Correspondence to Mr David Jone Lagura Herrera; [email protected]
STRENGTHS AND LIMITATIONS OF THIS STUDY
This study used a pilot-tested questionnaire to ensure reliable and appropriate data collection by addressing emerging survey issues from respondents’ feedback.
A priori assumption was used to determine potential associated factors of dyadic COVID-19 vaccination, reducing the omitted-variable bias.
The cross-sectional nature of the data limits causal inference between covariates and COVID-19 vaccination among dyads.
Predominance of mothers in the study may limit the applicability of our results to families where fathers or other caregivers have a greater influence on vaccination decisions.
The inclusion of primarily underserved parent participants, who were more likely to opt-in, limits the generalisability of the findings to the broader target population.
Background
Children tend to have milder COVID-19 symptoms and some may not show any symptoms at all, making it difficult to detect or diagnose the infection.1 Since children maintain close proximity with their peers and their parents, this raises concerns about the possibility of asymptomatic transmission of COVID-19 within and beyond the households.2
A study in 2023 highlighted the role of children in the spread of viral infection within households during the COVID-19 pandemic.3 Findings revealed that 70.4% of nearly 850 000 US household transmissions, including SARS-CoV-2, originated with a child and were heightened when schools were in session.3 4 On another note, several studies reported a risk of developing life-threatening reactions such as paediatric multisystem inflammatory syndrome, an uncommon emerging hyperinflammation disorder temporarily associated with SARS-CoV-2.2 5
Since June 2022, the Centers for Disease Control and Prevention recommends everyone ages 6 months and older to get an updated COVID-19 vaccine to protect against serious illness.6 Ongoing safety monitoring after the Food and Drug Administration approval shows that COVID-19 vaccination continues to be safe for children.7 While adverse reactions are rare, the benefits of COVID-19 vaccination outweigh the known risks of COVID-19 and possible severe complications.8
Despite the proven safety and effectiveness of COVID-19 vaccines across different age groups, vaccination rates remain low for children aged 11 and below.9 10 Only a quarter of children between 6 months to 4 years and less than half of those aged 5–11 years have been vaccinated in 2023.9 These rates are lower in rural areas and among children whose mothers have a high school education or less. In the Philippines, the Caraga Region has walk-in cold storage facilities, which enabled the vaccination of 89.27% of the target population, including children, against COVID-19.11 In 2023, a notable progress has been made In vaccinating children against COVID-19 in different provinces in the region.11 12 However, in the province of Agusan del Norte, only 1 out of 86 towns targeted ~90% attainment for vaccinating 2864 children aged 5–11, out of its 3168 total targets.12 Meanwhile, by this time, the focus had shifted from enforcing strict vaccination requirements to encouraging booster doses, particularly for underserved people.13 14 Vaccination was no longer mandatory, but it was still strongly recommended, especially in high-risk settings like healthcare facilities. Vaccination mandates for children aged 11 and below in the Philippines were also not strictly enforced.13 Instead, the government emphasised voluntary vaccination, encouraging parents to have their children vaccinated, particularly with booster doses if eligible.
Parental hesitancy and choices significantly influence children’s vaccination against COVID-19.15 For instance, over three-quarters of parent–child dyads were found to be concordant in their COVID-19 vaccination status.16 This concordance is linked to parental beliefs, societal norms and public health policies. A population-based study on paediatric vaccination further revealed that familial political views, vaccine hesitancy regarding children, mistrust in doctors and academics, and vaccine misconceptions also collectively explained 82.5% (63.5%–100.0%) of the reasons behind children being unvaccinated.17 Vaccine-willing or vaccinated parents were also far more likely to vaccinate their children immediately compared with vaccine-hesitant parents, with factors like race, ethnicity, education and previous COVID-19 experiences influencing this decision.16 A recent meta-analysis from the UK further identified the age and vaccination status of adults in the same household as significant factors for paediatric vaccination uptake, emphasising the importance of household influences.2
Despite the significant influence parental decisions have on children’s vaccination, there is still limited evidence regarding the extent of this impact. Only a few studies have specifically examined the concordance of COVID-19 vaccination status between parent–child dyads,16 18 and the influence of psychosocial factors around dyadic COVID-19 vaccination acceptance for their children.19 These leave gaps in our understanding of the extent to which social and psychological factors as well as parental vaccination status directly affect their children. Consequently, our current understanding of parent–child dyadic COVID-19 vaccination and the motivations driving parental decisions remains particularly limited, especially among underserved families with young children.2 In this paper, we aimed to explore the concordance between parent–child dyadic vaccination status, determine the association between parental motivations behind vaccination and PD as well as identify associated factors of parents’ decision to vaccinate their children.
Methods
Study design and setting
A cross-sectional study design, using a piloted self-administered questionnaire, was employed to collect data on parents’ sociodemographic characteristics, parent–child dyadic COVID-19 vaccination status and to assess parental psychological distress (PD) and motivations for vaccination. The study was conducted in Butuan City, Caraga Region, the Philippines. Additionally, this study followed the Strengthening the Reporting of Observational Studies in Epidemiology guidelines20 for the reporting of observational studies (see online supplemental appendix 1 for the checklist).
