Walaya Tupanich; Sasawan Attaworakun; Suteekarn Chaiyalap; Nattanan Wattanawikan

doi:10.4040/jkan.25147

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Effects of a health literacy program on COVID-19 awareness and preventive behaviors among older adults in Bangkok, Thailand: a quasi-experimental study: Walaya Tupanich¹, Sasawan Attaworakun¹, Suteekarn Chaiyalap², Nattanan Wattanawikan¹; DOI: https://doi.org/10.4040/jkan.25147
Published online: July 28, 2026

¹Kuakarun Faculty of Nursing, Navamindradhiraj University, Bangkok, Thailand

²Shinawatra University, Pathum Thani, Thailand

Corresponding author: Sasawan Attaworakun Kuakarun Faculty of Nursing, Navamindradhiraj University, Bangkok, Thailand E-mail: Sasawan@nmu.ac.th

• Received: October 30, 2025 • Revised: January 26, 2026 • Accepted: May 12, 2026

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License (http://creativecommons.org/licenses/by-nd/4.0) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

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Abstract
Introduction
Methods
Results
Discussion
Conclusion
Article Information
References

Abstract

Purpose
This study examined the effectiveness of a health literacy (HL) enhancement program in improving awareness of and preventive behaviors related to coronavirus disease 2019 (COVID-19) among older adults in an urban community in Bangkok, Thailand.
Methods
This quasi-experimental study included 76 older adults in Dusit District, Bangkok. Eight participants were lost to follow-up; however, all 76 participants (38 per group) were included in the primary analysis using all available observations. The intervention was based on Pengjuntr’s V-shape HL model, which includes six domains: access, understanding, interactive communication, decision-making, behavior change, and advocacy. The program was delivered through group sessions, LINE-based communication, community activities, and home visits. Data were collected at pre-test (baseline), post-test (4 weeks), and follow-up (12 weeks) using questionnaires. Outcomes were analyzed using linear mixed-effects models. This study was retrospectively registered with the Thai Clinical Trials Registry (TCTR20260502013).
Results
At post-test, the experimental group had significantly higher COVID-19 awareness and preventive behavior scores than the control group (p<.001). Within-group analysis showed significant improvements in both COVID-19 awareness and preventive behavior at post-test and follow-up. Significant between-group differences were also observed at follow-up (p<.001), with higher scores in the experimental group.
Conclusion
The intervention group receiving the HL enhancement program showed significant improvements in both COVID-19 awareness and preventive behaviors, which were sustained through follow-up. These findings support the use of nurse-led, community-based HL interventions with behavioral reinforcement to promote COVID-19 prevention among urban older adults.
Key words: Awareness; Behavior; COVID-19; Health literacy

Introduction

The outbreak of coronavirus disease 2019 (COVID-19) has had profound global health, economic, and social effects, with urban populations particularly vulnerable due to high density and mobility [1]. In Thailand, Bangkok—the nation’s economic and transportation hub—recorded some of the highest daily infection rates, averaging 3,167 new cases per day in April 2022 [2]. These circumstances disproportionately affected older adults, who were at elevated risk due to age, underlying conditions, and crowded living environments.

Globally, older adults bore the heaviest burden of the pandemic, accounting for more than 80% of COVID-19–related deaths among those aged ≥60 years in 2020–2021 [3]. People aged ≥65 years were consistently shown to have higher risk of severe illness, hospitalization, and mortality than younger adults [4]. In Thailand, these vulnerabilities were similarly evident. A 2020 UNFPA (United Nations Population Fund) survey involving 1,230 older adults reported substantial health, social, and economic disruptions during the pandemic [5]. Moreover, excess mortality analyses showed that between 2020 and 2022, Thailand recorded approximately 76,756 excess deaths, the majority among people aged ≥65 years [6]. These data underscore an urgent need for interventions tailored to older adults in urban areas.

COVID-19 awareness and preventive behaviors are critical for older adults in particular as timely recognition of infection risks and adherence to preventive measures, such as mask wearing, hand hygiene, physical distancing, and vaccination, are essential for reducing disease transmission and severe outcomes. Previous studies have demonstrated that higher levels of COVID-19-related awareness are associated with better adoption of preventive behaviors and lower infection risk among older populations [7,8]. Conversely, limited awareness and inconsistent preventive practices have been linked to increased vulnerability, delayed care-seeking, and adverse health outcomes [9]. In urban contexts where exposure risk is intensified by population density and daily mobility, inadequate awareness and preventive behavior among older adults may further exacerbate health disparities and excess mortality.

Health literacy is widely recognized as a determinant of health behavior, reflecting individuals’ ability to access, understand, appraise, and apply health information in decision-making [10,11]. Substantial evidence supports health literacy’s role in shaping preventive practices during the COVID-19 pandemic [8,12]. However, most interventions were developed in high-income or generalized populations with limited adaptation to the needs of urban communities in low- and middle-income countries [13,14]. In Thailand, while associations between health literacy and preventive behaviors among older adults have been reported, urban-specific vulnerabilities were insufficiently addressed [15,16]. This gap is critical, given the disproportionate risks and excess mortality experienced by older Thai adults during the pandemic [5,6].

Pengjuntr’s V-shape health literacy model was developed within Thai public health contexts to conceptualize literacy as a progressive, action-oriented process [17]. The “V-shape” metaphor represents a developmental trajectory: individuals begin with foundational competencies in accessing and understanding health information before progressing toward interactive communication and critical appraisal, and subsequently advancing to autonomous decision-making, behavior enactment, and community advocacy. Unlike models that primarily categorize literacy levels [10] or emphasize information-processing capacities [11], the V-shape framework embeds behavioral application and social advocacy as structural components of literacy development. This progression-oriented structure aligns with behavior change theories that emphasize self-efficacy, practice, and social reinforcement as mechanisms for sustained behavioral adoption [18,19].

To address this gap, the present study applied the V-shape health literacy model endorsed by the Department of Health, Ministry of Public Health, Thailand, which emphasizes six domains: access, understanding, interactive communication, decision-making, behavior change, and advocacy [17]. By incorporating these elements into a structured intervention, the study aimed to enhance health literacy, awareness, and preventive behaviors among older adults in the urban community of Dusit District, Bangkok.

Methods

1. Study design

A quasi-experimental design with two groups was employed, utilizing a pre-test–post-test–follow-up approach. This study was reported in accordance with the TREND (Transparent Reporting of Evaluations with Nonrandomized Designs) statement [20]. Data were collected at three time points: baseline (pre-test), immediately following the 4-week intervention (post-test), and 12 weeks after baseline, after completion of the reinforcement phase.

