Abstract
Background:
The risk of COVID-19 infection and related health consequences is higher among persons with mental illnesses (PMI). Vaccines have had an impact in reducing the morbidity and mortality in patients with COVID-19 infection. Understanding the reasons for vaccine hesitancy in PMI is crucial for promoting vaccine acceptance in this population, but it remains an under-researched topic.
Aims:
This cross-sectional study assessed perspectives among unvaccinated PMI regarding COVID-19 vaccination in a tertiary care teaching hospital. Factors associated with vaccine hesitancy in this population were explored.
Materials and Methods:
One-hundred consecutive PMI attending the psychiatric outpatient clinic who had not taken the COVID-19 vaccination were recruited after obtaining informed consent. A semi-structured questionnaire was used to elicit knowledge, attitudes, and practices regarding COVID-19 vaccination. The Oxford vaccine hesitancy scale was used to assess vaccine hesitancy; the Brief Psychiatric Rating Scale and Depression Anxiety Stress Scale-21 were administered to assess current psychopathology.
Results:
A majority of the participants (62%) were unwilling for the vaccination, the most common reasons being the perception that they were not at risk of infection, and worry about the possible side effects of the vaccination. Factors associated with low vaccine hesitancy were higher levels of education, greater perception of the risk of contracting the disease, belief that vaccination was effective, and easy accessibility to the vaccine.
Conclusion:
Improving awareness, providing accurate information, and ensuring better accessibility to vaccines are necessary to improve vaccine coverage among PMI. Mental health professionals need to assume an active role in providing education and clarifying misconceptions among our vulnerable patient population to help mitigate vaccine hesitancy.
Keywords: Patient perspectives, psychiatric disorders, vaccine hesitancy
Persons with mental illnesses (PMI) are considered to be at a greater risk of COVID-19 infection for a variety of reasons, including medical comorbidities, altered immune functions, sleep-related problems, and socioeconomic factors, with the prognosis being worse in those with more severe mental illness.[1,2] Given their greater vulnerability, PMI should be provided early access to COVID-19 vaccination as vaccines have been described as the single most important strategy that has helped in reducing morbidity and mortality related to SARS-CoV-2 virus infections.[3,4,5,6,7]
Despite evidence regarding their efficacy, vaccine hesitancy – defined by WHO as “delay in acceptance or refusal of vaccination despite the availability of vaccination services” – remains a significant hurdle in the general population. Studies from different parts of the world carried out in different phases of the pandemic report vaccine hesitancy rates of up to 33%.[8] In India too, surveys have suggested that a proportion of the eligible population were hesitant to take these vaccines.[9,10] Chandani et al. (2021)[11] reported that 37% of the people surveyed were either not sure or unwilling to take the vaccination. Complacency, confidence, and convenience have been identified as general factors that influence vaccine hesitancy.[12] Indian studies have identified several factors contributing to this complex phenomenon. These include concerns regarding the safety, side effects, and effectiveness of vaccines and misconceptions that vaccination would lead to infertility, worsening of health in those with comorbidities, or death.[11] Sociodemographic factors such as gender, employment, level of education, geographical location, and financial status have also been recognized to influence vaccine hesitancy.[13]
The phenomenon of vaccine hesitancy has not been adequately researched among PMI. A report from the United States suggested a vaccine hesitancy of approximately 12% in this population, with higher rates among those with substance use disorders and physical comorbidities, while a study from China reported rates of up to 47%.[14,15] In a study from India, 37.8% of outpatients in a psychiatry clinic stated definitely that they did not intend to receive vaccination, with lower educational achievement and practicing Islam as a religion being the factors associated with vaccine hesitancy.[4] The current study was planned in this context to better understand PMI perspectives regarding COVID-19 vaccination and factors associated with vaccine hesitancy. This will help plan effective strategies to improve acceptance toward vaccines in this vulnerable population.
MATERIALS AND METHODS
Study design
The study employed a cross-sectional design.
Setting
Patients were recruited from the psychiatry outpatient clinic of a tertiary care hospital in south India over a period of 6 months between October 2021 and March 2022. The study was conducted once the vaccine was available to the general public aged 18 years and above, in the national phased roll-out of the COVID-19 vaccine.
