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Article

Unlocking the Factors Associated with COVID-19-Related Fear in Older Adults from Kazakhstan

by
Assel Izekenova
1,2,
Dinara Sukenova
3,4,
Ardak Nurbakyt
3,
Maimakova Akmaral
4,5,
Aigulsum Izekenova
3,*,
Filip Milanovic
6,7,
Irena Lazic
8 and
Dejan Nikolic
7,9
1
Center for Social and Business Research, Kenzhegali Sagadiyev University of International Business, Almaty 050010, Kazakhstan
2
School of Social Work, Michigan State University, East Lansing, MI 48824, USA
3
Department of Public Health, Asfendiyarov Kazakh National Medical University, Almaty 050012, Kazakhstan
4
Faculty of Medicine, Kenzhegali Sagadiyev University of International Business, Almaty 050012, Kazakhstan
5
Department of Clinical Diagnostical Laboratory, Central City Clinical Hospital, Almaty 050012, Kazakhstan
6
Department of Pediatric Surgery, University Children’s Hospital, 11000 Belgrade, Serbia
7
Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia
8
Department of Public Health and Program Health Care, University Children’s Hospital, 11000 Belgrade, Serbia
9
Department of Physical Medicine and Rehabilitation, University Children’s Hospital, 11000 Belgrade, Serbia
*
Author to whom correspondence should be addressed.
COVID 2026, 6(3), 41; https://doi.org/10.3390/covid6030041
Submission received: 23 January 2026 / Revised: 16 February 2026 / Accepted: 1 March 2026 / Published: 3 March 2026
(This article belongs to the Section COVID Public Health and Epidemiology)
Versions Notes

Abstract

The aim of this study was to examine the factors associated with COVID-19-related fear in older adults from Kazakhstan, and to explore its associations with sociodemographic characteristics, health status and multiple domains of quality of life in a regional context. A total of 445 individuals aged 60 and above from both urban and rural locations in Kazakhstan participated in this cross-sectional study. To assess the quality of life among older people we used the OPQoL (Older People’s Quality of Life) Scale. Further variables were evaluated: sociodemographic (age, gender, education level, marital status, and place of residence); health-related (self-reported overall health, hypertension, diabetes, cerebrovascular disease, cardiovascular disease, and chronic obstructive pulmonary disease (COPD); and COVID-19-related fear variable. Female gender (OR = 2.344; p = 0.001), present hypertension (OR = 2.106; p = 0.008), the specialized secondary educational level (OR = 2.321; p = 0.012) and at the border of significance university educational level (OR = 1.832; p = 0.051) were variables significantly associated with the COVID-19-related fear in older adults. For individuals with reported COVID-19-related fear, advanced age was significantly negatively associated with leisure and activities domain (B = −0.747; p = 0.020) of OPQoL; better self-reported overall health was significantly positively associated with life overall domain (B = 0.691; p < 0.001), health domain (B = 1.320; p < 0.001), psychological and emotional well-being domain (B = 0.395; p = 0.001), home and neighborhood domain (B = 0.249; p = 0.036), independence, control over life and freedom domain (B = 1.082; p < 0.001), financial circumstances domain (B = 1.132; p < 0.001), and leisure and activities domain (B = 0.556; p = 0.026) of OPQoL; present hypertension was significantly negatively associated with health domain (B = −0.888; p = 0.004) of OPQoL; present cardiovascular disease was significantly negatively associated with life overall domain (B = −0.588; p = 0.027), health domain (B = −0.967; p = 0.009), and independence, control over life and freedom domain (B = −0.542; p = 0.039) of OPQoL; being single was significantly negatively associated with life overall domain (B = −0.481; p = 0.033), social relations domain (B = −0.671; p = 0.014) and financial circumstances domain (B = −0.694; p = 0.036) of OPQoL; and urban place of residency was significantly positively associated with health domain (B = 0.735; p = 0.011) and psychological and emotional well-being domain (B = 0.483; p = 0.010) of OPQoL. Our findings pointed that numerous variables were associated with the COVID-19-related fear and quality of life domains regarding COVID-19-related fear in older adults from Kazakhstan during pandemics.

1. Introduction

On 11 March 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic was declared by the World Health Organization (WHO) [1]. It was reported that older adults were the one that are affected the most, particularly by severe forms of the COVID-19, and with poor outcomes that were associated with comorbidities [2]. In the study of Abul et al., it was reported that despite the fact that about 16% of the US population encompassing adults 65 years and older, these adults represented 31% of reported COVID-19 cases, participated in 45% of hospitalizations, represented 53% of admissions to intensive care units (ICUs), and accounted for 80% of deaths associated with COVID-19 [3]. Physiological changes of aging are considered as contributing factors for poor health outcomes in older adults [4].
Described transmission routes in the study by Nanda et al. included person-to-person direct contact with large respiratory droplets and indirect contact with secretions or infectious droplets deposited on surfaces. Furthermore, the authors stated that 50% or more of asymptomatic individuals will shed the virus [5]. In addition to this, it was reported that disease severity correlates with transmission rates [4]. Thus, in order to control the spreading of the COVID-19 virus, authorities proposed several prevention and protection guidelines [6].
During a pandemic, the fear of infection is reported to be very common [7]. Piero et al. stated that fear can have a functional and adaptive role or dysfunctional and damaging effect on individuals’ health and well-being [8]. Furthermore, it was argued that chronic or disproportionate fear becomes harmful, and in a pandemic, the fear can increase stress and anxiety levels in healthy people [9]. Moreover, in the study of Autenrieth et al., it was stated that fear of COVID-19 can be considered as multifaceted, not limited to the single type of fear, covering different dimensions of the one such as fear of contagion and fear of dying [10]. Additionally, in a scoping review of Quadros et al., authors reported various domains of fear that are associated with the fear of COVID-19 infection in individuals, including the fear of getting infected for themselves and family members, the fear of being unemployed and of economic losses, the fear of making decision for performing certain actions such as parents visits, the fear of avoidance behaviors toward gaining knowledge about the pandemic, etc. [11]. These findings point to the fact how complex the fear of COVID-19 infection particularly can be, along with the less predictable trajectories of its influence on health and well-being in every individual. However, bearing in mind that the most susceptible population group in the COVID-19 pandemic was older adults, their fear of infection during the pandemic is justified and should be studied further.
A previous cross-sectional study from Poland on older adults reported that females were more often concerned with getting COVID-19 infection versus males, as well as that the fear of COVID-19 infection increased in older adults with coronary heart disease, chronic obstructive pulmonary disease (COPD) and heart failure [12]. Another cross-sectional study from Nepal on older adults stated that further factors such as increasing age, remoteness from the health facility, Dalit ethnicity, as well as being overwhelmed and concerned with COVID-19 were shown to be associated with greater fear of COVID-19, while preexisting health conditions demonstrated an inverse association [13].
To the best of our knowledge, there is insufficient data examining COVID-19-related fear among older adults in Kazakhstan, with special attention to the sociodemographic, health status, and cultural domains that might differ substantially from settings in which previous investigations have been performed. Additionally, there is a lack of data regarding analysis of the association of COVID-19-related fear in older adults with specific domains of quality of life, including social relationships, independence, psychological well-being, as well as leisure and activities in Kazakhstan.
Therefore, the aim of this study was to examine the factors associated with COVID-19-related fear in older adults from Kazakhstan, and to explore its associations with sociodemographic characteristics, health status and multiple domains of quality of life in a regional context.