2. Setting and participants

The study population consisted of older adults living in Dusit District, Bangkok, during 2024. A total of 76 individuals were recruited through a multi-stage sampling process.

In the first stage, two urban communities within Dusit District were purposively selected based on predefined criteria: the Wat Sawadwaree Sri Maram community (assigned as the experimental group) and the Samsen Pier community (assigned as the control group). Although both communities are located within the broader service area of the Faculty of Medicine, Vajira Hospital, the study was conducted independently of hospital administrative and clinical operations, and the research team held no supervisory or managerial authority over community health services in these areas. Both communities function independently under separate leadership structures and activity schedules. Intervention and follow-up activities were conducted exclusively within each community to minimize potential cross-group contamination.

In the second stage, eligible older adults were identified from official community registration lists according to predefined inclusion and exclusion criteria. Within each community, participants were selected through simple random sampling using computer-generated random numbers. Community leaders and village health volunteers (VHVs) assisted the research team in identifying eligible older adults and disseminating information about the study. Potential participants were invited to attend an information session, during which the purpose, procedures, and duration of the study were explained. Written informed consent was obtained from all participants prior to enrollment. Eligibility criteria included:

1) Inclusion criteria

Participants were eligible if they: (1) resided in Dusit District, Bangkok, in 2024; (2) were aged 60 years or older; (3) owned an internet-enabled communication device, such as a smartphone, tablet, or other device; (4) were able to perform self-care independently; (5) were able to communicate in Thai by speaking and listening; and (6) consented to participate throughout the study period.

2) Exclusion criteria

Participants were excluded if they (1) were clinically diagnosed with dementia or (2) had a previous history of COVID-19 infection.

3) Withdrawal criteria

Participants were withdrawn from the study if (1) they voluntarily requested to discontinue participation during the study or (2) they experienced abnormal levels of stress or anxiety related to the study.

4) Sample size determination

This was conducted in G*Power ver. 3.1 (Heinrich-Heine-Universität Düsseldorf), using a two-group comparison (two-tailed), α=.05 and power=.80. The effect size (d=0.68) was adopted from prior Thai research on health literacy interventions among older adults affected by COVID-19 [21]. The calculation indicated a minimum of 68 participants (34 per group). Allowing for an anticipated 10% attrition [22], the final target sample was 76 participants, 38 per group.

5) Participant flow

A total of 76 participants were enrolled, with 38 participants in each group. Eight participants were lost to follow-up: four from the experimental group and four from the control group. In the experimental group, two participants were unable to attend the follow-up assessments, and two participants could not be contacted during the follow-up period. In the control group, all four participants could not be contacted during the follow-up period. Data from 68 participants were included in the final analysis, with 34 participants in each group.

3. Intervention program development

The intervention program used was the Health Literacy Enhancement Program for the Prevention of COVID-19 Risk Factors, developed by the researcher based on Pengjuntr’s V-shape health literacy model [17]. The program comprised six components: (1) access, (2) understanding, (3) interactive communication, (4) decision-making, (5) behavioral change, and (6) advocacy.

Pengjuntr’s V-shape health literacy model was developed in the Thai public health context to conceptualize health literacy as a staged, action-oriented process [17]. The “V-shape” symbolizes a progression from basic abilities, such as accessing and understanding health information, to interactive communication, critical evaluation, informed decision-making, and ultimately behavior change and community advocacy. This structured progression is consistent with behavior change theories that highlight self-efficacy, repeated practice, and social reinforcement as key mechanisms for sustaining health behaviors [18,19].

The theoretical premise underlying this framework posits that improved access to reliable information and enhanced comprehension strengthen cognitive appraisal of health risks, thereby supporting informed decision-making and consistent preventive behaviors [17]. Advocacy and social sharing further reinforce behavioral maintenance through social modeling and accountability within community networks.

Evidence from available program evaluations suggests that interventions based on the V-shape health literacy model are associated with improvements in health literacy and related preventive behaviors. For example, Saedkong et al. [23] conducted a quasi-experimental study among diabetic and hypertensive patients with complications from chronic kidney disease in Thailand to examine the effects of V-shape health literacy media. In that study, the intervention was delivered over 4 weeks and targeted core components of health literacy, including access, understanding, interactive communication, decision-making, behavior change, and advocacy. The study demonstrated significant improvements in patients’ knowledge, health beliefs, and self-care behaviors, particularly in relation to dietary control, medication adherence, exercise, stress management, and follow-up care. Similarly, Wongkongdech et al. [24] implemented a participatory health literacy promotion program among people at risk of diabetes in a Thai community, which incorporated the six components of the V-shape model and focused on diabetes prevention behaviors using the 3E2S framework (eating, exercise, emotional management, smoking cessation, and alcohol reduction). Post-intervention results showed statistically significant improvements in health literacy levels and preventive health behaviors.

Overall, these studies indicated that the V-shape health literacy model has been effectively applied among both chronic disease patients and community-based at-risk populations to enhance health literacy and support behavior change, thereby justifying its application in the present study.

Within the implementation framework of this community-based program, clear role differentiation was established to ensure both clinical integrity and community engagement. Nurse researchers led the program, conducting health assessments, delivering the structured health literacy intervention, making home visits, coordinating referrals, safeguarding participants’ rights, and overseeing program evaluation to ensure evidence-based implementation. Prior to study initiation, nurses provided structured training to VHVs on health literacy content, intervention procedures, communication strategies, and monitoring responsibilities to promote consistent delivery.

In contrast, VHVs served as community-based public health representatives and trusted intermediaries between health services and residents. VHVs disseminated health information, mobilized participation, supported surveillance, assisted with screening and basic care, and collaborated in follow-up activities. While nurses ensured clinical and research oversight, VHVs strengthened community linkage and continuity of care, forming an integrated partnership in program delivery.

The program included six core activities implemented over a 12-week period. The operationalization of the six constructs of Pengjuntr’s V-shape health literacy model into specific program content and intervention methods is summarized in Table 1, adapted from the table structure presented by Kim and Kim [25].

4. Measurements/instruments

Data collection instruments consisted of a questionnaire developed by the researcher based on a comprehensive review of relevant literature and related studies [7], as well as recommendations from experienced experts. The questionnaire was designed to address the research objectives and comprised three sections. The COVID-19 awareness scale was developed and adapted from previously validated instruments [26,27], and the COVID-19 preventive behavior scale was developed and adapted from previously validated instruments [28,29]. The details are as follows:

1) Personal information section

This section included checklist and completion items covering demographic characteristics, including gender, age, education level, occupation, income, and underlying diseases.

