Structural equation modeling of factors influencing childhood vaccination in Saudi Arabia

Abstract

Background

Vaccines are a global health success story, saving millions of lives each year. However, barriers to acceptance, such as misinformation, safety concerns, and trust issues, persist among parents. This study aimed to explore factors influencing Saudi parents' decisions to vaccinate their children, focusing on attitudes, subjective norms, perceived behavioral control, and behavioral intentions.

Methods

A cross-sectional study was conducted in Jazan, Saudi Arabia, across 170 primary healthcare centers (PHCCs) in seven administrative sectors. A random sampling approach selected 10 PHCCs per sector. Saudi parents with children aged 0–6 years attending PHCCs were approached to complete an online questionnaire. Data were collected from December 2023 to February 2024 with a total sample size of n=1310. The inter-relationship in the Theory of Planned Behavior was examined based on the data collected. Structural Equation Modeling (SEM) was used to evaluate the direct relationship between the predictor variables: attitude, subjective norm, and parent perceived behavioral control, on a mediating variable: behavioral intention. Mediation analysis was further carried out to investigate the indirect relationship between the predictor variables and the parents’ vaccination decision-making.

Results

The largest proportion of participants was from the Central Sector (27.9%), and the majority were female (68.5%). Most participants were aged 31–40 years (49.8%), married (92.6%), had a university-level education (65.9%), and 66.6% of participants were employed. Approximately 96.3% of children had received vaccinations, and 95.4% were vaccinated. The SEM revealed significant influence of parental attitudes on behavioral intention (B = 0.18, p<0.05); significant influence of subjective norms on behavioral intention (B = 0.08,p<0.05), and negative significant influence of perceived behavioral control on behavioral intentions (B = -0.208, p<0.05). Behavioral intention partially mediated the relationships between the predictor variables and parents' vaccination decision-making. The model fit indices: P value 0.00, Root Mean Square Error of Approximation (RMSEA)= 0.058, Comparative Fit Index (CFI)= 0.866, Tucker Lewis index (TLI)= 0.911, demonstrate the model's overall fit to the data, which indicates a good model fit.

Conclusion

These findings highlight the influence of parental beliefs and social factors on vaccination decisions and emphasize the need for targeted interventions. Insights from this study can inform culturally and contextually relevant strategies to address vaccination hesitancy and strengthen trust in childhood vaccination programs in Saudi Arabia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-23657-5.

Background

Vaccination hesitancy is a global issue affecting many countries [1–4]. According to the World Health Organization (WHO), the percentage of children receiving vaccines decreased from 86% in 2019 to 83% in 2021 [5]. In 1998, Andrew Wakefield published a now-discredited study linking the MMR vaccine to autism. This study, later retracted in 2010, caused significant damage, sparking fear and reducing vaccination rates in some countries, leading to disease outbreaks [6]. Despite extensive evidence disproving a connection between vaccines and autism, misinformation persists and continues to fuel hesitancy [7].

During the COVID-19 pandemic, even with millions of infections and deaths, the introduction of effective vaccines did little to quell anti-vaccine sentiments. Misinformation and distrust led to hesitancy, even among healthcare workers [8]. Some families, including educated ones, believe that vaccines are unnecessary for diseases they perceive as eradicated, while others cite safety concerns, fears of side effects, or beliefs in harmful vaccine components [9]. The Expanded Program on Immunization (EPI), established in 1974 by the WHO, aimed to vaccinate children globally against six fatal diseases: Polio, tetanus, Measles, and tuberculosis. By 1984, advances in immunological knowledge allowed the inclusion of vaccines for Hepatitis B, yellow fever, and Haemophilus influenza for regions with high disease prevalence [10, 11]. However, anti-vaccine campaigns, beginning in the 1980s, raised concerns about vaccine safety, fueling mistrust and perceptions of vaccines as unnecessary or harmful [12, 13]. Additionally, social media platforms such as Facebook and X (formerly known as Twitter) have further amplified misinformation, including false claims about vaccine safety and exaggerated risks of side effects, that influenced parental decisions [14–16].

Parental perceptions and acceptance of vaccination are critical to achieving high coverage rates [17]. The continuum of attitudes toward vaccination ranges from full acceptance to complete refusal, with hesitancy in between [18]. While educational level and knowledge are often highlighted, parental beliefs and perceptions play a more significant role in compliance with vaccination schedules [19, 20]. The Theory of Planned Behavior (TPB), developed by the social psychologist Icek Ajzen in 1991, provides a useful framework for understanding how these beliefs and perceptions translate into vaccination decisions [21] The TPB proposes that attitudes and subjective norms, and perceived behavioral control are independently and positively related to behavior intention and that behavioral intention is positively associated with behaviors. In the model, parents’ attitudes, subjective norms, perceived behavioral control, and behavioral intentions predict their decision-making behavior in vaccinating their children [22].

Saudi Arabia’s Ministry of Health (MOH) implements the national vaccination program in line with the Centers for Disease Control and Prevention (CDC) and WHO recommendations [23]. The program has significantly reduced infectious disease incidence, supported by a network of over 2,390 primary healthcare centers providing free vaccinations to Saudi and non-Saudi children alike [24, 25]. Although childhood vaccination is mandatory in Saudi Arabia [26], vaccine hesitancy has still been identified among Saudi parents [26–28]. Approximately 31.3% of parents in one of Saudi Arabia’s major cities report hesitancy due to concerns over safety, side effects, and mistrust of vaccines [29, 30].

Vaccines play a unique and critical role in public health, contributing more than any other intervention to preventing disease, reducing mortality, and improving quality of life in both developed and developing countries [31]. Despite their significance, limited research has explored the factors affecting parents’ decision-making regarding childhood vaccination in Saudi Arabia. We sought to explore factors influencing Saudi parents’ decisions to vaccinate their children, focusing on attitudes, subjective norms, perceived behavioral control, and intentions.

Methods

Study design

This study utilized a cross-sectional design and adopted the TPB, as shown in Fig. 1. Figure 1 presents a schematic diagram that shows the variables included in the study, with a visual illustration of the relationships of the factors that affect the parents’ decision-making regarding children’s vaccination. In the model, parents’ attitudes, subjective norms, perceived behavioral control, and behavioral intentions impact their decision-making behavior in vaccinating their children. We posit the following hypotheses:

• H₁: Parent attitudes have a direct relationship with behavioral intention to children’s vaccination in Saudi Arabia.

• H₂: Parent subjective norms have a direct relationship with behavioral intention to children’s vaccination in Saudi Arabia.

• H₃: Parent-perceived behavioral control has a direct relationship with behavioral intention to children’s vaccination in Saudi Arabia.

• H₄: Parent-perceived behavioral control has a direct relationship with parents’ decision-making to vaccinate their children in Saudi Arabia.