2. Methodology

2.1. Study Design and Participants

A total of 445 individuals aged 60 and above from both urban and rural locations in Kazakhstan participated in this cross-sectional study. The minimum age for participation was set at 60 years or older, aligning with the national retirement ages in Kazakhstan—60 for females and 63 for males [14]. Data were gathered through face-to-face interviews conducted by trained personnel between June to July 2022. To ensure the sample reflected the broader population in the Republic of Kazakhstan, a stratified sampling method was used, focusing on residents from Almaty and its surrounding region to establish the study sample in the Republic of Kazakhstan, specifically in the city of Almaty and the surrounding Almaty region. This approach resulted in a sample that was representative of Kazakhstan’s population in terms of gender, age, and place where individuals reside.

2.2. Inclusion and Exclusion Criteria

Inclusion criteria:
  • Adults ≥ 60 years and above.
  • Residents of Almaty city and Almaty region.
Exclusion criteria:
  • Participants refusing to give oral informed consent.
  • Participants with aphasia or significant hearing loss.
  • Participants with cognitive impairment or dementia (because the study relied on participants’ ability to independently understand the questionnaire items, accurately interpret the questions, and provide reliable self-reported responses. Cognitive disorders such as dementia may significantly affect memory, comprehension, judgment, and decision-making capacity, which could compromise the validity and reliability of the collected data).

2.3. Sampling Methodology and Ethical Considerations

For the purpose of this investigation, a stratified sampling approach was performed in order to ensure that the study group accurately reflected the demographic composition of older adults aged 60 years and above, living in Almaty City and neighboring rural areas, as outlined by the Bureau of National Statistics of the Republic of Kazakhstan [15]. To achieve equal representation, 50% of participants were chosen from urban setting and 50% from rural ones. Within each stratum, older adults were further stratified by gender, with the aim of reaching a distribution of approximately 60% women and 40% men in the Almaty region [15].
Considering ethical practice and participants’ data protection, the study prioritized confidentiality. Trained interviewers conducted the data collection, and all potential participants were informed on the study’s aims, the research team, and their rights, including the freedom to withdraw or discontinue the survey at any point without consequence. Oral consent was obtained from every study individual. To safeguard anonymity, personal names were omitted from the dataset and replaced with unique ID numbers. For accuracy and quality control, interviews were recorded and securely stored in a cloud-based system, with access limited to the core research team members and protected by password security. According to ethical research standards, questionnaire data is usually stored for 5 years after publication to ensure transparency and verification. After the retention period, electronic data will be permanently deleted, and paper documents will be destroyed by shredding.

2.4. Testing Instrument

The OPQoL (Older People’s Quality of Life) Scale is an instrument for the measurement of the quality of life among older people. This questionnaire features 35 items that are divided into 8 categories: Life overall (4 items); Health (4 items); Social relationships (5 items); Independence, Control over life, Freedom (4 items); Home and neighborhood (4 items); Psychological and emotional well-being (4 items); Financial circumstances (4 items); Leisure and activities (6 items) [16]. For each statement, participants are asked to select one of five options: “strongly disagree”; “disagree”; “neither agree nor disagree”; “agree”; and “strongly agree” [17]. Each response is scored between 1 to 5 with higher scores indicating better QoL [17]. The total OPQoL score ranges between 35 (the lowest possible QoL) to 175 (the highest possible QoL) [16].

2.5. Examined Variables

Further variables were evaluated:
Sociodemographic variables: age (60–64 years group; 65–69 years group; 70–74 years group; 75–79 years group; and ≥80 years), gender (male, female), education level (primary school (3–4 grades); incomplete secondary school (8–9 grades); secondary school (10–11 grades); specialized secondary (technical school, college); higher (bachelor, specialist); postgraduate (master, doctor, PhD, professor, candidate of science, doctor of science, and other), marital status (single, married, widowed, divorced, other), and place of residence (urban, rural).
Health-related variables: self-reported overall health (weak; below average; average; good; and very good), hypertension (yes; no), diabetes (yes; no), cerebrovascular disease (yes; no), cardiovascular disease (yes; no), chronic obstructive pulmonary disease (COPD) (yes; no).
COVID-19 related variable: COVID-19-related fear (yes; no). The participants were asked the following question: Did you feel anxious or worried for the safety of yourself, close family members or friends, due to COVID-19? The outcome of this question represents self-reported COVID-19-related fear rather than a clinically assessed fear construct.
For the purpose of this study, further variables were modified and arranged into described categories [18]:
Age: 60–69 years age group, 70–79 years age group, and ≥80 years age group.
Education: Elementary and secondary (primary, incomplete secondary, secondary) educational level group, specialized secondary educational level group, and university (higher, postgraduate, other) educational level group
Marital status: Single group that included those who were single, widowed, divorced, other, and married group.

