Geriatric Health in Bangladesh during COVID-19: Challenges and Recommendations

Hossain, Mahbub; Mazumder, Hoimonty; Tasnim, Samia; Nuzhath, Tasmiah; Sultana, Abida

doi:10.1080/01634372.2020.1772932

Cited by 27 publications

(34 citation statements)

References 6 publications

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“…This phenomenon is evident in the findings of this review as well; a wide range of factors associated with mental health problems suggest that those should be examined using multi-disciplinary approaches enabling researchers from different disciplines to bring their unique insights and resources to better understand the social determinants of mental health in the era of a pandemic. Although health systems remain on the focus in such research efforts, other social systems and stakeholders should be engaged in future mental health research in COVID-19 and similar disruptive global events 64 , 65 .…”

Section: Discussionmentioning

confidence: 99%

Epidemiology of mental health problems in COVID-19: a review

et al. 2020

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The novel coronavirus disease 2019 (COVID-19) has become a pandemic affecting health and wellbeing globally. In addition to the physical health, economic, and social implications, the psychological impacts of this pandemic are increasingly being reported in the scientific literature. This narrative review reflected on scholarly articles on the epidemiology of mental health problems in COVID-19. The current literature suggests that people affected by COVID-19 may have a high burden of mental health problems, including depression, anxiety disorders, stress, panic attack, irrational anger, impulsivity, somatization disorder, sleep disorders, emotional disturbance, posttraumatic stress symptoms, and suicidal behavior. Moreover, several factors associated with mental health problems in COVID-19 are found, which include age, gender, marital status, education, occupation, income, place of living, close contact with people with COVID-19, comorbid physical and mental health problems, exposure to COVID-19 related news and social media, coping styles, stigma, psychosocial support, health communication, confidence in health services, personal protective measures, risk of contracting COVID-19, and perceived likelihood of survival. Furthermore, the epidemiological distribution of mental health problems and associated factors were heterogeneous among the general public, COVID-19 patients, and healthcare providers. The current evidence suggests that a psychiatric epidemic is cooccurring with the COVID-19 pandemic, which necessitates the attention of the global health community. Future epidemiological studies should emphasize on psychopathological variations and temporality of mental health problems in different populations. Nonetheless, multipronged interventions should be developed and adopted to address the existing psychosocial challenges and promote mental health amid the COVID-19 pandemic.

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Section: Discussionmentioning

confidence: 99%

Epidemiology of mental health problems in COVID-19: a review

et al. 2020

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“…Contemporary scholarly discourses highlight the fact that the use of AI does not consider potential pitfalls that may underestimate health disparities in marginalized populations or underrepresented groups [32,33]. Moreover, specific population groups may have unique health risks amid this pandemic, which includes older adults and people with co-morbid conditions [34][35][36][37]. In this regard, the use of AI should be leveraged to proactively identify…”

Section: Discussionmentioning

confidence: 99%

Applications of Artificial Intelligence Technologies in COVID-19 Research: A Bibliometric Study

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Sa²,

Elj³

et al. 2020

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The novel coronavirus disease (COVID-19) pandemic has impacted health and wellbeing globally. To strengthen preventive and clinical care amid this pandemic, technological innovations like artificial intelligence (AI) are increasingly used in different contexts. This bibliometric study aimed to assess the current scholarly development and prominent research domains in applications of AI technologies in COVID-19 research. A total of 105 articles were retrieved from MEDLINE database that emphasized on the use of AI in the context of COVID-19. Most articles had multiple authors with a collaboration index of 7.18. Moreover, most of the articles were produced from the USA (22.86%) and China (21.9%), whereas developing countries were underrepresented among the contributing nations. Furthermore, several research domains were identified, including prevention and control, diagnostics, epidemiological characteristics, therapeutics, psychological conditions, and different areas of data sciences related to COVID-19. The current bibliometric evidence shows the early stage of development in this field, which necessitates equitable applications of AI in COVID-19 research emphasizing on health disparities, socio-legal issues, vaccine development, and applied public health research in this pandemic.

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“…A huge number of individuals went jobless soon after COVID-19 pandemic. Table 1 shows the determined information of the initial half-year of the tourism industry (Ahmed et al, 2020;Anable & Gatersleben, 2005;Banik et al, 2020;Hossain et al 2020).…”

Section: Introductionmentioning

confidence: 99%

How does tourist perception lead to tourist hesitation? Empirical evidence from Bangladesh

Polas

Saha

Tabash

2021

Environ Dev Sustain

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The paper aims to identify the factors that cause prospective tourists’ hesitation to travel. The study also examines whether this relationship is mediated by the tourist perception in Bangladesh. The study is of quantitative design, and the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation were explored using a sample of 322 Bangladeshi prospective tourists. The three relationships were also examined through tourist perception. By using cross-sectional data, the researchers hypothesized that tourist knowledge, tourist health risk, and destination personality have a positive and significant effect on tourist hesitation. Besides, the researchers also hypothesized that tourist perception mediates the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation. In this respect, the Smart PLS 3.0 was employed to analyze the data. The results of the study confirm findings of previous related studies by not only highlighting the importance of tourist perception in shaping tourist hesitation but also indicating the way each dimension of tourism either enhances or inhibits the tourist hesitation. The results of the study also reveal a positive and significant relationship between tourist knowledge and tourist health risk with tourist hesitation. The analysis of data showed no conventional relationship between destination personality and tourist hesitation. Accordingly, this study identified the extent to which tourist perception mediates the relationship between tourist knowledge and destination personality with tourist hesitation. Meanwhile, the results of the study indicate the absence of any mediation role of tourist perception between tourist health risk and tourist hesitation. The study outcomes would encourage the government, policymakers, and tourism managements in creating a tailor-made responsiveness program by building a scenario that could offer more prominent sustainable tourism establishments. Besides, the results may assist stakeholders of tourist destinations in understanding tourist perception and the causes of tourist’s hesitation.

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Geriatric Health in Bangladesh during COVID-19: Challenges and Recommendations

Cited by 27 publications

References 6 publications

Epidemiology of mental health problems in COVID-19: a review

Epidemiology of mental health problems in COVID-19: a review

Applications of Artificial Intelligence Technologies in COVID-19 Research: A Bibliometric Study

How does tourist perception lead to tourist hesitation? Empirical evidence from Bangladesh

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