• H₅: Behavioral intention to children vaccination is a mediator between parent attitude and parent decision-making to vaccinate their children in Saudi Arabia.

• H₆: Behavioral intention for children vaccination is a mediator between parents’ subjective norms and parents’ decision-making to vaccinate their children in Saudi Arabia.

• H₇: Behavioral intention for children vaccination is a mediator between parents’ perceived behavioral control and parents’ decision-making to vaccinate their children in Saudi Arabia.

Fig. 1.

Hypothesized theoretical framework, theory of planned behavior

Study sample and setting

This study was nested within a broader investigation conducted in Jazan, Saudi Arabia, at primary healthcare centers (PHCCs) [32]. Jazan, located in the southwestern region of Saudi Arabia, has approximately 170 PHCCs distributed across seven administrative sectors. The sectors included Central, Farasan Island, Southern, Middle, Western, Eastern, and Northern sectors. For this study, PHCCs were selected from each sector using a simple random sampling technique, facilitated by web-based randomization software (https://www.random.org) [33]. A total of 10 PHCCs were selected per sector, except for the Farasan Island sector, where all three PHCCs were included due to their limited number. The selection ensured representation from urban and rural settings across the region. Inclusion criteria consisted of Saudi national parents with children aged 0 to 6 years. Exclusion criteria included non-Saudi parents and those with children older than 6 years.

The sample size for this study was determined using a priori sample size calculator for Structural Equation Modeling (SEM) [34]. The parameters used included an alpha level of 0.05, a power of 0.80, 47 observed variables, and five latent variables, with a medium effect size of 0.3 [35]. The minimum sample size required to detect the effect was 150, while the structural complexity of the model required a minimum sample size of 1,289. To ensure robustness, the final sample included 1,310 participants.

Data collection

Data collection was conducted between December 2023 and February 2024. Participants were recruited from randomly selected primary healthcare centers (PHCCs) in various sectors. After verifying eligibility, informed consent was obtained, and participants completed an online questionnaire. Parents were also provided the option to fill out the questionnaire in a quiet room within the PHC. The questionnaire consisted of closed-ended and self-reported items and was accessed via a secure barcode link. All collected data were stored on a password-protected computer to ensure confidentiality, and participants were informed of their right to withdraw at any time.

Demographic characteristics

The demographic information collected included parents’ characteristics, the sector of the PHCC they attended, the number of children, whether their children received all required vaccinations, whether vaccinations were received regularly according to the MOH schedule, educational level, age, gender, marital status, income, employment status, and job specifications.

Instrumentation

Attitude toward behavior

This study utilized the SHOT questionnaire, originally developed by Victoria P. Niederhauser based on the Theory of Reasoned Action (TRA) [36], to examine parents’ barriers to childhood vaccination. The Arabic version was validated and adapted for use to assess vaccination challenges among Saudi parents in a previous study [37]. The SHOT questionnaire comprises 23 items, each rated on a five-point Likert scale from 0 (“Not a Problem”) to 4 (“A Very Big Problem”), with total scores ranging from 0 to 92. Higher scores indicate greater barriers faced by parents in vaccinating their children. The instrument demonstrated robust psychometric properties, with a Cronbach’s alpha of 0.93, indicating excellent internal consistency [32]. For this study, the questionnaire was translated into Arabic using an integrated method that combines cultural adaptation with scale translation, marking its first use among an Arab population [38].

Subjective norms

The subjective norms questionnaire was developed based on a review of the literature to assess beliefs about whether key individuals approve or disapprove of behavior and the motivation to align with those expectations [39]. It evaluates how parents’ perceptions of vaccination are influenced by the opinions of significant others, such as family and friends, and community actions [39]. The measure included three items rated on a five-point Likert scale ranging from “Strongly Agree” to “Strongly Disagree.” The scale demonstrated acceptable reliability, with a Cronbach’s alpha of 0.70.

Behavioral intention

The behavioral intention questionnaire, developed based on a review of the literature, assessed parents’ perceptions of the likelihood of vaccinating their children [39]. It included questions about parents’ intentions or plans to vaccinate their children at the next scheduled appointment. The measure consisted of three items rated on a three-point Likert scale: “Yes,” “No,” or “Unsure.” The scale reliability is α = 0.94.

Perceived behavioral control

Perceived behavioral control reflects an individual’s perceived ease or difficulty in performing a behavior. A questionnaire developed from a literature review assessed parents’ confidence and ability to vaccinate their children [39]. The measure used a rating scale ranging from 0 (“Poor Control”) to 5 (“Good Control”). The scale demonstrated strong reliability, with a Cronbach’s alpha of 0.89.

Parents’ decision making on children’s vaccination

The Parental Attitudes Toward Childhood Vaccines (PACV) survey, originally developed by Opel et al., is designed to assess parental vaccine hesitancy [40]. Created using qualitative methods, it has demonstrated strong content and face validity, as well as predictive validity and test-retest reliability [40, 41]. This study utilized the validated Arabic version of the PACV survey [42]. The scale consists of 15 items with varied response formats: Questions 1, 2, and 11 are scored as Yes (1), No (2), or Don’t Know (3); Questions 3 and 15 are rated on a scale from 0 (“Not at all sure”) to 10 (“Completely sure”); and Questions 4–10 and 12–14 are rated from 5 (“Strongly Agree”) to 1 (“Strongly Disagree”). The scale demonstrated good internal consistency, with a reliability score of α = 0.78 [42].

Cultural adaptation and translation

To ensure the measures were culturally and linguistically appropriate for the Saudi population, a rigorous cultural adaptation and translation process was followed [38]. This process involved selecting culturally relevant measures, assessing conceptual equivalence, forward translation, and pre-testing. Back translation, though optional, was not conducted, as prior research demonstrated no significant differences in psychometric properties with its omission [38, 43]. The translation was conducted by two independent bilingual and bicultural healthcare professionals. Both translators ensured the original scale’s meaning was preserved while incorporating culturally relevant expressions. Any discrepancies were resolved collaboratively, and a consensus was reached. Cognitive interviews were conducted with bilingual and monolingual participants to refine the tool further, ensuring clarity, cultural relevance, and readability. A pilot study was then conducted with 602 Saudi parents of children aged from birth to six years, recruited from primary PHCCs in Jazan. Participants completed the self-administered questionnaire online or during their clinic visits. This pre-testing phase ensured the measures were understandable, free from ambiguity, and relevant to the target population. Feedback from participants helped identify any items needing adjustment. The finalized Arabic version of the questionnaire demonstrated clarity, ease of understanding, and cultural appropriateness. No modifications were deemed necessary after expert review.

Internal consistency

Cronbach’s alpha for the post-test for all instruments used in the current study is described in Table 4. The scales’ reliabilities/ internal consistency were calculated by Cronbach’s alpha (a), behavioral intention a = 0.70, subjective norms a = 0.86, perceived behavioral control a = 0,89, and parents’ attitude a = 0.95. Also, parents’ decision-making reliability is a = 0.88. Reliabilities, including test-retest as well as internal consistency, were computed in the pilot study reliability of the instruments.