2.6. Statistical Analysis

The results were presented for categorical variables as whole numbers (N) and percents (%) and for continuous variables as mean values (MV) and standard deviation (SD). We compared the frequencies of studied sociodemographic and health-related variables between groups with fear and without the fear of the COVID-19 and mean values of OPQoL domains between groups with fear and without the fear of the COVID-19. For the evaluation of differences between categorical variables, we performed the Chi-squared test and Fisher’s Exact test, while for assessment of continuous variables we use the Mann–Whitney U test. Cronbach’s alfa was calculated for each OPQoL domain.
Logistic regression analyses were performed to assess associations between the presence of COVID-19-related fear and sociodemographic and health-related characteristics. Multivariable logistic regression with backward elimination was conducted separately for sociodemographic and for health-related variables. Stratified multivariable linear regression analyses with backward selection were performed separately among older adults with and without COVID-19-realted fear as an exploratory approach to examine whether determinants of OPQoL domains differ according to fear status. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported for the logistic regression models, while B coefficient with 95%CI for linear regression analyses.
Statistical analysis was done using IBM SPSS statistical software (SPSS for Windows, version 26.0, SPSS, Chicago, IL, USA). The statistical significance was set at p < 0.05.

3. Results

From 445 participants in this study, 438 (98.4%) provided responses with (yes or no) to the question regarding COVID-19-related fear.
Table 1 presents the study group’s frequencies of sociodemographic and health-related variables by COVID-19-related fear. Frequencies across different levels of education significantly differed by the presence of the COVID-19-related fear (p = 0.012). Female gender (p < 0.001) and presence of hypertension (p = 0.007) were significantly more present in older adults with reported COVID-19-related fear.
Reliability and mean values of Older People’s Quality of Life domains regarding absence or presence of COVID-19-realted fear are presented in Table 2. Regarding internal consistency reliability of the OPQoL domains, lowest reliability was noticed for independence, control over life, freedom domain (Cronbach’s alfa = 0.56), followed by the life overall domain (Cronbach’s alfa = 0.59), suggesting heterogeneity of items within these domains and highest for psychological and emotional well-being domain (Cronbach’s alfa = 0.73) followed by social relationships domain (Cronbach’s alfa = 0.69). Life overall domain values differed significantly between those with and without COVID-19-related fear (U = 15252.50; z = 2.181; p = 0.029). Social relationship domain mean values differed significantly between those with and without COVID-19-related fear (U = 15499.50; z = 2.449; p = 0.014).
The results of multivariable logistic regression analyses with backward elimination analyzing sociodemographic and health-related variables associated with COVID-19-related fear are presented in Table 3. In the multivariate logistic backward regression model, female gender (OR = 2.344; p = 0.001), those with hypertension (OR = 2.106; p = 0.008), those with specialized secondary educational level (OR = 2.321; p = 0.012) and at the border of significance those with university educational level (OR = 1.832; p = 0.051) were significantly associated with COVID-19-related fear in older adults.
Multivariable linear regression analysis with backward selection of sociodemographic and health-related variables regarding certain OPQoL domains in the group of participants without/with COVID-19-related fear is presented in Table 4.
In the multivariable linear regression model with backward selection, we accounted for around 18% of the variance in the life overall domain of OPQoL, 29% of the variance in the health domain, around 18% of the variance in the psychological and emotional well-being of OPQoL, around 16% of the variance in the home and neighborhood domain of OPQoL, 11% of the variance in the social relations domain of OPQoL, around 14% of the variance in the independence, control over life, freedom domain of OPQoL, around 13% of the variance in the financial circumstances domain of OPQoL, and around 14% of the variance in the leisure and activities domain of OPQoL for those without COVID-19-related fear.
In the multivariable linear regression model with backward selection, we accounted for around 13% of the variance in the life overall domain of OPQoL, 26% of the variance of the health domain of OPQoL, around 7% of the variance in the psychological and emotional well-being domain of OPQoL, around 1% of the variance in the home and neighborhood domain of OPQoL, 3% of the variance in the social relations domain of OPQoL, around 20% of the variance in the independence, control over life and freedom domain of OPQoL, around 13% of the variance in the financial circumstances domain of OPQoL, and around 6% of the variance in the leisure and activities domain of OPQoL for those with COVID-19-related fear.
Multivariable linear regression analysis with backward selection of sociodemographic and health-related variables regarding OPQoL domains in the group of participants without/with reported COVID-19-related fear is presented in Table 5.
For individuals without COVID-19-related fear, a higher life overall domain is significantly negatively associated with present cardiovascular disease (B = −2.551; p = 0.002); a higher health domain is significantly positively associated with better self-reported overall health (B = 1.297; p < 0.001), present COPD (B = 5.035; p = 0.030), and urban place of residence (B = 1.449; p = 0.008); a higher psychological and emotional well-being domain is significantly positively associated with better self-reported overall health (B = 0.642; p = 0.024), present hypertension (B = 1.144; p = 0.035), and present COPD (B = 4.133; p = 0.029); a higher home and neighborhood domain is significantly positively associated with advanced age (B = 0.823; p = 0.021) and significantly negatively associated with present cardiovascular disease (B = −1.654; p = 0.010); a higher social relations domain is significantly negatively associated with present cardiovascular disease (B = −2.074; p = 0.035); a higher independence, control over life and freedom domain is significantly negatively associated with present cardiovascular disease (B = −1.707; p = 0.016) and significantly positively associated with present COPD (B = 4.393; p = 0.036); a higher financial circumstances domain is significantly negatively associated with present cardiovascular diseases (B = −2.469; p = 0.013) and being single (B = −1.634; p = 0.023); and a higher leisure and activities domain is significantly positively associated with better self-reported overall health (B = 1.064; p = 0.050), and present COPD (B = 10.399; p = 0.008).
For individuals with COVID-19-related fear, a higher life overall domain is significantly positively associated with better self-reported overall health (B = 0.691; p < 0.001), and significantly negatively associated with present cardiovascular disease (B = −0.588; p = 0.027) and being single (B = −0.481; p = 0.033); a higher health domain is significantly positively associated with better self-reported overall health (B = 1.320; p < 0.001) and urban place of residence (B = 0.735; p = 0.011), and significantly negatively correlated with present hypertension (B = −0.888; p = 0.004), and present cardiovascular disease (B = −0.967; p = 0.009); a higher psychological and emotional well-being domain is significantly positively associated with a better self-reported overall health domain (B = 0.395; p = 0.001), and urban place of residency (B = 0.483; p = 0.010); a higher home and neighborhood domain is significantly positively associated with better self-reported overall health (B = 0.249; p = 0.036); a higher social relations domain is significantly negatively associated with being single (B = −0.671; p = 0.014); a higher independence, control over life and freedom is significantly positively associated with better self-reported overall health (B = 1.082; p < 0.001) and significantly negatively associated with present cardiovascular disease (B = −0.542; p = 0.039); a higher financial circumstances domain is significantly positively associated with better self-reported overall health (B = 1.132; p < 0.001) and significantly negatively associated with being single (B = −0.694; p = 0.036); and a higher leisure and activities domain is significantly positively associated with better self-reported overall health (B = 0.556; p = 0.026), and significantly negatively associated with advanced age (B = −0.747; p = 0.020).

