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1.
Curr Psychol ; : 1-10, 2021 Apr 21.
Article in English | MEDLINE | ID: covidwho-2035352

ABSTRACT

The COVID-19 pandemic has prompted all countries to adopt restraining measures to mitigate the spread of the disease. Usually, large-scale disasters tend to be accompanied by significant increases of psychological distress, depression and anxiety. Confinement measures imposed during the COVID-19 pandemic are likely to have similar consequences. In the present study we aim to evaluate how COVID-19 affected the overall psychological functioning of Portuguese individuals by providing a comparison of current data with status prior to the COVID-19 pandemic. The study sample was composed of 150 cognitively healthy participants. Results show an overall maintenance of cognitive capacities, although subjective cognitive decline complaints significantly increased during the pandemic. Regarding mental health, restraining measures culminated in an aggravation of depressive and decrease of the perceived quality of life, associated with feelings of loneliness and perceived social isolation. Finally, higher levels of pre-COVID-19 quality of life seem to play a protective role against depression and anxiety and predict less difficulties in emotion regulation, feelings of solitude and cognitive complaints. In sum, confinement due to COVID-19 implied an aggravation of the mental health of the Portuguese population, which appears to have been attenuated in those with higher pre-pandemic levels of perceived quality of life.

2.
Soc Sci Med ; 309: 115253, 2022 Aug 06.
Article in English | MEDLINE | ID: covidwho-2036538

ABSTRACT

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.

3.
Environ Res ; : 114020, 2022 Aug 07.
Article in English | MEDLINE | ID: covidwho-2035991

ABSTRACT

OBJECTIVES: To assess the economic and mental health impacts of COVID-19 in the presence of previous exposure to flooding events. METHODS: Starting in April 2018, the Texas Flood Registry (TFR) invited residents to complete an online survey regarding their experiences with Hurricane Harvey and subsequent flooding events. Starting in April 2020, participants nationwide were invited to complete a brief online survey on their experiences during the pandemic. This study includes participants in the TFR (N = 20,754) and the COVID-19 Registry (N = 8568) through October 2020 (joint N = 2929). Logistic regression and generalized estimating equations were used to examine the relationship between exposure to flooding events and the economic and mental health impacts of COVID-19. RESULTS: Among COVID-19 registrants, 21% experienced moderate to severe anxiety during the pandemic, and 7% and 12% of households had difficulty paying rent and bills, respectively. Approximately 17% of Black and 15% of Hispanic households had difficulty paying rent, compared to 5% of non-Hispanic white households. The odds of COVID-19 income loss are 1.20 (1.02, 1.40) times higher for those who previously had storm-related home damage compared to those who did not and 3.84 (3.25-4.55) times higher for those who experienced Harvey income loss compared to those who did not. For registrants for whom Harvey was a severe impact event, the odds of having more severe anxiety during the pandemic are 5.14 (4.02, 6.58) times higher than among registrants for whom Harvey was a no meaningful impact event. CONCLUSIONS: Multiple crises can jointly and cumulatively shape health and wellbeing outcomes. This knowledge can help craft emergency preparation and intervention programs.

4.
Child Youth Serv Rev ; 142: 106619, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2035846

ABSTRACT

The COVID-19 pandemic has greatly impacted the lives of many around the world, particularly refugee and immigrant communities. In the United States, millions of children and youth had to quickly shift from in-person to remote learning, encountering new challenges and uncertainties in their overall educational experiences. This study explored some of the impacts of the COVID-19 pandemic on the educational, socialization, and mental and emotional health and wellbeing of Rohingya refugee youth from Myanmar resettled in the United States. Through in-depth qualitative interviews with 15 Rohingya refugees ages 12-17, we found that Rohingya youth's experiences with COVID-19 pandemic presented both challenges and opportunities. The challenges included unavailability of personal space to conduct school work, difficulties adjusting to online school due to computer literacy levels, and familial responsibilities that often conflicted with their schooling, as well as feelings of boredom and sadness that consequently impacted their emotional and mental health state. Youth also noted opportunities such as spending more time with their parents who were unable to work due to the pandemic as well as feeling helpful in acting as caregivers to their siblings and in working alongside their parents. Implications for policymakers and educators are also discussed.

