Abstract
Background
This study aims to investigate the factors shaping resilience during the COVID-19 pandemic among people living with HIV (PLWH).
Methods
A total of 341 participants were included in this cross-sectional study. The online survey included scales of resilience, depression & anxiety, loneliness, social support, COVID-19 fear, stress, and sociodemographic information.
Results
Logistic regression test results showed loneliness (OR = 2.548, 95% CI = 1.251, 5.189), social support (OR = 2.217, 95% CI = 1.148, 4.279), income (OR = 2.581, 95% CI = 1.217, 5.472), sexual orientation (OR = 2.707, 95% CI = 1.004, 7.300), age (OR = 1.044, 95% CI = 1.006, 1.083) and COVID-19 fear (OR = 0.891, 95% CI = 0.840, 0.944) were statistically significant factors associated with resilience among PLWH.
Conclusion
In conclusion, reducing COVID-19 fear by providing the correct information about the COVID-19 pandemic, fortifying the level of social support satisfaction, as well as minimising the level of loneliness have the potential to improve psychological resilience among PLWH.
Keywords: Fear of COVID-19, resilience, loneliness, social support, mental health, HIV
Introduction
Resilience has been described as the psychological, behavioural, and social adaptive coping ability of human beings during an unfavourable set of circumstances, enabling them to maintain regular physical and psychological functioning.1,2 Many elements were described in shaping resilience, such as neurochemical, genetic, developmental as well as psychosocial, structural, and socioeconomic factors. 3 Experts assert that resilience contributes to the overall physical and mental health of the individual, reducing the vulnerability of illness and potentially harmful effects of stressors by adapting to change and standing the negative influence of stressors. 2
The COVID-19 pandemic is one of the most common adversities faced and dealt with by many people nowadays. Not only the biological effects, but the pandemic was also associated with an increase in psychological symptoms, presumably due to the enormous change in social life, working conditions, and economic status.4–6 However, effective resilient coping mechanisms are thought to be protective of mental health and accomplished in defeating the adverse outcomes of the pandemic psychologically.7,8
The importance of resilient coping in people living with HIV (PLWH) facing everyday life adversities and its association with better health outcomes and therapy maintenance was shown. 9 During the COVID-19 pandemic, studies revealed that PLWH have higher levels of resilience and, therefore, lower levels of depression and anxiety symptoms compared with people living without HIV. 10 In addition, the role of economic hardship on mental health was buffered by resilience among PLWH during the pandemic. This buffering impact was crucial to maintaining adherence to antiretroviral drug therapy. 11
Gottert et al. came up with a conceptual framework of factors that are associated with resilience in a positive and negative way. There are three levels of influence to discuss the factors which have an impact on resilience among PLWH: individual (e.g. mental health, self-stigma, enacted stigma on HIV and key population, food & housing insecurities), interpersonal (e.g. social support from family and friends, intimate relationship), and structural (e.g. activism, legal protections). The factors selected to be studied in this study are influenced by their conceptual framework and the results of another study which indicated that people who reported higher resilience also had higher social support, lower depression, anxiety, and level of worry.12,13 Posttraumatic Growth Inventory had some items, such as sense of relationships with others, supported our selection of factors. 14 Since PLWH are maintaining their lives with a chronic condition, which can also generate stigma, it is still essential to improve the resilience among PLWH. 15 Therefore, our aim in this study was to investigate the factors associated with resilience in PLWH during the COVID-19 pandemic.
Methods
Study design
In this cross-sectional study, the target population was PLWH in Turkey. The participants were recruited with the sample of convenience technique. The questionnaire was prepared via Qualtrics and distributed online to PLWH with the help of Turkey-based non-governmental organisations (NGOs) such as Pozitif-İz, Positive Living Association, Positive Solidarity, and Red Ribbon Istanbul.
Participants
To be eligible to participate in the study, participants had to be diagnosed with HIV infection, over 18 years old, live in Turkey, and volunteer to complete the survey. The participants were provided written informed consent before starting to take the questionnaire.