Sample size calculation and sampling design
Cochran’s formula allowed us to calculate an ideal sample size given a desired level of precision, desired confidence level and the estimated proportion of the attribute present in the population (https://www.statisticshowto.com/probability-and-statistics/find-sample-size/). To calculate the minimum sample size needed, we used a formula that factors in the desired precision level (margin of error), the estimated proportion of the population with the attribute in question (p), and q (1–p), with the z-value derived from a Z table. Lacking specific data to estimate the proportions (p1 and p2), we used 0.5 for both to ensure a conservative sample size. Hence, for this study, the estimated sample size at a 5% level of significance was as follows:
.
Finally, to account for non-responses, the total estimated sample size was adjusted by 15%, resulting in a final sample size of 442.
Sampling design
To select participating schools in Butuan City, the Philippines, the study used stratified cluster sampling, stratified by type of community (urban or rural), school size (large, medium and small) and location along a highway or accessible roads. Meanwhile, cluster sampling approach was used to select parents of school children aged 5–11. One to two sections were randomly chosen from each grade level, and all parents in the selected sections were surveyed.
Participants
We included parents and guardians with children aged 11 years and below, currently residing, and attending one of the representative primary schools in Butuan City. The recruitment of parent participants was conducted by engaging with school head and teacher representatives at selected primary schools in Butuan City. These schools were visited, and courtesy calls to school heads were conducted to ensure their support and cooperation.
At the beginning of the survey, the trained data collectors provided a detailed orientation to participants, explaining the purpose of the study, the project’s objectives and the participants’ freedom to choose whether to respond or not to the questions. Informed consents were duly explained and obtained from the participants before answering the survey during the parents-teachers association meetings (figure 1). Participants then completed surveys for 10–15 min, with assistance from trained researchers and social science interns, between 1 March 2023 and 31 March 2023.
Enlarge this image.Figure 1. Schematic diagram of study procedure. MICE, multivariate imputation by chained equations; PTA, parent-teachers association.
Measures
Pilot-testing of survey questionnaire
Before administering the survey, we conducted a pilot test of the questionnaire with 29 parent respondents. This enabled us to identify questions that were likely to receive no responses or were found to be difficult for parents to answer or understand. Based on their feedback, we refined the questionnaire to ensure the questions were clear, concise and directly relevant to the study’s objectives. This preparatory phase aimed to reduce non-response rates by keeping the questionnaire length manageable and ensuring that all questions were clearly communicated and aligned with our research goals. To accommodate the needs of parents, many of whom were not proficient in English, we also translated the questionnaire to Cebuano or Bisaya Dialect. Additionally, data collectors were trained for a day on how to administer the survey and assist the parents in responding to the questionnaire.
Predictors
Data on sociodemographic characteristics were gathered, including the parent’s sex (female or male), age (categorised by age group), civil status (categorised as single, married, separated or widowed), educational attainment (categorised as no college degree, college degree or advanced education), ethnicity (indigenous or non-indigenous) and place of residence (rural, suburban or urban).
The assessment of parental PD was performed using the General Health Questionnaire-12 (GHQ-12), a widely recognised instrument for evaluating mental well-being by measuring deviations from normal, healthy functioning and identifying the presence of new, distressing symptoms.21 22 In this study, scores of 12 or higher indicate PD, while scores below 12 indicate without PD. Recent research further supports the GHQ-12’s applicability in adult populations to assess PD in relation to various stressors, reinforcing its suitability for this study.22–24
Outcome variable
The study’s primary outcome was the COVID-19 vaccination status within parent–child dyads, defined as either ‘vaccinated’ or ‘unvaccinated’ for parents and ‘parents with vaccinated children’. Vaccination status was determined based on self-reports and verified through official vaccination cards issued by the Department of Health or local government units. This ensured that the self-reported data on vaccination status were accurate and reliable, as participants were able to present these cards as proof of receiving at least one COVID-19 vaccine dose.
Parent–child dyadic vaccination concordance was evaluated based on whether both parent and child share the same current COVID-19 vaccination status—either both vaccinated or both unvaccinated. Discordance was identified if one was vaccinated and the other was not. To assess this, we queried parents about their own and their children’s vaccination status, specifically asking if they and their children had received at least one dose of the COVID-19 vaccine. Additionally, we explored parental motivations for vaccination, both for themselves and their children. Participants responded to semistructured questions about their vaccination reasons, including whether vaccination was compelled by workplace, school or travel requirements or motivated by a belief in the vaccine’s benefits and necessity for themselves and their children.
Statistical analysis
All statistical analyses were conducted by using the R software (R Foundation for Statistical Computing, V.4.0.3). Participants’ sociodemographic characteristics, the presence of PD and parent–child dyadic vaccination status against COVID-19 were summarised using frequencies and proportions. The χ2 test was employed to investigate differences in parent–child dyadic vaccination status, vaccination motivation and PD.
To determine the associated factors of dyadic vaccination status, including sociodemographic and psychosocial factors, we used a mixed-effects logistic regression model, incorporating locality and school sites as a random effect for the sensitivity analysis. Likelihood ratio test was used to test the significance of the multiple logistic regression model. This approach enabled us to account for unobserved, individual-specific factors presumed to be constant over time. We further conducted multiple imputation using the multivariate imputation by chained equations package in R, for handling data missing at random. We executed seven imputations (m=7) with a maximum of 30 iterations (maxit=30) for each imputation cycle. A seed value of 100 was established to guarantee reproducibility and consistency throughout the imputation process.
