Geriatric Population Mental Healthcare During COVID-19

Geriatric Population Mental Healthcare During COVID-19

People are coming to terms with the changes arising from the effects of COVID-19, leading to a consensus across all fields suggesting the need to have pre-and post- COVID-19 periods of history. Governments and healthcare organizations continue to encourage people to take preventive measures, including adapting to new ways of life. While the swift response by research organizations has yielded results, including more than five certified vaccines, the pandemic increased mortality rates, leading to an increased number of deaths among the elderly. This study aims to analyze how telehealth/telemedicine measures or programs during the coronavirus pandemic might have impacted the well-being and mental health of seniors at the center.

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The widespread prevalence of COVID-19 and other infectious diseases is linked with physical pain, mental illness, and psychological pain. Data show that widespread infectious diseases impact many people mentally more than physically, illustrating how such diseases influence mental health. For instance, the Middle East respiratory syndrome significantly affected people’s mental health by causing fear and anxiety. Healthcare institutions recorded many cases of post-traumatic stress disorder and other mental illnesses all through the severe acute respiratory syndrome outbreak in 2003. Stress caused by COVID-19 was 1.4 times higher than what people experience during natural calamities like earthquakes (Lee et al., 2020).

Even though COVID-19 infects people of all ages, severe illness and mortality were recorded among the elderly population. A 2020 report by the United States Centers for Disease Control and Prevention revealed that patients older than 65 years accounted for 80% of the fatalities, indicating seniors’ vulnerability to the pandemic. A significant proportion of the senior population has underlying medical conditions and reduced immune function, making them vulnerable to infections. The vulnerability makes it necessary to offer mental illness screening and care for the elderly (Lee et al., 2020).

According to Mukhtar (2020), pandemic containment measures like quarantine, self-isolation, and social distancing are traumatic events that threaten the lives of the vulnerable. The traumatic nature of COVID-19 exposed everyone to its negative effects, making it vital to adapt contingent approaches for minimizing mental harm. Vulnerable populations are exposed to the virus and are likely to have psychological trauma. The pandemic exposed everyone to interpersonal traumas like grief, financial burden, loneliness, behavioral and emotional issues, and mental health challenges (Mukhtar, 2020).

Countries implemented measures limiting social interactions to curb COVID-19. Even though the approach minimizes contact with pathogens effectively, it causes loneliness and social isolation. The Kaiser Family Foundation reports that the economic downturn caused by COVID-19 affected adults’ mental well-being. Also, the number of adults linking stress and anxiety caused by the pandemic to negative mental health impacts rose from 39% to 53%. Similarly, about half of adults older than 65 years confirmed that coronavirus-related trauma and anxiety affected their mental health (Koma et al., 2020)

The effect of the COVID-19 pandemic greatly affected the geriatric population. A focus on mental health, is vital because of the increased bereavement rates, loneliness, and social isolation among seniors. Scientific investigations need to understand the association between lack of social connections, loneliness, and mental health issues like depression and anxiety. Previous studies have connected loneliness with depression, dementia, stroke, and increased mortality risks (Koma et al., 2020).


Senior citizens have experienced a myriad of mental healthcare challenges since the onset of the coronavirus pandemic. Even though governments responded with strict containment measures, including curfews and lockdowns, authorities and policymakers paid insufficient attention to the psychological healthcare needs of senior citizens (Yang et al., 2020). Thus, healthcare researchers should identify scientific evidence to support informed decision-making among stakeholders and policymakers. The approach will serve the needs of the elderly by ensuring the availability of timely and high-quality mental healthcare services through telemedicine.

The federal and state governments implemented regulatory changes to expand medical coverage of telehealth services in response to the negative effects COVID-19. The expansion provided traditional Medicare subscribers mental health and emergency care coverage (Lee et al., 2020). However, the extent to which telehealth mental care improves the well-being of the geriatric population is not known. Besides, there exists a need to expand telehealth coverage by Medicare even after the pandemic.

COVID-19 vaccination drives continue to minimize the pandemic’s adverse healthcare effects. However, previous infection rates patterns suggest that more individuals are likely to get infected during the winter and fall. The containment measures continue to expose the senior population to isolation and loneliness, reducing their mental health quality. This project aims to uncover whether or not interventions such as telemedicine reduce social isolation while improving the mental well-being of the geriatric population.

Objective, Research Question, and Hypothesis

The study’s objective is to explore how the use of digital technologies in telemedicine reduces isolation and increases well-being among the geriatric population in a senior care center. The project will focus on finding evidence-based responses to the following question:  How do telemedicine influence seniors’ well-being and mental health outcomes at a Senior Living Center?