Table 4.

Construct reliability and validity

Construct	Reliability	Validity (AVE)
Decision	0.78	0.52
Behavioral Intention	0.94	0.50
Subjective norm	0.70	0.69
Perceived behavioral control	0.89	0.74
Attitude of the parent	0.90	0.51

*AVE The average variance extraction

Data analysis

Data were analyzed using the Statistical Package for Social Sciences (SPSS) version 29 (IBM Corp, 2023) and Analysis of Moment Structures (AMOS) version 26 (IBM Corp, 2019). The data collected through electronic forms were downloaded and imported into SPSS for analysis. Descriptive statistics, including frequencies and percentages, were used to summarize the socio-demographic characteristics of the participants. Measures of dispersion, such as standard deviation, skewness, and kurtosis, were computed to assess the normality of the data. According to Field (2018) normality of data can be observed if the skewness is within the value − 3.0 to 3.0, and the kurtosis is within the value − 8.0 to 8.0, and the skewness and kurtosis of all the constructs considered in the study were all within the limit [44].

The confirmatory factor analysis (CFA) conducted using AMOS version 26 evaluated the measurement models for 5 constructs (attitude, subjective norm, perceived behavioral control, decision, and behavioral intention). Standardized regression estimates were used to assess the factor loadings of each item, ensuring adequate representation of the intended constructs. Items with factor loadings below 0.5 were removed, following recommended guidelines [45]. To improve model fit indices, some items under the construct of decision and attitude were used as covariates [45]. The factor loadings of each item were examined to ensure they adequately represented their respective constructs, with a threshold of ≥ 0.5. Items that were not loading up to 0.5 were excluded as recommended in research [45, 46]. Figure 2 and Table 3 show the details of the factor loadings.

Fig. 2.

Confirmatory factor analysis of all the constructs used in the model. Note: e:error. D1-D13 decision making, BI1-3 behavioral intention, SN1-3subjective norms, PBC1-3 perceived behavioral control, A1- 22 attitude

Table 3.

Factor loadings of each item of the latent constructs

Items	⤎	Constructs	Factor Loadings
Decision (D15)	⤎	Decision	0.54
Decision (D14)	⤎	Decision	0.71
Decision (D13)	⤎	Decision	0.96
Decision (D12)	⤎	Decision	0.65
Decision (D10)	⤎	Decision	0.64
Decision (D9)	⤎	Decision	0.58
Decision (D8)	⤎	Decision	0.56
Decision (D7)	⤎	Decision	0.99
Decision (D5)	⤎	Decision	0.57
Decision (D4)	⤎	Decision	0.94
Decision (D3)	⤎	Decision	0.51
behavioral intention (BI3)	⤎	behavioral intention	0.63
behavioral intention (BI2)	⤎	behavioral intention	0.73
behavioral intention (BI1)	⤎	behavioral intention	0.61
Subjective norm (SN3)	⤎	Subjective norm	0.98
Subjective norm (SN2)	⤎	Subjective norm	0.72
Subjective norm (SN1)	⤎	Subjective norm	0.74
Perceived behavioral control (PBC3)	⤎	Perceived behavioral control	0.90
Perceived behavioral control (PBC2)	⤎	Perceived behavioral control	0.88
Perceived behavioral control (PBC1)	⤎	Perceived behavioral control	0.78
Attitude (C22)	⤎	Attitude	0.81
Attitude (C21)	⤎	Attitude	0.76
Attitude (I20)	⤎	Attitude	0.68
Attitude (C19)	⤎	Attitude	0.77
Attitude (I18)	⤎	Attitude	0.78
Attitude (I17)	⤎	Attitude	0.72
Attitude (C16)	⤎	Attitude	0.85
Attitude (C15)	⤎	Attitude	0.80
Attitude (I14)	⤎	Attitude	0.76
Attitude (C13)	⤎	Attitude	0.80
Attitude (A12)	⤎	Attitude	0.69
Attitude (A9)	⤎	Attitude	0.63
Attitude (A8)	⤎	Attitude	0.52
Attitude (A7)	⤎	Attitude	0.67
Attitude (A4)	⤎	Attitude	0.50
Attitude (A2)	⤎	Attitude	0.59
Attitude (A1)	⤎	Attitude	0.55

Composite reliability, average variance extracted (AVE), and discriminant validity (assessed using the Fornell-Larcker criterion) were calculated to evaluate the eligibility of each construct [47]. Multiple fit indices were used to assess the measurement model’s goodness of fit before proceeding to structural equation modeling (SEM). These indices included the Chi-square test statistic (a non-significant value indicating a good fit), adjusted goodness-of-fit index (AGFI), goodness-of-fit index (GFI), parsimony goodness-of-fit index (PGFI), comparative fit index (CFI), incremental fit index (IFI), normal fit index (NFI), Tucker-Lewis index (TLI), and root mean square error of approximation (RMSEA). SEM was then applied to evaluate the relationships between the constructs based on the study’s conceptual framework. The significance of the estimates was determined using p-values (p < 0.05), critical ratios (> 1.96), and confidence interval bias correction (CIBC), ensuring that zeros were not included within the intervals of the significant estimates [48].

Results

Background characteristics of the study participants

Table 1 presents participants’ sociodemographic characteristics and vaccination data. Most participants were female and resided in the central sector (68.5%, n = 897). The majority were married (92.6%, n = 1213), with ages ranging from 20 to over 50 years. The average number of children per family was three (SD = 1.76). Regarding education, 7.1% (n = 93) held higher education credentials, primarily university degrees (95.9%, n = 863). In terms of employment, 66.6% (n = 872) were employed, with notable representation in healthcare (18.4%, n = 456) and education sectors (18.4%, n = 241). Income distribution showed that 35% (n = 459) earned between 5,000 and 10,000 Saudi Riyals (SAR), while 40% (n = 530) earned between SAR 10,000 and 20,000. Vaccination data revealed that 96.3% (n = 1261) had vaccinated their children, with 95.4% (n = 1250) adhering to the MOH vaccination schedule.

Table 1.