Patient and public involvement
The public contributed to this research through the involvement of Bachelor of Arts in Sociology interns, who assisted with data collection and data encoding under the supervision of Dr. Jayrold Arcede and Ms. Rachel Arcede. Mr. Juanito Bas Jr. also co-supervised data collection, coordinating with school heads to facilitate the process within their respective schools. Additionally, pilot students were involved in refining the survey questionnaire by providing feedback on the accessibility of the questions and the efficiency of self-administered responses.
Results
Study participants’ characteristics
A face-to-face survey was conducted in selected elementary schools in Butuan City, the Philippines, from 1 March 2023 to 31 March 2023. Most participants were female (n=498, 84.0%) and were predominantly aged 40 years and below (n=336, 55.6%). About 44.7% (n=265) identified as indigenous people and 43.7% (n=259) lived in rural areas. The majority were also married (n=433, 73.0%), lacked a college degree (n=339, 57.2%) and reported very low to no income (n=531, 77.5%) (table 1).
Table 1Characteristics of parent participants categorised by psychological distress status
| Total (N=593) (n, %) | Without PD (N=241) (n, %) | With PD (N=352) (n, %) | X2 | df | P value | |
| Sex | 1.06 | 1 | 0.303 | |||
| Male | 95 (16.0) | 43 (17.8) | 52 (14.8) | |||
| Female | 498 (84.0) | 198 (82.2) | 300 (85.2) | |||
| Age group | 0.75 | 2 | 0.668 | |||
| <31 years | 117 (20.7) | 50 (20.7) | 67 (19.7) | |||
| 31–40 years | 219 (34.9) | 84 (34.9) | 135 (36.9) | |||
| >40 years | 234 (40.2) | 97 (40.2) | 137 (39.5) | |||
| Missing | 23 (4.1) | 23 (4.1) | 10 (3.9) | |||
| Ethnicity | 23.3 | 1 | <0.001* | |||
| Indigenous | 265 (44.7) | 78 (32.4) | 187 (53.1) | |||
| Non-indigenous | 311 (52.4) | 153 (63.5) | 158 (44.9) | |||
| Missing | 17 (2.9) | 10 (4.1) | 7 (2.0) | |||
| Locality | 9.37 | 2 | 0.009** | |||
| Rural | 259 (43.7) | 88 (36.5) | 171 (48.6) | |||
| Suburban | 171 (28.8) | 83 (34.4) | 88 (25.0) | |||
| Urban | 156 (26.3) | 66 (27.4) | 90 (25.6) | |||
| Missing | 7 (1.2) | 4 (1.7) | 3 (0.9) | |||
| Civil status | 3.35 | 3 | 0.341 | |||
| Single | 102 (17.2) | 49 (20.3) | 53 (15.1) | |||
| Separated | 18 (3.0) | 6 (2.5) | 12 (3.4) | |||
| Married | 433 (73.0) | 171 (71.0) | 262 (74.4) | |||
| Widowed | 39 (6.6) | 14 (5.8) | 25 (7.1) | |||
| Missing | 1 (0.2) | 1 (0.4) | 0 (0.0) | |||
| Educational attainment | 3.29 | 2 | 0.193 | |||
| No college degree | 339 (57.2) | 136 (56.4) | 203 (57.7) | |||
| College | 181 (30.5) | 68 (28.2) | 113 (32.1) | |||
| Master or PhD | 70 (11.8) | 35 (14.5) | 35 (9.9) | |||
| Missing | 3 (0.5) | 2 (0.8) | 1 (0.3) | |||
| Monthly income | 10.9 | 3 | 0.012* | |||
| No income | 206 (34.7) | 100 (40.5) | 106 (30.1) | |||
| Poor | 254 (42.8) | 85 (48.8) | 169 (48.0) | |||
| Low income | 71 (12.0) | 29 (10.9) | 42 (11.9) | |||
| Middle income | 49 (8.3) | 21 (7.7) | 28 (8.0) | |||
| Missing | 13 (2.2) | 6 (2.4) | 7 (2.0) |
Statistically Significant results are shown in bold. PD outcomes were measured using 12-item General Health Questionnaire (GHQ) with scales ranging from 0 to 3. Scores below 12 indicated no psychological distress and 12 above with psychological distress. The 12-item GHQ has a Cronbach’s alpha of 0.86, which indicates a good reliability score.
*P-value < 0.05; **P-value < 0.01; ***P-value < 0.001.
PD, psychological distress.
Parent–child dyadic vaccination status
Parental PD and vaccination status and motives
Findings show that ethnicity (p<0.001), locality (p=0.009) and monthly income (p=0.012) are significantly associated with PD among parent participants. Specifically, being Indigenous, living in rural areas and having lower income levels are significantly associated with higher rates of PD (table 1).
Among the 474 parents who received at least one dose of the COVID-19 vaccine, the majority (79.9%) recognised the vaccine’s benefits and necessity. However, the vaccination status of both parents and children was not significantly associated with PD (p=0.187 and p=0.142, respectively). No significant association was also found between parental motivation for vaccinating themselves or their children (whether due to official mandates or perceived benefits of the vaccines) and the presence of PD (p=0.36 and p=0.87, respectively) (table 2).