4. Discussion

In our study, female gender was associated with a higher likelihood of reporting COVID-19-related fear. Previously gender differences were reported in COVID-19 outcomes and mortality, with males being at the risk of worse outcomes as well as a lethal outcome [19]. Furthermore, in the study from China, it was reported that older males with comorbidities are more likely to be affected with COVID-19 [20]. Moreover, it was shown that females had higher levels of anxiety, stress and depression as well as the fact that the greater psychological impact of the COVID-19 outbreak was significantly associated with the female gender [21]. The study that was conducted in Kazakhstan reported as well that female gender was associated with higher likelihood of anxiety during the COVID-19 pandemic [22]. In a study from Argentina by Dinardi et al., authors argued that females reported higher levels of fear during the pandemic [23], despite lower mortality rates. Additionally, they stated that cultural norms and structural inequalities can have an influence on gendered response to fear, with the example of suppression or redirection of man’s fear responses because of cultural norms like masculinity’s association with stoicism and control [23]. Furthermore, it was reported that family-related factors such as household composition and marital status highly correlated with COVID-19 risk perception in females, while economic factors correlated more in males [24]. These findings clearly point to the complexity of the fear onset and responses between genders, particularly during the onsets of novel pandemics where there are more questions than answers. Therefore, better understanding of gender bio-psycho-social differences regarding fear would have a beneficial effect in prevention and reduction of consequences for the affected individuals. More effective preventive measures and interventional strategies could be proposed and implemented toward not just reduction in fear onset but reduction in the severity and associated complications that can arise, leading to better preparedness and more effective responses to potential new stressful events. Potential preventive measures should include health education to increase awareness. Interventional strategies should involve age-appropriate and gender-sensitive multidisciplinary approaches, integrating psychological support, stress management techniques, and community-based psychosocial interventions.
Furthermore, older adults with hypertension were more likely to report COVID-19-related fear. Due to the sudden surge in COVID-19 cases, there were significant disruptions in healthcare services [25]. There was a decreased number of visits to outpatient healthcare facilities [26]. Furthermore, increased psychological stress during the COVID-19 pandemic had negative effects on blood pressure regulation in controlled hypertensive patients [27]. This could have a potentially negative impact on patients with hypertension and their ability to seek and receive adequate healthcare services in time, thus raising the fear of uncertainty during the COVID-19 pandemic. Aside from hypertension in older adults, our findings revealed that presence of cardiovascular disease was associated with decreased life overall, health as well as independence, control over life and freedom domains of OPQoL in those who reported fear of COVID-19. With regards to the abovementioned, recommendations and policy actions that are oriented toward reducing the fear among older adults with hypertension as well as present cardiovascular disease particularly in the event of the pandemic should incorporate educational interventions that should focus on the positive effects of proper daily life activities, recognition of benefits of social participation in the community, importance of adequate medication use and knowledge of specific symptom recognition. Aside from educational interventions, public health strategies oriented toward adequate communication and proposing adaptive healthcare models that will ensure continuity of hypertension care are important and thus should be considered and implemented as well.
From the results of our study, it can be seen that older adults from Kazakhstan with specialized secondary and university levels of educational were associated with higher likelihood of reporting COVID-19-related fear. Previously, in the study from South Korea, it was reported that educational level in older adults was related to COVID-19 risk perception, where higher levels were associated with lower risk perception in older adults [24]. Moreover, in another study by Ranjbaran et al., authors argue that educational level and health literacy are required for better understanding and reducing fear of COVID-19 [28]. Furthermore, the cross-sectional study from Turkey noticed that higher health literacy was associated with lower FCoV-19 score [29]. Our findings are not consistent with previous reports. The possible explanation could be in different degrees of health literacy between different regional and age groups. In the study on the rural population of Almaty region in Kazakhstan, it was noticed that 35% of the respondents had an inadequate health literacy index, while 60.6% had problematic health literacy, demonstrating overall low health literacy [30]. The possible barriers to health literacy in rural areas of Kazakhstan are reported to be socio-economic disparities, geographic remoteness, cultural norms and linguistic diversity, digital divide between urban and rural areas in Kazakhstan, as well as challenges associated with educational systems in rural areas [31]. Moreover, it was argued that higher rates of limited health literacy were noticed in older adults [32]. Furthermore, it was reported that older adults were more fearful in cases when having family members and close friends diagnosed with COVID-19, and that there was an increase in misinformation or misleading medical advice on transmission, treatment and control of COVID-19, stressing the importance of health literacy [33]. In older adults particularly, it was shown that education affects health literacy, and that those with low health literacy usually experience poor physical and/or cognitive health [34]. In the study by Elkana et al., it was stated that many highly educated older adults report subjective cognitive decline and psychological distress [35]. These findings clearly point to the complex nature and multidimensional aspects of the role of educational level in older adults where numerous factors should be considered. Thus, the measures that will lead to the effective reduction of fear during pandemic situations in older adults should include educational strategies prioritizing development of functional health literacy. Moreover, adequate information from healthcare providers and social media might be beneficial for proper awareness, as well as promotion and implementation of age-appropriate interventions and coping strategies, bearing in mind physical, cognitive, emotional and social challenges that could have impact on fear in pandemic situations.
Moreover, our study findings revealed that older adults who reported COVID-19-related fear, with better self-reported overall health, had higher life overall; health, psychological and emotional well-being; independence, control over life, freedom; financial circumstances; and leisure and activities domains in OPQoL. These results clearly point to the importance of good self-reported overall health on numerous domains of quality of life in older adults. In the cross-sectional study on older adults, it was stated that self-reported frailty had negative relationship with quality of life [36]. Moreover, poor self-rated health was shown to be associated with depression [37,38], pain [39], fatigue, problems with mobility, deficits in vision, dizziness and heart disease [38]. All of these might have an influence on overall life satisfaction, psychological and emotional well-being, independence, financial circumstance as well as leisure and activity participation.
Additionally, being single, particularly during COVID-19 pandemic, was negatively associated with numerous aspects of quality of life in older adults, mainly in the overall life, social relations and financial circumstances domains for older adults who reported COVID-19-related fear. Furthermore, being in an urban area in such a pandemic was shown to be positively associated with certain aspects of quality of life, mainly in the health and psychological and emotional well-being domains in older adults who reported COVID-19-related fear.