Demographic characteristics of the study participant (N = 1310)

Characteristic	Frequency (n)	Percentage (%)
Sector to which the participant belongs
Central Sector	365	27.9%
Middle Sector	126	9.6%
Northern Sector	161	12.3%
Southern Sector	188	14.4%
Western Sector	243	18.5%
Eastern Sector	170	13%
Farasan Sector	57	4.4%
Child receive vaccination
Yes	1261	96.3%
No	49	3.7%
Children receive their vaccinations regularly according to MOH schedule
Yes	1250	95.4%
No	60	4.6%
Educational level
Dose no write or read	6	0.5%
Write and read	37	2.8%
Intermediate	68	5.2%
High school	243	18.5%
University	863	65.9%
Higher education	93	7.1%
Gender
Male	413	31.5%
Female	897	68.5%
Participant age
20 to 30 Years old	273	20.8%
31 to 40 Years old	653	49.8%
41 to 50 Years old	339	25.9%
More than 50 Years old	45	3.4%
Marital status
Married	1213	92.6%
Widow	25	1.9%
Divorced	54	4.1%
Single	18	1.4%
Income
Less than 5,000	165	12.6%
More than 20,000	102	7.8%
No income	54	4.1%
Between 10,000 to 20,000	530	40.5%
Between 5,000 to 10,000	459	35%
Work
Yes	872	66.6%
No	438	33.4%
Field of Work
Health sector	456	34.8%
Educational sector	241	18.4%
Engineering	18	1.4%
Free duty	19	1.5%
Housewife	212	16.2%
Military sector	63	4.8%
Private sector	28	2.1%
I don’t work	150	11.5%
Governmental sector	76	5.8%
Other	47	3.6%

Table 8 in the Appendix presents the mean and standard deviation of various variables related to parental decision-making and concerns regarding children’s vaccination. Items BI1, BI2, and BI3, which relate to parental plans for vaccination and the completion of required vaccinations, have relatively low mean values (around 1.0). This suggests that respondents generally exhibit positive intentions and behaviors regarding their children’s vaccination.

Items SN1, SN2, and SN3, related to subjective norms regarding vaccination, show mean values ranging from 2.01 to 2.73, indicating varying levels of influence from social norms on parents’ decision-making. Items PBC1, PBC2, and PBC3, reflecting perceived behavioral control, have high mean values (around 4.49 to 4.54), highlighting a strong perceived ability and confidence among parents to ensure their children receive vaccinations.

Items related to decision-making concerns and attitudes toward vaccination (Decision1 to Decision23) exhibit mean values that reflect varying levels of agreement or concern among parents regarding different aspects of vaccination. Items Access1 to Access12, representing barriers to accessing vaccination services, have mean values that suggest the degree of difficulty experienced by parents in accessing vaccination services.

Items Concerns 13 to Concerns 22, which capture concerns and fears related to vaccination, show mean values that indicate the level of anxiety or worry among parents regarding potential side effects, safety, and efficacy of vaccines. Finally, items Import14 to Import23, representing the importance parents attribute to vaccination, have mean values that reflect varying levels of belief in the importance and effectiveness of vaccines.

Measurement model

As illustrated in Fig. 2 and detailed in Table 2, the model fit was evaluated using multiple indices, including the parsimony goodness-of-fit index (PGFI) = 0.760, comparative fit index (CFI) = 0.917, incremental fit index (IFI) = 0.917, normed fit index (NFI) = 0.901, Tucker-Lewis index (TLI) = 0.911, and root mean square error of approximation (RMSEA) = 0.058. All fit indices met the recommended thresholds as shown in Fig. 2, confirming an acceptable overall goodness of fit for the constructs within the model.

Table 2.

Fit indices

Fit Indices	Recommended Value	Reference(s)	Estimated model
P value			0.00
ChiSqr/df	<5	[49]	5.42
RMSEA	< 0.08	[50]	0.05
RMSEA LOW 90% CI			0.05
RMSEA HIGH 90% CI			0.06
GFI	≥ 0.8	[51]	0.86
AGFI	> 0.8	[52]	0.84
PGFI	≥ 0.5	[53]	0.76
NFI	≥ 0.90	[54]	0.90
IFI	> 0.90	[55]	0.91
TLI	> 0.90	[56]	0.91
CFI	> 0.90	[56]	0.91
AIC	N/A	N/A	3557.92
BIC	N/A	N/A	3998.03

Table 3 depicts each construct’s factor loadings for each observed variable (item). It can be noticed that all the factor loadings were greater than or equal to 0.5 (≥ 0.5), which is an acceptable limit of factor loadings for a construct [45]. All the reliability of the construct was above 0.7, which shows excellent reliability. The average variance extraction (AVE) was used to validate each construct Table 4. Values greater than 0.5 and above are a good measure of construct validity [48]. The Fornell-Larcker criterion was applied to assess the discriminant validity of the constructs. According to this criterion, each construct must demonstrate a higher correlation with itself than with other constructs. As shown in Table 5, all constructs satisfied this criterion, indicating that the constructs are distinct from each other.

Table 5.

Construct discriminant validity (Fornell-Larcker Criterion)

Construct	Decision	Behavioral Intention	Subjective Norm	Perceived Behavioral Control	Attitude of the Parent
Decision	0.72
Behavioral Intention	−0.19	0.66
Subjective Norm	−0.11	0.10	0.83
Perceived Behavioral Control	0.21	−0.26	−0.11	0.86
Attitude of the Parent	−0.25	0.29	0.05	−0.27	0.71

For the direct effects on the behavioral intention of the parent, generally, all the effect that takes place in SEM can be given by a unit increase in the attitude of the parent, implying that the behavioral intention of the parents to immunize their children goes up by 18%. One unit increase in perceived behavioral control implies that the behavioral intention of the parents to immunize their children decreases by 21%. One unit increase in the parents’ subjective norm indicates that the parents’ behavioral intention to immunize their children increases by 8%. In terms of direct effects on the decision of the parents, a unit increase in attitude indicates that the decision of the parents to immunize their children goes down by 3%. One unit increase in the subjective norm of the parents indicates that the decision of the parents to immunize their children is reduced by 1%. One unit increase in perceived behavioral control implies the decision of the parents to immunize their children increases by 20%. One unit increase in behavioral intention of the parents indicates that the decision of the parents to immunize their children reduces by 15%.

It can be observed from Table 6 that hypotheses 1–4 were supported at varying estimated values and supported with a p-value less than 0.05 and confidence interval biased corrected, which shows that the interval between the lower and the upper bound does not contain zero.

Table 6.

Direct effects between the independent variables and dependent variables

	Path Coefficient	P values	Lower CI Bias Corrected 5%	Upper CI Bias Corrected	Decision
Attitude → Behavioral intention	0.18	0.02	5%	95%	Supported
Subjective norm → Behavioral intention	0.07	0.00	0.08	0.23	Supported
Perceived Behavioral control → Behavioral l intention	−0.20	0.00	0.01	0.15	Supported
Perceived Behavioral control → Decision	0.17	0.02	−0.30	−0.11	Supported
Behavioral intention → Decision	−015	0.00	0.09	0.22	Supported

Table 7 depicts the varying estimated value at which behavioral intention partially mediates the relationship between the independent variables (attitude, subjective norm, perceived behavioral control) and the dependent variable (decision). Thus, hypotheses 5–7 were fully supported with a P-value less than 0.05 and the confidence interval bias corrected, which shows that the interval between the lower and the upper bound does not contain zero. Figure 3 shows the structural model of the theoretical framework of the study. Items Access1 to Access12, which denote obstacles encountered in accessing vaccination services, show mean values indicative of the challenges parents face in securing vaccination for their children. Furthermore, the items Concerns 13 to Concerns 22, which reflect parental worries about vaccination, display mean values that suggest varying degrees of anxiety regarding potential side effects, safety, and vaccine efficacy. Lastly, the items Import 14 to Import 23, representing the value parents place on vaccination, exhibit mean scores that highlight diverse levels of belief in the significance and effectiveness of vaccines.