Data collection
The questionnaire was prepared between December 2020 and January 2021. The survey distribution to participants and completion of them took 2 months, between March and May 2021. In total, 341 PLWH participated in the study. However, 59 participants did not complete the survey; therefore, the data from 282 participants was utilised for the analysis.
Measurements
There were 46 questions in the survey that combined four scales and sociodemographic questions and questions about healthcare during the pandemic to address the possible adverse effects of COVID-19 on the mental health of PLWH.
The first section of the survey included sociodemographic information (gender, age, marital status, sexual orientation, education status, occupation, city, income, economic hardship, and job loss during the pandemic). Gender, sexual orientation, education status, and income questions were in multiple choice types.
Gender variable has three possible options as “male”, “female”, and “non-binary”.
Sexual orientation variable was converted into a trichotomous variable as “heterosexual”, “does not want to indicate”, and a combination of “homosexual” and “bisexual”. Education status variable was converted into a dichotomous variable as “high school graduate or below” and “university graduate or above”. Income variable was converted into a dichotomous variable as “minimum wage and below” (0-2824 TRY) and “above minimum wage” (2825 TRY and more).
Residency question was open-ended, and it was converted into a dichotomous variable as “living in Istanbul” and “not living in Istanbul” since Istanbul was at the top of the list of responses.
Economic hardship was investigated using one nominal item, which questioned, “During the pandemic, I had difficulty meeting my basic needs, including food and clothing.”. This item was answered as “Yes” or “No”.
In the second section, there were questions about healthcare during the pandemic (years after HIV diagnosis, COVID-19 diagnosis, antiretroviral drug supply/adherence, doctor visits, antidepressant use, and mental health services).
Years after the HIV diagnosis question was open-ended and converted into a dichotomous variable as “2019 and before” and “2020 and after”, according to the median.
COVID-19 diagnosis was a multiple-choice question, and the possible options were “Yes” and “No”.
Problems about antiretroviral drug supply and adherence during the pandemic were multiple choice questions, and the possible options were “Yes” and “No”.
In the last section, there were questions about social support, loneliness, partner violence, COVID-19 fear, depression & anxiety, perceived stress, and resilience.
COVID-19 Fear was measured using an adapted Turkish version of “The Fear of COVID-19 Scale” (Cronbach’s Alpha = 0.87).16,17 It is a 5-point Likert-type scale, and the sum of 7 items was used to calculate the score (minimum = 7, maximum = 35).
Perceived Stress was measured using an adapted Turkish version of the “Perceived Stress-4 Scale” (Cronbach’s Alpha = 0.66).18,19 It is a 5-point Likert-type scale. Items 2 and 3 were reverse coded, and the sum of the four items was used to calculate the score (minimum = 4, maximum = 16).
Depression & Anxiety was measured using an adapted Turkish version of the “Patient Health Questionnaire-4 Scale” (Cronbach’s Alpha = 0.83).20,21 It is a 4- point Likert-type scale, and the sum of the four items was used to calculate the score (minimum = 0, maximum = 12).
Loneliness was assessed using 1 item scored on a 5-point Likert-type scale, which asked, “How often do you feel alone?”. It was converted into a dichotomous variable according to the median value of the responses by combining “never”, “almost never”, and “sometimes” responses into one subgroup, “quite often”, and “frequently” responses into another subgroup.
Social support was analysed using 1 item scored on a 5-point Likert-type scale, which asked, “To what extent are you satisfied with the social support you feel from your environment/relatives?”. It was converted into a dichotomous variable according to the median value of the responses by combining “very dissatisfied”, “dissatisfied”, and “neither satisfied nor dissatisfied” responses into one subgroup, “satisfied” and “very satisfied” responses into another subgroup.
Partner violence was evaluated using one nominal item, which asked, “Have you ever been physically, psychologically, or sexually assaulted by your partner during the pandemic?”. Participants chose separately from these three types of violence they were exposed to. The options with no respondents were not indicated in Table 1. It was added to the analysis as a dichotomous variable, one subgroup who experienced at least one kind of partner violence and another subgroup who experienced no partner violence or did not have any partners.
