Exploring the impact of social protest on mental health: A study of the 2019 "Social Uprising" in Chile.

Socio-political conflicts, especially if accompanied by violent events, can affect the mental health of the population. This study aimed to estimate the causal effect of social protest-related violence on depressive symptoms during the 2019 social uprising in Chile. We collected population-representative data from a nationwide longitudinal survey (n = 2918), the fourth wave of which took place during the months of the social uprising in Chile (November 2019 and March 2020). Depressive symptoms were measured using the Patient Health Questionnaire-9, while violence related to social protest was measured as the perception of destruction at the neighbourhood level. To assess the casual relationship between destruction perception and depressive symptoms, we utilized an instrumental variable regression model. Our analysis controlled for relevant sociodemographic factors, participation in social protest, and history of mental health treatment. Results showed that perceived neighbourhood destruction during the 2019 social uprising significantly increased PHQ-9 score by 3.702 points, prevalence of moderate to severe depressive symptoms by 18.7%, and likelihood of having a Subthreshold or Major Depressive Episode by 15.2% (p < 0.01). The impact of perceived destruction on depressive symptoms varies by gender, with a significant effect found in men (an increase in depression indicators of 5.769 points, 26.8% and 23.0%, respectively, p < 0.05) but not in women. Stratified regression models by age demonstrate a positive association between the perception of neighbourhood destruction and depressive symptoms across all age groups, with a stronger effect observed among young adults. We found a casual effect of violence related to social protest on depressive symptoms. These findings have implications for the planning of social policies aimed at protecting the mental well-being of the population in times of increasing socio-political turmoil.

Suicide and quarantine during the COVID-19 pandemic: Do we know everything?

BACKGROUND: There is widespread concern over the impact of COVID-19 and lockdown measures on suicidal behaviour. We assessed their effects on suicide and hospitalization for attempted suicide during the initial phase of the pandemic in Chile. METHODS: We used panel data at the county and month level from January 1, 2016 to December 31, 2020 on suicides and related hospitalizations and a pandemic quarantine dataset. Poisson regression models and a difference-in-difference (DiD) methodology was used to estimate the impact of quarantine on both measures. FINDINGS: Suicide and hospitalizations for attempted suicide decreased (18% and 5.8%, respectively) during the COVID-19 outbreak in Chile (March-December 2020) compared to the same period in 2016-2019. The DiD analysis showed that there was at least a 13.2% reduction in suicides in quarantined counties relative to counties without such restrictions. This reduction was in male suicides and unaffected by age. There was no significant difference between quarantined and non-quarantined counties in terms of hospitalization for suicide attempts. CONCLUSIONS: This study shows a significant quarantine effect on reducing suicide during the initial phase of the COVID-19 pandemic in Chile. Changes in the number of hospitalizations for suicide attempts do not explain the differences between quarantined and non-quarantined counties.

A Longitudinal Nationwide Study of Psychological Distress During the COVID-19 Pandemic in Chile.

Background: Despite numerous efforts to assess the impact of the COVID-19 pandemic on mental health, there are few longitudinal studies that examine the change in the burden of psychological distress over time and its associated factors, especially in developing countries. Objective: The primary aim of this study was to assess the levels of psychological distress at two time points during the COVID-19 outbreak based on a representative community sample in Chile. The secondary aim was to identify groups that are more vulnerable to psychological distress during the pandemic. Methods: A nationally representative, longitudinal telephone survey of Chilean adults was conducted. This study analyses panel data from two waves in 2020: May 30 to June 10 and September 15 to October 9. A total of 823 people participated in both surveys. Changes in mental health outcomes (anxiety and depressive symptoms) were assessed, estimating the effect of demographic characteristics, psychosocial and economic factors, household conditions, and health status. Results: There was a significant increase in psychological distress (PHQ-4 ≥ 6) between Waves 1 (22.6%) and 2 (27.0%), especially among younger participants. Overall, the results of this study show that being female, living in or near the capital, living in overcrowded households and having a perceived lack of space in the home, loneliness or perceived social isolation, and having received mental health treatment within the last year are significantly associated with psychological distress over time (p < 0.05). Conclusion: This study highlights the need to implement psychosocial programs to protect people's psychological well-being, as well as social policies to improve household living conditions and levels of social connectedness during the COVID-19 outbreak.