Population and sample
Every 10th patient who had registered at the clinic was screened for eligibility for the study. Those who were Tamil speakers and who had not received even one dose of COVID-19 vaccination were invited to participate in the study. Those who provided written informed consent were enrolled. Those with an intellectual disability or visual/auditory impairment that precluded them from participating in the research interview were excluded. All research interviews were conducted by the first author (ACSS) and lasted approximately 45–60 minutes. Patients received treatment as usual.
Data collection tools
The sociodemographic and clinical details of the patients were collected using a specially designed proforma.
A semi-structured questionnaire was used to assess patients’ knowledge, attitudes, and practices regarding COVID-19 vaccination. This questionnaire evolved out of group discussions with patients and mental health professionals (psychiatrists, psychologists, psychiatric social workers, occupational therapists, and psychiatric nurses) at the hospital. Domains assessed included awareness about COVID-19 and measures to reduce/prevent its spread, COVID-19 vaccines and their effectiveness, effects of vaccination on psychiatric illness/psychotropic medications, accessibility to vaccination, and methods to address COVID-19 vaccine hesitancy. Content validity was checked independently by four psychiatrists. A Tamil translation was used for the study.
The Brief Psychiatric Rating Scale (BPRS)[16] was used to assess psychopathology in patients with severe mental illness. This is a reliable clinician-rated scale with 24 items. Scores range from 1 (not present) to 7 (extremely severe) for each item. The total score is calculated by summing up the ratings for all items and can range from 24 to 168.
The Depression Anxiety Stress Scale (DASS)-21 item scale was used to assess patient psychopathology in those without severe mental illnesses.[17] It is a self-reported scale to measure anxiety, depression, and stress. A 4-point severity score was used to assess the severity/frequency of the subject’s experience. Separate scores were calculated for depression, anxiety, and stress by adding the scores for relevant items under each category. The scales used in DASS have been shown to have good psychometric properties. Tamil versions of this scale have been used in previous research projects from this department.[18]
The Oxford COVID-19 vaccine hesitancy scale was used to assess vaccine hesitancy. This is a 7-item measure with response options scored from 1 to 5. “Don’t know” options were excluded from scoring. Higher scores indicate greater vaccine hesitancy.[19]
Ethical considerations
The institutional review board and ethics committee approved the study protocol (IRB Minute No-14047 dated June 30, 2021).
Sample size estimation
The sample size was calculated using the formula 4pq/d2, where P denotes the prevalence of vaccine hesitancy among PMI, estimated to be 30%, q = (100 − p), and d (the precision) was taken as 7.[13] The required sample size was 171. However, during data collection, recruitment had to be ceased after a period of time as most outpatients at the clinic had taken at least one dose of the vaccine by then. We were able to recruit only 100 PMI.
Statistical analysis
Mean, standard deviation, and range were used to describe continuous variables; frequency distributions were used to describe categorical variables. The Chi-square test was used to check the association for categorical variables and student’s t-test for continuous variables. Multivariate linear and logistic regression analysis was carried out using factors found significant in bivariate analysis. Analysis of data was performed using SPSS (IBM) for Windows (Version 16.0.1).
RESULTS
Sociodemographic details and clinical profile: [Table 1]
Table 1.
