COVID-19 Vaccination Among Adolescents and Young Adults: Test of the Triandis Model of Interpersonal Behavior and the Health Belief Model

Abstract

This study purpose was to test the Health Belief Model (HBM) and the Triandis Model of Interpersonal Behavior (TMIB) in predicting COVID-19 vaccine uptake among adolescents and young adults (AYAs). Data from an anonymous online survey were collected. Clusters of risk perceptions of infection were identified using Latent Class Analysis, and predictive values of TMIB and HBM factors were evaluated using logistic regression models. Response rate was 30% (468 participants). There was a combined significant effect of TMIB model components (habitual health behavior, intention, and facilitation conditions) on having received ≥1 dose of COVID-19 vaccine. Having received influenza vaccine in the past 12 months was associated with higher odds of COVID-19 vaccine uptake. Perceived vaccination benefits, and perceived risks of infection were associated with vaccine receipt; however, the HBM model performed inadequately. The HBM is commonly used in vaccine acceptance research; however, the TMIB may be more effective among AYAs.

Keywords

adolescents and young adults vaccination Health Belief Model Triandis Model of Interpersonal Behavior COVID-19 risk perceptions habitual health behavior

Introduction

Risk perceptions are often placed as core concepts in theories of health behavior, and the literature supports an at-least-modest association between risk perceptions and health behaviors.^1,2 As a central role in the Health Belief Model (HBM), risk perception is defined as an individual’s judgments and evaluations of hazards they are or could be exposed to.³ More specifically, perceived severity and susceptibility of the disease and the perceived benefits and risks of the vaccine relate to vaccine acceptance. The HBM has been used to investigate COVID-19 vaccine hesitancy and COVID-19 vaccine acceptance in adult populations as reported in 2 systematic reviews.^4,5 Results from these reviews were similar, indicating moderate support for association between COVID-19-perceived susceptibility and vaccine acceptance. Perceived susceptibility was negatively correlated with COVID-19 vaccine hesitancy in 8 of the 16 studies included in the review,⁴ while only 4 of 38 studies reported a positive relationship between perceived COVID-19 infection risk and COVID-19 vaccine willingness.⁵ Perceived COVID-19 risks have been substantially reported among adults in the literature; however, it has been scant in studies involving youth population. A cross-sectional study by Tu and Colleagues⁶ reported individuals vaccinated against COVID-19 showed higher COVID-19 risk perceptions than those unvaccinated among adolescents between 13 to 17 years of age.

The HBM is limited, as it does not clearly specify how its major components should be measured or how they are correlated, making comparisons of research results difficult. In addition, the model does not consider behaviors that are habitual, and it does not include the emotional components of the behavior⁷ or the social acceptability that may affect the decision-making processes, particularly in the context of an emergent health threat or crisis such as a global pandemic where aspects of risk perceptions and behaviors are still formative.

Less familiar in the field of vaccine acceptance research, the Triandis Model of Interpersonal Behavior (TMIB) recognizes the important role of both social factors and emotions in forming intentions and highlights the significance of past behaviors on the decisions to perform the recommended behavior. In the TMIB, the probability of performing a given behavior is a function of previous behavioral habits (H) and intention (I) moderated by facilitating conditions (F).^8,9 As indicated by Limbu and colleagues,⁴ behavioral habits (history of influenza vaccination) were significantly associated with COVID-19 vaccine uptake. The TMIB has been used as a framework for providing information to guide developing education in the context of vaccination and health promotion programs.^10-12 Montano¹³ reported the TMIB was useful in predicting intention and the likelihood of getting influenza vaccine in a group of patients at risk for serious influenza complications. The model suggested that the probability of being vaccinated was a function of a past habit (having previously received influenza vaccine) and intention (the probability that a person will vaccinate), both moderated by facilitating conditions (circumstances enabling or prompting the vaccination). Another study on influenza vaccination¹⁴ reported all TMIB variables to be strongly associated with receiving an annual vaccination.

To date, only a limited number of studies with focus on adolescents and young adults (AYAs) populations have assessed factors associated with COVID-19 vaccine acceptance, and none of them have utilized the HBM or TMIB. Among 16 to 21 years old participants of a survey conducted in Canada, only 65% indicated willingness to get a COVID-19 vaccine, and those who identified as Black or Latino and with lower family income had greater hesitancy and reduced confidence.¹⁵ In England, vaccine-hesitant adolescents were more likely to come from disadvantaged socioeconomic backgrounds, with higher rates of home rental, and their school locations were more likely to be in areas of greater deprivation.¹⁶ Research on vaccination intent has also focused on at-risk populations, showing similar findings.¹⁷

Understanding the willingness to receive the COVID-19 vaccine remains a significant area of research considering the surge of new variants and the potential benefits of vaccination, particularly among AYAs where the unique factors associated with vaccine hesitancy have not been well examined, more specifically factors from HBM and TIMB frameworks. A more complete understanding of the vaccine sentiment and potential determinants of AYAs’ behavior is vital for planning effective health communications to encourage uptake and successfully implementing future population immunization, especially as the virus continues to evolve.

Materials and Methods

Participants

Subjects included were AYAs between 16 and 21 years of age who had at least one visit between January and December 2021 at any sites of the hospital where this study was conducted. Adolescents and young adults unable to read English sufficiently to participate were excluded. International Classification of Diseases, 10th Revision (ICD-10) codes were used to identify and exclude potential participants with recorded information on developmental disabilities. We estimated that 30% of respondents would have a high likelihood of being infected with coronavirus if no preventive measures were taken. A total of 1646 survey invitations were mailed at a random selection of participants for this cross-sectional study from a pool of all eligible participants. The questionnaire was piloted to assess its readability.

Invitations letters were mailed with a link to the RedCap survey to selected participants. To enhance participant response, a $5 gift card claim code was sent with the first letter to all participants. The survey design also utilized 2 reminder letters to encourage participation. Survey responses were collected between April and June 2022. Survey participation was anonymous. This study received ethical approval from the Institutional Review Board at the hospital where it was carried out (approval no. 2021-058) on March 23, 2022. A written consent form was furnished to participants prior to starting the online questionnaire in RedCap. Considering the risk of harm is minimal for adolescent participation in this study and that the questionnaire contained questions related to activities where adolescents are legally considered autonomous, active parental consent was waived. Nonetheless, parents of participants aged 16 to 17 years were informed their children were invited to participate.

