior change approach) reported that this activity influenced their approach to and involvement with household responsibilities. However, it is unclear if program activities influenced health care decision-making or women’s autonomy. Women are involved to varying degrees in health decision-making. Program activities that focus on improving communication among spouses should be sustained to enhance women role in health decision-making. Male engagement strategies that emphasize spousal communication, provide health information, discuss household labor may enhance couple communication in Niger. Adapting the outreach strategies and messages by healthcare topic, such as couples counseling for family planning versus community-based nutrition messaging, are warranted.

Obesity and other nutrition-related chronic disease rates are high in American Indian (AI) populations, and an urgent need exists to identify evidence-based strategies for prevention and treatment. Multi-level, multi-component (MLMC) interventions are needed, but there are significant knowledge gaps on how to deliver these types of interventions in low-income rural AI communities. OPREVENT2 is a MLMC intervention targeting AI adults living in six rural reservations in New Mexico and Wisconsin. Aiming to prevent and reduce obesity in adults by working at multiple levels of the food and physical activity (PA) environments, OPREVENT2 focuses on evidence-based strategies known to increase access to, demand for, and consumption of healthier foods and beverages, and increase worksite and home-based opportunities for PA. OPREVENT2 works to create systems-level change by partnering with tribal stakeholders, multiple levels of the food and PA environment (food stores, worksites, schools), and the social environment (children as change agents, families, social media). Extensive evaluation will be conducted at each level of the intervention to assess effectiveness via process and impact measures. Novel aspects of OPREVENT2 include: active engagement with stakeholders at many levels (policy, institutional, and at multiple levels of the food and PA system); use of community-based strategies to engage policymakers and other key stakeholders (community workshops, action committees); emphasis on both the built environment (intervening with retail food sources) and the social environment. This paper describes the design of the intervention and the evaluation plan of the OPREVENT2. Clinical Trial Registration: NCT02803853 (June 10, 2016)

To date, research assessing discrimination has employed primarily explicit measures (i.e., self-reports), which can be subject to intentional and social desirability processes. Only a few studies, focusing on sex and race/ethnicity discrimination, have relied on implicit measures (i.e., Implicit Association Test, IAT), which permit assessing mental representations that are outside of conscious control. This study aims to advance measurement of discrimination by extending the application of implicit measures to multiple types of discrimination and optimizing the time required for the administration of these instruments. Between September 27th 2019 and February 9th 2020, we conducted six experiments (984 participants) to assess implicit and explicit discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age. Implicit discrimination was measured by using the Brief-Implicit Association Test (B-IAT), a new validated version of the IAT developed to shorten the time needed (from ≈15 to ≈2 min) to assess implicit mental representations, while explicit discrimination was assessed using self-reported items. Among participants (mean age = 37.8), 68.6% were White Non-Hispanic; 69% were females; 76.1% were heterosexual; 90.7% were gender conforming; 52.8% were medium weight; and 41.5% had an advanced level of education. Overall, we found implicit and explicit recognition of discrimination towards all the target groups (stronger for members of the target than dominant groups). Some exceptions emerged in experiments investigating race/ethnicity and weight discrimination. In the racism experiment, only people of Color showed an implicit recognition of discrimination towards the target group, while White people were neutral. In the fatphobia experiment, participants who were not heavy showed a slight implicit recognition of discrimination towards the dominant group, while heavy participants were neutral. This study provides evidence that the B-IAT is a valuable tool for quickly assessing multiple types of implicit discrimination. It shows also that implicit and explicit measures can display diverging results, thus indicating that research would benefit from the use of both these instruments. These results have important implications for the assessment of discrimination in health research as well as in social and psychological science.