5. Limitations

There are several limitations to this study. First, as the research was conducted in Kazakhstan, the findings may not be broadly applicable to other populations due to differences in demographic, cultural, socio-economic and healthcare contexts. Secondly, the cross-sectional nature of the study means that all findings should be interpreted as associations rather than causal relationships. An additional limitation is the small sample size of certain participant subgroups, reducing statistical power in study analyses. Furthermore, self-reported data in this study might influence the appearance of social desirability bias and recall bias [40]. Certain variables like health literacy, coping strategies, exposure to information, etc., were not taken into consideration, which could potentially have an impact on the observed associations. Moreover, COVID-19-related fear was evaluated by a single dichotomous question, addressing anxiety or worry related to personal, family or friends’ safety, which may not fully include the multidimensional nature or intensity of fear. This measure reflects a perceived threat response and may overlap with broader constructs of anxiety or concern; thus, such an approach was used during the COVID-19 pandemic to perform a brief assessment of the tested participants.

6. Conclusions and Future Considerations

Females, older adults with hypertension, those with specialized secondary educational level and those with a university educational level were more likely to report COVID-19-related fear. Moreover, female gender, those with hypertension, with specialized secondary as well as university education were significantly associated with COVID-19-related fear in older adults. For individuals with reported COVID-19-related fear, advanced age was negatively associated with leisure and activities domain; better self-reported overall health was positively associated with the life overall, health, psychological and emotional well-being, home and neighborhood, independence, control over life and freedom, financial circumstances, and leisure and activities domains of OPQoL; present hypertension was negatively associated with the health domain of OPQoL; present cardiovascular disease was negatively associated with the life overall, health, and independence, control over life and freedom domains of OPQoL; being single was negatively associated with life overall, social relations, and financial circumstances domains of OPQoL; and urban place of residency was positively associated with health, and psychological and emotional well-being domains of OPQoL. Our findings point to numerous variables that were associated with the COVID-19-related fear and quality of life domains regarding COVID-19-related fear in older adults from Kazakhstan during pandemics. There is a need for a multidisciplinary approach in proposing, developing and implementing the adequate and optimal gender- and age-appropriate strategies and interventions that will lead to a reduction in fear during a pandemic in older adults.
There is a need for further evaluation of gender-specific mechanisms that could have an influence on the fear emotion during pandemics, with particular attention to gender biological differences, psychosocial factors and coping patterns. Moreover, additional research on health literacy, and on exposure to information and misinformation impacts on fear and quality of life in older adults during a pandemic is needed. Given the fact that fear was more frequently noticed among older adults with hypertension during the COVID-19 pandemic, future investigations should assess the effectiveness of integrated care models.

Author Contributions

Conceptualization, A.I. (Assel Izekenova), D.N., D.S., A.I. (Aigulsum Izekenova) and A.N.; methodology, A.I. (Assel Izekenova), D.N., D.S., A.I. (Aigulsum Izekenova), M.A., F.M., I.L. and A.N.; investigation, A.I. (Assel Izekenova), D.N., D.S., A.I. (Aigulsum Izekenova), A.N. and M.A.; supervision, A.I. (Assel Izekenova), D.N., D.S., A.I. (Aigulsum Izekenova) and A.N.; formal analysis, M.A., F.M. and I.L.; visualization, F.M. and I.L.; writing—original draft, A.I. (Assel Izekenova), D.N., D.S., A.I. (Aigulsum Izekenova), A.N., M.A., F.M. and I.L. All authors have read and agreed to the published version of the manuscript.

Funding

No funding was received for this study.

Institutional Review Board Statement

Ethical approval for the study was granted by the Science Ethics Committee of Kenzhegali Sagadiyev University of International Business (No. 1/22) (Date: 25 April 2022).

Informed Consent Statement

Oral informed consent was obtained from the participants before inclusion in the study.