Questionnaire

The questionnaire was self-administered, comprised of a combination of multiple-choice and Likert scale questions. The survey questionnaire asked about: (1) sociodemographic characteristics of the participants, including age, sex, gender, educational level, parental educational level, and religious affiliation; (2) general health status, long-term disease history, smoking status, and influenza vaccine history; and (3) knowledge of COVID-19 symptoms, COVID-19 vaccine uptake, number of COVID-19 vaccine shots received, and reasons for accepting or not accepting COVID-19 vaccination.

Questions addressing factors from the HBM included: (1) questions addressing risk perception of infection, risk perception of infection compared to peers, and risk perception of infection compared to older people were investigated; (2) perceived severity, assessed by a question asking ’In general, how severe do you think COVID-19 disease is?”; and (3) questions regarding perceived benefits of vaccination, including questions about the comparative risks of unvaccinated and vaccinated persons being infected or spreading the disease, the risks of a fully vaccinated person developing severe COVID-19, and the risks of a fully vaccinated person dying from COVID-19. Since AYAs are users of their parents’ medical insurance; (4) perceived barriers were measured by asking if “parents think that is all right for me to get a COVID-19 vaccine” and feelings regarding receiving COVID-19 vaccine (safe/unsafe, pleasant/unpleasant); and finally (5) having a long-term disease, general health, chances of developing severe COVID-19, loss of someone close to COVID-19, and having someone close to them being tested positive for COVID-19 were used as cues to action.

Triandis Model of Interpersonal Behavior factors were assessed using the following questions: (1) behavioral habit as having receiving influenza vaccine in the past 12 months and (2) vaccine hesitancy was used as a proxy for vaccination intent. Findings of a national longitudinal study among American adults¹⁸ indicate that COVID-19 vaccine hesitancy was associated with lower odds of subsequent vaccine uptake for vaccine refusers (aOR = 0.02; 95% CI: 0.01, 0.03). Finally, (3) facilitating conditions were assessed by asking if “parents think that is all right for me to get a COVID-19 vaccine.”

As survey participation was anonymous, COVID-19 levels in their county of residence were not possible to obtain at the time the survey data were collected. As a proxy, we asked them what their chances of personally encountering someone infected with coronavirus in the next 3 months using a 5-point Likert scale.

Statistical Analysis

Descriptive statistics for continuous variables (mean, standard deviation) and categorical variables (frequency, percentage) are provided. Group comparisons were assessed using univariate analysis (chi-square or Fisher’s exact test for categorical data; Student’s t test or analysis of variance [ANOVA] for continuous data). Risk perception of infection, risk perception of infection compared to peers, and risk perception of infection compared to older people were used to identify clusters of risk perceptions using Latent Class Analysis. Gamma is a measure of association for ordinal variables. A Gamma coefficient of 1.00 reflects a positive perfect relationship between variables. Gamma coefficients between clusters and perceived risk, perceived risk compared to peers, and perceived risk compared to older people were evaluated. Subsequently, binary logistic regression models were developed to investigate the relationship between COVID-19 vaccine acceptance and factors from the TIMB and HBM, adjusting for demographics. Considering model overfitting and multicollinearity, the most insignificant variable was removed one at a time until all remaining variables were significant. Akaike Information Criterion (AIC) and ‎Bayesian Information Criterion (BIC) were used for model performance comparisons. All analyses were performed in SAS 9.4 (Cary, NC, USA) and JMP Pro 14 (SAS Institute Inc., Cary, NC). All tests were 2-sided and P < .05 was considered statistically significant.

Results

A 30% response rate was achieved. This response rate is consistent with population- and hospital-based patient surveys generally, which typically range between 16% and 80%.^19-22 Most respondents were White (69%) and non-Hispanic (81%), and 45% identified themselves as Christians. Fifty-one percent were female, and 18% percent self-identified as LGBTQ+ (Table 1). Twenty percent reported prior diagnosis with a long-term disease, and 16% were former or current e-cigarette smokers.

Table 1.

Demographic Characteristics of Participants, n = 468.

	n or mean	% or SD
Age group (years)
16-17	143	30.6
18-21	325	69.5
Sex
Female	239	51.1
Male	158	33.8
No answer/prefer not to answer	71	15.2
Sexual orientation
Heterosexual or straight	301	64.3
LGBTQ+	86	18.4
No answer/prefer not to answer	81	17.3
Race
White	324	69.2
African American	33	7.1
Other race group	47	10.1
Prefer not to answer/no answer	64	13.7
Hispanic/Latino(a)
No	378	80.8
Yes	22	4.7
Prefer not to answer/no answer	68	14.5
Number of people in your household	4.3	1.9
Participant highest degree or level of school
Less than high school	145	31
High school graduate	160	34.2
Participant highest degree or level of school
Some college	90	19.2
College graduate or more	12	2.6
Prefer not to answer/no answer	61	13
Parents highest degree or level of school
Less than high school	26	5.6
High school graduate	92	19.7
Some college	75	16
College graduate or higher	214	45.7
Prefer not to answer/no answer	61	13
General health
Excellent	76	16.2
Very good	175	37.4
Good	111	23.7
Fair	41	8.8
Poor	5	1.1
Prefer not to answer/no answer	60	12.8
Have been told by a health care professional that have any of the following long-term diseases
Pulmonary diseases (such as asthma, emphysema, long-term bronchitis, cystic fibrosis)	49	10.5
Heart condition (such as heart failure, coronary artery disease)	15	3.2
Chronic kidney disease	2	0.4
Diabetes	13	2.8
Sickle cell disease	0	0
conditions that may weaken your immune system like bone marrow or organ transplant, HIV/AIDS	5	1.1
Cancer	1	0.2
Other	30	6.4
Prefer not to answer/no answer	82	17.5
I have not been told to have a long-term disease	290	62
Have ever smoked cigarettes
Never	374	79.9
Yes, I am a current smoker	12	2.6
Yes, I am a former smoker	19	4.1
Prefer not to answer/no answer	63	13.5
Have ever smoked e-cigarettes
Never	326	69.7
Yes, I am a current smoker	44	9.4
Yes, I am a former smoker	33	7.1
Prefer not to answer/no answer	65	13.9
Identify themselves with any of the following religions
Christianity	210	45
Other religion	27	5.8
Atheist/Agnostic/no religion	131	28
Prefer not to answer/no answer	100	21.4

Some participants reported more than one long-term disease.