5.
Child Abuse Negl ; : 105852, 2022.
Article in English | PubMed | ID: covidwho-2035843

ABSTRACT

BACKGROUND: The Keep Children and Families Safe Act amendment to the Child Abuse Prevention and Treatment Act (CAPTA) of 2003 mandated children under age three who are involved with Child Welfare (CW) to receive a referral to the system for early intervention (EI). While there is strong rationale for providing developmental services to young children and families impacted by maltreatment, the early implementation of this policy brought about many challenges related to interagency coordination and readiness of providers to provide cross-systems care. Currently, as the system and providers within the system recover from the effects of Covid-19, a predicted increase in need of services may exacerbate historical gaps in the provision of services to families involved with CW. PARTICIPANTS AND SETTING: This policy-focused paper explores issues impacting CW and EI providers who coordinate care between CW and EI services. METHODS: This paper provides a historical examination of these challenges and proposes an approach for improving developmental services for families referred from CW, specifically through the lens of addressing resources and supports available to providers. RESULTS: The proposed approach includes an increase and reprioritization of resources to support provider readiness and well-being. CONCLUSIONS: By focusing on support for providers, the authors propose a reduction of stress and improvement of services at each level of the "well-being" system.

6.
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach ; : 1-51, 2022.
Article in English | Scopus | ID: covidwho-2035585

ABSTRACT

Mental disorders are a critical issue in modern society, yet it remains to be consistently neglected. The COVID19 pandemic has made it much more difficult to seek assistance when one needs it. People are feeling increasingly anxious and uncertain about their futures while being socially separated from their friends and relatives. As people continue to quarantine among the limitations imposed by governments, interaction between clinical therapists or social workers and those suffering from mental illness has gotten increasingly limited. Machine learning is a vital approach for allowing virtual analysis of many forms of textual, audio, and visual data for sentiment analysis and understanding the mental health of people utilizing numerous critical parameters in this situation. This chapter aims to provide a systematic review of the current literature investigating COVID-19's impact on mental well-being, as well as studies that explore machine learning and artificial intelligence techniques to detect and treat mental illnesses when traditional therapies are unavailable due to lockdown and social distancing norms imposed. The different machine learning algorithms and deep learning approaches utilized in earlier studies are thoroughly discussed in this chapter. Detailed explanation of the data sources utilized and a review of the types of features investigated in mental disorder identification are included as well. The study's major findings are thoroughly discussed. The obstacles of employing machine learning techniques in biomedical applications are explored, as well as possibilities to enhance and progress the discipline. © 2022 Elsevier Inc. All rights reserved.

7.
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach ; : 235-258, 2022.
Article in English | Scopus | ID: covidwho-2035583

ABSTRACT

Web users are progressively connecting during the pandemic of Covid-19. It causes the social web to grow exponentially by the huge amount of collective information. For example, Twitter, which has been growing very fast as one of the most popular social networking websites. The platform enables tracking mental health surveillance via online by using text classification methods. Latest text classification research showed that tweets can be classified accurately by using word embedding combined with the K-means algorithm. Word embedding is a way for representing words into numbers, so that the word representation can be further fed into the clustering algorithm. However, given the number of choices of word embedding models (Word2Vec, ELMo, and BERT), it raises the question of which type of word embedding has the best performance for text classification tasks. Many kinds of thoughts are spread through Twitter especially which are related to anxiety during the pandemic. This study aims to determine the most accurate web embedding methods in classifying tweets related to Covid pandemic anxiety into a more specific cluster. Each cluster is evaluated whether it has relation to the feeling of loneliness. To analyze the performance of the classification, each model is judged for their quality in which the representation method gets the best quality of clusters. Lastly, three word embedding methods are compared in terms of performance using confusion matrix (precision, recall, F1, and accuracy). © 2022 Elsevier Inc. All rights reserved.

8.
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach ; : 189-208, 2022.
Article in English | Scopus | ID: covidwho-2035582

ABSTRACT

Prior research has discussed the impact of the COVID-19 pandemic on people's lifestyles and the reduced human development index. However, little is known about how the COVID-19 pandemic and socioeconomic factors influence global mobility and, in turn, impact our mental health. Also, little is known about how computational models would predict global mobility under the influence of COVID-19 and socioeconomic variables. The primary objectives of this paper are to investigate the influence of the COVID-19 pandemic and socioeconomic factors on people's mobility worldwide and to develop a regression model to predict the future impact on mobility due to the COVID-19 lockdown. The two datasets used for this study are the mobility and the COVID-19 dataset. The data taken into consideration was for 14 months, i.e., from April 1, 2020 to May 31, 2021. The mobility dataset contained retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential areas. In contrast, the COVID-19 and socioeconomic dataset contained total confirmed cases, total deaths, total tests, population density, human development index, and other variables. Multiple regression models were built to predict the pandemic's impact on different mobility variables around the world. Variables such as the total number of cases and total deaths per million were negatively correlated with people's mobility at retail and recreation centers, indicating fear and uncertainty. There was a significant negative correlation between reported cases of domestic violence and mobility to the workplace. This indicates the increased stress and anxiety level among individuals due to imposed lockdown during the pandemic. Implications of computational modeling are discussed. © 2022 Elsevier Inc. All rights reserved.