2) COVID-19 Awareness Scale

This scale contained 10 items aimed at assessing awareness of COVID-19 risk factors and prevention. Five items addressed awareness of the disease (e.g., transmissibility, treatability, severity among older adults, lifestyle adaptation to the “new normal,” and socioeconomic impact), and five items assessed awareness of preventive measures (e.g., mask-wearing, hand hygiene, consuming freshly cooked food, using serving spoons, covering the mouth and nose when coughing or sneezing, and avoiding crowded places). Each item was rated on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Item scores were summed to produce a total score ranging from 10 to 50, with higher scores indicating greater COVID-19 awareness.

3) COVID-19 Preventive Behavior Scale

This section comprised 10 items for assessing preventive behaviors related to COVID-19 risk factors, including dietary practices, use of serving spoons, mask-wearing, avoidance of sharing personal items, hand hygiene, respiratory etiquette, symptom monitoring, and self-assessment of possible infection. Each item was rated on a 5-point Likert scale, ranging from 1 (never) to 5 (always). Item scores were summed to produce a total score ranging from 10 to 50.

The cutoff scores for COVID-19 awareness and preventive behaviors were determined using percentage-based criteria commonly applied in health literacy and preventive behavior research. Scores of ≥80% (40–50) indicated high levels or good practice, scores of 60%–79.9% (30–39) indicated moderate levels, and scores <60% (<30) indicated low levels or poor practice [30,31].

5. Content validity and reliability

The Health Literacy Enhancement Program, the COVID-19 Awareness Scale, and the COVID-19 Preventive Behavior Scale were reviewed for content validity by a panel of five experts, including two nursing lecturers, one physician, and two community health nurses. The experts evaluated program contents and activities in relation to the six constructs of Pengjuntr’s V-shape health literacy model [17] for relevance, clarity, and appropriateness, as well as congruence of questionnaire items with study objectives. The content validity index was .85 for the intervention program, .84 for the COVID-19 Awareness Scale, and .82 for the COVID-19 Preventive Behavior Scale.

A pilot test with 30 older adults from Dusit District, Bangkok, was conducted to assess reliability. Cronbach’s α coefficients were .88 for the COVID-19 Awareness Scale and .77 for the COVID-19 Preventive Behavior Scale.

6. Data collection/procedure

Data were collected between August and November 2024. Following approval from the Institutional Review Board, the researcher obtained permission to conduct the study in two communities in Dusit District, Bangkok. Official letters were submitted to community authorities. Community leaders and VHVs assisted in identifying eligible participants. Potential participants were informed about the study objectives, procedures, duration, and data collection schedule. Written informed consent was obtained prior to enrollment.

Baseline data (pre-test) were collected before the intervention. The experimental group then received the health literacy enhancement program with a 4-week core phase, followed by an extended reinforcement phase that included home visits, telephone follow-ups, and LINE-based communication until 12 weeks after baseline. Post-test data were collected immediately after the 4-week core phase and follow-up data were collected 12 weeks after baseline. The control group received routine community health services, including one 60-minute educational session on COVID-19 preventive behaviors delivered by the researcher during the first week. Printed leaflets covering the same content were distributed immediately after the session.

7. Ethical consideration

This study was approved by the Institutional Review Board of Faculty of Medicine Vajira Hospital (COA No. 146/2564; initial approval date: 10 August 2021) and was renewed annually on 10 August 2022, 10 August 2023, and 10 August 2024. The most recent approval was valid until 9 August 2025. Prior to data collection, all participants were informed about the objectives, procedures, benefits, and risks of the study. Written informed consent was obtained from all participants who voluntarily agreed to participate. Data were kept strictly confidential and analyzed anonymously. Participants in the control group were provided with the intervention program after the completion of the study if the program was found to be effective. This study was retrospectively registered with the Thai Clinical Trials Registry (TCTR20260502013).

8. Data analysis

This quasi-experimental study enrolled 76 older adults in Dusit District, Bangkok; all 76 participants (38 per group) were included in the primary analysis. Data were analyzed using IBM SPSS Statistics ver. 31.0.1.0 (IBM Corp.). Statistical significance was set at p<.05. Descriptive statistics were used to summarize participants’ demographic characteristics, with continuous variables presented as mean±standard deviation and categorical variables as frequency and percentage. Outcome variables, including COVID-19 awareness and preventive behavior scores, were summarized using mean and standard deviation.

A linear mixed-effects model with restricted maximum likelihood estimation and an unstructured covariance matrix was used to examine changes in COVID-19 awareness and preventive behavior over time. The primary analysis used all available observations under the missing-at-random assumption; therefore, no imputation was performed. The model included fixed effects for group (experimental vs. control), time (pretest, posttest, follow-up), and the group-by-time interaction, with adjustment for sex, occupation status, and the corresponding pre-test value. Sex and occupation status were included to account for potential baseline confounding; occupation status differed significantly between groups at baseline (p=.003), whereas the difference in sex was not statistically significant (p=.068). The corresponding pre-test value was included to account for baseline variation in each outcome. Least-squares means and corresponding p-values were reported. A complete-case sensitivity analysis was conducted among the 68 participants (34 per group) who completed all assessments.

Results

Data from 76 participants, with 38 participants in each group, were included in the baseline analysis. Table 2 presents the baseline characteristics of the participants. At baseline, no statistically significant differences were observed between the groups in age, sex, education level, occupation status, median monthly income, income sufficiency, health insurance scheme, or underlying diseases (all p>.05). However, a statistically significant difference was observed in occupation (p=.003).

Of the 76 participants, 68 completed all assessments (34 in each group), while 8 participants were lost to follow-up (4 in each group). Baseline characteristics of completers are presented in Supplementary Tables 1–2.

Table 3 presents the adjusted within-group changes in COVID-19 awareness and preventive behavior and the differences in change between the experimental and control groups. In the experimental group, awareness increased significantly from pre-test to post-test (change, 1.95; 95% CI, 0.18–3.72; p=.031) and follow-up (change, 2.10; 95% CI, 0.27–3.94; p=.025). In contrast, awareness in the control group decreased significantly at post-test (change, −2.44; 95% CI, −4.23 – −0.66; p=.007) and follow-up (change, −4.23; 95% CI, −6.07 – −2.39; p<.001). The between-group differences in change were significant at both post-test (4.40; 95% CI, 1.89–6.90; p=.001) and follow-up (6.33; 95% CI, 3.75–8.92; p<.001).

Preventive behavior in the experimental group also increased significantly at post-test (change, 2.24; 95% CI, 0.57–3.92; p=.009) and follow-up (change, 3.79; 95% CI, 1.84–5.73; p<.001), whereas the control group showed significant decreases at post-test (change, −2.38; 95% CI, −4.08 – −0.68; p=.006) and follow-up (change, −4.82; 95% CI, −6.76 – −2.88; p<.001). The between-group differences in change were significant at post-test (4.62; 95% CI, 2.25–6.99; p<.001) and follow-up (8.61; 95% CI, 5.86–11.35; p<.001).