Table 1.
Demographics, health status and psychosocial factors.
| Variable | N (%) | Mean (median, SD) | Interquartile range |
|---|---|---|---|
| Age (years) | 33.25 (31, 9.719) | 26–38 | |
| Fear of COVID-19 | 17.45 (17, 6.08) | 14–21 | |
| Depression & anxiety | 5.32 (4, 3.57) | 3–8 | |
| Perceived stress | 7.65 (8, 3.18) | 6–9 | |
| Resilience | 3.23 (3.17, 0.75) | 2.8–3.67 | |
| Gender | |||
| Male | 218 (77.3) | ||
| Female | 22 (7.8) | ||
| Non-binary | 42 (14.9) | ||
| Sexual orientation | |||
| Heterosexual | 53 (18.8) | ||
| LGB* | 190 (67.4) | ||
| Does not want to indicate | 34 (12.1) | ||
| Marital status | |||
| Single | 246 (87.2) | ||
| Married | 34 (12.1) | ||
| Income | |||
| No income | 54 (19.2) | ||
| 1-2824 TRY | 34 (12.1) | ||
| 2825-4999 TRY | 78 (27.8) | ||
| 5000-7999 TRY | 48 (17.1) | ||
| 8000 TRY + | 67 (23.8) | ||
| Education status | |||
| Literate | 1 (0.4) | ||
| Primary school | 4 (1.4) | ||
| Secondary school | 18 (6.4) | ||
| High school | 46 (16.4) | ||
| University degree | 159 (56.8) | ||
| Master’s degree | 46 (16.4) | ||
| PhD degree | 6 (2.1) | ||
| Residency | |||
| Istanbul | 179 (64.4) | ||
| Other cities in Turkey | 99 (35.6) | ||
| Job loss during pandemic | |||
| Yes | 58 (20.6) | ||
| No | 178 (63.1) | ||
| No job before pandemic | 46 (16.3) | ||
| Problems meeting basic needs | |||
| Yes | 74 (26.2) | ||
| No | 208 (73.8) | ||
| Problems about antiretroviral drug supply | |||
| Yes | 21 (7.4) | ||
| No | 261 (92.6) | ||
| Problems about antiretroviral drug adherence | |||
| Yes | 24 (8.5) | ||
| No | 258 (91.5) | ||
| Consulting mental health services during pandemic | |||
| Yes | 62 (22.1) | ||
| No | 219 (77.9) | ||
| Antidepressant drug use during pandemic | |||
| Yes | 36 (12.8) | ||
| No | 245 (87.2) | ||
| Continuation of HIV status follow-ups | |||
| Continued | 78 (24.4) | ||
| Disrupted | 202 (75.6) | ||
| Years of HIV diagnosis | |||
| 2020–2021 | 67 (24.3) | ||
| 2019 and before | 208 (75.7) | ||
| Partner violence | |||
| Only psychological violence | 22 (7.8) | ||
| Physical and psychological violence | 3 (1.1) | ||
| Physical, psychological, and sexual violence | 3 (1.1) | ||
| No experience of violence | 122 (43.3) | ||
| Do not have partner | 132 (46.8) | ||
| Feeling lonely | |||
| Never | 26 (9.3) | ||
| Almost never | 26 (9.3) | ||
| Sometimes | 120 (42.9) | ||
| Quite often | 65 (23.2) | ||
| Frequently | 43 (15.4) | ||
| Social support satisfaction | |||
| Very dissatisfied | 37 (13.3) | ||
| Dissatisfied | 29 (10.4) | ||
| Neither satisfied nor dissatisfied | 88 (31.5) | ||
| Satisfied | 91 (32.6) | ||
| Very satisfied | 34 (12.2) | ||
*LGB: homosexual and bisexual.
The dependent variable of this study was resilience, and it was measured using an adapted Turkish version of “The Brief Resilience Scale” (Cronbach’s Alpha = 0.76).22,23 It is a 5-point Likert-type scale. Items 2, 4, and 6 were reverse coded, and the mean of the six items was used to calculate the score (minimum = 1, maximum = 5). It was converted into a dichotomous variable as “low levels of resilience” and “high levels of resilience”, according to the median value of the responses (3.17).