Table 2Parent–child vaccination status and reasons for vaccinating
| Total (n, %) | Without PD (n, %) | With PD (n, %) | X2 | P value | |
| N=593 | n=241 | n=352 | |||
| Vaccination status of parents | 1.195 | 0.274 | |||
| Vaccinated | 478 (80.6) | 198 (82.2) | 276 (78.4) | ||
| Unvaccinated | 115 (19.4) | 41 (17.0) | 74 (21.0) | ||
| Missing | 0 | 2 (0.8) | 2 (0.6) | ||
| Vaccination status of children | 2.16 | .142 | |||
| Vaccinated | 215 (36.2) | 97 (40.2) | 118 (33.5) | ||
| Unvaccinated | 365 (61.5) | 142 (58.9) | 223 (63.4) | ||
| Missing | 13 (2.2) | 2 (0.8) | 11 (3.1) | ||
| Parents’ motivation for vaccinating | N=478 | n=198 | n=276 | ||
| Pressured to get vaccinated | 96 (20.1) | 35 (19.5) | 63 (22.7) | 0.827 | 0.363 |
| Perceived COVID-19 vaccine as beneficial for them | 376 (78.7) | 128 (59.5) | 180 (79.1) | ||
| Missing | 6 (4.6) | 11 (5.4) | 11 (4.0) | ||
| Parents’ motivation for vaccinating their children | N=215 | n=97 | n=118 | ||
| Pressured to get the child vaccinated | 27 (12.8) | 8 (8.0) | 12 (10.2) | 0.028 | 0.866 |
| Perceived COVID-19 vaccine as beneficial for the child | 184 (80.7) | 81 (83.9) | 100 (84.7) | ||
| Missing | 0 | 8 (8.2) | 6 (5.1) |
Statistically Significant results are shown in bold. Data are presented in n (%). A p value of χ2 was used with df=1.
*P-value < 0.05; **P-value < 0.01; ***P-value < 0.001.
PD, psychological distress.
Concordance
Of the participating parents, 80.6% (478 individuals) have received at least one COVID-19 vaccine dose, yet only 35.6% (211) have vaccinated their children (table 3). Varied levels of concordance and discordance were also observed. Notably, the majority of the dyads demonstrated vaccination concordance (vaccinated dyads: n=197, 35.2% and unvaccinated dyads: n=94, 16.8%). However, a high discordance was observed, with 45.7% of cases (256 dyads), with vaccinated parents having unvaccinated children. Discordance was seen in 2.3% (13 dyads) with unvaccinated parents and vaccinated children, while 16.8% (94 dyads) showed concordance among unvaccinated parents and children (table 3). Furthermore, we stratified parents by age group and parental vaccination status to explore the children’s vaccination status in more detail (figure 2). Findings show that the highest proportion of parents who opted not to vaccinate their children were unvaccinated, younger parents, specifically aged between 25 and 40 years.
Enlarge this image.Figure 2. COVID-19 vaccination status of parent-child dyads by parental age groups.
Parent–child COVID-19 vaccination concordance (n=560)
| Child’s vaccination status n (%) | |||
| Vaccinated 210 (37.5) | Unvaccinated 350 (62.5) | ||
| Parent’s vaccination status | Vaccinated parents 453 (80.9) | 197 (35.2) | 256 (45.7) |
| Unvaccinated parents 107 (19.1) | 13 (2.3) | 94 (16.8) | |
Observations included in this analysis were limited to cases with both parent and child vaccination status available. The overall missing data for vaccination concordance are 5.56% of the 593 cases.
Associated factors of child vaccination against COVID-19
Findings from the adjusted regression model identify parental education attainment and vaccination status as crucial determinants of children’s vaccination status (table 4). While non-indigenous participants are 32% less likely to have unvaccinated children compared with indigenous participants, our findings did not establish a significant association between ethnicity and vaccination status after controlling for age, ethnicity, locality, educational attainment and parents’ vaccination status (adj OR 0.68, 95% CI 0.45 to 1).
Table 4Multiple logistic regression model for parent–child dyads vaccination status
| Variables | Category | VC (n)* | UnVC* | P value | Crude OR | 95% CI lower | 95% CI upper | Adj OR* | 95%CI lower | 95%CI upper |
| Sex | Male | 30 | 61 | ref | 1 | ref | ref | – | – | – |
| Female | 196 | 306 | 0.27 | 0.76 | 0.47 | 1.22 | – | – | – | |
| IP | Indigenous | 89 | 178 | ref | 1 | ref | ref | 1 | ref | ref |
| Non-indigenous | 137 | 189 | 0.03* | 0.68 | 0.49 | 0.96 | 0.68 | 0.45 | 1.00 | |
| Locality | Rural | 104 | 159 | ref | 1 | ref | ref | 1 | ref | ref |
| Suburban | 56 | 115 | 0.15 | 1.34 | 0.89 | 2.01 | 1.73 | 1.10 | 2.75 | |
| Urban | 66 | 93 | 0.68 | 0.92 | 0.61 | 1.37 | 1.21 | 0.77 | 1.91 | |
| Civil status | Single | 38 | 62 | ref | 1 | ref | ref | 1 | ref | Ref |
| Separated | 9 | 9 | 0.34 | 0.61 | 0.22 | 1.70 | – | – | – | |
| Married | 162 | 274 | 0.87 | 1.03 | 0.65 | 1.61 | – | – | – | |
| Widowed | 17 | 22 | 0.54 | 0.79 | 0.37 | 1.69 | – | – | – | |
| Family role | Parent | 195 | 314 | ref | 1 | ref | ref | 1 | ref | ref |
| Guardian | 31 | 53 | 0.80 | 1.06 | 0.66 | 1.72 | – | – | – | |
| Educational attainment | No college degree | 107 | 218 | ref | ref | ref | ref | 1 | ref | ref |
| College | 74 | 113 | 0.13 | 0.74 | 0.51 | 1.08 | 0.76 | 0.51 | 1.13 | |
| Master or PhD | 45 | 36 | <0.01** | 0.39 | 0.23 | 0.64 | 0.52 | 0.30 | 0.87 | |
| Parental vaccination status | Vaccinated | 213 | 267 | ref | ref | ref | ref | Ref | ref | ref |
| Unvaccinated | 13 | 100 | <0.01** | 6.13 | 3.46 | 11.74 | 6.19 | 3.14 | 12.02 | |
| PD | Yes | 127 | 231 | 0.218 | 1.32 | 0.94 | 1.85 | 1.10 | 0.76 | 1.58 |
| No | 99 | 136 | ref | ref | ref | ref | ref | ref | ref | |
| Variables | β | SE | P value | Crude OR | 95% CI lower | 95% CI upper | Adj OR* | 95% CI lower | 95% CI upper | |
| Age | −0.015 | 0.007 | 0.03* | 0.98 | 0.97 | 0.99 | 0.97 | 0.96 | 0.99 | |
Statistically Significant results are shown in bold. The count data differ from the original (from complete case analysis) because we applied multiple imputations prior to conducting our primary analysis. Adj OR, for vaccination status of children=adjusted for age, IP, locality, educational attainment and parental vaccination status.