Table 4 presents the adjusted between-group comparisons of COVID-19 awareness and preventive behavior over time. At pre-test, no statistically significant differences were observed between the experimental and control groups in awareness (difference, 0.05; 95% CI, −1.73–1.83; p=.957) or preventive behavior (difference, −0.21; 95% CI, 1.96–1.54; p=.814). At post-test, the experimental group had significantly higher awareness (difference, 4.44; 95% CI, 2.43–6.46; p<.001) and preventive behavior (difference, 4.41; 95% CI, 2.44–6.38; p<.001) than the control group. These differences remained significant at follow-up for awareness (difference, 6.38; 95% CI, 4.19–8.57; p<.001) and preventive behavior (difference, 8.40; 95% CI, 6.06–10.73; p<.001).

Sensitivity analysis. The complete-case sensitivity analysis (n=68) yielded findings consistent with the primary analysis based on all 76 participants. No changes in the statistical significance of the findings were observed for the analyses presented in Tables 3 and 4 (Supplementary Tables 1–2).

Discussion

This study developed the health literacy enhancement program for older adults in an urban community, guided by Pengjuntr’s V-shape health literacy model [17], which includes access, understanding, interactive communication, decision-making, behavior change, and advocacy. The program was designed to address common gaps in COVID-19 awareness and preventive practices by combining group education, LINE-based communication, community activities, and home visits. Initial sessions focused on improving access to reliable information and understanding of COVID-19 risk factors, while interactive discussions and decision-making activities supported participants in selecting appropriate preventive behaviors for daily life. Ongoing follow-up through community monitoring, individualized feedback, and advocacy activities with family members and health volunteers reinforced behavior change beyond the classroom setting. In contrast to traditional lecture-based programs, this approach emphasized participation and real-life application, which may explain the significant improvements observed in preventive behaviors. Separating the groups by community reduced information contamination and strengthened the validity of the intervention effects.

The health literacy enhancement program led to clear improvements in COVID-19 preventive behaviors among older adults in the experimental group. Preventive behavior scores in the experimental group increased significantly at both post-test and follow-up, suggesting sustained improvement in preventive practices over time. These results aligned with evidence from systematic reviews showing that individual-focused health literacy interventions can improve older adults’ ability to understand and use health information, particularly when interventions were designed to actively engage participants and support practical application of information [32,33]. By contrast, awareness or knowledge outcomes tend to diminish without ongoing reinforcement, as long-term maintenance of health literacy knowledge remains challenging in older populations due to variability in intervention designs and follow-up duration [14,32]. In this program, repeated decision-making activities, individualized feedback, and home visits likely contributed to the sustained improvements in preventive behaviors observed across both post-test and follow-up.

The program improved both COVID-19 awareness and preventive behaviors within the experimental group, with significant improvements observed at both post-test and follow-up. COVID-19 awareness increased significantly at both post-test and follow-up, while preventive behaviors also improved significantly at both time points. Previous research has shown that awareness or knowledge alone does not consistently translate into sustained preventive practices among older adults without continued reinforcement and contextual support [34,35]. In contrast, preventive behaviors are more likely to be maintained when interventions include repeated practice, social support, and follow-up at the community or household level [35,36]. Therefore, the continued reinforcement provided through decision-making activities, individualized feedback, and home visits may partly explain why preventive behaviors were sustained above baseline, while awareness showed a smaller but sustained improvement over time.

Preventive skills in this study were strengthened through repeated practice and behavioral reinforcement integrated into the intervention design. Participants engaged in decision-making activities, individualized feedback, and continued monitoring through home visits and follow-up communication, which supported the application of preventive practices in daily life [36]. Previous studies have shown that community-based follow-up and home visiting approaches enabled older adults to translate health knowledge into sustained self-care behaviors by providing contextualized guidance and ongoing support [37]. In addition, repeated observation and feedback have been reported to enhance the maintenance of preventive behaviors beyond the initial intervention period [38]. In this study, this reinforcement was further supported through advocacy activities, in which participants shared photographs of their COVID-19 preventive practices with family members via digital communication platforms, promoting accountability and social support within the household. These findings support the present results, suggesting that health literacy programs emphasizing practical skill development and real-world reinforcement are effective in strengthening and sustaining preventive behaviors among older adults.

The experimental group showed significantly greater improvements in both COVID-19 awareness and preventive behaviors than the control group at post-test and follow-up, indicating that the intervention effect was maintained over the 12-week period. This sustained effect suggests that the program influenced behavioral adoption. Previous studies have shown that health promotion and health literacy–based interventions are more likely to produce behavior change when they incorporate active skill practice, feedback, and social reinforcement rather than information delivery alone [34,36]. In this study, practical application was emphasized through structured decision-making exercises, direct observation, and individualized feedback, enabling participants to rehearse preventive behaviors and receive corrective guidance in real-life contexts. The inclusion of home visits and digital communication further strengthened this process by allowing continuous monitoring and reinforcement within participants’ living environments, thereby supporting habit formation and behavioral consistency. The integration of nurse-led home visits with community volunteers and telephone-based follow-up represented a practical approach to delivering accessible and effective COVID-19 preventive care for older adults in community settings.

These findings suggest that the program’s effectiveness was largely driven by emphasis on repeated practice and contextual support, which facilitated the translation of health knowledge into sustained preventive action. However, such practice-intensive approaches require considerable time and human resources, which may limit scalability. To address this challenge, future programs should consider integrating standardized video-based demonstrations or digital training modules to complement face-to-face activities, thereby maintaining behavioral fidelity while improving feasibility and broader implementation.

This study included only two communities, with group allocation conducted at the community level without randomization. Although the analyses were adjusted for sex, occupation, and the corresponding pre-test value, unmeasured community-level differences may have influenced the findings.

Conclusion

This study developed and tested a health literacy enhancement program to improve COVID-19 awareness and preventive behaviors among older adults in an urban community. The findings showed that a nurse-led, community-based program combining education, decision-making, and behavioral reinforcement improved both COVID-19 awareness and preventive behaviors, with significant improvements maintained through follow-up. By demonstrating its effectiveness, this study provides evidence to support the practical use of health literacy–based interventions in community health nursing. The program may be adapted for use in similar community settings to strengthen disease prevention efforts among older adults.