Abbreviations: AIDS, acquired immunodeficiency syndrome; HIV, human immunodeficiency virus; LGBTQ, lesbian, gay, bisexual, transgender, queer; SD, standard deviation.

COVID-19 Knowledge and Risk Perceptions

Although 86.5% reported knowing the COVID-19 main symptoms, only 58% correctly named at least 3 of these symptoms (Table 2). When asked what their chances of being infected will be in the next 3 months, if no preventive measure is taken, 47% responded very low or very low.

Table 2.

COVID-19 Knowledge and Perceived Risks.

	n	%
Do you know the ways COVID-19 is transmitted?
Yes	399	85.4
No	68	14.6
No answer	1	0.2
Please name the ways COVID-19 is transmitted
Airborne/droplets	275	58.8
Close contact	158	33.8
Bodily fluids	55	11.8
Contaminated surfaces	73	15.6
Through mouth/nose/eyes	17	3.6
Sharing food/drinks/cigarettes	7	1.5
Do you know the main symptoms of COVID-19?
No	63	13.5
Yes	405	86.5
Please name the main symptoms
Fever	248	53
Cough	224	47.9
Loss of taste and smell	192	35
Body aching/tiredness	127	27.1
Difficulty breathing	105	22.4
Headache	90	19.2
Sore throat	72	15.4
Stuffy/runny nose/sneezing	66	14.1
Chills/sweats	51	10.9
Diarrhea/nausea/vomiting	39	8.3
Cold/flu like symptoms	36	7.7
Dizziness	7	1.5
Hives/itchy skin/skin rash	4	0.9
Confusion	1	0.2
Dehydration	1	0.2
Pneumonia	1	0.2
Jaundice	1	0.2
Participant named at least 3 main symptoms correctly
Yes	273	58.3
No	195	41.7
Which of the following groups is more likely to be asymptomatic?
Children and adolescents (0-17 years)	200	42.7
Young adults (18-26 years)	147	31.4
Adults (27-55 years)	8	1.7
Older adults (above 55 years)	31	6.6
I don’t know/prefer not to answer	78	16.7
Asymptomatic individuals cannot infect others	4	0.9
False	447	95.5
True	19	4.1
No answer/prefer not to answer	2	0.4
In your opinion, what are your chances that you will personally encounter someone infected with coronavirus in the next 3 months?
Very high	40	8.6
High	63	13.5
Moderate	168	35.9
Low	115	24.6
Very low	55	11.8
I don’t know	22	4.7
No answer/prefer not to answer	5	1.1
In your opinion, what are your chances that you will be infected in the next 3 months if you don’t take any preventive measure?
Very low	100	21.4
Low	120	25.6
Moderate	115	24.6
High	71	15.2
Very high	44	9.4
I don’t know	13	2.8
No answer/prefer not to answer	5	1.1
Compared to people of your age and sex, what are your chances that you will be infected in the next 3 months if you don’t take any preventive measures?
Very low	75	16
Low	107	22.9
Moderate	142	30.3
High	72	15.4
Very high	40	8.6
I don’t know	24	5.1
No answer/prefer not to answer	8	1.7
Compared to people older than you, what are your chances that you will be infected in the next 3 months if you don’t take any preventive measures?
Very low	96	20.5
Low	136	29.1
Moderate	119	25.4
High	65	13.9
Very high	29	6.2
I don’t know	18	3.9
No answer/prefer not to answer	5	1.1
What would be your chances of developing severe COVID-19?
Very low	218	46.6
Low	100	21.4
Moderate	79	16.9
High	32	6.8
Very high	12	2.6
I don’t know	21	4.5
No answer/prefer not to answer	6	1.3
In general, how severe you think COVID-19 disease is?
No answer/prefer not to answer	4	0.9
I don’t know	4	0.9
Not at all serious	19	4.1
Slightly serious	72	15.4
Moderately serious	221	47.2
Severely serious	148	31.6
Have you lost someone close to you to COVID-19
Yes	56	12
No	352	75.2
No answer/prefer not to answer	60	12.8
Have you been tested for COVID-19
Yes, negative	182	38.9
Never tested	66	14.1
Yes, positive	157	33.5
No answer/prefer not to answer	63	13.5
Have someone close to you tested positive
No	74	15.8
Yes	333	71.1
No answer/prefer not to answer	61	13

Abbreviation: COVID, coronavirus disease.

Risk perception of infection, risk perception of infection compared to peers, and risk perception compared to older people were used to identify classes of risk perceptions among participants using Latent Class Analysis. The smallest AIC (2291.8) and smallest BIC (2372.9) were reached, identifying 3 clusters as the optimal number of clusters. Effect sizes of each of the 3 risk perception variables in the original latent class were higher than 0.75, indicating high likelihood of individuals being classified accurately in a latent class. The first cluster was identified as “low perceived risk,” which included 39% of participants; 2 other clusters with 38 and 23% of participants, were identified as moderate and high-risk perception of infection clusters, respectively. Gamma coefficient between clusters and perceived risk, between clusters and perceived risk compared to peers and clusters and between clusters and perceived risk compared to older people were, respectively, 0.83 (95% CI: 0.76, 0.89), 0.93 (95% CI: 0.94, 0.99), and 0.89 (94% CI: 0.85, 0.93).

COVID-19 Vaccine Uptake

Sixty-five percent of participants reported having received ≥1 dose of COVID-19 vaccine (Table 3). Of those, 6.3% received only 1 dose, 30.5% received 2 doses, and 27.7% received an additional booster shot. Seventy-nine percent of those who had not received COVID-19 vaccine reported they will probably not/definitely not be vaccinated. Reported top 5 main reasons for receiving COVID-19 vaccine were “it will keep me from getting COVID-19” (72%), “not passing COVID-19 to family, friends, and others around me” (70%), “be able to visit friends, relatives” (56%), “COVID-19 vaccines are effective” (51%), and “COVID-19 vaccines are safe” (50%). Similarly, those who had not been vaccinated reported their top 5 reasons for not receiving COVID-19 vaccine. They stated they had concerns about long-term side effects (71%), concerns about short-term side effects (43%), planned to “wait and see” if it is safe (42%), distrust in COVID-19 vaccines (40%), and reported vaccination against COVID-19 was “not a priority now” (48%).