Sociodemographic and clinical details
| Sociodemographic and clinical variables | Unwilling for COVID-19 vaccination (n=62) |
Willing for COVID-19 vaccination (n=38) |
||
|---|---|---|---|---|
| Mean (SD) | n (%) | Mean (SD) | n (%) | |
| Age of the patient in years | 41.45 (11.95) | 39.89 (11.87) | ||
| Gender - female | 33 (53.2) | 19 (50) | ||
| Marital status - currently married | 41 (66.1) | 26 (68.4) | ||
| Residence - rural | 49 (79) | 28 (73.7) | ||
| Employment status - unemployed | 35 (56.5) | 23 (60.5) | ||
| Education in years | 7.63 (4.85) | 10.03 (4.94) | ||
| Family type - nuclear | 44 (71) | 25 (67.6) | ||
| Has more than 4 family members living at home - yes | 24 (38.7) | 16 (42.1) | ||
| Has children less than 18 years at home - yes | 27 (43.5) | 18 (47.4) | ||
| Has older people greater than 60 years at home - yes | 25 (40.3) | 16 (42.1) | ||
| Diagnosis - severe mental illness | 54 (87.1) | 32 (84.2) | ||
| Diagnoses | ||||
| Schizophrenia | 37 (59.7) | 17 (447) | ||
| Bipolar disorder | 9 (14.5) | 12 (31.6) | ||
| Other psychotic disorders* | 6 (9.7) | 3 (7.9) | ||
| Neurotic disorders# | 10 (16.2) | 6(15.8) | ||
| Distance to the nearest vaccination center in km | 1.27 (1.84) | 1.28 (1.57) | ||
| Age of onset of illness in years | 31.73 (11.74) | 28.16 (8.46) | ||
| Duration of illness in months | 100.39 (91.7) | 121.11 (97.88) | ||
| Past inpatient stay - yes | 11 (17.7) | 13 (342) | ||
| Past ECT - yes | 6 (9.7) | 4 (10.5) | ||
| Alcohol use disorder - yes | 6 (9.7) | 3 (7.9) | ||
| Nicotine use disorder - yes | 10 (16.1) | 10 (26.3) | ||
| Medical comorbidity - yes | 17 (27.4) | 12 (31.6) | ||
| Diabetes - yes | 6 (9.7) | 5 (132) | ||
| Hypertension - yes | 2 (3.2) | 0 | ||
| Dyslipidemia - yes | 3 (4.8) | 1 (2.6) | ||
| Total BPRS Scoring | 43.46 (25.22) | 43.88 (24.51) | ||
| Total DASS Scoring | 36 (6) | 3983 (1354) | ||
| Depression score | 11.12 (3.36) | 1367 (596) | ||
| Anxiety score | 13 (3.7) | 1317 (387) | ||
| Stress score | 11.88 (2.1) | 13 (498) | ||
| Total Oxford vaccine hesitancy score | 26.76 (4.74) | 15.82 (5.36) | ||
*Acute psychosis, delusional disorder, #Dysthymia, obsessive-compulsive disorder, panic disorder, and substance use disorder
The mean age of the participants was 40.86 years. The majority were women (52%), married (67%), unemployed (58%), and from a rural background (77%). The majority (86%) had a diagnosis of a severe mental illness (schizophrenia, bipolar disorder, recurrent depressive disorder), with schizophrenia being the most common diagnosis (54%).
Knowledge, attitudes, and practices regarding COVID-19 infection and vaccination [Tables 2 and 3]
Table 2.
Knowledge, attitude, and practices regarding COVID-19 infection
| Knowledge, attitude, and practices regarding COVID-19 | Frequency (%) |
|---|---|
| Heard about the COVID-19 pandemic | 77 (77) |
| Think the COVID-19 illness is a real threat to one’s life | 53 (53) |
| Awareness about common COVID-19 symptoms | |
| Fever, chills | 46 (46) |
| Cough | 42 (42) |
| Cold | 16 (16) |
| Breathing difficulty | 25 (25) |
| Anosmia | 3 (3) |
| Body ache/Headache | 14 (14) |
| Don’t know | 28 (28) |
| Awareness of the mode of spread | |
| Airborne | 67 (67) |
| Contaminated surfaces | 7 (7) |
| Waterborne | 3 (3) |
| Has anyone in your family or neighborhood tested positive for COVID-19 - yes | 21 (21) |
| Will you disclose your illness to others if you become COVID-19 positive - yes | 29 (29) |
| Reasons for non-disclosure* | |
| No need for disclosure | 36 (36) |
| Stigma | 34 (34) |
| Personal choice | 3 (3) |
| Do you think you are at risk of developing COVID-19 infection - yes | 3 (3) |
| Protective measures can help prevent COVID-19 spread - | |
| Mask | 65 (43.33) |
| Handwash/Sanitiser/Soap | 23 (15.33) |
| Social distancing | 22 (14.66) |
| Vaccine | 20 (13.33) |
| Measures helping in preventing the spread of COVID-19 | |
| Wearing mask | 84 (84) |
| Hand hygiene | 74 (74) |
| Social distancing/avoiding mass gathering | 74 (74) |
| Willing to follow quarantine protocols for COVID-19 - yes | 79 (79) |
| Reasons for not willing to comply with quarantine protocol | |
| Not necessary | 19 (19) |
| It will spread anyway | 2 (2) |
| Preventive measures practiced by participants against COVID-19 | |
| Home remedies | 29 (29) |
| Social distancing | 8 (8) |
*Some participants gave more than one response
Table 3.