The research hypothesis of the study is:

: Telemedicine does not improve the well-being and mental health outcomes of seniors residing at a Senior Living Center.

: Telemedicine improves the well-being and mental health outcomes of seniors residing at a Senior Living Center.


A mixed-methods approach will be utilized to gather insights into how any telehealth programs for mental health care might have impacted seniors’ well-being and mental health at the Senior Living Center. According to Caffery et al. (2016), mixed-method research integrates quantitative and qualitative investigation that give a complete understanding of multifaceted interventions like telemedicine. Thus, mixed methods are better than single-method studies, hence more essential in healthcare research. Coffey et al. (2016) proposed mixed methods in their assessment of the linkages between mental health recovery and quality of life. The researcher’s proposal provided a framework for using statistical approaches to understand the important social elements that influence mental health recovery (Coffey et al., 2016).


The project will follow a quasi-experimental design and will involve control and an intervention group. The practical and ethical considerations will require the author to use convenient sampling to recruit and assign participants to control or intervention groups randomly. The author will seek the institutional review board’s (IRB) consent to perform the quasi-experimental study. Besides, the approved IRB will be submitted to the medical ethical review board of the senior care center for validation. The participants’ legal representatives will sign the consent forms before the commencement of the research.


Participants will include ten nursing staff and 20 individuals living in the Senior Care Center. The proposed intervention will be implemented through technologies supporting telemedicine, including video and teleconferencing software. Any negative or positive changes to respondents’ mental wellbeing will be captured through direct interviews and questionnaires with staff and residents. The intended impact is the improved overall well-being of seniors at the care center. The author will ensure the participants’ anonymity. Besides, the intended use of the collected data will be communicated to all the participants who will have the right to terminate their participation at their convenience.

Measurement and Data Collection

The author will use questionnaires for pretest and post-test data collection. Moreover, individual and group interviews with residents at the Senior Living Care center will facilitate qualitative data. The questionnaires and interviews will capture both qualitative and quantitative metrics to support understanding of how feelings of loneliness and isolation caused by COVID-19 containment measures have impacted overall the well-being of the elderly population. The questionnaires and interview questions will be adapted from Ridloff’s (1977) Center for Epidemiological Studies-Depression (CES-D) scale.


Many nursing homes are using telemedicine, including the application of digital technologies, to enhance residents’ healthcare outcomes (Eze et al., 2020). The project goal is to find out the extent to which these a telehealth intervention will reduce mental health challenges linked to isolation and increase patients’ well-being. The procedure will include training nursing staff at the senior care home on how the intervention works and enlightening them about its full implementation resources. The author will separate the control and intervention groups to ensure that they don’t share knowledge. Both intervention and control groups will consist of 10 nursing staff and five patients.

Staff participants in the intervention group will receive telemedicine training for mental health wellness. Patients will access mental healthcare services through telemedicine and digital technologies. On the other hand, the author will not train nursing staff placed in the control group. They will be required to deliver care to as usual. The project will run for one month.

Data Analysis

The author will use the Statistical Package for Social Sciences (SPSS) for qualitative and quantitative data analytics. The procedure will involve using Pearson’s chi-square and independent samples t-test to analyze the differences between the control and intervention groups. The effect of the intervention will also be analyzed using regression models. The author will review the resultant regression coefficients and make statistical inferences regarding the overall effect of the intervention on seniors’ mental health.

Analysis Plan

The author will derive variables from the Center for Epidemiological Studies-Depression (CES-D) scale. The evidence-based scale enables respondents to report how frequently they encountered mental illness symptoms such as loneliness, poor appetite, restlessness, and lack of sleep. The responses will be captured on a scale of 0-3. Besides, the author will use a Likert scale with five response options to assess participants’ likelihood of getting stress during the project performance period. A telehealth knowledge test for the caregivers will be conducted pre and post-test in the intervention group. The test will include an assessment of caregivers’ competence in performing an MMSE, popularly known as the Mini-Mental State Examination (Ciemins et al., 2009).

To understand pretest and post-test patients ‘ mental well-being, the author will analyze five variables from the CES-D scale, including loneliness, sadness, restless sleep, feeling depressed, and withdrawal. On the other hand, the pretest and post-test knowledge test for staff will include the MMSE measures of cognitive function such as language, orientation, registration, calculation and attention, and recall. Both the CES-D and the MMSE elements will be integrated into the questionnaire and interview questions for the control group.