Table 3.

COVID-19 Vaccine Acceptance, Knowledge, and Affect Regarding COVID-19 Vaccine, Social Influence, and General Vaccine Hesitancy, n = 468.

	n	%
Have you received at least one shot of COVID-19 vaccine?
No	160	34.2
Yes	302	64.5
No answer	6	1.3
How many shots did you have? (n = 302)
1	29	9.6
2	141	46.7
2 + booster	128	42.4
No answer	4	1.3
When did you receive the last shot or booster?
Less than 6 months	133	28.4
Between 6 and 12 months	138	29.5
More than a year ago	22	4.7
I don’t know/refused to answer	175	37.4
What are the main reasons you have taken COVID-19 vaccine?
It will help keep me from getting COVID-19	217	71.9
Not passing the COVID-19 to family, friends, and others around me	212	69.9
Be able to visit friends and relatives	170	56.3
COVID-19 vaccines are effective	153	50.7
COVID-19 vaccines are safe	152	50.3
Be able to travel	134	44.4
Not using face masks	79	26.2
Other health problems not getting worse due the COVID-19	69	22.8
Other	29	6.2
Please specify ‘other’ reason
School/college required	16	3.4
Family/parents made me take it	4	0.8
Work required	3	0.6
It’s the right thing to do/why not?	2	0.4
To lower hospitalization risk	2	0.4
Recommended to high-risk group member	1	0.2
Army required	1	0.2
How likely are you to be vaccinated against COVID-19 in the next 3 months (n = 160)
Definitely	9	5.6
Probably	24	15
Probably not	55	34.4
Definitely not	71	44.4
No answer	1	0.6
What would be reasons you would not take a vaccine against COVID (n = 126)
I am concerned about long-term side effects of COVID-19 vaccine	89	70.6
It is not a priority in my life at this moment	61	48.4
I am concerned about short term side effects of COVID-19 vaccine	54	42.9
I plan to wait and see if it is safe	53	42.1
I don’t trust COVID-19 vaccines	50	39.7
I don’t believe I need COVID-19 vaccine	46	36.5
I don’t know if COVID-19 vaccine will work	41	32.5
I don’t like vaccines in general	28	22.2
The best way is to leave nature take its course	28	22.2
I think other people need it more than I do right now	26	20.6
I am afraid of needles	19	15.1
My doctor has not recommended it	17	13.5
Religious reasons	15	11.9
I believe natural medicine is the best option	15	11.9
Other	13	10.3
Refuse to answer/I don’t know	8	6.3
Difficulties in accessing health care services	4	3.2
I have allergies to the vaccine components	3	2.4
I had severe reactions to previous vaccines	3	2.4
Other reason
Blood clots	5
I had COVID-19 in 2020/I had it	2
Still recovering from COVID-19	1
No parental consent	1
I’m young and so my risk for serious COVID-19 is low	1
No answer	2
Please tell us why you believe you don’t need to be vaccinated (n = 46)
I already had COVID-19	27	58.7
I am not a member of a high-risk group	20	43.5
I plan to use masks or other precautions instead	12	26
I don’t believe COVID-19 is a serious illness	12	26
I don’t believe COVID-19 vaccine is effective	28	60.9
Other	6	13
For you, getting COVID-19 vaccine is:
Pleasant	93	19.9
Somewhat pleasant	98	20.9
For you, getting COVID-19 vaccine is:
Somewhat pleasant	98	20.9
Somewhat unpleasant	135	28.9
Unpleasant	133	28.4
No answer	9	1.9
For you, getting COVID-19 vaccine is:
Safe	219	46.8
Somewhat safe	105	22.4
Somewhat unsafe	62	13.3
Unsafe	72	15.4
No answer	10	2.1
For you, getting COVID-19 vaccine is:
Valuable	209	44.7
Somewhat valuable	110	23.5
Somewhat worthless	77	16.5
Worthless	64	13.7
No answer	8	1.7
For you, getting COVID-19 vaccine is:
A foolish decision	57	12.2
Somewhat a foolish decision	70	15
Somewhat a wise decision	106	22.7
A wise decision	224	47.9
No answer	11	2.4
For you, getting COVID-19 vaccine is:
Punishing	56	12
Somewhat punishing	84	18
Somewhat rewarding	151	32.3
Rewarding	167	35.7
No answer	10	2.1
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person getting the virus that causes COVID-19 is
Insignificant	25	5.3
Lower	259	55.3
The same	122	26.1
Higher	9	1.9
I don’t know	24	5.1
No answer	29	6.2
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person spreading COVID-19 is
Insignificant	24	5.1
Lower	216	46.2
The same	159	34
Higher	10	2.1
I don’t know	29	6.2
No answer	30	6.4
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person developing severe COVID-19 is
Insignificant	43	9.2
Lower	290	62.0
The same	67	14.3
Higher	11	2.4
I don’t know	25	5.3
No answer	32	6.8
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person dying from COVID-19 is:
Insignificant	72	15.4
Lower	262	56.0
The same	59	12.6
Higher	12	2.6
I don’t know	33	7.1
No answer	30	6.4
When COVID-19 vaccines first became available, they received an emergency use authorization (EUA). This means that (select all that apply):
The emergency use authorization came from the Food and Drug Administration (FDA), the same federal agency that has approved and licensed other vaccines	164	35
There is a public health emergency, thus circumstances existed to justify the authorization of emergency use of vaccines against COVID-19	217	46.4
Clinical trials were conducted according to the rigorous standards to generate the scientific data and other information needed to determine safety and effectiveness of COVID-19 vaccines before EUA was granted	131	28
FDA determined that the known and potential benefits outweighed the known and potential risks of the COVID-19 vaccines before EUA was granted	142	30.3
Manufacturers who received an EUA can continue their clinical trials to obtain additional safety and effectiveness information and pursue full approval	110	23.5
I don’t know	161	34.4
Other	2	0.4
No answer	41	8.8
Have you received the influenza vaccine in the last 12 months?
No answer	23	4.9
Yes	205	43.8
No	213	45.5
Unsure	27	5.8
If not, what is the main reasons you have not received the influenza vaccine
I don’t believe I need a influenza vaccine	80	17.1
Other reasons	47	10
I’m concerned about possible side effects of influenza vaccine	38	8.1
I don’t believe the influenza vaccine will work	31	6.6
My doctor has not recommended it	28	6
I don’t like vaccines in general	27	5.8
I’m afraid of needles	27	5.8
The best way is to leave the nature take its course	24	5.1
My parents would advise me against it	22	4.7
I believe natural medicine is the best option	10	2.1
Religious reasons	9	1.9
Difficulties accessing health care services	6	1.3
Other reasons
Forget	15	3.2
Had reaction in the past/allergic/family allergies	8	1.7
No doctor appointment	3	0.6
I don’t know	2	0.4
Busy schedule	2	0.4
I don’t want to	2	0.4
I still wear a mask indoors	1	0.2
I will	1	0.2
My family has history of Guillain-Barré syndrome (GBS)	1	0.2
Doctor forgot	1	0.2
No medical insurance	1	0.2
Why do you believe that you don’t need a influenza vaccine? (n = 80)
I never get the influenza	39	8.3
I am not a member of a high-risk group	38	8.1
I don’t believe the influenza is a serious illness	19	4.1
I don’t believe the influenza vaccine is effective	20	4.3
Other	5	1.1
Other reasons
I don’t want anything that the government says is best for me to put in my body	1
I will build natural immunity to it. I got sick and recovered	1
Just haven’t felt the need to get it	1
Never had it	1
When I get sick	1
My parents think that is all right for me to get a COVID-19 vaccine
No answer	27	5.8
No	84	18
Unsure	65	13.9
Yes	292	62.4
My friends think that is all right for me to get a COVID-19 vaccine
No answer	24	5.1
No	72	15.4
Unsure	92	19.7
Yes	280	59.8
I want to do what my parents think I should do
No answer	26	5.6
No	136	29.1
Unsure	86	18.4
Yes	220	47
I want to do what my friends think I should do
No answer	28	6
No	246	52.6
Unsure	82	17.5
Yes	112	23.9
If your doctor recommends you a vaccine, do you get it?
No answer	24	5.1
Never	22	4.7
Rarely	37	7.9
Sometimes	108	23.1
Very often	145	31
Always	132	28.2
How hesitant are you about getting vaccinations?
No answer	28	6
Not at all	138	29.5
A little	143	30.6
Somewhat	83	17.7
Very much	42	9
Completely	34	7.3
How much do you trust vaccines?
No answer	27	5.8
Not at all	42	9
A little	47	10
Somewhat	121	25.9
Very much	175	37.4
Completely	56	12
Do you think vaccines are safe?
No answer	27	5.8
Not at all	30	6.4
A little	47	10
Somewhat	133	28.4
Very much	164	35
Completely	67	14.3
Do you think vaccines are effective in preventing diseases?
No answer	26	5.6
Not at all	24	5.1
A little	47	10
Somewhat	120	25.6
Very much	176	37.6
Completely	75	16

