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Background & methods National protests in the summer of 2020 drew attention to the significant presence of police in marginalized communities. Recent social movements have called for substantial police reforms, including “defunding the police,” a phrase originating from a larger, historical abolition movement advocating that public investments be redirected away from the criminal justice system and into social services and health care. Although research has demonstrated the expansive role of police to respond a broad range of social problems and health emergencies, existing research has yet to fully explore the capacity for health insurance policy to influence rates of arrest in the population. To fill this gap, we examine the potential effect of Medicaid expansion under the Affordable Care Act (ACA) on arrests in 3,035 U.S. counties. We compare county-level arrests using FBI Uniform Crime Reporting (UCR) Program Data before and after Medicaid expansion in 2014–2016, relative to counties in non-expansion states. We use difference-in-differences (DID) models to estimate the change in arrests following Medicaid expansion for overall arrests, and violent, drug, and low-level arrests. Results Police arrests significantly declined following the expansion of Medicaid under the ACA. Medicaid expansion produced a 20–32% negative difference in overall arrests rates in the first three years. We observe the largest negative differences for drug arrests: we find a 25–41% negative difference in drug arrests in the three years following Medicaid expansion, compared to non-expansion counties. We observe a 19–29% negative difference in arrests for violence in the three years after Medicaid expansion, and a decrease in low-level arrests between 24–28% in expansion counties compared to non-expansion counties. Our main results for drug arrests are robust to multiple sensitivity analyses, including a state-level model. Conclusions Evidence in this paper suggests that expanded Medicaid insurance reduced police arrests, particularly drug-related arrests. Combined with research showing the harmful health consequences of chronic policing in disadvantaged communities, greater insurance coverage creates new avenues for individuals to seek care, receive treatment, and avoid criminalization. As police reform is high on the agenda at the local, state, and federal level, our paper supports the perspective that broad health policy reforms can meaningfully reduce contact with the criminal justice system under historic conditions of mass criminalization.

The aim of this article is to assess both the economic and social value of balneotherapy and spa tourism, being the first paper in carrying out this analysis. The study has been conducted in Maresme, a region of Catalonia, Spain. On the one hand, an Input-Output (IO) model with a Social Accounting Matrix (SAM) has been carried out to assess the economic value. On the other hand, a Cost-Benefit Analysis (CBA) has been used to monetise the social value in this region, taking into account, among other concepts, direct and indirect health profits, given that balneotherapy helps to alleviate various diseases. The results show that whereas the economic multiplier is 1.529 considering the direct and indirect effects and 1.712 taking into account also the induced effects, which are similar to health and medical tourism multipliers, social value generates additional positive value, given that the cost-benefit ratio is 1.858. The theoretical implications of the paper as well as the findings’ implications for policy so as to encourage investments in spa tourism are discussed.