Article Information

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Acknowledgements

Generative AI (ChatGPT) was used only to assist with language editing and clarity during manuscript preparation. No AI tool was used to generate original data, perform data analysis, interpret findings, or make scientific decisions. The authors reviewed and verified the final manuscript and take full responsibility for all content.

Funding

This study was funded by Navamindradhiraj University Research Fund (No. วจ.สนธ. 031-1/2565).

Data Sharing Statement

Please contact the corresponding author for data availability.

Supplementary Data

Supplementary data to this article can be found online at https://doi.org/10.4040/jkan.25147.

Supplementary Table 1.

jkan-25147-Supplementary-Table-1.pdf

Supplementary Table 2.

jkan-25147-Supplementary-Table-2.pdf

Author Contributions

Conceptualization: WT. Methodology: WT. Software: SA. Validation: WT. Formal analysis: WT, SA. Investigation: WT, NW. Resources: NW. Data curation: WT, SA, NW. Visualization: SA. Supervision: WT, SC. Project administration: WT, SA. Funding acquisition: WT. Writing–original draft: WT, SA. Writing–review & editing: WT, SA, SC, NW. Final approval of the manuscript: WT, SA, SC, NW.

Table 1.

The intervention program based on the V-shape health literacy model

V-shape health literacy constructs	Key points	Program content (based on intervention activities)	Intervention methods	Session duration
Access	Access reliable COVID-19 information and digital communication channels.	Health literacy made easy through access: introduction to COVID-19 prevention knowledge using informational media; explanation of the importance of health literacy; demonstration and hands-on practice using the LINE Official Account.	Lectures, demonstrations, and hands-on practice led by nurse researchers using the LINE Official Account.	Week 1; 60 min (group session).
Understanding	Understand COVID-19 risk factors and appropriate preventive measures.	Being healthy through health awareness: group activities involving information searches, brainstorming, and identification of accurate information on COVID-19 prevention.	Lectures, videos, and guided discussions led by nurse researchers.	Week 1; 60 min (group session).
Interactive communication	Communicate health information and exchange experiences.	Communicate confidently: question-and-answer sessions and group discussions with nurse researchers and peers to reflect on learned content and exchange experiences.	Group discussions, facilitated dialogue, and LINE group communication led by nurse researchers.	Week 1; 60 min; ongoing online interaction.
Decision-making	Select appropriate preventive practices and commit to action.	Make preventive decisions: joint selection of appropriate COVID-19 prevention strategies for daily life; commitment to personal action plans; and identification of solutions to barriers.	Discussions, decision-making exercises, and pledge writing facilitated by nurse researchers.	Week 1; 60 min (group session).
Behavior change	Practice and sustain COVID-19 preventive behaviors.	Practice and monitor preventive behaviors, including mask wearing, hand hygiene, physical distancing, and vaccination, with individualized feedback as needed.	Group and individual feedback.	Weeks 2–3; 120 min total.
Advocacy	Monitor and reinforce preventive behaviors and disseminate knowledge to family members.	Home visits and telephone follow-up were conducted by nurse researchers in collaboration with village health volunteers to provide individualized advice and monitor COVID-19 preventive behaviors among older adults. Weekly communication and information exchange were conducted through the LINE application, including photo sharing of participants’ preventive practices and teach-back activities with family or household members.	Community walk campaign for COVID-19 prevention and control and community loudspeaker broadcasts conducted with village health volunteers and nurse researchers. Home visits, telephone counseling, LINE-based photo sharing and weekly monitoring, and teach-back activities were conducted by nurse researchers.	Weeks 5–11; Community walk campaign and weekly broadcasts; home visits/telephone follow-up (20–30 min per contact); weekly communications by the LINE application.

This table was developed based on the framework presented by Kim and Kim [25]. Intervention activities were delivered during Weeks 1–3, and post-test data collection was conducted in Week 4. Reinforcement activities were delivered during Weeks 5–11, followed by follow-up data collection in Week 12.

COVID-19, coronavirus disease 2019.

Table 2.

General characteristics of participants (N=76)

Characteristics	Experimental group (n=38)	Control group (n=38)	p
Average age (yr)	70.21±6.68	68.47±6.69	.261^a)
Sex			.064^b)
Male	6 (15.8)	13 (34.2)
Female	32 (84.2)	25 (65.8)
Education level			.462^c)
No formal education	1 (2.6)	2 (5.3)
Primary school	17 (44.7)	24 (63.2)
Secondary/vocational certificate	11 (29.0)	6 (15.8)
Associate’s degree	7 (18.4)	5 (13.1)
Bachelor’s degree	2 (5.3)	1 (2.6)
Occupation			.003^c)
Not working/homemaker	18 (47.4)	8 (21.0)
Daily wage laborer	11 (28.9)	5 (13.2)
Business owner	3 (7.9)	13 (34.2)
Unemployed	3 (7.9)	6 (15.8)
Agriculturalist	1 (2.6)	0 (0.0)
Other	2 (5.3)	6 (15.8)
Occupation status			.107^b)
Unemployed	21 (55.3)	14 (36.8)
Employed	17 (44.7)	24 (63.2)
Median monthly income (Baht)	3,000 (800–7,000)	3,000 (600–9,000)	.979^d)
Income sufficiency			.295^c)
No income	2 (5.3)	2 (5.3)
Sufficient	14 (36.8)	8 (21.0)
Insufficient	22 (57.9)	28 (73.7)
Health insurance scheme			.396^c)
Universal coverage	28 (73.7)	29 (76.3)
Social security	5 (13.2)	4 (10.5)
Civil servant scheme	4 (10.5)	2 (5.3)
State enterprise	1 (2.6)	0 (0.0)
Private insurance	0 (0.0)	3 (7.9)
Underlying diseases			>.999^b)
Present	27 (71.1)	27 (71.1)
Absent	11 (28.9)	11 (28.9)

Values are presented as mean±standard deviation, median (Q1–Q3), number (%), or number unless otherwise stated.

^a)By independent samples t-test. ^b)By chi-square test. ^c)By Fisher exact test. ^d)By Mann-Whitney U test.

Table 3.