Table 7.

Indirect effects (Mediation Effect) the independent variables and dependent variables

	Path Coefficient	P values	Lower CI Bias Corrected 5%	Upper CI Bias Corrected	Decision
Attitude → Decision	−0.02	0.00	−0.55	−0.01	Supported
Subjective Norm → Decision	−0.03	0.00	0.01	0.06	Supported
Perceived Behavioral Control → Decision	−0.01	0.00	−0.03	−0.00	Supported

Fig. 3.

Structural model of the theoretical framework of the study. Note: e:error. D1-D13 decision making, BI1-3 behavioral intention, SN1-3subjective norms, PBC1-3 perceived behavioral control, A1- 22 attitude

Discussion

The current study utilized a robust methodology to explore the factors influencing Saudi parents’ decisions to vaccinate their children. It is one of the few studies addressing this critical public health concern in the region. Using a validated and culturally adapted survey based on the TPB, this research examined key constructs, including parental attitudes, subjective norms, perceived behavioral control, and behavioral intentions. SEM was applied to analyze the relationships among these variables and their influence on decision-making. The study results revealed many important findings: 1) Parent attitudes directly correlate with behavioral intention to children’s vaccination in Saudi Arabia. 2) Parent subjective norms directly correlate with behavioral intention to children’s vaccination in Saudi Arabia. 3) Parent-perceived behavioral control is directly related to behavioral intention regarding children’s vaccination in Saudi Arabia. 4) Parent-perceived behavioral control has a direct relationship with parents’ decision-making to vaccinate their children in Saudi Arabia. 5) Behavioral intention to children’s vaccination is a partial mediator between parents’ attitude and parents’ decision-making to vaccinate their children in Saudi Arabia. 6) Behavioral intention regarding children’s vaccination partially mediates parents’ subjective norms and parents’ decision-making to vaccinate their children in Saudi Arabia. 7) Behavioral intention to children’s vaccination is a mediator between parent-perceived behavioral control and parent decision-making to vaccinate their children in Saudi Arabia.

Parental attitudes toward decision-making regarding childhood vaccination can be varied, despite most parents understanding the importance of vaccinations and following recommended vaccination schedules. These results are similar to previous studies that examined parents’ attitudes toward children’s vaccination, which found that parents’ attitudes were positive in Saudi Arabia [57–59]. In contrast, a study conducted among parents in Thailand found that they expressed negative perceptions, unpleasant emotions, and strong personal convictions regarding vaccinating their children [60]. These differences highlight how cultural and contextual factors shape vaccination perceptions, with more positive parental attitudes observed in Saudi Arabia compared to the ambivalence and resistance reported in studies from Thailand. Ultimately, parents’ attitudes, whether positive or negative, shape their perceptions of the importance of child vaccination and significantly influence their decision to vaccinate.

Behavioral intention measures the relative power of a person’s intention to act on behavior, the perceived probability of performing a behavior, and the intended plan by parents to vaccinate their children or not [61]. The current results showed that parents’ behavioral intention for children’s vaccination is a mediator between attitude, subjective norms, perceived behavioral control, and parents’ decision-making to vaccinate their children in Saudi Arabia. This finding is consistent with the TPB, which suggests that behavioral intention is a central pathway linking individual beliefs and eventual behaviors. A systematic review by Brewer et al. (2017) found that attitudes and social norms were strong predictors of vaccination intentions across multiple vaccines, emphasizing the central role of behavioral intention [62]. Additionally, parents’ perceptions of a particular behavior are influenced by the judgments and expectations of significant others within their family and community. Parental subjective norms are directly related to behavioral intentions regarding children’s vaccination. This finding is consistent with a study conducted in Indonesia, which revealed that subjective norms positively influenced mothers’ intentions to provide primary vaccination for their children, although the intention did not necessarily translate into actual vaccination behavior [63]. Subjective norms can influence an individual’s intention to carry out a behavior. In this study, a direct relationship was found between subjective norms and parents’ behavioral intentions regarding children’s vaccination. This may be attributed to the social influence of family members or the community, whose opinions parents considered important when deciding whether to immunize their children. Such social influences could lead to feelings of pressure, affecting parents’ decision-making. As a result, parents may feel compelled to follow the suggestions or expectations of those they perceive as significant [64]. In a study conducted in Saudi Arabia, participants mentioned that the MOH, family members, medical professionals, social media, and other sources exerted varying degrees of influence on their perspectives regarding vaccination [65]. Positive social and community influences, particularly when they promote vaccination as a social norm, can encourage hesitant parents to vaccinate their children [44]. Strengthening these supportive environmental factors may therefore play a critical role in improving vaccination uptake.

Furthermore, the findings indicate that parent-perceived behavioral control has a direct influence on their intention to vaccinate their children, as well as on the actual decision-making process. Many parents reported that easy access to vaccination services influenced their sense of control. The study further demonstrated that higher perceived control was associated with stronger vaccination intentions. Conversely, perceived uncertainty significantly predicted lower levels of perceived control regarding childhood vaccinations [66].

Additionally, in our study, we found that perceived behavioral control significantly negatively influences behavioral intentions. Other research indicates that the relationship between perceived behavioral control and intention can be influenced by cultural and contextual factors [67]. For example, in collectivist cultures, social norms and the opinions of significant others may play a more substantial role in shaping intentions than individual perceptions of control [68]. Vaccine hesitancy refers to the decision-making process through which individuals accept, refuse, or delay vaccination, influenced by a variety of contextual factors and barriers, and resulting in different behavioral outcomes. It is shaped by individuals’ levels of commitment to healthism, perceptions of threat culture, and confidence in health authorities [69]. Misconceptions about vaccine safety, effectiveness, and potential side effects, often spread through social media, religious circles, or other informal sources, can contribute to vaccine hesitancy among parents.

This study is among the few conducted in Saudi Arabia that explores factors influencing parents’ decision-making regarding childhood vaccination. A key strength lies in the random selection of primary healthcare centers from each of the seven administrative sectors in Jazan, allowing for broader representation across different socioeconomic and cultural contexts within Jazan region. The application of the TPB offers interesting insights into the factors that shape parental decision-making. Moreover, the use of SEM strengthens the study by enabling the testing of complex associations across various types of data, including categorical, dimensional, censored, and count variables, and by allowing comparisons between alternative theoretical models [70]. SEM also facilitates validation of the underlying theoretical framework by assessing the interaction of multiple latent variables across different domains [71]. Despite the high sample size typically required for SEM, our study successfully met this analytical requirement.