Knowledge, attitude, and practices about COVID-19 vaccination
| Knowledge, attitudes, and practices | Frequency (%) |
|---|---|
| Know that there is a vaccine to prevent COVID-19 - yes | 78 (78) |
| Know the names of at least one of the available vaccines in the country - yes | 29 (29) |
| Number of doses of vaccine required - | |
| <2 doses | 25 (25) |
| 2 doses | 59 (59) |
| >2 doses | 16 (16) |
| Minimum gap, in number of days, between 1st and 2nd doses of vaccine - mean (SD) | 46.39 (32.37) |
| Minimum number of days after vaccination, for vaccine to be effective against COVID-19 - mean (SD) | 13.85 (13.62) |
| Willing to take COVID-19 vaccination - yes | 62 (62) |
| Reasons for willingness: | 6 (9.68) |
| No harm in taking it | 33(51.61) |
| Useful in protecting me. | 6 (9.68) |
| Free of cost/affordable | 6 (9.68) |
| Doctor’s/other’s recommendation | 4 (6.45) |
| Social responsibility | 9 (1452) |
| Friends and relatives have taken it. | 37 (5968) |
| Reasons for unwillingness: | 3 (4.84) |
| I do not feel I am at risk. | 6 (9.68) |
| I am religious - God will protect. | 46 (74.19) |
| Fear of putting foreign material in the body. | 7 (1129) |
| It might have unforeseen side effects. | 3 (4.84) |
| Lack of trust in vaccine/health system | 13 (20.97) |
| I am afraid of needles/blood/doctors/hospitals. | |
| Others - conspiracy theories, medication interaction, etc., | |
| Priority for vaccination should be given to those with psychiatric illness - yes | 3 (3) |
| The vaccine is effective against COVID-19 - yes | 68 (68) |
| Have concerns regarding the safety of the COVID-19 vaccine - yes | 45 (45) |
| Transmit the virus or infection. | 8 (8) |
| Will affect fertility. | 4 (4) |
| Will cause sexual problems. | 5 (5) |
| Allergies | 20 (20) |
| Interaction between COVID-19 vaccine and psychiatric medications - yes | 70 (70) |
| Vaccination can worsen psychiatric illness - yes | 60 (60) |
| Vaccination can cause neurological manifestations such as paralysis or brain damage - yes | 12 (12) |
| Vaccination is only meant for people without psychiatric illness - yes | 10 (10) |
| Vaccination may make the side effects of psychiatric medication worse - yes | 72 (72) |
| Is willing to take the COVID-19 vaccine only if | |
| The government makes it compulsory. | 39 |
| Incentives attached. | 7 |
| More accessible | 9 |
| Recommendation of religious leaders/indigenous practitioners | 4 |
| Source of information about vaccination is mainly from | |
| Television/internet/radio/newspaper/social media | 80 (80) |
| Health care workers | 11 (11) |
| Friends, relatives, neighbors | 83 (83) |
| Politicians, religious leaders, actors | 5 (5) |
| Think COVID-19 vaccine available at | |
| Government hospital | 71 (71) |
| Only private hospital | 7 (7) |
| Door-to-door service | 3 (3) |
| Other:Camps | 22 (22) |
| Problems that you faced trying to get COVID-19 vaccine | |
| Vaccine shortage | 2 (2) |
| Difficulty in registering on the online portal | 2 (2) |
| Did you feel you had difficulty in trying to get the COVID-19 vaccine? - yes | 16 (16) |
| Distance from home to the nearest vaccination center in km mean (SD) | 1.28 (1.73) |
Approximately a quarter (23%) of the participants stated that they were not aware of the pandemic, 28% did not have knowledge about the symptoms of COVID-19, and 53% considered the illness as possibly life-threatening. A minority (26%) thought that it was not a communicable disease. Although almost all participants (97%) thought that they themselves were not at risk of contracting COVID-19, 65% believed that face masks were useful to prevent transmission of COVID-19 infection. A few patients stated that home remedies such as hot water and turmeric milk were effective in preventing infection.