Comparison of COVID-19 awareness and preventive behavior within the experimental and control groups (N=76)

Variable	Experimental group (n=38)		Control group (n=38)		Difference in change between groups (95% CI)	p
Variable	Change from pre-test (95% CI)	p	Change from pre-test (95% CI)	p	Difference in change between groups (95% CI)	p
Awareness
Pre-test	Reference		Reference		-
Post-test	1.95 (0.18–3.72)	.031	–2.44 (–4.23 – –0.66)	.007	4.40 (1.89–6.90)	.001
Follow-up	2.10 (0.27–3.94)	.025	–4.23 (–6.07 – –2.39)	<.001	6.33 (3.75–8.92)	<.001
Preventive behavior
Pre-test	Reference		Reference		-
Post-test	2.24 (0.57–3.92)	.009	–2.38 (–4.08 – –0.68)	.006	4.62 (2.25–6.99)	<.001
Follow-up	3.79 (1.84–5.73)	<.001	–4.82 (–6.76 – –2.88)	<.001	8.61 (5.86–11.35)	<.001

Analyses were conducted using a linear mixed-effects model with restricted maximum likelihood and an unstructured covariance matrix, adjusted for sex, occupation, and the corresponding pre-test value (pre-test awareness for the awareness outcome and pre-test preventive behavior for the preventive behavior outcome). CI, confidence interval; COVID-19, coronavirus disease 2019.

Table 4.

Comparison of mean scores for COVID-19 awareness and preventive behavior between the experimental and control groups over time (N=76)

Variables	Experimental group (n=38)	Control group (n=38)	Difference between groups (95% CI)	p
Variables	Last-squares means (95% CI)	Least-squares means (95% CI)	Difference between groups (95% CI)	p
Awareness
Pre-test	45.26 (44.03–46.50)	44.95 (43.71–46.18)	0.05 (–1.73–1.83)	.957
Post-test	47.22 (45.81–48.62)	42.50 (41.08–43.92)	4.44 (2.43–6.46)	<.001
Follow-up	47.37 (45.83–48.90)	40.72 (39.17–42.26)	6.38 (4.19–8.57)	<.001
Preventive behavior
Pre-test	44.68 (43.47–45.90)	44.79 (43.58–46.00)	–0.21 (–1.96–1.54)	.814
Post-test	46.93 (45.57–48.29)	42.41 (41.02–43.80)	4.41 (2.44–6.38)	<.001
Follow-up	48.47 (46.84–50.10)	39.97 (38.35–41.60)	8.40 (6.06–10.73)	<.001