Data Availability Statement

Data are available upon reasonable request from the author Dinara Sukenova.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Shahid, Z.; Kalayanamitra, R.; McClafferty, B.; Kepko, D.; Ramgobin, D.; Patel, R.; Aggarwal, C.S.; Vunnam, R.; Sahu, N.; Bhatt, D.; et al. COVID-19 and Older Adults: What We Know. J. Am. Geriatr. Soc. 2020, 68, 926–929. [Google Scholar] [CrossRef]
  2. Tana, C.; Moffa, L.; Falasca, K.; Vecchiet, J.; Tana, M.; Mantini, C.; Ricci, F.; Ticinesi, A.; Meschi, T.; Cipollone, F.; et al. Approach to COVID-19 in older adults and indications for improving the outcomes. Ann. Med. 2023, 55, 2265298. [Google Scholar] [CrossRef] [PubMed]
  3. Abul, Y.; Leeder, C.; Gravenstein, S. Epidemiology and Clinical Presentation of COVID-19 in Older Adults. Infect. Dis. Clin. N. Am. 2023, 37, 1–26. [Google Scholar] [CrossRef] [PubMed]
  4. Nikolich-Zugich, J.; Knox, K.S.; Rios, C.T.; Natt, B.; Bhattacharya, D.; Fain, M.J. SARS-CoV-2 and COVID-19 in older adults: What we may expect regarding pathogenesis, immune responses, and outcomes. Geroscience 2020, 42, 505–514. [Google Scholar] [CrossRef] [PubMed]
  5. Nanda, A.; Vura, N.V.R.K.; Gravenstein, S. COVID-19 in older adults. Aging Clin. Exp. Res. 2020, 32, 1199–1202. [Google Scholar] [CrossRef]
  6. Cirrincione, L.; Plescia, F.; Ledda, C.; Rapisarda, V.; Martorana, D.; Lacca, G.; Argo, A.; Zerbo, S.; Vitale, E.; Vinnikov, D.; et al. COVID-19 Pandemic: New Prevention and Protection Measures. Sustainability 2022, 14, 4766. [Google Scholar] [CrossRef]
  7. Angın, Ü.; Karaahmet, E. The Relationship Between Fear of COVID-19, Fear of Death and Anxiety in the Accompanists of Patients Diagnosed with COVID-19. Eur. Arch. Med. Res. 2022, 38, 171–177. [Google Scholar] [CrossRef]
  8. Peiró, J.M.; Luque-García, A.; Soriano, A.; Martínez-Tur, V. Fears during the Covid-19 pandemics and their influence on physical health: A cross-sectional study on the general population in Spain. Int. J. Clin. Health Psychol. 2023, 23, 100361. [Google Scholar] [CrossRef]
  9. Ornell, F.; Schuch, J.B.; Sordi, A.O.; Kessler, F.H.P. “Pandemic fear” and COVID-19: Mental health burden and strategies. Braz. J. Psychiatry 2020, 42, 232–235, Erratum in Braz. J. Psychiatry 2020, 42, 333. [Google Scholar] [CrossRef]
  10. Autenrieth, L.K.; Asselmann, E.; Melzig, C.A.; Benke, C. Fear of COVID-19 predicts increases in anxiety, depressive symptoms, health anxiety, psychosocial distress, and loneliness: Findings from a prospective two-year follow-up study. J. Psychiatr. Res. 2024, 177, 162–168. [Google Scholar] [CrossRef]
  11. Quadros, S.; Garg, S.; Ranjan, R.; Vijayasarathi, G.; Mamun, M.A. Fear of COVID 19 Infection Across Different Cohorts: A Scoping Review. Front. Psychiatry 2021, 12, 708430. [Google Scholar] [CrossRef] [PubMed]
  12. Agrawal, S.; Dróżdż, M.; Makuch, S.; Pietraszek, A.; Sobieszczańska, M.; Mazur, G. The Assessment of Fear of COVID-19 among the Elderly Population: A Cross-Sectional Study. J. Clin. Med. 2021, 10, 5537. [Google Scholar] [CrossRef] [PubMed]
  13. Yadav, U.N.; Yadav, O.P.; Singh, D.R.; Ghimire, S.; Rayamajhee, B.; Kanti Mistry, S.; Rawal, L.B.; Ali, A.M.; Kumar Tamang, M.; Mehta, S. Perceived fear of COVID-19 and its associated factors among Nepalese older adults in eastern Nepal: A cross-sectional study. PLoS ONE 2021, 16, e0254825. [Google Scholar]
  14. Social Code of the Republic of Kazakhstan. “Adilet” Legal Information System of Regulatory Legal Acts of the Republic of Kazakhstan. Available online: https://adilet.zan.kz/eng/docs/K2300000224 (accessed on 20 April 2023).
  15. Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Bureau of National Statistics. Beijing, China. Available online: https://stat.gov.kz/ (accessed on 13 March 2021).
  16. International Longevity Center UK. Older People’s Quality of Life Questionnaire (OPQOL-35). Available online: https://ilcuk.org.uk/wp-content/uploads/2019/03/OPQOL-full-questionnaire.pdf (accessed on 27 March 2025).
  17. Bilotta, C.; Bowling, A.; Nicolini, P.; Casè, A.; Pina, G.; Rossi, S.V.; Vergani, C. Older People’s Quality of Life (OPQOL) scores and adverse health outcomes at a one-year follow-up. A prospective cohort study on older outpatients living in the community in Italy. Health Qual. Life Outcomes 2011, 9, 72. [Google Scholar]
  18. Izekenova, A.; Izekenova, A.; Sukenova, D.; Nikolic, D.; Chen, Y.; Rakhmatullina, A.; Nurbakyt, A. Factors Associated with Loneliness and Psychological Distress in Older Adults During the COVID-19 Pandemic in Kazakhstan: A Cross-Sectional Study. Medicina 2025, 61, 703. [Google Scholar] [CrossRef]
  19. Jin, J.M.; Bai, P.; He, W.; Wu, F.; Liu, X.F.; Han, D.M.; Liu, S.; Yang, J.K. Gender Differences in Patients With COVID-19: Focus on Severity and Mortality. Front. Public Health 2020, 8, 152. [Google Scholar]
  20. Chen, N.; Zhou, M.; Dong, X.; Qu, J.; Gong, F.; Han, Y.; Qiu, Y.; Wang, J.; Liu, Y.; Wei, Y.; et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet 2020, 395, 507–513. [Google Scholar]
  21. Wang, C.; Pan, R.; Wan, X.; Tan, Y.; Xu, L.; Ho, C.S.; Ho, R.C. Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. Int. J. Environ. Res. Public Health 2020, 17, 1729. [Google Scholar] [CrossRef]
  22. Mergenova, G.; Rosenthal, S.L.; Myrkassymova, A.; Bukharbayeva, A.; Iskakova, B.; Izekenova, A.; Izekenova, A.; Alekesheva, L.; Yerdenova, M.; Karibayev, K.; et al. The COVID-19 pandemic and mental health in Kazakhstan. Glob. Ment. Health 2023, 10, e52. [Google Scholar]
  23. Dinardi, G.; Llovet, I.; Gonzalez Fernandez, M.O. Older adults, gender, and emotions: Fear during the COVID-19 pandemic in Buenos Aires City, Argentina. Int. J. Popul. Stud. 2025, 11, 90–102. [Google Scholar] [CrossRef]