This study has several limitations that should be considered when interpreting the findings. First, there is a potential for selection bias due to the use of a non-probability sampling approach. Participants were recruited from healthcare facilities in Jazan, which may exclude individuals who do not regularly engage with the healthcare system or those residing in remote areas. As such, the sample may overrepresent individuals with higher health awareness or greater access to health services. Additionally, the data were collected through self-reported questionnaires, which introduces the risk of information and social desirability bias. Participants may have provided responses that align with socially acceptable attitudes toward vaccination, rather than their actual beliefs or behaviors.

The study did not include key covariates such as socioeconomic status, educational background, or healthcare access. This limits the ability to adjust for known contextual factors that influence vaccine decision-making. This is particularly relevant given that the study was conducted exclusively in Jazan, a region with distinct socioeconomic, geographic, and healthcare access characteristics that may not reflect the diversity found across other regions in Saudi Arabia. The population in Jazan tends to have more conservative cultural practices and differing levels of healthcare access, which may influence perceptions and practices around shared decision-making in vaccinating their children. Additionally, although our sample included a relatively large proportion of educated individuals, educational attainment alone does not account for broader regional disparities in health literacy, access, or cultural perceptions of vaccines. These contextual factors may limit the applicability of the findings to regions with different socio-cultural dynamics and healthcare systems, such as Riyadh or Jeddah [72].

Although the TPB was used to identify factors influencing parents’ attitudes, subjective norms, and perceived behavioral control regarding vaccination intentions, the model had some limitations. While model fit indices were acceptable (RMSEA = 0.058; TLI = 0.911), the exclusion of key demographic variables may further restrict the generalizability of the results. Future studies should incorporate a broader range of demographic variables to better understand barriers to childhood vaccination in Saudi Arabia.

Internal consistency was low for both the subjective norms scale (α = 0.64) and the behavioral intention scale (α = 0.51). Although these scales were theoretically grounded, their reliability fell below accepted standards, potentially threatening the validity of the findings. Future research should refine and validate these measurement tools to improve reliability and strengthen the integrity of results.

Lastly, the study’s cross-sectional design precludes any conclusions about causal relationships.

Despite these limitations, the study offers critical insights into the dynamics of vaccine hesitancy in a culturally unique region of Saudi Arabia. Future research should incorporate longitudinal designs, expand demographic variables, and validate culturally adapted measurement tools to better inform national immunization strategies and parental engagement.

Conclusion

This study examined factors influencing Saudi parents’ decisions to vaccinate their children through the lens of the TPB. Key findings revealed that parental attitudes, subjective norms, and perceived behavioral control significantly affect behavioral intentions and vaccination decisions. To address vaccine hesitancy and improve vaccination coverage, targeted educational campaigns to correct misinformation, particularly through trusted governmental social media channels; enhancing healthcare provider communication to build parental confidence and trust; and improving accessibility to vaccination services by offering flexible clinic hours and mobile vaccination units. Future research should explore vaccine decision-making dynamics across diverse regions of Saudi Arabia and adopt longitudinal approaches to capture changes over time better.

Abbreviations

MOH

Ministry of health

PHCCs

Primary healthcare centers

TPB

Theory of planned behavior

SEM

Structural equation modeling

WHO

World health organization

EPI

Expanded program on Immunization

MMR

Measles, mumps, and rubella

SHOT

Screening for health opportunities for teens questionnaire

PACV

Parental attitudes toward childhood vaccines

AVE

Average variance extracted

CFA

Confirmatory factor analysis

SPSS

Statistical package for social sciences

AMOS

Analysis of a moment structures

Appendix

Description of the study variables (N= 1310)