Statistical analysis
Continuous variables were documented as mean value, median, and standard deviation and compared across groups using non-parametric tests. Categorical variables were expressed as percentages. The normality of the data was investigated with the Kolmogorov-Smirnov Test. Bivariate analyses were evaluated with the chi-square test. Correlations between continuous variables were indicated as Spearman’s rho. Logistic regression was applied for the selected variables from the bivariate analysis that were found to have a statistically significant impact on resilience. P-value <0.05 was considered statistically significant. Based on the previous literature,11,24,25 sexual orientation, COVID-19 fear, social support, and loneliness were planned to be included in logistic regression a priori regardless of their statistical significance in bivariate analysis. p < 0.05 was considered statistically significant for adding variables to the logistic regression. Each analysis was performed with the participants answering the questions and missing data were excluded from the analysis. The reliability of scales was stated as Cronbach’s Alpha. SPSS v26 was used for statistical analysis.
Results
Demographics and health status
The demographic information and health status of participants are listed in Table 1. The majority of the participants were male (n = 218, 77.3%), 22 participants (7.8%) were female, and 42 (14.9%) participants defined themselves as non-binary. The mean age was 33.25 years (SD = 9.7). The participants were primarily from Istanbul (n = 179, 64.4%). The city of İzmir (n = 22, 7.8%) and Ankara (n = 16, 5.7%) came after Istanbul. More than half of the participants (n = 160, 57.8%) identified themselves as homosexuals, and 30 (10.8%) were bisexuals. One fifth of the participants (n = 54, 19.2%) stated that they had no income, and 193 (68.7%) had income above the minimum wage in Turkey. More than a quarter of the participants (n = 74, 26.2%) stated that they had difficulties meeting their basic needs; additionally, 58 (20.6%) participants indicated that they lost their job during the pandemic, and 46 (16.3%) participants did not have a job before the pandemic.
A few participants reported that they had difficulty in the supply of antiretroviral drugs (21, 7.4%); 36 (n = 36, 12.8%) had started to use antidepressants during the pandemic, and 62 (n = 62, 22.1%) had consulted mental health services during the pandemic. Almost a quarter of the participants (n = 67, 24.3%) were diagnosed with HIV between 2020 and 2021.
Bivariate analysis
Table 2 illustrates the results of the bivariate analysis. The variables which are found statistically significant were added to the multivariable analysis model for further investigation. Additionally, we performed a chi-square test and found that there is a statistically significant association between “income”, “job loss during the pandemic”, and “economic hardship” variables showing collinearity between these variables. Likewise, we have found that there is a statistically significant association between “problems with antiretroviral drug supply” and “problems with antiretroviral drug adherence” and between “consulting mental health services” and “antidepressant use” indicating collinearity. The results of these analyses are shown in the Appendix. Therefore, we have “income”, “problems with antiretroviral drug adherence”, and “antidepressant use” to the multivariable analysis to overcome the collinearity problem.
Table 2.
Bivariate Analysis of Factors Associated with Resilience (Chi-square test).