9.
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach ; : 141-165, 2022.
Article in English | Scopus | ID: covidwho-2035580

ABSTRACT

COVID-19 caused a dramatic change in the lifestyle of people around the globe and has had an impact on all sectors, including mental health, the economy, and social behavior. Mental health is of great concern for the survival of the young people in achieve their goals. This chapter concentrates on mental health in the education sector during the pandemic. Students and faculty members experienced a high amount of frustration, stress, anxiety, fear, and loneliness during the pandemic. The implementation of online classes was a burden to faculty and students and led to an unsatisfactory mode of teaching in which eye-to-eye contact was missing. Although experience was gained for both teacher-centric and student-centric modes of teaching, mental health resulting from online classes is analyzed in this chapter. Mental health during the pandemic period we analyzed by collecting data from students and staff in the higher education sector from the point of view of undergraduates, postgraduates, and research scholars. Deep learning algorithms pave the way to analyzing mental health for people in the education sector. It predicts the percentage of staff and students who are disturbed in their profession and study. This analysis helps to reduce the gap of interaction between staff and students in the blended mode of teaching. It also provides insight into government policies related to future modes of education. © 2022 Elsevier Inc. All rights reserved.

10.
Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach ; : 167-187, 2022.
Article in English | Scopus | ID: covidwho-2035577

ABSTRACT

The traditional education system is focused on peer-to-peer learning, which helps in engagement, interactivity, and building confidence in students. However, the COVID-19 pandemic has shifted the focus from the traditional education system to online learning. The radical change in the education system has increased the mental stress in students. The parameters that affect the mental health of students include: anxiety, academic stress, difficulty in concentrating, sleeping pattern disorders, decreased social interaction, job fear, etc. In this work, we design a modular framework for predicting the students' mental health based on a set of questions. First, we create a questionnaire to assess and analyze the parameters associated with mental health among college students in the Indian context. Based on these parameters, we first survey 600 students from Indian universities. Then, we categorize the students into two groups: high mental stress and low mental stress using k-means clustering. Using the labels identified by k-means and further validated by the students, we then apply different classification models to predict the class of students. The proposed framework is experimentally validated through the dataset created from the questionnaire. In addition, we also analyze students' responses to find the parameters of utmost concern to the students. Therefore, our proposed work can be used to find the mental stress level of students so that corrective actions can be taken. © 2022 Elsevier Inc. All rights reserved.

11.
Indian Pediatrics ; 59(5):424-425, 2022.
Article in English | CAB Abstracts | ID: covidwho-2035429

ABSTRACT

Lactating mothers (n=126) residing in Pune, Maharashtra were interviewed to assess the prevalence of stress, rate of exclusive breastfeeding (EBF), and its association with different demographic factors. 75.4% mothers were found to be moderately stressed. Rate of EBF was 62.7%. Moderate stress and testing positive for COVID-19 were significantly negatively associated with EBF (P < 0.001).

12.
Journal of Rural Social Sciences ; 37(2), 2022.
Article in English | GIM | ID: covidwho-2034033

ABSTRACT

According to the National Institute of Mental Health, anxiety disorders are a common mental health disorder but often remain undetected and undertreated. During the COVID-19 pandemic, Extension professionals have worked hard to address emerging issues that communities face, possibly impacting the amount of anxiety they experience. This study determined the prevalence of anxiety symptoms among Extension professionals in the United States. Participants from 24 states completed a survey containing the Generalized Anxiety Disorder 2-item (GAD-2) screener. Almost one-quarter of Extension professionals had a GAD-2 score greater than three, an indicator of anxiety with a possibility of generalized anxiety disorder, which is similar to that of the general population. Also, female and male Extension professionals were about equal in the prevalence of anxiety symptoms, which is contrary to the literature. Extension administrators should consider ways to help their employees with this anxiety, especially during and after traumatic events.