*P-value < 0.05; **P-value < 0.01; ***P-value < 0.001.
IP, indigenous people; PD, psychological distress; UnVC, parents with unvaccinated child(ren); VC, parent with vaccinated child(ren).
Parents with advanced degrees are 48% less likely to have unvaccinated children than those with lower levels of education, maintaining significance after adjustment for various factors (adj OR 0.52, 95% CI 0.30 to 0.87). Unvaccinated parents are significantly more likely to have unvaccinated children, with a sixfold increase in odds compared with vaccinated parents (adj OR 6.1, translating to a 510% increase, 95% CI 3.14 to 12.02). Additionally, with each additional year of parental age, the likelihood of children being vaccinated decreases by about 3% (adj OR 0.97, indicating a 3% decrease per year, 95% CI 0.96 to 0.99), though this relationship did not achieve statistical significance across all examined variables. The model shows a modest fit, explaining about 8.85% of the variance (R²=0.0885), with a significant overall effect (χ²=73.4, df=12, p<0.001), indicating that the model is statistically significant.
Discussion
Understanding the dynamics between parental decisions to vaccinate themselves and their children remains complex. This study provides substantial insights into the concordance of parent–child dyadic COVID-19 vaccination status, the motivations behind their decisions and its relation to parental PD. We further identified factors influencing children’s vaccination status to deepen the understanding of the underlying psychological, social and contextual dynamics. Our findings show that most parent–child pairs (dyads) were concordant, with both parents and their children either vaccinated or unvaccinated. However, when we focus solely on vaccinated parents only, our findings show that the majority remains to have unvaccinated children despite being vaccinated themselves. Parents, predominantly mothers, with no college degrees are also more likely to have unvaccinated children compared with those with advanced degrees. Additionally, unvaccinated parents were six times more likely to have unvaccinated children compared with their vaccinated counterparts.
A meta-analysis found that children in unvaccinated households were less likely to be vaccinated against COVID-19.2 Meanwhile, the high level of discordance observed in our study may be explained by factors similar to those identified in a study from Ireland, where parents often believed COVID-19 vaccines were unsafe and held negative views about the scientific community, contributing to their reluctance to vaccinate their children.25 These vaccine-hesitant parents were also more likely to be younger, less educated, poorer and to distrust scientists and healthcare professionals,16 25 which corroborated closely with the present study. Other studies also demonstrated the significant influence of education on COVID-19 vaccination acceptance among children, specifically parents with tertiary or higher education showing less vaccine hesitancy compared with parents who have lower education.26–29 Consistent with other studies, the main reasons for refusing to vaccinate children were concerns about side effects, the newness of the vaccines and a lack of trust in the government and scientists.29
Interestingly, the impact of mother’s education on vaccination acceptance is not unique to COVID-19. For example, a study on HPV vaccination found that mothers with higher levels of education were more likely to vaccinate their daughters aged 9–17.30 Additionally, a systematic review of 108 studies identifies several key barriers to childhood vaccination, including lower education levels among mothers, financial instability, low confidence in new vaccines and the influence of unmonitored social media platforms.31 These barriers are critical in understanding why some parents remain hesitant to vaccinate their children, as they are closely tied to socioeconomic and informational disadvantages.