| Resilience | ||||
|---|---|---|---|---|
| Low resilience | High resilience | Total | p-value | |
| N (%) | N (%) | N (%) | ||
| Gender | ||||
| Female | 12 (57.1) | 9 (42.9) | 21 | 0.081 |
| Male | 101 (49) | 105 (51) | 206 | |
| Non-binary | 26 (68.4) | 12 (31.6) | 38 | |
| Marital status | ||||
| Single | 14 (42.4) | 19 (57.6) | 33 | 0.235 |
| Married | 123 (53.5) | 107 (46.5) | 230 | |
| Sexual orientation | ||||
| Heterosexual | 23 (45.1) | 28 (54.9) | 51 | 0.252 |
| LGB* | 92 (52.3) | 84 (47.7) | 176 | |
| Not want to indicate | 21 (63.6) | 12 (36.4) | 33 | |
| Education status | ||||
| High school and below | 35 (58.3) | 25 (41.7) | 60 | 0.271 |
| University degree and above | 102 (50.2) | 101 (49.8) | 203 | |
| Residency | ||||
| Istanbul | 73 (43.7) | 94 (56.3) | 167 | <0.001 |
| Other cities in Turkey | 64 (67.4) | 31 (32.6) | 95 | |
| Income | ||||
| 0-2824 TRY | 61 (76.3) | 19 (23.8) | 80 | <0.001 |
| 2825 + TRY | 77 (41.8) | 107 (58.2) | 184 | |
| Job loss during pandemic | ||||
| Yes | 37 (64.9) | 20 (35.1) | 57 | 0.019 |
| No | 75 (45.7) | 89 (54.3) | 164 | |
| Not have job before pandemic | 27 (61.4) | 17 (38.6) | 44 | |
| Difficulty meeting basic needs | ||||
| Yes | 49 (71) | 20 (29) | 69 | <0.001 |
| No | 90 (45.9) | 106 (54.1) | 196 | |
| Problems about antiretroviral drug supply | ||||
| Yes | 15 (71.4) | 6 (28.6) | 21 | 0.070 |
| No | 124 (50.8) | 120 (49.2) | 244 | |
| Problems about antiretroviral drug adherence | ||||
| Yes | 17 (77.3) | 5 (22.7) | 22 | 0.015 |
| No | 122 (50.2) | 121 (49.8) | 243 | |
| HIV follow up visits | ||||
| Continued | 33 (45.2) | 40 (54.8) | 73 | 0.134 |
| Disrupted | 106 (55.5) | 85 (44.5) | 191 | |
| Years of HIV diagnosis | ||||
| 2020–2021 (during pandemic) | 36 (60) | 24 (40) | 60 | 0.196 |
| 2019 and before | 101 (50.5) | 99 (49.5) | 200 | |
| Antidepressant drug use during pandemic | ||||
| Yes | 25 (75.8) | 8 (24.2) | 33 | 0.004 |
| No | 113 (48.9) | 118 (51.1) | 231 | |
| Use of mental health services during pandemic | ||||
| Yes | 40 (71.4) | 16 (28.6) | 56 | 0.001 |
| No | 98 (47.1) | 110 (52.9) | 208 | |
| Partner violence | ||||
| Yes | 20 (76.9) | 6 (23.1) | 26 | 0.009 |
| No or no partner | 119 (49.8) | 120 (50.2) | 239 | |
| Loneliness | ||||
| Never and low levels of loneliness | 65 (39.2) | 101 (60.8) | 166 | <0.001 |
| High levels of loneliness | 73 (74.5) | 25 (25.5) | 98 | |
| Social support satisfaction | ||||
| Never and low levels of satisfaction | 96 (68.6) | 44 (31.4) | 140 | <0.001 |
| High levels of satisfaction | 43 (34.7) | 81 (65.3) | 124 | |
*LGB: homosexuals and bisexuals.
Scales
Reliability analysis was performed, and Cronbach’s Alpha score was found to be 0.88, 0.89, 0.77, and 0.82 for COVID-19 Fear, Patient Health Questionnaire-4, Perceived Stress, and Brief Resilience Scale, respectively.
Table 1 illustrates the mean, median, standard deviation, and interquartile ranges of the COVID-19 Fear, Depression & Anxiety (D&A), Perceived Stress, and Resilience scores. In addition, the correlation analysis is shown in Table 3, showing the statistically significant correlations of COVID-19 fear, D&A, and Perceived Stress scores with Resilience scores, with the correlation coefficients of −0.291, −0.648, and −0.601, respectively, with p < 0.001.
Table 3.
Correlation coefficients of associations among continuous variables (Spearman’s rho).
| Variables | D&A** | Perceived stress | COVID-19 fear | Age |
|---|---|---|---|---|
| Resilience | −0.648* | −0.601* | −0.291* | 0.239* |
| D&A** | 0.751* | 0.291* | −0.334* | |
| Perceived stress | 0.223* | −0.257* | ||
| COVID-19 fear | −0.026a |
(*p < 0.001, ap = 0.669).