References

1. World Health Organization. Strengthening Preparedness for COVID-19 in cities and urban settings [Internet]. World Health Organization; 2020 [cited 2025 Oct 20]. Available from: https://www.who.int/publications/i/item/WHO-2019-nCoV-Urban_preparedness-2020.1
2. World Health Organization. Thailand COVID-19 situation: report 231 [Internet]. WHO Regional Office for South-East Asia; 2022 [cited 2025 Oct 20]. Available from: https://cdn.who.int/media/docs/default-source/searo/thailand/2022_04_12_tha-sitrep-231-covid-19_eng.pdf?sfvrsn=2aca959
3. Wong MK, Brooks DJ, Ikejezie J, Gacic-Dobo M, Dumolard L, Nedelec Y, et al. COVID-19 mortality and progress toward vaccinating older adults: World Health Organization, Worldwide, 2020-2022. MMWR Morb Mortal Wkly Rep. 2023;72(5):113-118. https://doi.org/10.15585/mmwr.mm7205a1Article PubMed PMC
4. Yanez ND, Weiss NS, Romand JA, Treggiari MM. COVID-19 mortality risk for older men and women. BMC Public Health. 2020;20(1):1742. https://doi.org/10.1186/s12889-020-09826-8Article PubMed PMC
5. United Nations Population Fund. The impact of COVID-19 on older persons in Thailand [Internet]. UNFPA; 2020 [cited 2025 Oct 20]. Available from: https://asiapacific.unfpa.org/en/publications/impact-covid-19-older-persons-thailand
6. Dul-Amnuay A, Peansukwech U, Hanapun C, Sharma A. Excess mortality due to COVID-19 in Thailand between the pandemic and post-pandemic periods. Sci Rep. 2025;15(1):957. https://doi.org/10.1038/s41598-025-85324-4Article PubMed PMC
7. Zhong BL, Luo W, Li HM, Zhang QQ, Liu XG, Li WT, et al. Knowledge, attitudes, and practices towards COVID-19 among Chinese residents during the rapid rise period of the COVID-19 outbreak: a quick online cross-sectional survey. Int J Biol Sci. 2020;16(10):1745-1752. https://doi.org/10.7150/ijbs.45221Article PubMed PMC
8. Paakkari L, Okan O. COVID-19: health literacy is an underestimated problem. Lancet Public Health. 2020;5(5):e249-e250. https://doi.org/10.1016/S2468-2667(20)30086-4Article PubMed PMC
9. Wolf MS, Serper M, Opsasnick L, O’Conor RM, Curtis L, Benavente JY, et al. Awareness, attitudes, and actions related to COVID-19 among adults with chronic conditions at the onset of the U.S. outbreak: a cross-sectional survey. Ann Intern Med. 2020;173(2):100-109. https://doi.org/10.7326/M20-1239Article PubMed PMC
10. Nutbeam D. Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health Promot Int. 2000;15(3):259-267. https://doi.org/10.1093/heapro/15.3.259Article
11. Sørensen K, Van den Broucke S, Fullam J, Doyle G, Pelikan J, Slonska Z, et al. Health literacy and public health: a systematic review and integration of definitions and models. BMC Public Health. 2012;12:80. https://doi.org/10.1186/1471-2458-12-80Article PubMed PMC
12. Okan O, Bollweg TM, Berens EM, Hurrelmann K, Bauer U, Schaeffer D. Coronavirus-related health literacy: a cross-sectional study in adults during the COVID-19 infodemic in Germany. Int J Environ Res Public Health. 2020;17(15):5503. https://doi.org/10.3390/ijerph17155503Article PubMed PMC
13. Palumbo R. Examining the impacts of health literacy on healthcare costs: an evidence synthesis. Health Serv Manage Res. 2017;30(4):197-212. https://doi.org/10.1177/0951484817733366Article PubMed
14. Visscher BB, Steunenberg B, Heijmans M, Hofstede JM, Devillé W, van der Heide I, et al. Evidence on the effectiveness of health literacy interventions in the EU: a systematic review. BMC Public Health. 2018;18(1):1414. https://doi.org/10.1186/s12889-018-6331-7Article PubMed PMC
15. Pechrapa K, Yodmai K, Kittipichai W, Charupoonpol P, Suksatan W. Health literacy among older adults during COVID-19 pandemic: a cross-sectional study in an urban community in Thailand. Ann Geriatr Med Res. 2021;25(4):309-317. https://doi.org/10.4235/agmr.21.0090Article PubMed PMC
16. Nilnate W, Hengpraprom S, Hanvoravongchai P. Level of health literacy in Thai elders, Bangkok, Thailand. J Health Res. 2016;30(5):315-321. https://doi.org/10.14456/jhr.2016.43Article
17. Pengjuntr W. Development of a V-shape model for strengthening health literacy in Thai communities. Thai J Health Educ. 2017;40(1):1-12.
18. Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004;31(2):143-164. https://doi.org/10.1177/1090198104263660Article PubMed PMC
19. Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6:42. https://doi.org/10.1186/1748-5908-6-42Article PubMed PMC
20. Des Jarlais DC, Lyles C, Crepaz N; TREND Group. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health. 2004;94(3):361-366. https://doi.org/10.2105/ajph.94.3.361Article PubMed PMC
21. Hlanden K, Jewpattanakul Y, Koshakri R. Effects of a long COVID literacy enhancement program on reducing the severity of post-infection COVID-19 behaviors of elderly in communities, Bangkok metropolitan area. Nurs J CMU [Internet]. 2024 [cited 2025 Oct 20];51(4):1-13. Available from: https://he02.tci-thaijo.org/index.php/cmunursing/article/view/269620
22. Polit DF, Hungler BP. Nursing research: principles and methods [Internet]. 6th ed. Lippincott Williams & Wilkins; 1999 [cited 2025 Oct 20]. Available from: https://archive.org/details/nursingresearchp00poli
23. Saedkong P, Rupunya N, Klungklang R, Thitiyanviroj B. Effects of V-shape health literacy media on knowledge, belief, and self-care behaviors among patients with diabetes mellitus and hypertension complicated by chronic kidney disease. J Nurs Sci Health [Internet]. 2025 [cited 2025 Oct 20];48(2):59-72. Available from: https://he01.tci-thaijo.org/index.php/nah/article/view/275864
24. Wongkongdech A, Kumchan J, Namyota C, Chanthamath S, Wongkongdech R. The effectiveness of participatory health literacy promoting programs among diabetes risk groups in community, Thailand. Asian J Soc Health Behav. 2024;7(4):172-179. https://doi.org/10.4103/shb.shb_166_24Article
25. Kim JE, Kim SS. Development and evaluation of suicide prevention nursing competency programs for visiting nurses. J Korean Acad Nurs. 2020;50(1):14-25. https://doi.org/10.4040/jkan.2020.50.1.14Article PubMed
26. Agarwal A, Ranjan P, Rohilla P, Saikaustubh Y, Sahu A, Dwivedi SN, et al. Development and validation of a questionnaire to assess preventive practices against COVID-19 pandemic in the general population. Prev Med Rep. 2021;22:101339. https://doi.org/10.1016/j.pmedr.2021.101339Article PubMed PMC
27. Alden SJ, Magesh KT, Sivachandran A, Aravindhan R, Sathyakumar M, Deenadayalan P. A survey on the COVID-19 awareness and vaccination acceptance/hesitance among the transgender population in various districts of Tamilnadu. J Pharm Bioallied Sci. 2022;14(Suppl 1):S788-S791. https://doi.org/10.4103/jpbs.jpbs_166_22Article PubMed PMC
28. Mercadante AR, Chu V, Chen AM, Wong JC, Khare MM, Law AV. COVID-19 behavioral questionnaire (CoBQ): Comparing the pandemic’s impact on health behavior in three US states. J Am Coll Clin Pharm. 2022;5(6):590-598. https://doi.org/10.1002/jac5.1625Article PubMed PMC
29. Nakayama K, Yonekura Y, Danya H, Hagiwara K. COVID-19 preventive behaviors and health literacy, information evaluation, and decision-making skills in Japanese adults: cross-sectional survey study. JMIR Form Res. 2022;6(1):e34966. https://doi.org/10.2196/34966Article PubMed PMC
30. World Health Organization. Advocacy, communication and social mobilization for TB control: a guide to developing knowledge, attitude and practice surveys [Internet]. World Health Organization; 2008 [cited 2025 Oct 20]. Available from: https://apps.who.int/iris/handle/10665/43790
31. Bloom BS. Taxonomy of educational objectives: the classification of educational goals. Longmans; 1956.
32. Marshall N, Butler M, Lambert V, Timon CM, Joyce D, Warters A. Health literacy interventions and health literacy-related outcomes for older adults: a systematic review. BMC Health Serv Res. 2025;25(1):319. https://doi.org/10.1186/s12913-025-12457-7Article PubMed PMC
33. Sardareh M, Matlabi H, Shafiee-Kandjani AR, Bahreini R, Mohammaddokht S, Azami-Aghdash S. Interventions for improving health literacy among older people: a systematic review. BMC Geriatr. 2024;24(1):911. https://doi.org/10.1186/s12877-024-05522-zArticle PubMed PMC
34. Poonthawe P, Junprasert S, Toonsiri C, Rattanagreethakul S, Intolo S, Luecha T. Factors influencing COVID-19 preventive behavior among older adults in Eastern Thailand. NU J Nurs Health Sci [Internet]. 2024 [cited 2025 Oct 20];18(1):36-52. Available from: https://he01.tci-thaijo.org/index.php/NurseNu/article/view/263093
35. Saisanan Na Ayudhaya W, Thanapop C, Wongrith P, Loonlawong S, Laor P, Fajriyah R. Health literacy and preventive behaviors towards COVID-19 among village health volunteers and residents in urban and rural areas of upper Southern Thailand. Soc Sci. 2023;12(7):377. https://doi.org/10.3390/socsci12070377Article
36. Rojpaisarnkit K, Kaewpan W, Pengpid S, Peltzer K. COVID-19 preventive behaviors and influencing factors in the Thai population: a web-based survey. Front Public Health. 2022;10:816464. https://doi.org/10.3389/fpubh.2022.816464Article PubMed PMC
37. Dobarrio-Sanz I, Chica-Pérez A, López-Entrambasaguas OM, Martínez-Linares JM, Granero-Molina J, Hernández-Padilla JM. Promoting the empowerment and emancipation of community-dwelling older adults with chronic multimorbidity through a home visiting programme: a hermeneutical study. BMC Nurs. 2024;23(1):444. https://doi.org/10.1186/s12912-024-02117-2Article PubMed PMC
38. Maruyama K, Kono A. Effect of self-monitoring education on health literacy among older adults with chronic disease who use home visiting nursing services: a non-randomized study. J Jpn Acad Nurs Sci. 2024;44:732-742. https://doi.org/10.5630/jans.44.732Article

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Effects of a health literacy program on COVID-19 awareness and preventive behaviors among older adults in Bangkok, Thailand: a quasi-experimental study

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Effects of a health literacy program on COVID-19 awareness and preventive behaviors among older adults in Bangkok, Thailand: a quasi-experimental study