Although our findings did not show a significant association between parental PD and their motivation to vaccinate—whether due to government mandates or perceived benefits of COVID-19 vaccines, several studies reported that policies restricting access to work, education and social activities based on vaccination status may impinge on human rights and exacerbate stigma, social polarisation and adverse effects on parents’ mental health.32–34 This may also contribute to increased vaccine hesitancy, as evidenced by parents experiencing PD exhibiting higher levels of vaccine hesitancy for themselves, their spouses and their children.35 Furthermore, while our analysis did not reveal a significant direct association between parental PD and the vaccination status of their children, it is essential to consider the potential indirect effects of PD on parental vaccination decisions. Specifically, our findings indicate that ethnicity, locality and monthly income are significantly associated with parental PD, with higher levels of distress prevalent among those who are indigenous, reside in rural areas and have lower income levels. Studies have shown that PD, including cognitive attitudes and perceived behavioural control, as well as parental anxiety, is a significant predictor of vaccine hesitancy and paediatric vaccine refusal, with higher levels of distress correlating with reduced confidence in vaccines.19 36
Strength and weaknesses of the study
This study is the first in the Philippines to explore parent–child dyads in COVID-19 vaccination, focusing on parents with children 11 years and below. The study provides new insights into parental motivations for vaccinating themselves and their children and its association with parental PD, and the factors influencing their decision-making regarding COVID-19 vaccination for their children. The strengths of our study also lie in the methodological approaches employed, including the use of pilot-tested questionnaires and a robust statistical approach. This includes the use of multiple imputation to address missing values and sensitivity analysis to assess and mitigate the impact of non-responses, ensuring the reliability of our findings. Additionally, our study involves diverse parents, both from rural, suburban and urban areas, and from different educational levels, socioeconomic and ethnic backgrounds. Finally, the use of individual face-to-face surveys by trained interns and researchers ensured that responses were clear and questions were well understood by parents, especially those who have low literacy skills.
Our study has several limitations that warrant cautious interpretation of the findings. Most surveyed parents were predominantly females with low to moderate income and no college degrees, limiting the generalisability of our findings to the general population. Specifically, the predominance of mothers among the participants may introduce bias, as mothers are typically more involved in their children’s healthcare decisions, including vaccination. This gender imbalance could potentially limit the applicability of our results to families where fathers or other caregivers have a greater influence on vaccination decisions. The use of convenience sampling and the potential influence of social pressures and expectations in parents’ responses might also be subject to potential selection and social desirability biases, respectively. Furthermore, non-respondents may differ systematically from respondents in ways that could affect the study’s results, such as having PD, lower socioeconomic status, or educational attainment, or being unvaccinated. To mitigate this potential bias, participants were oriented about the study purpose and confidentiality of the survey responses. We also conducted a sensitivity analysis, exploring scenarios where non-response might be related to these covariates.
Implications for practice
Our findings reveal higher rates of PD found among indigenous parents, those residing in rural areas and those with lower incomes. Additionally, our findings indicate a significant association between parental education and vaccination choices with children’s vaccination rates. Therefore, efforts to increase childhood vaccination should prioritise engaging underserved parents through educational initiatives that highlight the benefits and necessity of vaccines. This approach may be more effective than relying solely on mandates, which could potentially lead to resistance and unintended negative consequences. Additionally, targeted interventions should be developed to address the specific needs of parents based on ethnicity, locality and income level, as these factors are significantly associated with parental PD. Finally, given that mothers are often primary caregivers and play a central role in managing their children’s health, interventions must be tailored to their specific concerns, such as fears about vaccine safety, the influence of misinformation and the perceived necessity of vaccines. However, to foster a holistic approach, it is equally important to engage fathers, who may have different perspectives or influence the decision-making process in ways that are less visible but equally significant.
Implications for future research
Future research should explore the long-term impact of parental PD on vaccination decisions through longitudinal studies. Such studies could provide valuable insights into how changes in PD over time influence dyadic vaccination, particularly parental decisions to vaccinate both themselves and their children. Further research is also needed to understand the specific fears and barriers that contribute to the reluctance of unvaccinated parents to vaccinate their children against COVID-19. Identifying these factors will be essential in developing more effective communication strategies to address vaccine hesitancy. Finally, while our study predominantly involved mothers, there is still a need to understand how fathers perceive vaccination and how their involvement might influence childhood vaccination uptake. Thus, future research should explore the psychological factors, such as risk perception, trust in healthcare providers and susceptibility to misinformation, that drive vaccine hesitancy among both parents.
We would like to thank the following Bachelor of Arts in Sociology interns for their invaluable assistance in the data collection and encoding: Ariel Dalanon, Charlene Jean Maxilom, Jessa Mae Jomboy, Ken Cyril Achas, Krisly Jane Arcolar, Louise Marie Forinas, Niña Marie O. Aldover, Mark Gil Baring, Mary Joy Eramis Pomar, Niña Marie Aldover, Norjielyn Morano, Elaiza Pino, Jecile Mae Collantes Omayana, Mia Jane Quirequire, Rejel Jamili Arias and Abel Mahinay, Norjielyn Moran and to Mr. Juanito Bas Jr. for co-supervising the data collection by initiating and maintaining close collaboration with different school heads. We also extend our appreciation to the heads of the participating schools in Butuan City for their assistance in coordinating with teachers during data collection. Lastly, our sincere gratitude to Dr. Jess H. Jumawan and Dr. Lillia Boyles for sharing constructive feedback during the write-up.
Data availability statement
Data are available on reasonable request. The data that support the findings of this study are available from the corresponding author on reasonable request. The data are not publicly available due to privacy or ethical restrictions.
Ethics statements
Patient consent for publication
Consent obtained from parent(s)/guardian(s).
Ethics approval
This study involves human participants and was approved by the Caraga Health Research and Development Consortium-Research Ethics Committee (reference code: CHRDC-REC-2022-008). Participants gave informed consent to participate in the study before taking part.