13.
Boletin de Malariologia y Salud Ambiental ; 61(Edicion Especial II 2021):181-187, 2021.
Article in Spanish | GIM | ID: covidwho-2033928

ABSTRACT

The COVID-19 pandemic has wreaked havoc in the lives of workers in different parts of the world. The instability inherent to this stage of health emergency has had repercussions on the mental health of this population. The aim was to evaluate the psychometric properties of a financial stress scale for Peruvian dependent workers. Observational, analytical, instrumental and cross-sectional study in 749 workers. An exploratory factor analysis (EFA), by unweighted least squares, was performed after analysis of Bartlett's test and the Kaiser-Meyer-Olkin coefficient (KMO). The absolute and incremental goodness of fit was determined by means of the comparative fit index (CFI) and the Tucker-Lewis Index (TLI). A PFA was performed after analysis of the Kaiser-Meyer-Olkin index (KMO = 0.903) and Bartlett's test of sphericity (1751.9;gl = 36;p < 0.001), which were adequate. The items converged into a single factor. The EFT-Cov19 correlated positively with the LABOR-PE (r = 0.564, p < 0.01) and with a medium effect size. The reliability of the EFT-Cov19 was calculated with Cronbach's a coefficient, obtaining an acceptable value (a = 0.896;95% CI = 0.88 - 0.90). In conclusion, the EFT-Cov19 scale is a valid, reliable and adequate scale to measure financial stress in dependent workers during the COVID-19 pandemic.

14.
Boletin de Malariologia y Salud Ambiental ; 61(Edicion Especial II 2021):53-60, 2021.
Article in Spanish | CAB Abstracts | ID: covidwho-2033822

ABSTRACT

At the beginning of the pandemic, an excessive purchase of some products was observed, but this has not been evaluated if it is related to mental health. Therefore, the objective was to determine the factors associated with the purchase of basic necessities in the Peruvian population at the beginning of the first wave of the COVID-19 pandemic. An analytical cross-sectional study was carried out, based on a secondary data analysis. Information from 3379 Peruvians from all regions was used, they were asked about the purchases they made, crossing these with the results of the "KNOW-P-COVID-19", "F-COVID-19" and "MED-COVID-19" scales;obtaining descriptive and analytical results. The most purchased products were disinfectant (43.9%), followed by soap (43.6%) and alcohol (40.8%). In the multivariate analysis, the purchase of disinfectants (p=0.009), soap (p < 0.001) and alcohol (p=0.002) was found to be associated with sex;the purchase of personal protective equipment (p=0.027), antibacterial gel (p=0.010) and face masks (p=0.015) was associated with age;to the fatalism score the purchase of food (p=0.005), personal protective equipment (p < 0.001), soap (p=0.014), alcohol (p=0.043) and face masks (p < 0.001);to the score of fears and concern conveyed by the media the purchase of personal protective equipment (p=0.007), soap (p < 0.001) and face masks (p=0.005) and to the score of knowledge of the disease the purchase of soap (p < 0.001), antibacterial gel (p=0.011) and toilet paper (p=0.009). Significant associations were found with the purchase of supplies (p < 0.011).

15.
American Journal of Public Health ; 112(10):1363-1364, 2022.
Article in English | ProQuest Central | ID: covidwho-2033797

ABSTRACT

Largely because of the COVID-19 pandemic, the United States experienced a decrease in life expectancy from 2019 to 2020, with a disproportionate burden among Hispanic and non-Hispanic Black populations.1 COVID-19 has also illustrated and continues to show the "fault lines" in public health, including inadequate surveillance systems, underfunding of public health and primary care, structural inequities, misand disinformation, and the intrusion of partisan politics into public health practice.2,3 In addressing the many opportunities and challenges for public health and preventive medicine, Matthew Boulton and Robert Wallace have assembled an impressive set of 186 chapters across 11 sections, authored by world-class experts on each topic. Global Health, Health Disparities & Vulnerable Populations, Nutrition & Physical Activity, and Mental Health & Substance Use. Across the many sections and chapters in this book, competencies can be mapped to academic course work, clinical rotations, short courses, practica, and on-the-job training programs for professionals in public health and preventive medicine.8,9 IMPLEMENTING KNOWN SOLUTIONS As described in multiple chapters, but particularly in the chapter on implementation science, the decades of scientific progress in medicine and public health have too often not been translated into equitable improvements in population health.10 By influencing how scientific evidence is scaled up into practice, implementation science has great potential to accelerate progress toward achieving public health goals by seeking to understand and influence how scientific evidence is put into practice.11 Evidence in multiple forms, but particularly evidence-based interventions, is the foundation of implementation science and progress in public health.12 FOCUSING ON HEALTH EQUITY Concepts of health disparities and health equity are more prominently featured in this new edition, across many chapters but particularly in section 3 on health disparities and vulnerable populations.