**D&A: depression and anxiety.
Multivariable analysis
The result of the multivariable analysis can be seen in Table 4. Loneliness (OR = 2.548, 95% CI = 1.251, 5.189), social support (OR = 2.217, 95% CI = 1.148, 4.279), income (OR = 2.581, 95% CI = 1.217, 5.472), sexual orientation (OR = 2.707, 95% CI = 1.004, 7.300), age (OR = 1.044, 95%CI = 1.006, 1.083), and COVID-19 fear (OR = 0.904, 95% CI = 0.856, 0.954) were found to be statistically significant factors associated with the resilience according to logistic regression analysis. With an OR of 2.895 (CI = 0.987, 8.495), “antidepressant use during the pandemic” was not found to be significantly associated with resilience.
Table 4.
Multivariable analysis of factors associated with resilience.
| Variables | Odds ratio | 95% CI | SE | P-value | |
|---|---|---|---|---|---|
| Age | 1.044 | (1.006, 1.083) | 0.019 | 0.023 | |
| Sexual orientation | Do not want to indicate | 0.026 | |||
| LGB** | 2.707 | (1.004, 7.300) | 0.506 | 0.49 | |
| Heterosexual | 1.037 | (0.339, 3.176) | 0.571 | 0.949 | |
| Residency | Other cities (R) | 0.968 | |||
| Living in istanbul | 1.014 | (0.510, 2.018) | 0.351 | ||
| Income | 0-2824 TRY (R) | 0.013 | |||
| 2825 + TRY | 2.581 | (1.217, 5.472) | 0.383 | ||
| Problems with ART* drug adherence | Experienced no problem (R) | 0.937 | |||
| Experienced problem | 1.055 | (0.284, 3.920) | 0.670 | ||
| Antidepressant use during pandemic | Yes (R) | 0.053 | |||
| No | 2.895 | (0.987, 8.495) | 0.549 | ||
| Partner violence | Yes (R) | 0.429 | |||
| No | 1.668 | (0.470, 5.922) | 0.647 | ||
| Loneliness | High levels of loneliness (R) | 0.010 | |||
| Low levels of loneliness | 2.548 | (1.251, 5.189) | 0.363 | ||
| Social support | Low social support (R) | 0.018 | |||
| High social support | 2.217 | (1.148, 4.279) | 0.336 | ||
| Covid-19 fear | 0.891 | (0.840, 0.944) | 0.030 | <0.001 |
(R): indicates reference category within variables.
*ART: antiretroviral.
**LGB: homosexual and bisexual.
Discussion
Resilient coping has been proposed as a protective factor during the COVID-19 pandemic, and resilience was indicated as a target to prevent the development of depressive symptoms among PLWH. 15 In line with this, our study has found significant associations of resilience with loneliness, social support, age, sexual orientation, COVID-19 fear, and level of income.
Age
Our study results illustrated a significant association between age and resilience in the multivariable analysis, which is in line with the literature. The coping skills might have been improved with age as a response to everyday life events and problems. Through these perceived as life experience, resilience might have been improved which then buffers the overall life stressors of PLWH.26,27
Social support
Social support has been defined as one of the interpersonal level determinants forming resilient coping among PLWH. 1 Our study results illustrated a significant association between social support and resilient coping in the multivariable analysis. Since the participants in our study were recruited through NGOs, this result might be attributed to the social ties of the study population. A comparative study among PLWH by Jones et al. indicated that the association between social support and coping was attributed to the collectivistic lifestyle in Argentina compared to the individualistic nature of the USA.12,28
A study by Wen et al. in 2021 found a positive association between social support and resilience, and they suggested the cause of association as the positive influence of social support on antiretroviral drug adherence, which provided an external contribution to the resilience among PLWH. 29 Similar outcomes of the positive relationship between social support and resilience were obtained in different studies conducted in diverse populations among PLWH, such as older PLWH,24,30 young gay and bisexual men living with HIV. 31
Income and economic hardship
The COVID-19 pandemic caused global economic stagnation with an impact on financial security and caused difficulty in meeting basic needs, health care, and an overall decline in social well-being.32,33 As Çakmaklı et al. demonstrated, Turkey was not an exception to this economic stagnation. 34 Poverty has increased from 10.2% in 2019 to 12.2% in 2020. 35 Our results also indicated that lower income level was significantly associated with lower resilience scores among PLWH.