  24. Kang, S.; You, C.H.; Kwon, Y.D. Factors affecting risk perception of COVID-19: Differences by age and gender. Front. Public Health 2025, 12, 1484306. [Google Scholar] [CrossRef]
  25. Moskal, A.; Kowalski, S.; Żak-Kowalska, K.; Al-Wathinani, A.M.; Goniewicz, K.; Goniewicz, M. The impact of the COVID-19 pandemic on hypertension management in southeastern Poland: Challenges and adaptations for emergency medical teams. Medicine 2025, 104, e42416. [Google Scholar] [CrossRef] [PubMed]
  26. Özcan, A.; Avcı, İ.A. The influence of the pandemic on fear of contagion, blood pressure management and adherence to medication in hypertensive older adults in Turkey. J. Hum. Hypertens. 2022, 36, 852–859. [Google Scholar] [CrossRef] [PubMed]
  27. Celik, M.; Yilmaz, Y.; Karagoz, A.; Kahyaoglu, M.; Cakmak, E.O.; Kup, A.; Celik, F.B.; Karaduman, A.; Kulahcioglu, S.; Izci, S.; et al. Anxiety disorder associated with the COVID-19 pandemic causes deterioration of blood pressure control in primary hypertensive patients. Medeni. Med. J. 2021, 36, 83–90. [Google Scholar] [PubMed]
  28. Ranjbaran, S.; Chollou, K.M.; Abedi-Nerbin, S.; Babazadeh, T. Predictors of fear of COVID-19 in a low-income country: Health literacy is important. Front. Psychol. 2024, 15, 1394957. [Google Scholar] [CrossRef]
  29. Türkoglu, N.; Kavuran, E.; Ay, E. The relationship between health literacy and Covid 19 fear: A cross sectional study from Turkey. J. Health Lit. 2022, 7, 86–94. [Google Scholar]
  30. Shayakhmetov, S.S.; Toguzbayeva, K.K.; Ismailova, A.A.; Tabibi, R.; Derbishalieva, Z.K.; Dzhusupov, K.O. Health Literacy of Rural Population of Kazakhstan. Iran. J. Public Health 2020, 49, 1269–1277. [Google Scholar]
  31. Ermakhan, Z.; Suleimenova, R.; Bakhtiyar, S.; Lucero-Prisno, D.E., III. Challenges and opportunities for improving health literacy in rural areas of Kazakhstan: Current trends and strategies for improvement. J. Health Dev. 2024, 4, 81–89. [Google Scholar]
  32. Coughlin, S.S.; Vernon, M.; Hatzigeorgiou, C.; George, V. Health Literacy, Social Determinants of Health, and Disease Prevention and Control. J. Environ. Health Sci. 2020, 6, 3061. [Google Scholar]
  33. Ayaz-Alkaya, S.; Dülger, H. Fear of coronavirus and health literacy levels of older adults during the COVID-19 pandemic. Geriatr. Nurs. 2022, 43, 45–50. [Google Scholar] [CrossRef]
  34. Chesser, A.K.; Keene Woods, N.; Smothers, K.; Rogers, N. Health Literacy and Older Adults: A Systematic Review. Gerontol. Geriatr. Med. 2016, 2, 2333721416630492. [Google Scholar] [CrossRef]
  35. Elkana, O.; Levy, M.; Tal Bicovsky, Y.; Tal, N.; Oren, N.; Ash, E.L. Objective and Subjective Measures of Cognitive Decline in Highly Educated Older Adults: A 10-Year Longitudinal Study. J. Dement. Alzheimers Dis. 2025, 2, 18. [Google Scholar] [CrossRef]
  36. Souza Júnior, E.V.; Cruz, D.P.; Silva, C.S.; Rosa, R.S.; Siqueira, L.R.; Sawada, N.O. Implications of self-reported fragility on the quality of life of older adults: A cross-sectional study. Rev. Esc. Enferm. USP 2021, 55, e20210040. [Google Scholar] [CrossRef]
  37. Chang-Quan, H.; Xue-Mei, Z.; Bi-Rong, D.; Zhen-Chan, L.; Ji-Rong, Y.; Qing-Xiu, L. Health status and risk for depression among the elderly: A meta-analysis of published literature. Age Ageing 2010, 39, 23–30. [Google Scholar] [CrossRef]
  38. Lisko, I.; Törmäkangas, T.; Jylhä, M. Structure of self-rated health among the oldest old: Analyses in the total population and those living with dementia. SSM Popul. Health 2020, 11, 100567. [Google Scholar]
  39. Mäntyselkä, P.T.; Turunen, J.H.; Ahonen, R.S.; Kumpusalo, E.A. Chronic pain and poor self-rated health. JAMA 2003, 290, 2435–2442. [Google Scholar] [CrossRef]
  40. Althubaiti, A. Information bias in health research: Definition, pitfalls, and adjustment methods. J. Multidiscip. Healthc. 2016, 9, 211–217. [Google Scholar] [PubMed]
Table 1. Frequencies of sociodemographic and health-related variables by COVID-19-related fear.
Table 1. Frequencies of sociodemographic and health-related variables by COVID-19-related fear.
VariablesCOVID-19-Related Fearp
NoYes
Age, years, N (%)60–69 years40 (55.6)225 (61.5)0.615 *
70–79 years27 (37.5)116 (31.7)
80 years and above5 (6.9)25 (6.8)
Gender, N (%)Male41 (56.9)129 (35.2)<0.001 *
Female31 (43.1)237 (64.8)
Educational level, N (%)Primary and secondary29 (40.3)86 (23.5)0.012 *
Specialized secondary18 (25.0)126 (34.4)
University25 (34.7)154 (42.1)
Self-reported overall health, N (%)Weak3 (4.2)9 (2.5)0.314 **
Below average1 (1.4)24 (6.6)
Average31 (43.1)165 (45.1)
Good31 (43.1)146 (39.9)
Very good6 (8.3)22 (6.0)
Hypertension, N (%)Yes21 (29.2)170 (46.4)0.007 *
No51 (70.8)196 (53.6)
Diabetes, N (%)Yes7 (9.7)34 (9.3)0.908 *
No65 (90.3)332 (90.7)
Cerebrovascular disease, N (%)Yes1 (1.4)16 (4.4)0.329 **
No71 (98.6)350 (95.6)
Cardiovascular disease, N (%)Yes10 (13.9)85 (23.2)0.079 *
No62 (86.1)281 (76.8)
COPD, N (%)Yes1 (1.4)14 (3.8)0.483 **
No71 (98.6)352 (96.2)
Marital status, N (%)Single25 (34.7)126 (34.4)0.961 *
Married47 (65.3)240 (65.6)
Place of residence, N (%)Urban33 (45.8)182 (49.7)0.546 *
Rural39 (54.2)184 (50.3)
p—values represent comparisons between participants with and without fear of COVID-19. *—Chi-Square test; **—Fisher’s Exact test.
Table 2. Reliability and mean values of Older People’s Quality of Life (OPQoL) domains regarding the absence or presence of COVID-19-related fear.
Table 2. Reliability and mean values of Older People’s Quality of Life (OPQoL) domains regarding the absence or presence of COVID-19-related fear.