Sampling a small number of participants from an entire country is not straightforward. In this case, researchers reluctantly sample from a single setting or few settings, which limits the generalizability of findings. Therefore, there is a need to design efficient sampling method for small sample size surveys that can produce generalizable results at the country level. Data comprised of twenty proxy variables to measure health services demands, structures, and outcomes of 413 districts of Iran. We used two data mining methods (hierarchical clustering method (HCM) and model-based clustering method (MCM)) to create homogenous groups of districts, i.e., strata based on these variables. We compared the internal and stability validity of the methods by statistical indices. An expert group checked the face validity of the methods, particularly regarding the total number of strata and the combination of districts in each stratum. The efficiency of selected method, which is measured by the inverse of variance, was compared with a simple random sampling (SRS) through simulation. The sampling design was tested in a national study in Iran, which aimed to evaluate the quality and costs of medical care for eight selected diseases by only recruiting 300 participants per disease at the country level. MCM and HCM divided the districts into eight and two clusters, respectively. The measures of internal and stability validity showed that clusters created by MCM were more separated, compact, and stable, thus forming our optimum strata. The probability of death from stroke, chronic obstructive pulmonary disease, and in-hospital mortality rate were the most important indicators that distinguished the eight strata. Based on the simulation results, MCM increased the efficiency of the sampling design up to 1.7 times compared to SRS. The use of data mining improved the efficiency of sampling up to 1.7 times greater than SRS and markedly reduced the number of strata to eight in the entire country. The proposed sampling design also identified key variables that could be used to classify districts in Iran for sampling from these target populations in the future studies.

Current approaches for estimating social mixing patterns and infectious disease transmission at mass gatherings have been limited by various constraints, including low participation rates for volunteer-based research projects and challenges in quantifying spatially and temporally accurate person-to-person interactions. We developed a proof-of-concept project to assess the use of automated video analysis for estimating contact rates of attendees of the GameFest 2013 event at Rensselaer Polytechnic Institute (RPI) in Troy, New York. Video tracking and analysis algorithms were used to estimate the number and duration of contacts for 5 attendees during a 3-minute clip from the RPI video. Attendees were considered to have a contact event if the distance between them and another person was ≤1 meter. Contact duration was estimated in seconds. We also simulated 50 attendees assuming random mixing using a geo-spatially accurate representation of the same GameFest location. The 5 attendees had an overall median of 2 contact events during the 3-minute video clip (range: 0–6). Contact events varied from less than 5 seconds to the full duration of the 3-minute clip. The random mixing simulation was visualized and presented as a contrasting example. We were able to estimate the number and duration of contacts for 5 GameFest attendees from a 3-minute video clip that can be compared to a random mixing simulation model at the same location. The next phase will involve scaling the system for simultaneous analysis of mixing patterns from hours-long videos and comparing our results with other approaches for collecting contact data from mass gathering attendees.

Streetcar or train tracks in urban areas are difficult for bicyclists to negotiate and are a cause of crashes and injuries. This study used mixed methods to identify measures to prevent such crashes, by examining track-related crashes that resulted in injuries to cyclists, and obtaining information from the local transit agency and bike shops. We compared personal, trip, and route infrastructure characteristics of 87 crashes directly involving streetcar or train tracks to 189 crashes in other circumstances in Toronto, Canada. We complemented this with engineering information about the rail systems, interviews of personnel at seven bike shops about advice they provide to customers, and width measurements of tires on commonly sold bikes. In our study, 32 % of injured cyclists had crashes that directly involved tracks. The vast majority resulted from the bike tire being caught in the rail flangeway (gap in the road surface alongside rails), often when cyclists made unplanned maneuvers to avoid a collision. Track crashes were more common on major city streets with parked cars and no bike infrastructure, with left turns at intersections, with hybrid, racing and city bikes, among less experienced and less frequent bicyclists, and among women. Commonly sold bikes typically had tire widths narrower than the smallest track flangeways. There were no track crashes in route sections where streetcars and trains had dedicated rights of way. Given our results, prevention efforts might be directed at individual knowledge, bicycle tires, or route design, but their potential for success is likely to differ. Although it may be possible to reach a broader audience with continued advice about how to avoid track crashes, the persistence and frequency of these crashes and their unpredictable circumstances indicates that other solutions are needed. Using tires wider than streetcar or train flangeways could prevent some crashes, though there are other considerations that lead many cyclists to have narrower tires. To prevent the majority of track-involved injuries, route design measures including dedicated rail rights of way, cycle tracks (physically separated bike lanes), and protected intersections would be the best strategy.