16.
American Journal of Public Health ; 112(10):1374-1378, 2022.
Article in English | ProQuest Central | ID: covidwho-2033786

ABSTRACT

According to a detailed analysis of state health spending over five years,7 US states devoted $236 billion (60%) of their health budgets to clinical services (Box 1 ).4 Only $28.6 billion (7%) of the public health spending activity of states was in foundational capabilities, whereas $101.4 billion (28%) was spent on public health areas.4 Because we know more about what states-as opposed to counties-spend their money on, we can assess how spe-cific types of spending are associated with capacity to control the spread of the pandemic. Because funding for clinical service personnel was contractually tied to specific services, program officers for the contracts had to agree to release workers tied to prior grants (e.g., grants for behavioral health services). "14,15 Deevolution is how organizations survive financial starvation, by sloughing off functions that are not explicitly paid for by grants or fees for services. [...]starving health departments have no choice but to eliminate their local epidemiologists, policy analysts, and community organizers unless these roles can be justified as line items in an earmarked program. Neither the Centers for Disease Control and Prevention (CDC) nor the National Institutes of Health (NIH) offer programmatic research funding to support the systematic study of public health functions and foundational capacity in localities across the United States.

17.
Psychiatric Times ; 39(9):30-31, 2022.
Article in English | CINAHL | ID: covidwho-2033756

ABSTRACT

The article discusses the "Roadmap to the Ideal Crisis System: Essential Elements, Measurable Standards and Best Practices for Behavioral Health Crisis Response," written by the Group for the Advancement of Psychiatry Committee on Psychiatry and the Community. Topics covered include the 3 interacting design elements of a crisis system as described in the "Roadmap," and suggestions for psychiatrists and leaders in getting involved in determining the future of behavioral health crisis care.

18.
Boletin de Malariologia y Salud Ambiental ; 61(Edicion Especial II 2021):114-122, 2021.
Article in Spanish | CAB Abstracts | ID: covidwho-2033749

ABSTRACT

Due to the pandemic, an increase in mental health problems has been reported in members of the health personnel, with the self-report being an initial way of evaluating it. The objective was to determine the factors associated with the perception of repercussions in the mental sphere in health professionals in Latin America before COVID-19. An analytical cross-sectional study was carried out between June and August 2020 in Latin America. The perception of repercussions was measured through an instrument previously validated in Peru, which was taken virtually from 406 doctors, nurses and others;this was crossed versus other variables. The main concern was returning home and infecting their family (22% strongly agree), followed by feeling the abuse because they do not give them the necessary amount of personal protective equipment (13% strongly agree) and perceiving mental exhaustion for all the activities they did (12% strongly agree). In the multivariate analysis, the older there was a lower perception of mental repercussion (aPR: 0.98;95% CI: 0.97-0.99;p value = 0.012);In addition, those who had a greater perception of repercussions in the mental sphere also had more anxiety at a low level (aPR: 1.84;95% CI: 1.14-2.98;p value = 0.013) and post-traumatic stress (aPR: 2.28;95% CI: 1.61-3.22;p value <0.001), adjusted for depression and stress. Despite being an exploratory analysis, important associations were found in the mental sphere;which should continue to be investigated in larger studies.

19.
Boletin de Malariologia y Salud Ambiental ; 61(Edicion Especial II 2021):97-105, 2021.
Article in Spanish | GIM | ID: covidwho-2033720

ABSTRACT

COVID-19 has generated an unprecedented pandemic. This scenario could affect the mental health of healthcare personnel, influencing their work performance with the possibility of leaving long-term sequelae. The objective was to determine the socio-occupational factors associated with suffering from anxiety, depression and stress in health professionals in the Peruvian highlands during the pandemic. Cross-sectional study. Doctors and other professionals at the Ramiro Priale Priale National Hospital in the Peruvian highlands were surveyed virtually. Depression, anxiety and stress were measured with the DASS-21 scale;these were associated with different socio-labour variables. More severe depression was found at older ages and if a family member had been ill at home, but less severe depression was found among those who had children, those who had more years of professional practice and those who had social security. Those who had children had less anxiety;less severe anxiety and those who had a relative away from home who became ill;on the other hand, those who worked more hours per day had more moderate anxiety, severe anxiety if the respondent had become ill and both types if a family member had died had more moderate anxiety. Those who worked more hours per day and those who had a deceased family member had more stress. The most relevant characteristics of health workers with mental health problems were older age, family history of COVID-19, history of death of a family member from COVID-19 and longer working hours.

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