VariablesCronbach AlphaCOVID-19-Related Fearp *
NoYes
OPQoL domains, MV ± SDLife overall0.5914.89 ± 2.3515.39 ± 2.120.029
Health0.6814.35 ± 2.6013.71 ± 3.010.204
Psychological and emotional well-being0.7316.40 ± 1.9616.54 ± 1.740.707
Home and neighborhood0.6716.24 ± 1.9816.44 ± 1.820.439
Social relationships0.6919.36 ± 2.9620.38 ± 2.460.014
Independence, Control over life, Freedom0.5614.43 ± 2.1614.30 ± 2.200.474
Financial circumstances0.6613.22 ± 2.9212.59 ± 3.100.112
Leisure and activities0.6720.28 ± 3.9820.66 ± 3.700.528
*—Mann-Whitney U test.
Table 3. Regression analysis of sociodemographic and health-related variables regarding the COVID-19-related fear.
Table 3. Regression analysis of sociodemographic and health-related variables regarding the COVID-19-related fear.
VariablesCOVID-19-Related Fear, Ref. No
Multivariable Logistic Regression with Backward Elimination
OR (95%CI)p
Sociodemographic variables
Gender,
Ref. male		2.344
(1.390–3.951)		0.001
Educational level, Ref. elementary and secondary educationSpecialized secondary2.321
(1.203–4.479)		0.012
University1.832
(0.997–3.367)		0.051
Health-related variables
Hypertension,
Ref. no		2.106
(1.218–3.644)		0.008
Table 4. Variability of evaluated OPQoL domains in groups of participants without/with COVID-19-related fear.
Table 4. Variability of evaluated OPQoL domains in groups of participants without/with COVID-19-related fear.
OPQoL DomainsWithout COVID-19-Related FearWith COVID-19-Related Fear
R2FpR2Fp
Life overall0.1754.8060.0040.12517.285<0.001
Health0.2919.291<0.0010.26025.252<0.001
Psychological and emotional well-being0.1813.7060.0090.0676.495<0.001
Home neighborhood0.1556.3240.0030.0124.4340.036
Social relations0.1114.3130.0170.0305.5280.004
Independence, control over life, freedom0.1395.5830.0060.19543.942<0.001
Financial circumstances0.1254.9510.0100.13418.625<0.001
Leisure and activities0.1355.3880.0070.0577.232<0.001
Table 5. Multivariable linear regression analysis with backward selection of sociodemographic and health related variables regarding OPQoL domains in the group of participants without/with COVID-19-related fear.
Table 5. Multivariable linear regression analysis with backward selection of sociodemographic and health related variables regarding OPQoL domains in the group of participants without/with COVID-19-related fear.
VariablesOPQoL Domains
Multivariable Linear Backward Regression Analysis
Without COVID-19-Related FearWith COVID-19-Related Fear
B (95%CI)pB (95%CI)p
Life overall domain
Self-reported overall health--0.691 (0.411–0.970)<0.001
Hypertension1.140 (−0.074–2.354)0.065--
Cardiovascular disease−2.551 (−4.144–−0.958)0.002−0.588 (−1.108–−0.068)0.027
COPD4.147 (−0.256–8.549)0.064--
Marital status--−0.481 (−0.923–−0.040)0.033
Health domain
Age--−0.437 (−0.893–0.019)0.060
Self-reported overall health1.297 (0.664–1.929)<0.0011.320 (0.942–1.697)<0.001
Hypertension--−0.888 (−1.491–−0.286)0.004
Cardiovascular--−0.967 (−1.691–−0.243)0.009
COPD5.035 (0.510–9.561)0.030--
Place of residency1.449 (0.388–2.511)0.0080.735 (0.171–1.298)0.011
Psychological and emotional well-being domain
Self-reported overall health0.642 (0.086–1.198)0.0240.395 (0.159–0.630)0.001
Hypertension1.144 (0.084–2.204)0.035−0.345 (−0.710–0.019)0.063
Cardiovascular disease−1.268 (−2.608–0.073)0.063--
COPD4.133 (0.440–7.827)0.0290.783 (−0.135–1.702)0.094
Place of residency--0.483 (0.116–0.850)0.010
Home and neighborhood domain
Age0.823 (0.128–1.518)0.021--
Self-reported overall health--0.249 (0.016–0.481)0.036
Cardiovascular disease−1.654 (−2.907–−0.402)0.010--
Social relations domain
Self-reported overall health--0.276 (−0.041–0.594)0.088
Cardiovascular disease−2.074 (−4.001–−0.146)0.035--
COPD5.426 (−0.270–11.122)0.062--
Marital status--−0.671 (−1.205–−0.136)0.014
Independence, control over life, freedom domain
Self-reported overall health--1.082 (0.811–1.354)<0.001
Cardiovascular disease−1.707 (−3.091—0.322)0.016−0.542 (−1.057–−0.028)0.039
COPD4.393 (0.303–8.484)0.036--
Financial circumstances domain
Self-reported overall health--1.132 (0.740–1.524)<0.001
Cardiovascular disease−2.469 (−4.396–−0.542)0.013--
Marital status−1.634 (−3.033–−0.234)0.023−0.694 (−1.340–−0.047)0.036
Place of residency--−0.544 (−1.170–0.082)0.088
Leisure and activities domain
Age--−0.747 (−1.375–−0.118)0.020
Self-reported overall health1.064 (0.001–2.127)0.0500.556 (0.067–1.045)0.026
Hypertension--−0.667 (−1.457–0.122)0.097
COPD10.399 (2.831–17.967)0.008--
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Izekenova, A.; Sukenova, D.; Nurbakyt, A.; Akmaral, M.; Izekenova, A.; Milanovic, F.; Lazic, I.; Nikolic, D. Unlocking the Factors Associated with COVID-19-Related Fear in Older Adults from Kazakhstan. COVID 2026, 6, 41. https://doi.org/10.3390/covid6030041

AMA Style

Izekenova A, Sukenova D, Nurbakyt A, Akmaral M, Izekenova A, Milanovic F, Lazic I, Nikolic D. Unlocking the Factors Associated with COVID-19-Related Fear in Older Adults from Kazakhstan. COVID. 2026; 6(3):41. https://doi.org/10.3390/covid6030041

Chicago/Turabian Style

Izekenova, Assel, Dinara Sukenova, Ardak Nurbakyt, Maimakova Akmaral, Aigulsum Izekenova, Filip Milanovic, Irena Lazic, and Dejan Nikolic. 2026. "Unlocking the Factors Associated with COVID-19-Related Fear in Older Adults from Kazakhstan" COVID 6, no. 3: 41. https://doi.org/10.3390/covid6030041

APA Style

Izekenova, A., Sukenova, D., Nurbakyt, A., Akmaral, M., Izekenova, A., Milanovic, F., Lazic, I., & Nikolic, D. (2026). Unlocking the Factors Associated with COVID-19-Related Fear in Older Adults from Kazakhstan. COVID, 6(3), 41. https://doi.org/10.3390/covid6030041

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