Seventy-eight participants (78%) were aware that vaccines were available against COVID-19 infection, and 29% were able to name the common types. Most participants did not think there was a need for PMI to be prioritized (97%) for the vaccine. Though the majority (84%) said that the vaccine was easily accessible, most (62%) were unwilling to take it. The commonly cited reasons for this were concerns regarding possible side effects (74%) and a perception that they were not at risk of infection (60%). More than half (70%) reported concerns about possible interactions between psychotropic medication and vaccines, and 60% were worried about worsening psychiatric illness following vaccination.
Factors associated with vaccine hesitancy
On bivariate analyses, the factors associated with vaccine hesitancy were lower educational levels (t = −2.38, df = 98, P = 0.02), a diagnosis of bipolar disorder (χ2 = 4.31, df = 1, P = 0.04), a perception of not being at risk of infection (χ2 = 5.05, df = 1, P = 0.03), belief that COVID-19 spread can be prevented by adequate measures (χ2 = 4.24, df = 1, P = 0.04), a belief that the vaccine was not effective (χ2 = 10, df = 1, P = 0.002), a belief that the vaccine can worsen the psychiatric illness (χ2 = 5.13, df = 1, P = 0.02), and a perception that vaccines were inaccessible (χ2 = 120.87, df = 1, P = 0.002). These factors were used for logistic regression analyses to adjust for confounders, and those that remained significant in multivariate analyses included the belief that vaccines were effective (OR = 0.19, 95% CI = 0.04–0.84, P = 0.03), and the perception that vaccines were difficult to access (OR = 0.18, 95% CI = 0.04–0.8, P = 0.02) [Table 4].
Table 4.
Factors associated with willingness to take vaccine (bivariate and multivariate statistics)
| Variables | Willing for COVID-19 vaccination | Bivariate | Multivariate† | ||||
|---|---|---|---|---|---|---|---|
|
|
|
|
|||||
| No Mean (SD)/n (%) | Yes Mean (SD)/n (%) | t/χ2 | df | P | Odds Ratio (CI) | P | |
| Age in years | 41.45 (11.95) | 39.89 (11.87) | 0.63 | 98 | 0.53 | - | - |
| Years of education | 7.63 (4.85) | 10.03 (4.94) | -2.38 | 98 | 0.02* | 1.04 (0.92–1.16) | 0.57 |
| Age of onset in years | 31.73 (11.74) | 28.16 (8.46) | 1.63 | 98 | 0.11 | - | - |
| Duration of illness in months | 100.39 (91.7) | 121.11 (97.88) | -1.07 | 98 | 0.29 | - | - |
| Children less than 18 at home | |||||||
| No | 35 (56.5) | 20 (52.6) | 0.14 | 1 | 0.71 | - | - |
| Yes | 27 (43.5) | 18 (47.4) | |||||
| Elderly relatives at home | |||||||
| No | 37 (59.7) | 22 (57.9) | 0.03 | 1 | 0.86 | - | - |
| Yes | 25 (40.3) | 16 (42.1) | |||||
| Diagnosis - severe mental illness | |||||||
| No | 8(12.9) | 6 (15.8) | 0.16 | 1 | 0.77 | - | - |
| Yes | 54 (871) | 32 (84.2) | |||||
| Diagnosis - Schizophrenia | |||||||
| No | 37 (712) | 15 (46.9) | 2.8 | 1 | 0.09 | - | - |
| Yes | 17 (28.8) | 17 (53.1) | |||||
| Diagnosis - Bipolar disorder | |||||||
| No | 43 (82.7) | 20 (62.5) | 4.31 | 1 | 0.04* | 0.39 (0.12–1.29) | 0.12 |
| Yes | 9 (17.3) | 13 (37.5) | |||||
| Medical comorbidity | |||||||
| No | 45 (72.6) | 26 (68.4) | 0.2 | 1 | 0.66 | - | - |
| Yes | 17 (27. 4) | 12 (31.6) | |||||
| Total BPRS Scoring | 43.46 (25.22) | 43.88 (24.51) | -0.07 | 84 | 0.94 | - | - |
| BPRS subscale - suspiciousness≥4) | |||||||
| No | 34 (654) | 23 (71.9) | 0.38 | 1 | 0.54 | - | - |
| Yes | 18 (34.6) | 9 (28.1) | |||||
| Total DASS score | 36 (6) | 39.83 (13.54) | -0.72 | 12 | 0.49 | - | - |