Abbreviations: COVID, coronavirus disease; EUA, emergency use authorization; FDA, food and drug administration.

COVID-19 Vaccine Affects, Knowledge, and Hesitancy

Most of participants responded receiving COVID-19 vaccine would be unpleasant/somewhat unpleasant (57%), yet most said it would be safe/somewhat safe (69%) (Table 3). Important to note, 71% and 71.4% believed that fully vaccinated people, compared to unvaccinated people, had insignificant or lower risks of developing severe COVID-19 and dying from COVID-19, respectively.

Sixteen percent reported being very much or completely hesitant (Table 3). When asked if their parents think that is all right for them to received COVID-19 vaccine, 62% responded yes. Fifty-nine percent of participants indicated they would accept vaccination very often or always if recommended by their doctor.

Factors Associated With COVID-19 Acceptance

Having received at least one dose of COVID-19 vaccine was associated with participant educational level, parent educational level, race, and sexual orientation (Table 4).

Table 4.

Factors Associated With COVID-19 Vaccine Acceptance, n = 462.

	Have received at least one dose of COVID-19 vaccine		P
	No, n = 160	Yes, n = 302
	n (%)	n (%)
Age group			.307
16-17	54 (38.0)	88 (62.0)
18-21	106 (33.1)	214 (66.9)
Gender
Female	77 (32.2)	162 (67.8)	.531
Male	55 (35.3)	101 (34.7)
No answer	28 (41.8)	39 (58.2)
Sexual orientation: LGBTQ+			.002
No	108 (36.1)	191 (63.9)
Yes	16 (18.6)	70 (81.4)
No answer	36 (46.8)	41 (53.3)
Race			.003
Caucasian/White	101 (31.4)	221 (68.6)
African American	19 (57.6)	14 (42.4)
Other race	11 (23.4)	36 (76.6)
No answer	29 (48.3)	31 (51.7)
Ethnicity			.318
Non-Hispanic	124 (33.0)	252 (67.0)
Hispanic	5 (22.7)	17 (77.3)
No answer	31 (48.4)	33 (51.6)
Participant educational level			<.0001
HS or less	118 (38.9)	185 (61.1)
Some college or higher	15 (14.7)	87 (85.3)
No answer	27 (47.4)	30 (52.6)
Parent educational level			.0002
HS or less	55 (46.6)	63 (53.4)
Some college or higher	78 (27.2)	209 (72.8)
No answer	27 (47.4)	30 (52.6)
Religion			.698
No religion	41 (32.0)	87 (68.0)
Christianity	69 (31.4)	151 (68.6)
Other religion	4 (22.2)	14 (77.8)
No answer	46 (47.9)	50 (52.1)	.636
Cigarette smoker			.004
Never	116 (31.2)	256 (68.8)
Current smoker/former smoker	17 (56.7)	13 (43.3)
No answer	27 (45.0)	33 (55.0)
E-cigarette smoker			.009
Never	98 (30.3)	226 (69.7)
Current smoker/former smoker	33 (43.4)	43 (56.6)
No answer	29 (46.8)	33 (53.2)
General health			.528
Excellent/very good/good	116 (32.3)	243 (67.7)
Fair/poor	17 (37.0)	29 (63.0)
No answer	27 (47.4)	30 (52.6)
Been told by a health care provider that has a long-term disease			.277
No	97 (33.6)	192 (66.4)
Yes	30 (31.6)	65 (68.4)
No answer	33 (42.3)	45 (57.7)
Loss of someone close to COVID-19			.549
No	113 (32.3)	237 (67.7)
Yes	20 (36.4)	35 (63.6)
No answer	27 (47.4)	30 (52.6)
Someone close to you was COVID-19 positive			414
No	27 (37.0)	46 (63.0)
Yes	106 (32.0)	225 (68.0)
No answer	27 (46.5)	31 (53.5)
COVID-19 test			.136
Not tested	28 (43.1)	37 (56.9)
Tested negative	56 (31.0)	125 (69.0)
Tested positive	47 (30.0)	110 (70.0)
No answer	29 (49.1)	30 (50.9)
Indicated to know at least one aspect of the emergency use authorization			<.0001
No	73 (45.1)	89 (54.9)
Yes	76 (27.1)	204 (72.9)
No answer	11 (55.0)	9 (45.0)
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person being infected with COVID-19 is			<.0001
Higher	7 (77.8)	2 (22.2)
Insignificant/lower	54 (19.1)	229 (80.9)
The same	71 (58.7)	50 (41.3)
No answer	28 (57.1)	21 (42.9)
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person spreading COVID-19 is:			<.0001
Higher	7 (70.0)	3 (30.0)
Insignificant/lower	52 (21.8)	187 (78.2)
The same	72 (45.6)	86 (54.4)
No answer	29 (52.70	26 (47.3)
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person developing severe COVID-19 is			<.0001
Higher	8 (72.7)	3 (27.3)