Background During the Coronavirus Disease 2019 (COVID-19) pandemic, the number of consultations and diagnoses in primary care and referrals to specialist care declined substantially compared to prepandemic levels. Beyond deferral of elective non-COVID-19 care by healthcare providers, it is unclear to what extent healthcare avoidance by community-dwelling individuals contributed to this decline in routine healthcare utilisation. Moreover, it is uncertain which specific symptoms were left unheeded by patients and which determinants predispose to healthcare avoidance in the general population. In this cross-sectional study, we assessed prevalence of healthcare avoidance during the pandemic from a patient perspective, including symptoms that were left unheeded, as well as determinants of healthcare avoidance. Methods and findings On April 20, 2020, a paper COVID-19 survey addressing healthcare utilisation, socioeconomic factors, mental and physical health, medication use, and COVID-19–specific symptoms was sent out to 8,732 participants from the population-based Rotterdam Study (response rate 73%). All questionnaires were returned before July 10, 2020. By hand, prevalence of healthcare avoidance was subsequently verified through free text analysis of medical records of general practitioners. Odds ratios (ORs) for avoidance were determined using logistic regression models, adjusted for age, sex, and history of chronic diseases. We found that 1,142 of 5,656 included participants (20.2%) reported having avoided healthcare. Of those, 414 participants (36.3%) reported symptoms that potentially warranted urgent evaluation, including limb weakness (13.6%), palpitations (10.8%), and chest pain (10.2%). Determinants related to avoidance were older age (adjusted OR 1.14 [95% confidence interval (CI) 1.08 to 1.21]), female sex (1.58 [1.38 to 1.82]), low educational level (primary education versus higher vocational/university 1.21 [1.01 to 1.46), poor self-appreciated health (per level decrease 2.00 [1.80 to 2.22]), unemployment (versus employed 2.29 [1.54 to 3.39]), smoking (1.34 [1.08 to 1.65]), concern about contracting COVID-19 (per level increase 1.28 [1.19 to 1.38]) and symptoms of depression (per point increase 1.13 [1.11 to 1.14]) and anxiety (per point increase 1.16 [1.14 to 1.18]). Study limitations included uncertainty about (perceived) severity of the reported symptoms and potentially limited generalisability given the ethnically homogeneous study population. Conclusions In this population-based cross-sectional study, 1 in 5 individuals avoided healthcare during lockdown in the COVID-19 pandemic, often for potentially urgent symptoms. Healthcare avoidance was strongly associated with female sex, fragile self-appreciated health, and high levels of depression and anxiety. These results emphasise the need for targeted public education urging these vulnerable patients to timely seek medical care for their symptoms to mitigate major health consequences., Marije J. Splinter and colleagues assess the prevalence of healthcare avoidance during the COIVD-19 pandemic and investigate related determinants, Author summary Why was this study done? ➢ During the Coronavirus Disease 2019 (COVID-19) pandemic, consultation rates in both primary and specialist care declined compared to prepandemic levels, which can partially be attributed to the postponement or cancellation of elective and nonurgent medical care. ➢ It is unclear to what extent these declines in consultation rates could be related to healthcare avoidance by patients in the general population. ➢ To evaluate the collateral health damage of the COVID-19 pandemic, it is important to not only assess the prevalence of healthcare avoidance, but also for what symptoms healthcare was avoided and which determinants are associated with this behaviour. What did the researchers do and find? ➢ We sent out a paper questionnaire to 8,732 participants of the population-based Rotterdam Study containing several COVID-19–related subjects, such as healthcare utilisation, work status, mental and physical health, and concerns about contracting COVID-19. ➢ About 6,241 participants (73%) returned the questionnaire, of whom 5,656 participants (90.6%) were included in our analyses. We found that 1,142 of them (20.2%) avoided healthcare during the COVID-19 pandemic, often for symptoms that might have needed urgent medical evaluation, such as limb weakness (13.6%), palpitations (10.8%), and chest pain (10.2%). ➢ Determinants that were most strongly associated with healthcare avoidance were female sex, poor self-appreciated health, and high levels of depression and anxiety. What do these findings mean? ➢ The results of this population-based study suggest that healthcare avoidance contributed to the decline in consultation rates during the COVID-19 pandemic. Importantly, our findings suggest that this behaviour may be associated with certain vulnerable groups within the population. ➢ These findings should be interpreted in light of the limitations of this study, which include that the actual severity of the symptoms that were reported by participants is unknown, since they were not medically evaluated when they experienced these symptoms. ➢ The findings of this study can be used to develop policy interventions targeted to vulnerable individuals who may be more likely to exhibit healthcare avoiding behaviours.