Characteristic	Frequency (n)	Percentage (%)
Behavioral intention
Do you plan to have or continue to have your child/children immunized?
Yes	1245	95%
No	16	1.2%
Have you already obtained vaccination for your children?
Yes	1239	94.6%
No	35	2.7%
Did you complete the required vaccination for your children according to your child age?
Yes	1251	95.5%
No	31	2.4%
Subjective norms
People around me expect from me to vaccinate my children
Strongly Agree	718	54.8%
Agree	298	22.7%
Not Sure	67	5.1%
Not Agree	23	1.8%
Strongly not Agree	204	15.6%
If people around me delay vaccinating their children, I will do the same
Strongly Agree	494	37.7%
Agree	233	17.8%
Not Sure	98	7.5%
Not Agree	113	8.6%
Strongly not Agree	372	28.4%
If the people around me vaccinate their children on time, I will do the same
Strongly Agree	613	46.8%
Agree	283	21.6%
Not Sure	114	8.7%
Not Agree	30	2.3%
Strongly not Agree	270	20.6%
Perceived behavioral control
Rate your ability to get the vaccines for your children
Very Weak Control	50	3.8%
Weak Control	27	2.1%
Neutral	102	7.8%
Strong Control	139	10.6%
Very Strong Control	992	75.7%
How sure will you take your child for vaccination when it is due
Very Weak Control	57	4.4%
Weak Control	33	2.5%
Neutral	93	7.1%
Strong Control	158	12.1%
Very Strong Control	969	74.0%
How sure will you take your child for vaccination when he/she is healthy
Very Weak Control	54	4.1%
Weak Control	30	2.3%
Neutral	80	6.1%
Strong Control	135	10.3%
Very Strong Control	1011	77.2%
Parents decision making
Have you ever delayed having your child get a SHOT for reasons other than illness or allergy?
Yes	367	28%
No	862	65.8%
Don't' know	81	6.2%
Have you ever decided not to have your child get a SHOT for reasons other than illness or allergy?
Yes	198	15.1%
No	1055	80.5%
Don't know	57	4.4%
How sure are you that following the recommended shot schedule is a good idea for your child? Please answer on a scale of 0 to 10, where 0 is Not at all sure and 10 is Completely sure
Not at all sure	19	1.5%
1	45	3.4%
2	47	3.6%
3	26	2%
4	19	1.5%
5	44	3.4%
6	19	1.5%
7	35	2.7%
8	76	5.8%
9	122	9.3%
Completely sure	858	65.5%
Children get more shots than are good for them
Strongly Not Agree	47	3.6%
Not Agree	49	3.7%
Not Sure	81	6.2%
Agree	362	27.6%
Strongly Agree	771	58.9%
I believe that many of the illnesses that shots prevent are severe
Strongly Not Agree	54	4.1%
Not Agree	63	4.8%
Not Sure	152	11.6%
Agree	390	29.8%
Strongly Agree	651	49.7%
It is better for my child to develop immunity by getting sick than to get a shot
Strongly Not Agree	59	4.5%
Not Agree	62	4.7%
Not Sure	69	5.3%
Agree	376	28.7%
Strongly Agree	744	56.5%
It is better for children to get fewer vaccines at the same time
Strongly Not Agree	46	3.5%
Not Agree	47	3.6%
Not Sure	65	5.0%
Agree	370	28.2%
Strongly Agree	782	59.7%
How concerned are you that your child might have a serious side effect from a shot?
Very Concerned	78	6.0%
Somewhat Concerned	211	16.1%
Not Sure	135	10.3%
Not Too Concerned	341	26.0%
Not At All Concerned	545	41.6%
How concerned are you that anyone of the childhood shots might not be safe?
Very Concerned	80	6.9%
Somewhat Concerned	159	12.1%
Not Sure	173	13.2%
Not Too Concerned	345	26.3%
Not At All Concerned	543	41.5%
How concerned are you that a shot might not prevent the disease?
Very Concerned	56	4.3%
Somewhat Concerned	109	8.3%
Not Sure	182	13.9%
Not Too Concerned	387	29.5%
Not At All Concerned	576	43.9%
If you had another infant today, would you want him/her to get all the recommended shots?
Yes	1205	92%
No	64	4.9%
Don't Know	41	3.1%
Overall, how hesitant about childhood shots would you consider yourself to be?
Very Hesitant	58	4.4%
Somewhat Hesitant	94	7.2%
Not Sure	71	5.4%
Not too Hesitant	326	24.9%
Not at All Hesitant	761	58.1%
I trust the information I receive about shots
Strongly Not Agree	46	3.5%
Not Agree	48	3.7%
Not Sure	59	4.5%
Agree	368	28.1%
Strongly Agree	789	60.2%
I am able to openly discuss my concerns about shots with my child's doctor
Strongly Not Agree	38	2.9%
Not Agree	62	4.7%
Not Sure	97	7.4%
Agree	445	34%
Strongly Agree	668	51%
All things considered; how much do you trust your child’s doctor? Please answer on a scale of 0 to 10, where 0 is Do not trust at all and 10 is Completely trust
Don't trust at all	24	1.8%
1	46	3.5%
2	47	3.6%
3	26	2%
4	32	2.4%
5	74	5.6%
6	31	2.4%
7	81	6.2%
8	133	10.2%
9	145	11.1%
Completely trust	671	51.2%
Parents attitude
I didn’t know when my child needed to get his/her shots
Strongly Not Agree	713	54.4%
Not Agree	134	10.2%
Not Sure	195	14.9%
Agree	115	8.8%
Strongly Agree	153	11.7%
I didn’t know where to take my child to get his/her shots
Strongly Not Agree	878	67%
Not Agree	123	9.4%
Not Sure	116	8.9%
Agree	86	6.6%
Strongly Agree	107	8.2%
There were no appointments available at the clinic for shots
Strongly Not Agree	808	61.7%
Not Agree	161	12.3%
Not Sure	141	10.8%
Agree	88	6.7%
Strongly Agree	112	8.5%
The shots cost too much
Strongly Not Agree	806	61.5%
Not Agree	112	8.5%
Not Sure	128	9.8%
Agree	84	6.4%
Strongly Agree	180	13.7%
The clinic/facility wasn’t open at a time I could go
Strongly Not Agree	854	65.2%
Not Agree	142	10.8%
Not Sure	154	11.8%
Agree	62	4.7%
Strongly Agree	98	7.5%
I didn’t have a ride to the clinic
Strongly Not Agree	844	64.4%
Not Agree	156	11.9%
Not Sure	140	10.7%
Agree	71	5.4%
Strongly Agree	99	7.6%
I didn’t have someone to take care of my other children
Strongly Not Agree	810	61.8%
Not Agree	167	12.7%
Not Sure	157	12%
Agree	77	5.9%
Strongly Agree	99	7.6%
My child was sick and could not get his/her shots
Strongly Not Agree	658	50.2%
Not Agree	179	13.7%
Not Sure	185	14.1%
Agree	108	8.2%
Strongly Agree	180	13.7%
The clinic wait was too long
Strongly Not Agree	677	51.7%
Not Agree	198	15.1%
Not Sure	223	17%
Agree	102	7.8%
Strongly Agree	110	8.4%
I couldn’t get time off from work
Strongly Not Agree	746	56.9%
Not Agree	142	10.8%
Not Sure	170	13%
Agree	103	7.9%
Strongly Agree	149	11.4%
Getting my children for shots is too much trouble
Strongly Not Agree	773	59.0%
Not Agree	190	14.5%
Not Sure	167	12.7%
Agree	88	6.7%
Strongly Agree	92	7.0%
I just forgot
Strongly Not Agree	807	61.6%
Not Agree	151	11.5%
Not Sure	163	12.4%
Agree	83	6.3%
Strongly Agree	106	8.1%
I’m scared of the side effects of the shots
Strongly Not Agree	674	51.5%
Not Agree	205	15.6%
Not Sure	205	15.6%
Agree	91	6.9%
Strongly Agree	135	10.3%
I worry about the number of shots my child gets at one time
Strongly Not Agree	753	57.5%
Not Agree	197	15%
Not Sure	159	12.1%
Agree	85	6.5%
Strongly Agree	116	8.9%
I worry about what is in the shots
Strongly Not Agree	778	59.4%
Not Agree	189	14.4%
Not Sure	169	12.9%
Agree	69	5.3%
Strongly Agree	105	8.0%
I worry my child might get sick from the shot
Strongly Not Agree	629	48%
Not Agree	214	16.3%
Not Sure	223	17%
Agree	109	8.3%
Strongly Agree	135	10.3%
If something bad happened to my child after a shot, I would feel like it was my fault
Strongly Not Agree	756	57.7%
Not Agree	156	11.9%
Not Sure	183	14%
Agree	95	7.3%
Strongly Agree	120	9.2%
I worry about how safe shots are
Strongly Not Agree	741	56.6%
Not Agree	204	15.6%
Not Sure	178	13.6%
Agree	73	5.6%
Strongly Agree	114	8.7%
I don’t believe in getting kids shots
Strongly Not Agree	939	71.7%
Not Agree	124	9.5%
Not Sure	99	7.6%
Agree	47	3.6%
Strongly Agree	101	7.7%
I don’t think keeping my child up to date on shots is important
Strongly Not Agree	778	59.4%
Not Agree	166	12.7%
Not Sure	169	12.9%
Agree	83	6.3%
Strongly Agree	114	8.7%
I don’t think the shots work to prevent diseases
Strongly Not Agree	856	65.3%
Not Agree	161	12.3%
Not Sure	135	10.3%
Agree	59	4.5%
Strongly Agree	99	7.6%
My health care provider told me NOT to get my child his/her shots
Strongly Not Agree	892	68.1%
Not Agree	124	9.5%
Not Sure	129	9.8%
Agree	58	4.4%
Strongly Agree	107	8.2%
I don’t think kids' shots are important
Strongly Not Agree	606	46.3%
Not Agree	96	7.3%
Not Sure	112	8.5%
Agree	66	5%
Strongly Agree	430	32.8%