Psychological distress during the COVID-19 epidemic in Chile: The role of economic uncertainty.

Previous research has shown that the COVID-19 outbreak, social distancing, and lockdown can affect people's psychological well-being. The aims of this study were (1) to estimate the extent to which perceptions and expectations regarding the social, economic, and domestic effects of the COVID-19 outbreak are associated with psychological distress and (2) to identify some demographic, psychosocial, and economic factors associated with increased vulnerability to psychological distress during the COVID-19 outbreak in Chile. 1078 people participated in a telephone survey between May 30 and June 10, 2020. The sample is representative of the Chilean adult population. Psychological distress was assessed through a questionnaire of anxious and depressive symptoms (Patient Health Questionnaire-4). We analyzed the data set using ordinary least-squares regression models, first estimating models for the entire sample, and then stratifying the sample into different groups to explore differences by gender and age. 19.2% of participants displayed significant psychological distress (PHQ-4 ≥ 6), with moderate to severe anxiety-depression symptoms being more prevalent in women than in men (23.9% vs 14.1%, χ2 16.78, p<0.001). The results of this study suggest that being a woman, feeling lonely and isolated, living in the areas hit hardest by the pandemic and lockdown, expecting a lack of income due to having to stop working as a consequence of the pandemic, and having a history of diagnosed mental disorders are significantly associated with psychological distress (p<0.05). The results of this study highlight the need to implement psychosocial programs to guard people's psychological well-being and social policies to address economic uncertainty during the current COVID-19 outbreak in Chile.

Encouraging Mammograms Using Behavioral Economics: A Randomized Controlled Trial in Chile.

OBJECTIVES: This article illustrates the effect of a direct mail campaign that used insights from behavioral economics and psychology to increase the number of free mammograms in Chilean women aged 50 years or older. METHODS: We hypothesized 4 barriers in obtaining a mammogram based on previous literature and focus group analysis. A behavioral economic approach providing incentives was used to help overcome these barriers. We accessed a unique data set, which comprised 12 000 women 50 years old or older, with private health insurance who have not had a mammogram for 24 or more months. We conducted a randomized controlled trial with 8 treatments, each involving a specific combination of messages. RESULTS: The intervention overall led to a 167% increase in the use of free mammograms, a 1.13% to 3.03% average increase from the control to treatment groups, respectively. Regarding barriers, we found that all messages were effective, with a slightly larger and persistent effect for the less complex ones in terms of information. This finding illustrates the benefits of keeping the message simple. CONCLUSIONS: Finally, these results suggest a successful public policy for increasing use of free mammography programs. Moreover, they are potentially transferable because the study considered decision-making heuristics that are not specific to one culture or social context.

The Effect Of The Affordable Care Act On Cancer Detection Among The Near-Elderly.

During the period 2014-16 the Affordable Care Act (ACA) dramatically reduced rates of uninsurance and underinsurance in the United States. In this study we estimated the effects of these coverage increases on cancer detection among the near-elderly population (ages 60-64). Using 2010-16 Surveillance, Epidemiology, and End Results (SEER) Program data, we estimated that the ACA increased cancer detection among this population. We found that 45 percent of the jump in cancer detection that occurs when people reach Medicare eligibility age was eliminated by the ACA coverage expansions. The ACA coverage expansions had large effects on cancers with and without routine screening tests, and 68 percent of newly detected cancers were early- and middle-stage cancers. In addition, the empirical strategy used to identify the effects of the ACA on cancer detection confirmed the role of health insurance as the key mechanism to explain Medicare's effects on health care use and health outcomes as described in the prior literature. Our results highlight the importance of the ACA, Medicare, and health insurance coverage generally for disease detection.

The cost of dementia in an unequal country: The case of Chile.