| Depression score | 11.12 (3.56) | 13.67 (5.96) | -1.02 | 12 | 0.33 | - | - |
| Anxiety score | 13 (3.7) | 13.17 (3.87) | -0.08 | 12 | 0.94 | - | - |
| Stress score | 11.88 (2.1) | 13 (4.98) | -0.58 | 12 | 0.57 | - | - |
| Time interval between the two doses of vaccine in days | 45.3 (34.39) | 48.11 (29.26) | -0.42 | 96 | 0.68 | - | - |
| Time to developing immunity after vaccination in days | 13.62 (14.6) | 14.26 (11.96) | -0.22 | 93 | 0.83 | - | - |
| Distance to vaccination center in km | 1.71 (2.4) | 1.63 (1.44) | 0.2 | 98 | 0.84 | - | - |
| Feels they are at risk for COVID-19 | |||||||
| No | 62 (100) | 35 (92.1) | 5.05 | 1 | 0.03* | 0 | >0.99 |
| Yes | 0 | 3 (79) | |||||
| Thinks that COVID-19 spread can be prevented by adequate measures | |||||||
| No | 15 (24.2) | 3 (7.9) | 4.24 | 1 | 0.04* | 1.06 (0.15–7.53) | 0.95 |
| Yes | 47 (75.8) | 35 (92.1) | |||||
| Believes that vaccine is effective | |||||||
| No | 27 (43.5) | 5 (13.2) | 10 | 1 | 0.002* | 0.19 (0.04–0.84) | 0.03* |
| Yes | 35 (56.5) | 33 (86.8) | |||||
| Has concerns regarding safety of vaccines | |||||||
| No | 33 (53.2) | 22 (57.9) | 0.21 | 1 | 0.65 | - | - |
| Yes | 29 (46.8) | 16 (42.1) | |||||
| Thinks vaccine worsens psychiatric illness | |||||||
| No | 28 (45.2) | 26 (68.4) | 5.13 | 1 | 0.02* | 1.8 (0.6–5.37) | 0.29 |
| Yes | 34 (548) | 12 (31.6) | |||||
| Thinks that vaccine affects fertility | |||||||
| No | 59 (952) | 37 (974) | 0.3 | 1 | >0.99 | - | - |
| Yes | 3 (4.8) | 1 (2.6) | |||||
| Thinks that vaccine will cause sexual problems | |||||||
| No | 58 (935) | 37 (974) | 0.72 | 1 | 0.65 | - | - |
| Yes | 4 (6.5) | 1 (2.6) | |||||
| Made more accessible | |||||||
| No | 61 (98.4) | 30 (78.9) | 10.87 | 1 | 0.002* | 0.18 (0.04–0.8) | 0.02* |
| Yes | 1 (1.6) | 8 (21.1) | |||||
χ2 – Pearson’s Chi-square value, t - Independent sample t-test value, *P<0.05, †Multivariate logistic regression (years of education, diagnosis of bipolar disorder, belief that COVID-19 spread can be prevented by adequate measures, perception of being at risk of infection, belief that the vaccine was effective, belief that vaccine can worsen the psychiatric illness, and perception that vaccines were inaccessible were entered into the model), CI=Confidence interval
There was no correlation between Oxford vaccine hesitancy scores and BPRS or DASS (total and subscale) scores. Age of the patient, presence of children or elderly persons in the patient’s home, severe mental illness, and presence of medical comorbidity were not associated with the patient’s willingness to take the vaccination. Participant willingness for vaccination was not found to be associated with the caregiver’s vaccination status (χ2 = 0, df = 1, P = 0.99).
DISCUSSION
Herd immunity in the community achieved either through natural infection or vaccination is a factor that can curtail a pandemic. This was evident during the COVID-19 pandemic as the related restrictions were gradually eased following the vaccine rollout, proving that vaccination is pivotal for eradicating or controlling infectious diseases in the community.[20] However, despite their cost-effectiveness and increased availability, vaccine hesitancy is a concern. It has been suggested that if 30% of the population refuses to take vaccines, it can result in inadequate herd immunity and consequently a continuing pandemic-like situation.[13,21] This study explored perspectives regarding COVID-19 vaccination among PMI.