Descriptive statistics of the study variables (N = 1310)

TPB subscales	Mean statistic	SD	Skewness Statistic	Std error	kurtosis Statistic		Std error
Behavioral intention
Do you plan to have or continue to have your child/children immunized?	1.09	0.39	4.47	0.06	18.48	0.13
Have you already obtained vaccination for your children?	1.08	0.36	4.57	0.06	20.24	0.13
Did you complete the required vaccination for your children according to your child age?	1.07	0.32	4.73	0.06		0.13
Subjective norms
People around me expect from me to vaccinate my children	2.01	1.44	1.28	0.06	0.13	0.13
If people around me delay vaccinating their children, I will do the same	2.73	1.68	0.33	0.07	-1.60	0.14
If the people around me vaccinate their children on time, I will do the same	2.28	1.55	0.87	0.06	-0.83	0.15
Perceived behavioral control
Rate your ability to get the vaccines for your children	4.52	0.99	-2.25	0.06	4.40	0.13
How sure will you take your child for vaccination when it is due	4.49	1.03	-2.17	0.06	3.90	0.13
How sure will you take your child for vaccination when he/she is healthy	4.54	1.00	-2.36	0.06	4.80	0.13
Parents decision making
Have you ever delayed having your child get a shot for reasons other than illness or allergy?	2.38	0.89	-0.815	0.06	-1.13	0.13
Have you ever decided not to have your child get a shot for reasons other than illness or allergy?	2.65	0.73	-1.728	0.06	1.13	0.13
How sure are you that following the recommended shot schedule is a good idea for your child? Please answer on a scale of 0 to 10, where 0 is Not at all sure and 10 is Completely sure.	8.52	2.73	-1.85	0.06	2.11	0.13
Children get more shots than are good for them.	4.34	1.00	-1.81	0.06	2.90	0.13
I believe that many of the illnesses that shots prevent are severe.	4.16	1.07	-1.36	0.06	1.25	0.13
It is better for my child to develop immunity by getting sick than to get a shot	4.28	1.06	-1.72	0.68	2.32	0.13
It is better for children to get fewer vaccines at the same time	4.37	0.98	-1.91	0.07	3.34	0.14
How concerned are you that your child might have a serious side effect from a shot?	3.81	1.29	-0.71	0.06	0.71	0.13
How concerned are you that anyone of the childhood shots might not be safe?	3.83	1.27	-0.84	0.07	0.48	0.14
How concerned are you that a shot might not prevent the disease?	4.02	1.18	− 0.0.34	0.06	5.64	0.14
If you had another infant today, would you want him/her to get all the recommended shots?	1.11	0.40	3.75	0.06	13.46	0.13
Overall, how hesitant about childhood shots would you consider yourself to be?	4.25	1.12	-1.56	0.06	1.49	0.13
I trust the information I receive about shots.	4.38	0.98	-1.93	0.06	3.44	0.13
I am able to openly discuss my concerns about shots with my child’s doctor.	4.25	0.98	-1.55	0.06	2.13	0.13
All things considered; how much do you trust your child’s doctor? Please answer on a scale of 0 to 10, where 0 is Do not trust at all and 10 is Completely trust.	8.05	2.81	-1.44	0.06	0.93	0.13
0
Parents attitude
I didn’t know when my child needed to get his/her shots	2.13	1.44	0.88	0.06	-0.69	0.13
I didn’t know where to take my child to get his/her shots	1.79	1.31	1.43	0.06	0.62	0.13
There were no appointments available at the clinic for shots	1.88	1.32	1.28	0.06	0.26	0.13
The shots cost too much	2.02	1.48	1.08	0.06	-0.42	0.13
The clinic/facility wasn’t open at a time I could go	1.78	1.26	1.45	0.06	0.84	0.13
I didn’t have a ride to the clinic	1.80	1.26	1.43	0.06	0.76	0.13
I didn’t have someone to take care of my other children	1.85	1.27	1.33	0.06	0.49	0.13
My child was sick and could not get his/her shots	2.22	1.47	0.81	0.06	-0.81	0.13
The clinic wait was too long	2.06	1.32	0.96	0.06	-0.33	0.13
I couldn’t get time off from work	2.06	1.42	1.00	0.06	-0.47	0.13
Getting my children for shots is too much trouble	1.88	1.26	1.25	0.06	0.32	0.13
I just forgot	1.88	1.30	1.26	0.06	0.27	0.13
I’m scared of the side effects of the shots	2.09	1.36	0.97	0.06	-0.37	0.13
I don’t believe in getting kids shots	1.66	1.23	1.77	0.06	1.81	0.13
I worry about the number of shots my child gets at one time	1.94	1.32	1.19	0.06	0.114	0.13
I worry about what is in the shots	1.88	1.28	1.29	0.06	0.42	0.13
I don’t think keeping my child up to date on shots is important	1.92	1.32	1.20	0.06	0.122	0.13
I don’t think the shots work to prevent diseases	1.77	1.25	1.51	0.06	1.04	0.13
I worry my child might get sick from the SHOT	2.17	1.37	0.85	0.06	-0.58	0.13
My health care provider told me NOT to get my child his/her shots	1.75	1.27	1.54	0.06	1.03	0.13
If something bad happened to my child after a shot, I would feel like it was my fault	1.98	1.35	1.09	0.06	-0.16	0.13
I worry about how safe shots are	1.94	1.30	1.19	0.06	0.17	0.13
I don’t think kids’ shots are important	2.71	1.79	0.30	0.06	-1.71	0.13

Authors’ contributions

F.H. and M.A. designed the study and selected the study measures. F.H. recruited the participants and analyzed the data. M.A. and A.A. provided extensive guidance in the analysis and interpretation of results. All authors contributed to drafting the manuscript, critically reviewed its content, and provided substantive feedback to finalize it prior to submission. The authors have read and approved the final version of the manuscript.

Funding

This research has no funding source.

Data availability

The data supporting this study’s findings are available from the corresponding author upon request. Access to the dataset is restricted to protect participant confidentiality and comply with ethical guidelines approved by the IRB.

Declarations

Ethics approval and consent to participate

The study was conducted according to the Declaration of Helsinki. This study received ethical approval from the Institutional Review Board of King Saud University (KSU-HE-23-565) and the Saudi Ministry of Health (No. 2353). Informed consent was obtained after participants were briefed on the study’s aims, procedures, risks, and benefits. Participation was voluntary, with the option to withdraw at any time. Confidentiality was maintained by coding participant data during analysis and securely storing all information. Permission to record interviews was also obtained, ensuring anonymity throughout the process.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.