We study the economic cost of dementia in Chile, and its variation according to socioeconomic status (SES). We use primary data from a survey of 330 informal primary caregivers who completed both a RUD-Lite and a socio-demographic questionnaire to evaluate the severity of dementia and caregiver's burden. The costs of dementia are broken into three components: direct medical costs (medical care, drugs, tests); direct social costs (social service, daycare); and indirect costs (mostly associated to informal care). The average monthly cost per patient is estimated at US$ 1,463. Direct medical costs account for 20 per cent, direct social costs for 5 per cent and indirect costs for 75 per cent of the total cost. The mean monthly cost is found to be inversely related to SES, a pattern largely driven by indirect costs. The monthly cost for high SES is US$ 1,083 and US$ 1,588 for low SES. A multivariate regression analysis suggests that severity of dementia and caregiver's burden account for between 49 and 70 per cent of the difference in the indirect cost across SES. However, between one-third and one-half of the variation across SES is not due to gradient in severity of dementia. Direct medical costs increase in higher SES, reflecting differences in purchasing power, while indirect costs are inversely related to SES and more than compensate differences in medical costs. Moreover, in lower SES groups, female caregivers, typically family members who are inactive in the labor market, mostly provide informal care. The average annual cost of dementia in Chile (US$ 17,559) is lower in comparison to high-income countries (US$ 39,595) and the proportion of cost related to informal cost is higher (74 per cent compared to 40 per cent). SES is a key determinant in the cost of dementia. In the absence of universal access to treatment, part of the social cost of dementia potentially preserves or increases income and gender inequality.

The Effect of the 2009 Influenza Pandemic on Absence from Work.

In July 2009, the World Health Organization declared the first flu pandemic in nearly 40 years. Although the health effects of the pandemic have been studied, there is little research examining the labor productivity consequences. Using unique sick leave data from the Chilean private health insurance system, we estimate the effect of the pandemic on missed days of work. We estimate that the pandemic increased mean flu days missed by 0.042 days per person-month during the 2009 peak winter months (June and July), representing an 800% increase in missed days relative to the sample mean. Calculations using the estimated effect imply a minimum 0.2% reduction in Chile's labor supply. Copyright © 2017 John Wiley & Sons, Ltd.

Opportunities and challenges in supply-side simulation: physician-based models.

OBJECTIVE: To provide a conceptual framework and to assess the availability of empirical data for supply-side microsimulation modeling in the context of health care. DATA SOURCES: Multiple secondary data sources, including the American Community Survey, Health Tracking Physician Survey, and SK&A physician database. STUDY DESIGN: We apply our conceptual framework to one entity in the health care market-physicians-and identify, assess, and compare data available for physician-based simulation models. PRINCIPAL FINDINGS: Our conceptual framework describes three broad types of data required for supply-side microsimulation modeling. Our assessment of available data for modeling physician behavior suggests broad comparability across various sources on several dimensions and highlights the need for significant integration of data across multiple sources to provide a platform adequate for modeling. A growing literature provides potential estimates for use as behavioral parameters that could serve as the models' engines. Sources of data for simulation modeling that account for the complex organizational and financial relationships among physicians and other supply-side entities are limited. CONCLUSIONS: A key challenge for supply-side microsimulation modeling is optimally combining available data to harness their collective power. Several possibilities also exist for novel data collection. These have the potential to serve as catalysts for the next generation of supply-side-focused simulation models to inform health policy.

Price elasticity of expenditure across health care services.

Policymakers in countries around the world are faced with rising health care costs and are debating ways to reform health care to reduce expenditures. Estimates of price elasticity of expenditure are a key component for predicting expenditures under alternative policies. Using unique individual-level data compiled from administrative records from the Chilean private health insurance market, I estimate the price elasticity of expenditures across a variety of health care services. I find elasticities that range between zero for the most acute service (appendectomy) and -2.08 for the most elective (psychologist visit). Moreover, the results show that at least one third of the elasticity is explained by the number of visits; the rest is explained by the intensity of each visit. Finally, I find that high-income individuals are five times more price sensitive than low-income individuals and that older individuals are less price-sensitive than young individuals.