Contributors DJLH and DJH contributed to the conceptualisation and design of the study, assisted in questionnaire development and pilot testing, helped in data collection, encoding and validation and wrote the full manuscript. KMA contributed to the conceptualisation of the study, led the pilot testing of the questionnaire, assisted in data validation and critically reviewed the manuscript. MH contributed to the conceptualisation and design of the study, led participant recruitment and partnerships, supervised data collection and courtesy calls and critically reviewed the manuscript. ALAM contributed to the conceptualisation and design of the study, reviewed the questionnaire and consent forms, prepared the orientation script, assisted in data collection and provided critical feedback on the manuscript. RES, SB and DA assisted in the pilot-testing of the questionnaire, conducted the data collection and validation and provided critical feedback on the manuscript. RPT conducted the data collection and validation and provided critical feedback on the manuscript. NMB contributed to the conceptualisation and design of the study, led questionnaire development and data cleaning, performed data analysis, supervised the study and critically reviewed the manuscript. DJLH is responsible for the overall content as guarantor. He accepts full responsibility for the conduct of the study, has access to the data and controls the decision to publish. At the finalisation of the manuscript, ChatGPT and Grammarly tools were used solely for correcting grammatical/spelling errors and improve accessibility of the sentence structures, especially for lay or non-expert readers in the field of Epidemiology. This was made to supplement the initial proof-reading of the all authors in this study.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
1 European center for disease prevention and control. COVID-19 in Children and the Role of School Settings in COVID-19. 2020.
2 Aldridge SJ, Agrawal U, Murphy S, et al. Uptake of COVID-19 vaccinations amongst 3,433,483 children and young people: meta-analysis of UK prospective cohorts. Nat Commun 2024; 15: 2363. doi:10.1038/s41467-024-46451-0
3 Shope TR, Chedid K, Hashikawa AN, et al. Incidence and Transmission of SARS-CoV-2 in US Child Care Centers After COVID-19 Vaccines. JAMA Netw Open 2023; 6: e2339355. doi:10.1001/jamanetworkopen.2023.39355
4 Beusekom Mv. More than 70% of us household covid spread started with a child, study suggests. University of Minnesota; 2023. Available: https://www.cidrap.umn.edu/covid-19/more-70-us-household-covid-spread-started-child-study-suggests
5 Grimaud M, Starck J, Levy M, et al. Acute myocarditis and multisystem inflammatory emerging disease following SARS-CoV-2 infection in critically ill children. Ann Intensive Care 2020; 10: 69. doi:10.1186/s13613-020-00690-8
6 Center for Disease Control and Prevention. Updated covid-19 vaccine recommendations are now available. U.S. Department of Health & Human Services; 2023. Available: https://www.cdc.gov/ncird/whats-new/covid-vaccine-recommendations-9-12-2023.html
7 Centers for Disease Control and Prevention. Vaccines & immunizations: 6 things to know. U.S. Department of Health & Human Services; 2023. Available: https://www.cdc.gov/vaccines/covid-19/planning/children/6-things-to-know.html
8 Centers for Disease Control and Prevention. Safety of covid-19 vaccines. U.S. Department of Health & Human Services; 2023. Available: https://www.cdc.gov/coronavirus/2019-ncov/vaccines/safety/safety-of-vaccines.html
9 Centers for Disease Control and Prevention. Child. COVIDVaxView; 2023. Available: https://www.cdc.gov/vaccines/imz-managers/coverage/covidvaxview/interactive/children.html
10 Centers for Disease Control and Prevention. Vaccination trends. U.S. Department of Health & Human Services; 2024. Available: https://www.cdc.gov/respiratory-viruses/data-research/dashboard/vaccination-trends-children.html
11 UNICEF Philippines. Strengthening the immunization cold chain in caraga region: old chain facilities provided by unicef and the government of australia help increase routine and covid-19 vaccination coverage. UNICEF; 2022. Available: https://www.unicef.org/philippines/stories/strengthening-immunization-cold-chain-caraga-region
12 Lopez A. Agusan sur town hits 100% covid vax rate among 5-11 kids. Philippine News Agency; 2023. Available: https://www.pna.gov.ph/articles/1194899
13 World Health Organization (the Philipppines). Philippines Coronavirus Disease 2019 (COVID-19) Situation Report #123, 2023. Available: https://www.who.int/philippines/internal-publications-detail/covid-19-in-the-philippines-situation-report-123
14 World Health Organization Philippines. Philippines disease 2019 (covid-19) situation report #124. 2023. Available: https://www.who.int/philippines/internal-publications-detail/covid-19-in-the-philippines-situation-report-124
15 Deng J-S, Chen J-Y, Lin X-Q, et al. Parental hesitancy against COVID-19 vaccination for children and associated factors in Taiwan. BMC Public Health 2023; 23: 571. doi:10.1186/s12889-023-15158-0
16 Tu P, Smith D, Parker T, et al. Parent-Child Vaccination Concordance and Its Relationship to Child Age, Parent Age and Education, and Perceived Social Norms. Vaccines (Basel) 2023; 11: 1210. doi:10.3390/vaccines11071210
17 Ni Y, Flores FP, Lun P, et al. Understanding paediatric COVID-19 vaccination during the pandemic: a prospective cohort and a population-based registry study. Lancet Reg Health West Pac 2024; 43: 100976. doi:10.1016/j.lanwpc.2023.100976
18 Robison SG, Osborn AW. The Concordance of Parent and Child Immunization. Pediatrics 2017; 139: e20162883. doi:10.1542/peds.2016-2883
19 Capasso M, Bianchi M, Caso D. Psychosocial Factors Influencing Parents’ Acceptance of COVID-19 Vaccination for Their Children: An Italian Cross-Sectional Study. Vaccines (Basel) 2024; 12: 317. doi:10.3390/vaccines12030317
20 von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. Ann Intern Med 2007; 147: 573. doi:10.7326/0003-4819-147-8-200710160-00010