Insignificant/lower	75 (22.7)	256 (77.3)
The same	51 (76.1)	16 (23.9)
No response	26 (49.1)	27 (50.9)
In your opinion, compared to unvaccinated people, the risk of a fully vaccinated person dying from COVID-19 is:			<.0001
Higher	10 (83.3)	2 (16.7)
Insignificant/lower	74 (22.3)	258 (77.7)
The same	46 (78.0)	13 (22.0)
For you, getting COVID-19 vaccine is			<.0001
Unpleasant/somewhat unpleasant	135 (50.6)	132 (49.4)
Pleasant/somewhat pleasant	22 (11.6)	168 (88.4)
No answer	3 (60.0)	2 (40.0)
For you, getting COVID-19 vaccine is			<.0001
Unsafe/somewhat unsafe	108 (81.2)	25 (18.8)
Safe/somewhat safe	47 (14.6)	276 (85.4)
No answer	5 (83.3)	1 (16.7)
For you, getting COVID-19 vaccine is			<.0001
Worthless/somewhat worthless	106 (75.2)	35 (24.8)
Valuable/somewhat valuable	51 (16.1)	266 (83.9)
No answer	3 (75.0)	1 (25.0)
For you, getting COVID-19 vaccine is			<.0001
A foolish decision/somewhat a foolish decision	100 (64.5)	26 (8.7)
A wise decision/somewhat a wise decision	55 (35.5)	274 (91.3)
No answer	5 (71.4)	2 (28.6)
For you, getting COVID-19 vaccine is			<.0001
Punishing/somewhat punishing	103 (73.6)	37 (26.4)
Rewarding/somewhat rewarding	52 (16.5)	264 (83.5)
No answer	5 (83.3)	1 (16.7)
Chances that you will personally encounter someone infected with coronavirus in the next 3 months			<.0001
Low/very low	79 (47.0)	89 (53.0)
Moderate	48 (28.7)	119 (71.3)
Very high/high	20 (19.4)	83 (80.6)
No answer	13 (54.2)	11 (45.8)
Chances that you will be infected in the next 3 months if you don’t take any preventive measure (risk perception clusters)			.008
Low	72 (42.1)	99 (57.9)
Moderate	53 (34.0)	103 (66.0)
High	23 (23.5)	75 (76.5)
No answer	12 (32.4)	25 (67.6)
What would be your chances of developing severe COVID-19?			.088
Low/very low	99 (31.1)	219 (68.9)
Moderate	30 (38.5)	48 (61.5)
Very high/high	20 (46.5)	23 (53.5)
No answer	11 (47.8)	12 (52.2)
In general, how severe you think COVID-19 disease is?			<.0001
Not at all serious/slightly serious	44 (48.9)	46 (51.1)
Moderately serious	84 (38.2)	136 (61.8)
Severely serious	31 (21.0)	117 (79.0)
No answer	1 (25.0)	3 (75.0)
How hesitant are you about getting vaccination?			<.0001
Not all all/a little	54 (19.3)	226 (80.7)
Somewhat	38 (45.8)	45 (54.2)
Very much/completely	58 (77.3)	17 (22.7)
No answer	10 (41.7)	14 (58.3)
How much do you trust vaccines?			<.0001
Not all all/a little	64 (71.9)	25 (28.1)
Somewhat	50 (41.7)	70 (58.3)
Very much/completely	35 (15.2)	195 (84.8)
No answer	11 (47.8)	12 (52.2)
Do you think vaccines are effective in preventing diseases?			<.0001
Not all all/a little	45 (64.3)	25 (35.7)
Somewhat	73 (60.8)	47 (39.2)
Very much/completely	32 (12.8)	218 (87.2)
No answer	10 (45.5)	12 (54.6)
Do you think vaccines are safe?			<.0001
Not all all/a little	55 (72.4)	21 (27.6)
Somewhat	64 (48.1)	69 (51.9)
Very much/completely	31 (13.5)	199 (86.5)
No answer	10 (46.5)	113 (56.5)
Have received influenza vaccine in the past 12 months			<.0001
No/Unsure	117 (48.8)	123 (51.2)
Yes	34 (16.7)	170 (83.3)
No answer	9 (50.0)	9 (50.0)
Accept doctor’s recommendations			<.0001
Never/rarely	53 (89.8)	6 (10.2)
Sometimes	68 (63.6)	39 (36.5)
Very often/always	30 (10.9)	246 (89.1)
No answer	9 (45.0)	11 (55.0)
My parents think that is all right for me to receive COVID-19 vaccine			<.0001
No/unsure	108 (72.5)	41 (27.5)
Yes	39 (13.5)	251 (86.5)
No answer	13 (56.5)	10 (43.5)
I want to do what my parents think I should do			<.0001
No/unsure	101 (45.5)	121 (54.5)
Yes	48 (22.0)	170 (78.0)
No answer	11 (50.0)	11 (50.0)
My friends think that is all right for me to receive COVID-19 vaccine			<.0001
No/unsure	100 (61.0)	64 (39.0)
Yes	50 (18.0)	228 (82.0)
No answer	10 (50.0)	10 (50.0)
I want to do what my friends think I should do			.002
No/unsure	125 (83.9)	203 (70.2)
Yes	24 (16.1)	86 (29.8)
No answer	10 (50.0)	10 (50.0)

Chi-square test or Fisher’s exact test for categorical data; Student’s t test for continuous data.

n (%) or mean (SD).