In a study inquiring about the factors shaping resilience in PLWH conducted in Cambodia, the Dominican Republic, and Uganda, economic hardship, measured by food and housing insecurity, was found to be a factor affecting the resilience of PLWH in Uganda. 10 Taylor et al. have found that financial hardship during COVID-19 was associated with diminished resilience in older adults and suggested that policies such as unemployment benefits and tax credits were important for enhancing psychological resilience. 36 A study by Friedman et al. conducted in the USA demonstrated that both PLWH and people who do not carry HIV who have lower socioeconomic status were affected more by the adverse impacts of COVID-19, resulting in lower resilient coping and other adverse psychosocial outcomes. 37 Also, they found income as the significant predictor for psychosocial health outcomes and stated that financial interventions might be effective in alleviating the negative impact of COVID-19. 37
COVID-19 fear
Our study showed that higher COVID-19 fear was associated with significantly decreased resilience among PLWH in Turkey. One possible explanation is that the uncertainty at the beginning of the pandemic regarding the early findings on susceptibility to COVID-19 and the available treatment options might have generated anxiety among people living with chronic conditions such as PLWH. 38 Studies from Saudi Arabia showed immunocompromised people had increased fear more than others, 39 and HIV has delineated this fear in PLWH. Even though there is no conclusive evidence, PLWH in Spain assume that HIV increases the likelihood of contracting COVID-19 with a consequent decrease in engagement with care among PLWH due to increased social distancing. 40 Moreover, COVID-19-related stigma creates a critical risk to the patients, survivors, and workers in the healthcare system 41 that can re-emerge PLWH’s past experiences of discriminatory attitudes in the case of contracting COVID-19. 42 A study conducted in Thailand showed that another issue regarding resilience and anxiety is the possible disclosure of information about patients’ HIV status to colleagues or the public by healthcare authorities after COVID-19 diagnosis. 43
Sexual orientation
Our study results illustrated that people who did not want to disclose their sexualities have significantly lower resilience than LGB, while heterosexual participants showed no significant association. They might have chosen not to reveal their sexual orientation due to the increased level of heteronormativity, hate speech, and stigmatisation towards sexual minorities in Turkey.44,45 Therefore, not disclosing sexual orientation on an anonymous survey may indicate fear of shame and stigma, contributing to lower resilience levels compared to heterosexuals. Similarly, a study conducted among older PLWH demonstrated that people who did not disclose their sexualities had lower resilience compared to gays/lesbians and also heterosexuals. 24 Another study from Canada showed that heterosexual women living with HIV (WLWH) had significantly higher levels of resilience than sexual minority WLWH. 25
Loneliness
In our study, the association between loneliness and resilience among PLWH during the COVID-19 pandemic was found to be statistically significant. Although pandemic measures such as stay-at-home orders were necessary to limit COVID-19 cases, they might have exacerbated isolation-related vulnerabilities among PLWH. As Marziali et al. stated, while PLWH had already been at greater risk of experiencing social isolation due to experienced stigma, measures increased the level of social isolation with diminished interpersonal relationships that resulted in greater severity of loneliness among PLWH. 46 Another study examining the relationship between resilience and loneliness in a Danish sample showed that all facets of resilience were negatively associated with loneliness. 47 In an observational study among PLWH comparing the relationship between frailty and resilience before the pandemic in 2019 and during the pandemic in 2021, loneliness was associated with impaired resilience among PLWH only during the pandemic. 48
Limitations
This study is subject to several limitations. First, the participants were questioned about some information they needed to remember, which can create recall bias. However, the survey was designed to investigate only the last two weeks to minimise recall bias. Second, as our sample was recruited from NGOs, people with higher social support levels might have been more represented and cannot be generalised to the target population. Some measures consist of only one item, such as loneliness and social support, which could be another limitation. Lastly, the cross-sectional study design has no power to yield a causal relationship; moreover, reverse causation or the existence of a third variable affecting both variables is a possibility.