21 Goldberg D, Williams P. A user’s guide to the general health questionnaire. NFER-Nelson; 1998.
22 Baksheev GN, Robinson J, Cosgrave EM, et al. Validity of the 12-item General Health Questionnaire (GHQ-12) in detecting depressive and anxiety disorders among high school students. Psychiatry Res 2011; 187: 291–6. doi:10.1016/j.psychres.2010.10.010
23 Virtanen M, Kivimäki M, Elovainio M, et al. Selection from fixed term to permanent employment: prospective study on health, job satisfaction, and behavioural risks. J Epidemiol Community Health 2002; 56: 693–9. doi:10.1136/jech.56.9.693
24 Hystad SW, Johnsen BH. The Dimensionality of the 12-Item General Health Questionnaire (GHQ-12): Comparisons of Factor Structures and Invariance Across Samples and Time. Front Psychol 2020; 11: 1300. doi:10.3389/fpsyg.2020.01300
25 Ceannt R, Vallieres F, Burns H, et al. Covid-19 vaccine hesitancy and resistance amongst parents of children under 18 years of age in Ireland. Vaccine (Auckl) 2022; 40: 6196–200. doi:10.1016/j.vaccine.2022.08.073
26 Zychlinsky Scharff A, Paulsen M, Schaefer P, et al. Students’ age and parental level of education influence COVID-19 vaccination hesitancy. Eur J Pediatr 2022; 181: 1757–62. doi:10.1007/s00431-021-04343-1
27 Lupu D, Tiganasu R. Does education influence COVID-19 vaccination? A global view. Heliyon 2024; 10: e24709. doi:10.1016/j.heliyon.2024.e24709
28 Alharbi HS. Review: factors influencing parents’ decisions to vaccinate children against covid-19. 2023. Available: https://doi.org/10.1016/j.vaccine.2023.09.020
29 Sehgal NKR, Rader B, Gertz A, et al. Parental compliance and reasons for COVID-19 Vaccination among American children. PLOS Digit Health 2023; 2: e0000147. doi:10.1371/journal.pdig.0000147
30 Lin Z, Chen S, Su L, et al. Exploring mother-daughter communication and social media influence on HPV vaccine refusal for daughters aged 9-17 years in a cross-sectional survey of 11,728 mothers in China. Hum Vaccin Immunother 2024; 20: 2333111. doi:10.1080/21645515.2024.2333111
31 Khan YH, Rasheed M, Mallhi TH, et al. Barriers and facilitators of childhood COVID-19 vaccination among parents: A systematic review. Front Pediatr 2022; 10: 950406. doi:10.3389/fped.2022.950406
32 Bardosh K, de Figueiredo A, Gur-Arie R, et al. The unintended consequences of COVID-19 vaccine policy: why mandates, passports and restrictions may cause more harm than good. BMJ Glob Health 2022; 7: e008684. doi:10.1136/bmjgh-2022-008684
33 Dyer O. Covid-19: Ottawa declares emergency as truckers’ protest continues. BMJ 2022; 376: 352. doi:10.1136/bmj.o352
34 Juen C-M, Jankowski M, Huber RA, et al. Who wants COVID-19 vaccination to be compulsory? The impact of party cues, left-right ideology, and populism. Politics (Syd) 2023; 43: 330–50. doi:10.1177/02633957211061999
35 Xu Y, Zhang R, Zhou Z, et al. Parental psychological distress and attitudes towards COVID-19 vaccination: A cross-sectional survey in Shenzhen, China. J Affect Disord 2021; 292: 552–8. doi:10.1016/j.jad.2021.06.003
36 Rodriguez VJ, Kozlova S, LaBarrie DL, et al. Parental anxiety and pediatric vaccine refusal in a US national sample of parents. Vaccine (Auckl) 2023; 41: 7072–5. doi:10.1016/j.vaccine.2023.10.015
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Details
; Herrera, Deborah Jael 1
; Anore, Krisha Marie 1
; Herrera, Miraluna 2
; Masing, Anna Lyn A 3
; Sanchez, Ruth E 3
; Bas, Sherlyn 4
; Amora, Donnacham 5
; Tabudlong, Renante Pandawatnon 6
; Berhe, Neamin M 7
1 Biology Department, College of Mathematics and Natural Sciences, Caraga State University, Butuan City, Philippines
2 Mathematics Department, College of Mathematics and Natural Sciences, Caraga State University, Butuan, Agusan del Norte, Philippines
3 Psychology Department, College of Humanities and Social Sciences, Caraga State University, Butuan City, Agusan del Norte, Philippines
4 College of Mathematics and Natural Sciences, Caraga State University, Butuan City, Philippines
5 College of Engineering and Geosciences, Caraga State University, Butuan City, Agusan del Norte, Philippines
6 Office of Curriculum and Instruction Development, Caraga State University, Butuan, Caraga, Philippines
7 Department of Public Health, ABH Campus, Jimma University, Jimma, Ethiopia