Background mHealth innovations have been proposed as an effective solution to improving adolescent access to and use of Sexual and Reproductive Health (SRH) services; particularly in regions with deeply entrenched traditional social norms. However, research demonstrating the effectiveness and theoretical basis of the interventions is lacking. Aim Our aim was to describe mHealth intervention components, assesses their effectiveness, acceptability, and cost in improving adolescent’s uptake of SRH services in Sub-Saharan Africa (SSA). Methods This paper is based on a systematic review. Twenty bibliographic databases and repositories including MEDLINE, EMBASE, and CINAHL, were searched using pre-defined search terms. Of the 10, 990 records screened, only 10 studies met the inclusion criteria. The mERA checklist was used to critically assess the transparency and completeness in reporting of mHealth intervention studies. The behaviour change components of mHealth interventions were coded using the taxonomy of Behaviour Change Techniques (BCTs). The protocol was registered in the ‘International Prospective Register for Systematic Reviews’ (PROSPERO-CRD42020179051). Results The results showed that mHealth interventions were effective and improved adolescent’s uptake of SRH services across a wide range of services. The evidence was strongest for contraceptive use. Interventions with two-way interactive functions and more behaviour change techniques embedded in the interventions improved adolescent uptake of SRH services to greater extent. Findings suggest that mHealth interventions promoting prevention or treatment adherence for HIV for individuals at risk of or living with HIV are acceptable to adolescents, and are feasible to deliver in SSA. Limited data from two studies reported interventions were inexpensive, however, none of the studies evaluated cost-effectiveness. Conclusion There is a need to develop mHealth interventions tailored for adolescents which are theoretically informed and incorporate effective behaviour change techniques. Such interventions, if low cost, have the potential to be a cost-effective means to improve the sexual and reproductive health outcomes in SSA.

Using microdata from the Chinese General Social Survey (CGSS 2010), this paper investigates whether there are green returns to education in China, where educational attainment promotes pro-environmental attitudes and behaviors. We establish causality by exploiting the exogenous variation induced by the implementation of the Compulsory Schooling Law (CSL) in China. We find evidence that educational attainment is associated with higher levels of pro-environmental attitudes and behaviors, and these estimates are robust to various robustness checks. Further analysis reveals that the acquisition of environmental knowledge is the channel that drives the effect of education on pro-environmental attitudes and behaviors. Finally, the effects of education are heterogeneous across individuals.

Background Over the last decade, mobile health applications (mHealth App) have evolved exponentially to assess and support our health and well-being. Objective This paper presents an Artificial Intelligence (AI)-enabled mHealth app rating tool, called ACCU3RATE, which takes multidimensional measures such as user star rating, user review and features declared by the developer to generate the rating of an app. However, currently, there is very little conceptual understanding on how user reviews affect app rating from a multi-dimensional perspective. This study applies AI-based text mining technique to develop more comprehensive understanding of user feedback based on several important factors, determining the mHealth app ratings. Method Based on the literature, six variables were identified that influence the mHealth app rating scale. These factors are user star rating, user text review, user interface (UI) design, functionality, security and privacy, and clinical approval. Natural Language Toolkit package is used for interpreting text and to identify the App users’ sentiment. Additional considerations were accessibility, protection and privacy, UI design for people living with physical disability. Moreover, the details of clinical approval, if exists, were taken from the developer’s statement. Finally, we fused all the inputs using fuzzy logic to calculate the new app rating score. Results and conclusions ACCU3RATE concentrates on heart related Apps found in the play store and App gallery. The findings indicate the efficacy of the proposed method as opposed to the current device scale. This study has implications for both App developers and consumers who are using mHealth Apps to monitor and track their health. The performance evaluation shows that the proposed mHealth scale has shown excellent reliability as well as internal consistency of the scale, and high inter-rater reliability index. It has also been noticed that the fuzzy based rating scale, as in ACCU3RATE, matches more closely to the rating performed by experts.

Every day, people make many food decisions without thinking, repeatedly falling for the unhealthy option instead of the healthy option. While making these mindless decisions, people often rely on heuristics. In this paper, we demonstrate that these heuristics can be exploited to nudge consumers towards healthy alternatives. Specifically, we explore how the attraction effect (i.e., adding a decoy to a choice set) can nudge people to choose a healthy snack. The results of our choice experiment indicate that adding a decoy (i.e., a less attractive food alternative) to a self-control situation (i.e., choosing between a healthy and an unhealthy food alternative) can help people maintain self-control and choose the healthy option. This mixed choice set thus nudges people towards the healthy option. Moreover, our results show differential effects of the attraction effect depending on the (un)healthiness of the products in the choice set. Specifically, the attraction effect is prominent when the choice set consists of unhealthy products only (i.e., the unhealthy choice set), but not in the choice set that consists of only healthy products (i.e., healthy choice set). Importantly, our results indicate when the attraction effect can exploit consumers’ heuristics to help them make better, healthier food choices.