Additionally, further research aiming to investigate the factors shaping resilience among PLWH would be guiding for understanding the measures which could be utilised to improve the levels of resilience.
Conclusion
The outcomes of this study point out that loneliness, lack of social support, sexual orientation, age, fear of COVID-19, and lower levels of income were associated with psychological resilience at different levels among PLWH living in Turkey. Resilience is an essential factor contributing to the overall well-being of PLWH, who have a higher risk for the negative impacts of COVID-19. Therefore, in times of such public health emergencies, social and financial support mechanisms for vulnerable groups, including PLWH, should be put in place to maintain equity.
Appendix.
Table A1.
Chi-square test between “income”, “job loss during pandemic” and “difficulty meeting basic needs”.
| Income | ||||
|---|---|---|---|---|
| 0-2824 TRY | 2825 TRY and more | Total | p-value | |
| N (%) | N (%) | N | ||
| Job loss during pandemic | ||||
| Yes | 51 (68.9) | 23 (31.1) | 74 | <0.001 |
| No | 22 (12.4) | 156 (87.6) | 178 | |
| Not have job before pandemic | 32 (71.1) | 13 (28.9) | 45 | |
| Difficulty meeting basic needs | ||||
| Yes | 51 (68.9) | 23 (31.1) | 74 | <0.001 |
| No | 37 (17.9) | 170 (82.1) | 207 | |
Table A2.
Chi square test between “problems with antiretroviral drug supply” and “problems with antiretroviral drug adherence”.
| Problems with antiretroviral drug adherence | ||||
|---|---|---|---|---|
| Yes | No | Total | p-value | |
| N (%) | N (%) | N | ||
| Problems with antiretroviral drug supply | ||||
| Yes | 11 (52.4) | 10 (47.6) | 21 | <0.001 |
| No | 13 (5) | 248 (95) | 261 | |
Table A3.
Chi square test between “consulting mental health services during pandemic” and “antidepressant use during pandemic”.
| Antidepressant use during pandemic | ||||
|---|---|---|---|---|
| Yes | No | Total | p-value | |
| N (%) | N (%) | N | ||
| Consulting mental health services during pandemic | ||||
| Yes | 28 (45.2) | 34 (54.8) | 62 | <0.001 |
| No | 8 (3.7) | 211 (96.3) | 219 | |
Footnotes
Authors’ contributions: Conceptualization: NEK, ÇNB, AAC, KK, AM, ŞK, ST, İK; Literature search: NEK, ÇNB, AAC, KK, AM, ŞK; Data collection: NEK, ÇNB, AAC, KK, AM, ŞK, ST; Data Analysis: NEK, ÇNB, AAC, KK, AM, ŞK, İK, Original manuscript draft: NEK, ÇNB, AAC, KK, AM, ŞK; Review and Editing: ST, İK.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
Ethics approval: The questionnaire and methodology for this study was approved by the Human Research Ethics committee of the Koç University (Ethics approval number: 2021.027.IRB3.008).
Consent to participate: Informed consent was obtained from all individual participants included in the study.
Consent for publication: All participants provided written informed consent regarding publishing their data
Availability of data and material: Data described in the manuscript will be made available upon request pending application and approval by the principal investigator.
Code availability: The codes of the software application (SPSS) are available.
ORCID iDs
Nesrin Ecem Killi https://orcid.org/0000-0002-1813-0319
Kardelen Karabulut https://orcid.org/0000-0003-0290-8226
Ali Mutlu https://orcid.org/0000-0003-1808-7872
Şeyhmus Karataş lı https://orcid.org/0000-0002-0838-1851
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