Abbreviations: COVID, coronavirus disease; LGBTQ, lesbian, gay, bisexual, transgender and queer.

Significant associations were observed between COVID-19 vaccine receipt and cluster of perceived risk of infection; 76.5% of vaccinated participants were identified in the high-risk perception cluster, compared to 23% of unvaccinated participants. Likewise, more vaccinated AYAs believed COVID-19 is a severely serious disease (79% vs 21%, P < .0001). Perceived benefits of vaccination regarding lowering one’s changes of developing severe COVID-19 and dying from COVID-19 were higher among vaccinated (P < .0001) compared to unvaccinated AYAs. Internal cues to action (general health status, being diagnosed with a long-term disease, chances of developing severe COVID-19) and external cues to action (loss of someone close due to COVID-19, having someone close to them being tested positive for COVID-19) were not associated with vaccination status (P > .05), although parental approval to vaccinate, whether receiving the vaccine is safe and pleasant (perceived barriers) and vaccination status were significantly associated (P < .0001) with receiving COVID-19 vaccine. Finally, vaccinated AYAs reported low levels of vaccine hesitancy (81% vs 19%, P < .0001) and higher influenza vaccination in the past 12 months (83% vs 17%, P < .0001).

TMIB: Logistic Regression Model Results

The probability of having received ≥1 dose of COVID-19 vaccine (yes/no) was investigated as a function of previous flu vaccine uptake (yes/no) and vaccine hesitancy, moderated by parental approval to receive COVID-19 vaccine and age group. The model was adjusted for demographic factors with P ≤ 0.2 in the univariate analysis. The model fitting statistics of the final binary logistic regression model indicated good fitting (C: 90%, percent concordant 88.3%, percent discordant 10.3%). The adjusted odds of having received ≥1 dose of COVID-19 vaccine was 2.2 (95% CI: 1.2, 4.2, Table 5) times larger for those who had also received influenza vaccine in the past 12 months than for those who had not.

Table 5.

Binary Logistic Regression Results: Assessing TMIB Factors Association With COVID-19 Vaccine Uptake.

Effect	Degrees of Freedom	Wald chi-square	P
Influenza vaccine uptake	1	6.52	.0107
Vaccine hesitancy	2	19.28	<.0001
Parents think is alright	1	43.31	<.0001
Vaccine hesitancy*parents think is alright	2	4.52	.104
Age group	1	0.41	.522
Vaccine hesitancy*age group	2	6.79	.034
Race group	2	6.18	.046
Adolescent educational level	1	9.22	.002
	OR estimate	OR 95% Confidence limits
Parents think is alright No vs Yes at vaccine hesitance = low	0.06	0.03	0.14
Parents think is alright No vs Yes at vaccine hesitance = mod	0.27	0.09	0.85
Parents think is alright No vs Yes at vaccine hesitance = high	0.07	0.02	0.33
Age group 16-17 vs 18-21 at vaccine hesitancy = low	0.76	0.33	1.77
Age group 16-17 vs 18-21 at vaccine hesitancy = mod	0.88	0.26	3.03
Age group 16-17 vs 18-21 at vaccine hesitancy = high	7.85	1.55	39.91
Vaccine hesitancy mod vs low at parents think is alright = No Age group = 16-17	1.36	0.35	5.28
Vaccine hesitancy high vs low at parents think is alright = No Age group = 16-17	0.80	0.18	3.63
Vaccine hesitancy mod vs high at parents think is alright = No Age group = 16-17	1.70	0.34	8.55
Vaccine hesitancy mod vs low at parents think is alright = No Age group = 18-21	1.18	0.37	3.79
Vaccine hesitancy high vs low at parents think is alright = No Age group = 18-21	0.08	0.02	0.40
Vaccine hesitancy mod vs high at parents think is alright = No Age group = 18-21	15.19	2.67	86.49
Vaccine hesitancy mod vs low at parents think is alright = yes Age group = 16-17	0.31	0.07	1.31
Vaccine hesitancy high vs low at parents think is alright = yes Age group = 16-17	0.69	0.13	3.53
Vaccine hesitancy mod vs high at parents think is alright = yes Age group = 16-17	0.44	0.07	3.02
Vaccine hesitancy mod vs low at parents think is alright = yes Age group = 18-21	0.26	0.09	0.77
Vaccine hesitancy high vs low at parents think is alright = yes Age group = 18-21	0.07	0.02	0.24
Vaccine hesitancy mod vs high at parents think is alright = yes Age group = 18-21	3.96	0.95	16.39

Abbreviation: OR, odds ratio.

Among those with high vaccine hesitancy, the odds of having received ≥1 dose of COVID-19 vaccine was 7.8 (95% CI: 1.5, 39.9) times larger for age group 16 to 17 years than for age group 18 to 21 years. Conversely, among those with high vaccine hesitancy, the odds of having received ≥1 dose of COVID-19 vaccine was 0.07 (95% CI: 0.02, 0.33) times lower for participant with parental disapproval to receive the vaccine than for those with parental approval. Interaction between vaccine hesitancy levels and age group was significant (P = .0336). Although a decrease in the probability of being vaccinated was observed among high vaccine-hesitant AYAs in both groups (with and without parental approval), this decrease was much sharper in the older group (18 to 21 y.o.).