In this study, more than half the PMI who had not yet been vaccinated stated their unwillingness to take it. This suggests that targeted interventions are required to help reduce vaccine hesitancy in this group. Earlier research has found that a recommendation to take the vaccination by a healthcare provider positively influences vaccination uptake among individuals with severe mental illness.[4,22] This implies that the mental health treating team can play an active role in motivating their patients to accept vaccination. Setting up vaccination clinics in standalone psychiatric hospitals/clinics with the help of public health services could also help to improve vaccination rates by increasing accessibility.[23]
Previous studies have suggested that women are more disinclined to take vaccinations; however, no gender differences were found in this study.[24,25] Higher levels of education were associated with less vaccine hesitancy among the participants of this study, similar to previous reports from the same region.[4] In contrast to other research findings, greater vaccine hesitancy among PMI was not associated with unemployment, rural residence, lower socioeconomic status, and nature of mental illness.[26,27]
The role of an individual’s perception of the risk of contracting infection has been reported to significantly influence whether he/she would follow the recommended preventive measures including vaccination.[28,29,30,31] In this study, PMI who perceived that they were at a greater risk of contracting the infection were found to be more likely to engage with vaccination services. Though illness severity was not found to be associated with perception of risk, identification of other factors that may influence risk perception would help to better understand patient perspectives regarding vaccination. Similar to earlier findings from the general population, PMI who believed that vaccines were effective were more likely to consider taking the vaccination. Some participants held misconceptions regarding the COVID-19 vaccine through misinformation circulated on social media, resulting in vaccine hesitancy. This finding highlights the importance of health education programs regarding vaccines and the role of the media in responsible reporting. Providing accurate information to PMI regarding the effectiveness and safety of the COVID-19 vaccine could help reduce negative attitudes and vaccine hesitancy in this group. Mental health professionals can play a crucial role in improving vaccine acceptability among their patients by serving as a bridge between PMI and the general medical system. During routine mental health consultations, relevant general health information should be shared with patients and their families, appropriate to their educational and cultural background. When vaccine hesitancy is evident, motivational interviewing techniques should be used to improve vaccine uptake.
While the debate over the ethics of vaccinations in PMI who lack the capacity to consent continues, it is suggested that in public health emergencies, the benefits may justify providing vaccination regardless of the individual’s preferences.[32,33]
Strengths and limitations
The strengths of the study include a reasonable sample size, the use of validated questionnaires, and minimal selection bias. This is probably the first study from this region that explored patients’ perspectives regarding the COVID-19 vaccination among PMI. Though the disease may have moved to the endemic stage, these study findings remain relevant as periodic exacerbations are expected and vaccination is an effective measure to minimize the effect of the disease. The study provides an understanding of some of the reasons for vaccine hesitancy among PMI, which can help plan effective interventions in this group in future mass vaccination programs.
Limitations include the cross-sectional design of the study, which prevents us from making conclusions regarding the directionality of the associations. A true prevalence of vaccine hesitancy could have been estimated if the study had been carried out in all PMIs attending the clinic and not just among those who had not taken the vaccine. Adding an educational intervention with a pre-post-test study design would have added to the understanding of this issue.
CONCLUSION AND FUTURE IMPLICATIONS
Vaccine hesitancy among PMI has not been well studied. Identifying factors associated with it will help to plan and implement effective interventions to improve vaccine uptake in this vulnerable group. The role of mental health professionals in promoting vaccine acceptance among PMI is crucial to provide accurate information, inspire confidence, and motivate them to take the vaccine. Multicentric and longitudinal studies would help in a better understanding about vaccine hesitancy in different cultures and the changes over time. More such studies should be designed to address these gaps in our knowledge.
Ethics approval: The institutional review board and ethics committee approved the study protocol. (IRB Minute No-14047 dated June 30, 2021)
Financial support and sponsorship
The study was funded by a Fluid Research Grant from Christian Medical College No. 22Q589.
Conflicts of interest
There are no conflicts of interest.
Acknowledgement
Dr. Jibi Achamma Jacob for helping with the manuscript.
REFERENCES
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