The independent samples t-test will support the evaluation of the pretest and post-test results in the intervention group. Similarly, data collected from the control group before and after the intervention will be analyzed. The author will then evaluate whether differences exist between the pretest and post-test results in the control and intervention groups. Moreover, the Pearson’s Chi-square test will facilitate a between-group comparison.

The author will fit a logistic regression model to assess the likelihood of a telehealth intervention improving the mental health outcomes of seniors living at a care center. The intervention and control data will be merged based on a response variable labeled as 0 for the control group and 1 for the intervention group. The dependent variable will be regressed against numerical variables, and the result will be used to make the statistical inferences.

The fitted model will yield a probabilistic outcome that will help explain the extent to which adapting telemedicine and digital technology for the geriatric population can enhance their mental health outcomes throughout the current pandemic. Moreover, the significance levels of variables from the MMSE and CES-D to the model will be reviewed. The statistical inference drawn from the 95% significance level logistic regression model will validate the preliminary results from the Pearson’s chi-square tests and the independent samples t-tests.

Possible Results

There exists a literature gap concerning the use of quasi-experimental design and mixed methods approach to investigate how telemedicine affects mental health outcomes of the geriatric during a pandemic. The author anticipates that the intervention group will report improved mental well-being than the control group. The intervention will empower nursing care teams to offer real-time, high-quality care to seniors while ensuring their safety from infection COVID-19.

A systematic review conducted by Langarizadeh et al. (2017) identified the applications, challenges, advantages, and technologies for telemedicine focusing on mental healthcare. The researchers’ findings suggest that telehealth services offer adaptable and effective solutions for mental health patients. The researchers noted that telemedicine improved access to affordable healthcare among isolated communities through current adaptable technologies (Langarizadeh et al., 2017). Eze et al. (2020) report that telemedicine can help patients improve patients’ mental health status. There are concerns that telemedicine is less effective in ensuring continued patient engagement. Besides, there exist usability barriers among patients and healthcare teams.


The project’s expected results suggest how beneficial the adoption of telemedicine for seniors can be to their mental health. However, organizations need to emphasize training staff and patients to support their usability of telehealth systems. The use of a quasi-experimental design can provide reliable and valid outcomes that healthcare executives can generalize to support the elderly’s mental healthcare needs.







Caffery, L. J., Martin-Khan, M., & Wade, V. (2016). Mixed methods for telehealth research. Journal of Telemedicine and Telecare, 23(9), 764–769.×16665684

Ciemins, E. L., Holloway, B., Coon, P. J., McClosky-Armstrong, T., & Min, S. J. (2009). Telemedicine and the mini-mental state examination: Assessment from a distance. Telemedicine journal and e-health: The Official Journal of the American Telemedicine Association15(5), 476–478.

Coffey, M., Hannigan, B., Meudell, A., Hunt, J., & Fitzsimmons, D. (2016). Study protocol: A mixed methods study to assess mental health recovery, shared decision-making and quality of life (Plan4Recovery). BMC Health Services Research, 16(1).

Eze, N. D., Mateus, C., & Cravo Oliveira Hashiguchi, T. (2020). Telemedicine in the OECD: An umbrella review of clinical and cost-effectiveness, patient experience and implementation. PLOS ONE, 15(8), e0237585.

Koma, W., True, S., Biniek, J. F., Cubanski, J., & Orgera, K. (2020). One in four older adults report anxiety or depression amid the COVID-19 pandemic. Kaiser Family Foundation.

Langarizadeh, M., Tabatabaei, M. S., Tavakol, K., Naghipour, M., Rostami, A., & Moghbeli, F. (2017). Telemental health care, an effective alternative to conventional mental care: A systematic review. Acta Informatica Medica: AIM: Journal of the Society for Medical Informatics of Bosnia & Herzegovina: Casopis Drustva za Medicinsku Informatiku BiH25(4), 240–246.

Lee, K., Jeong, G. C., & Yim, J. (2020). Consideration of the psychological and mental health of the elderly during COVID-19: A theoretical review. International Journal of Environmental Research and Public Health17(21), 8098.

Mukhtar S. (2020). Psychological health during the coronavirus disease 2019 pandemic outbreak. The International Journal of Social Psychiatry66(5), 512–516.

Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurements, 1, 385-401.

Yang, Y., Li, W., Zhang, Q., Zhang, L., Cheung, T., & Xiang, Y. T. (2020). Mental health services for older adults in China during the COVID-19 outbreak. The Lancet Psychiatry7(4), e19.


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