HBM: Logistic Regression Model Results

The significant association observed between risk perceptions of infection in the univariate analysis did not hold in the logistic regression model. The model failed the Hosmer-Lemeshow test for goodness of fit (P < .05). Significant factors in the model were perceived benefits of vaccination regarding lowering one’s chances of developing severe COVID-19, parental approval to vaccinate, whether receiving the vaccine is safe, and whether it is pleasant (P < .0001). Adolescents and young adults with parental approval had higher odds of being vaccinated compared with those whose parents disapproved it (aOR = 5.1, 95% CI: 2.6, 9.9). Similarly, believing that it is safe and pleasant to receive the vaccine and believing that vaccinated individuals are less likely to develop severe COVID-19 compared to unvaccinated individuals, were associated with higher odds of being vaccinated.

Discussion of Study Findings

COVID-19 vaccine coverage was similar to the Ohio State adult population. In our sample, 64.5% had received ≥1 dose and 27.7% had received an additional booster dose. At the time, this survey was sent to participants (April-June 2022), these numbers were 64% and 31% in the Ohio State adult population.²³

The results of this cross-sectional study showed that all TMIB model components, health behavior habit (influenza vaccine receipt), vaccine intention (measured by the proxy variable vaccine hesitancy) and facilitating conditions (measured by the proxy variables parental approval and age group) were significant predictors of probabilities of having received at least one dose of the COVID-19 vaccine, resulting in a strong model that fitted the data well. Conversely, the HBM components did not result in a valid binary logistic regression model. Similar to our findings, most of the studies in a systematic review⁵ did not find a significant association between risk perceptions and vaccination status. Influenza vaccination history, however, was a strong predictor of COVID-19 vaccination willingness among adults and in our study sample of AYAs, confirming the strength of this association across populations.

Our findings indicated that perceived risk of infection was associated with vaccine acceptance, but in the presence of other factors in the logistic regression, this association did not hold. Although risk perceptions may act as triggers for precautionary action,^23,24,25 engagement in preventive health behaviors, such as vaccination, may not solely be determined by the awareness of one’s own health risks^26-28 in the population of AYAs.

This survey contributes to the literature in 3 ways. This study is the first to present findings about COVID-19 vaccine acceptance among AYAs using the TMIB and the HBM as a theoretical framework to examine the utility of its constructs in predicting the receipt of at least one dose of the vaccine among AYAs. Second, our study presents the comparison between the HBM and TMIB regarding their usefulness in predicting vaccine uptake in our study population; and third, our study is the first to report vaccine rates for AYAs by demographic variables such as sexual orientation, and perceived risk of infection, perceived vaccine benefits, vaccine hesitancy, sentiments regarding vaccination, influenza vaccination status in the past 12 months, and by parental approval in receiving the vaccine.

This study has several limitations. At the time of this study data collection, uncertainty remained regarding the protection vaccines may provide against COVID-19 new variants. These uncertainties may have hindered AYAs to form an accurate evaluation of their own perceptions of risk. Moreover, during the 2 years prior to this study, strict precautionary measures were in place, daily incidence of COVID-19 was higher, and pandemic related news coverage with low scientific quality were available. The combination of these factors may have exacerbated the fear of the disease, and therefore, the perception of risk among AYAs may have been higher in the year before our study data were collected. Moreover, it is beyond the scope of this study to address all the potential factors influencing adolescents’ cost/benefit assessments regarding vaccination, although many of the barriers and motivators have been identified in the literature, including perceptions about vaccine safety and efficacy and social influences on behavior.^6,29,30 The same can be said about how the various vaccines factor into decisions, although all used to date have shown acceptable risk-benefit profiles, particularly in their protection against severe disease. Adequately updating the public is essential to assist the population in evaluating their own perceived risks for COVID-19, as well as their perceived risk of vaccine side effect and perceived benefits of the vaccine, as new research findings about this virus and its variants, and efficacy of new treatments and vaccines are reported.

Continued research is needed to evaluate shifting attitudes around COVID-19 risk perceptions among AYAs, as new developments about COVID-19, new pharmaceutical treatments and vaccines become available, along with new findings regarding benefits and risks of vaccination. Compared to our study, studies reported in the literature assessed COVID-19 knowledge and perceived risk in unique manners to address their study aims. Measuring general risk perceptions in this population consistently could have facilitated comparisons across populations.

Moreover, our study population included only AYAs who used the hospital services. We acknowledge that individuals sampled from the hospital patient population, who are seeking services, may consent or refuse to participate in research, and their willingness to participate is unlikely to be random. To meliorate that, we included any visit to all hospital sites and departments. Some bias might be also implied due to the low number of participants of minority race groups in this sample.

Conclusions

Our findings indicate that online survey in young population is feasible and may yield reasonable response rate with a small financial incentive, without using parental responses as proxy.

To our knowledge, no other study has used the TMIB as a framework in this study population. Our results indicate that the TMIB significantly predicted COVID-19 vaccine uptake, with a combined significant effect of age, parental approval, vaccine hesitancy, and having received the influenza vaccine (habitual health behavior). Confirming the findings in the adult population reported in the literature, AYAs vaccinated against influenza were more likely to have been vaccinated against COVID-19. As one of the main factors from the HBM, risk perceptions of infection and risk perception of developing severe COVID-19 did not contribute to a valid predictive model.

Further future longitudinal studies may benefit from collecting vaccine intention and uptake and investigating the utility of the TMIB in predicting vaccine uptake. Because this study used a cross-sectional design approach, vaccine hesitancy was used as proxy for intent to receive COVID-19 vaccine. Nevertheless, findings of a national longitudinal study among American adults¹⁸ indicate that COVID-19 vaccine hesitancy was associated with lower odds of subsequent vaccine uptake for vaccine refusers (aOR = 0.02; 95% CI: 0.01, 0.03).

Author Contributions

MFB: Conception and design, acquisition of data, analysis, and interpretation of data, Acquisition of funding, Drafting the article, and Final approval of the version to be published.

VKC, JBV, TCS, DLL: Substantial contributions to design, and interpretation of data, Substantial contributions to acquisition of funding, Critically reviewed the manuscript for important intellectual content, and Final approval of the version to be published.

Footnotes

Acknowledgements

The authors are grateful for the adolescents and young adults who kindly agreed to participate in this study and for the support from the Rebecca D. Considine Institute staff.

Declaration of Conflicting Interests

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research project was funded by Akron Children’s Foundation Research Grant (grant no. 4500086).

ORCID iD

Miraides F. Brown

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