V-shape health literacy constructs	Key points	Program content (based on intervention activities)	Intervention methods	Session duration
Access	Access reliable COVID-19 information and digital communication channels.	Health literacy made easy through access: introduction to COVID-19 prevention knowledge using informational media; explanation of the importance of health literacy; demonstration and hands-on practice using the LINE Official Account.	Lectures, demonstrations, and hands-on practice led by nurse researchers using the LINE Official Account.	Week 1; 60 min (group session).
Understanding	Understand COVID-19 risk factors and appropriate preventive measures.	Being healthy through health awareness: group activities involving information searches, brainstorming, and identification of accurate information on COVID-19 prevention.	Lectures, videos, and guided discussions led by nurse researchers.	Week 1; 60 min (group session).
Interactive communication	Communicate health information and exchange experiences.	Communicate confidently: question-and-answer sessions and group discussions with nurse researchers and peers to reflect on learned content and exchange experiences.	Group discussions, facilitated dialogue, and LINE group communication led by nurse researchers.	Week 1; 60 min; ongoing online interaction.
Decision-making	Select appropriate preventive practices and commit to action.	Make preventive decisions: joint selection of appropriate COVID-19 prevention strategies for daily life; commitment to personal action plans; and identification of solutions to barriers.	Discussions, decision-making exercises, and pledge writing facilitated by nurse researchers.	Week 1; 60 min (group session).
Behavior change	Practice and sustain COVID-19 preventive behaviors.	Practice and monitor preventive behaviors, including mask wearing, hand hygiene, physical distancing, and vaccination, with individualized feedback as needed.	Group and individual feedback.	Weeks 2–3; 120 min total.
Advocacy	Monitor and reinforce preventive behaviors and disseminate knowledge to family members.	Home visits and telephone follow-up were conducted by nurse researchers in collaboration with village health volunteers to provide individualized advice and monitor COVID-19 preventive behaviors among older adults. Weekly communication and information exchange were conducted through the LINE application, including photo sharing of participants’ preventive practices and teach-back activities with family or household members.	Community walk campaign for COVID-19 prevention and control and community loudspeaker broadcasts conducted with village health volunteers and nurse researchers. Home visits, telephone counseling, LINE-based photo sharing and weekly monitoring, and teach-back activities were conducted by nurse researchers.	Weeks 5–11; Community walk campaign and weekly broadcasts; home visits/telephone follow-up (20–30 min per contact); weekly communications by the LINE application.

Characteristics	Experimental group (n=38)	Control group (n=38)	p
Average age (yr)	70.21±6.68	68.47±6.69	.261^a)
Sex			.064^b)
Male	6 (15.8)	13 (34.2)
Female	32 (84.2)	25 (65.8)
Education level			.462^c)
No formal education	1 (2.6)	2 (5.3)
Primary school	17 (44.7)	24 (63.2)
Secondary/vocational certificate	11 (29.0)	6 (15.8)
Associate’s degree	7 (18.4)	5 (13.1)
Bachelor’s degree	2 (5.3)	1 (2.6)
Occupation			.003^c)
Not working/homemaker	18 (47.4)	8 (21.0)
Daily wage laborer	11 (28.9)	5 (13.2)
Business owner	3 (7.9)	13 (34.2)
Unemployed	3 (7.9)	6 (15.8)
Agriculturalist	1 (2.6)	0 (0.0)
Other	2 (5.3)	6 (15.8)
Occupation status			.107^b)
Unemployed	21 (55.3)	14 (36.8)
Employed	17 (44.7)	24 (63.2)
Median monthly income (Baht)	3,000 (800–7,000)	3,000 (600–9,000)	.979^d)
Income sufficiency			.295^c)
No income	2 (5.3)	2 (5.3)
Sufficient	14 (36.8)	8 (21.0)
Insufficient	22 (57.9)	28 (73.7)
Health insurance scheme			.396^c)
Universal coverage	28 (73.7)	29 (76.3)
Social security	5 (13.2)	4 (10.5)
Civil servant scheme	4 (10.5)	2 (5.3)
State enterprise	1 (2.6)	0 (0.0)
Private insurance	0 (0.0)	3 (7.9)
Underlying diseases			>.999^b)
Present	27 (71.1)	27 (71.1)
Absent	11 (28.9)	11 (28.9)

Variable	Experimental group (n=38)		Control group (n=38)		Difference in change between groups (95% CI)	p
Variable	Change from pre-test (95% CI)	p	Change from pre-test (95% CI)	p	Difference in change between groups (95% CI)	p
Awareness
Pre-test	Reference		Reference		-
Post-test	1.95 (0.18–3.72)	.031	–2.44 (–4.23 – –0.66)	.007	4.40 (1.89–6.90)	.001
Follow-up	2.10 (0.27–3.94)	.025	–4.23 (–6.07 – –2.39)	<.001	6.33 (3.75–8.92)	<.001
Preventive behavior
Pre-test	Reference		Reference		-
Post-test	2.24 (0.57–3.92)	.009	–2.38 (–4.08 – –0.68)	.006	4.62 (2.25–6.99)	<.001
Follow-up	3.79 (1.84–5.73)	<.001	–4.82 (–6.76 – –2.88)	<.001	8.61 (5.86–11.35)	<.001

Variables	Experimental group (n=38)	Control group (n=38)	Difference between groups (95% CI)	p
Variables	Last-squares means (95% CI)	Least-squares means (95% CI)	Difference between groups (95% CI)	p
Awareness
Pre-test	45.26 (44.03–46.50)	44.95 (43.71–46.18)	0.05 (–1.73–1.83)	.957
Post-test	47.22 (45.81–48.62)	42.50 (41.08–43.92)	4.44 (2.43–6.46)	<.001
Follow-up	47.37 (45.83–48.90)	40.72 (39.17–42.26)	6.38 (4.19–8.57)	<.001
Preventive behavior
Pre-test	44.68 (43.47–45.90)	44.79 (43.58–46.00)	–0.21 (–1.96–1.54)	.814
Post-test	46.93 (45.57–48.29)	42.41 (41.02–43.80)	4.41 (2.44–6.38)	<.001
Follow-up	48.47 (46.84–50.10)	39.97 (38.35–41.60)	8.40 (6.06–10.73)	<.001

Table 1. The intervention program based on the V-shape health literacy model

COVID-19, coronavirus disease 2019.

Table 2. General characteristics of participants (N=76)

Values are presented as mean±standard deviation, median (Q1–Q3), number (%), or number unless otherwise stated.

^a)By independent samples t-test. ^b)By chi-square test. ^c)By Fisher exact test. ^d)By Mann-Whitney U test.

Table 3. Comparison of COVID-19 awareness and preventive behavior within the experimental and control groups (N=76)

Table 4. Comparison of mean scores for COVID-19 awareness and preventive behavior between the experimental and control groups over time (N=76)