A cross-sectional descriptive study was conducted between March 9 and April 3, 2026. The survey targeted adults from the five administrative regions of Saudi Arabia (Central, Western, Eastern, Northern, and Southern), with a small number of respondents reporting residence outside the Kingdom.

A non-probability convenience sampling approach was used. Eligible participants were adults aged 18 years or older who were able to read and understand Arabic. Individuals younger than 18 years or unable to read Arabic were excluded. A total of 300 responses were retained for analysis. No formal a priori sample-size calculation was conducted. The achieved sample size was comparable with sample sizes used in related awareness surveys [12][13].

The 34-item questionnaire comprised eight sections covering demographic characteristics, basic knowledge of microplastics, characteristics of paper and plastic products, awareness of potential health harms, plastic-use behaviors, perception of harm and readiness to change, information sources and trust, and applied behavioral scenarios. Before full distribution, the questionnaire was piloted with approximately 10 adults to assess clarity, readability, and completion time, and minor wording refinements were made. The final questionnaire was administered through Google Forms and distributed through social media platforms. Participation was voluntary and responses were anonymous.

Three composite scores were computed. The knowledge score was based on 10 items (questions 7 - 16) with correct/incorrect coding and was expressed as the percentage of correct responses; scores were categorized as high (≥75%), moderate (50% - 74%), or low (<50%). The behavioral exposure score was the mean of eight items (questions 17 - 24) rated on a 5-point Likert scale from 1 (Never) to 5 (Always). The perception score was the mean of four items (questions 25 - 28) rated from 1 (Do not agree) to 5 (Strongly agree).

Questionnaire content and wording were reviewed by the research team and supervising faculty for relevance and clarity before distribution. Internal consistency was assessed using the Kuder-Richardson coefficient (KR-20) for the dichotomous knowledge scale and Cronbach’s alpha for the behavioral exposure and perception scales. The coefficients were 0.754, 0.726, and 0.710, respectively.

Participation was voluntary and anonymous. No personal identifiers, biological samples, clinical procedures, or sensitive personal information were collected. Electronic informed consent was obtained from all participants before participation. Data were collected through an anonymous online questionnaire and used solely for research purposes. In accordance with applicable local regulations for anonymous survey research, National Committee of Bioethics (NCBE), Kingdom of Saudi Arabia, Version 3, 2025, formal ethical approval and written informed consent were not required.

Analyses were performed using IBM SPSS, with statistical significance set at p < 0.05. Normality was assessed using the Shapiro-Wilk test, skewness, and kurtosis. Descriptive statistics included frequencies, percentages, means, standard deviations, medians, and interquartile ranges. Spearman’s rank correlation was used to examine associations among knowledge, behavioral exposure, and perception scores. Mann-Whitney U and Kruskal-Wallis tests were used for group comparisons, with epsilon-squared effect sizes and Bonferroni-corrected post-hoc comparisons where applicable. Chi-square tests with Cramer’s V were used for categorical associations. When small expected cell counts affected the assumptions of Pearson’s chi-square test, Monte Carlo inference was used to estimate statistical significance. For adjusted binary logistic regression, readiness to change was dichotomized as Yes = 1 and No/Not sure = 0. Predictors were knowledge score entered per 10-point increase, behavioral exposure mean, perception mean, gender, age category, and education category. Gender was coded as male = 0 and female = 1. Age and education were entered as ordinal trend variables according to ascending categories; their odds ratios therefore represent the change in odds associated with a one-category increase rather than comparison with a single reference category. This coding was selected to estimate ordered trends while limiting model parameters. Adjusted odds ratios (ORs) with 95% confidence intervals were reported.

Table 1 presents the demographic characteristics of the participants (N = 300). Females constituted 68.3% of the sample, while males represented 31.7%. Participants were distributed across different age groups, with the largest proportion aged 18 - 24 years (28.7%). Most participants resided in the Western (48.7%) and Central (40.0%) regions of Saudi Arabia. Regarding educational attainment, 56.7% held a bachelor’s degree, whereas 14.0% held a master’s degree and 3.7% held a doctorate degree.

Table 1. General characteristics of participants (N = 300).

Overall, findings from Tables 2-6indicate a moderate level of knowledge (65.47% ± 24.85%), a behavioral exposure score of 3.00 ± 0.69, and a perception score of 3.56 ± 0.91. Knowledge was positively associated with perceived harm (rho = 0.416, p < 0.001), whereas no significant association was observed between knowledge and behavioral exposure. Higher knowledge scores and older age were associated with greater readiness to change.

Table 2 summarizes participants’ knowledge regarding microplastics and the overall knowledge score. The highest correct-response rates were observed for the risks of leaving plastic bottles exposed to heat (90.3%) and heating food inside plastic containers (87.0%). In contrast, the lowest correct-response rates were observed for awareness of microplastics in human tissues (39.3%) and the presence of microplastics in some drinking water sources (45.7%). The overall mean knowledge score was 65.47% ± 24.85%, and 41.0% of participants were classified

Table 2. Knowledge about microplastics and overall knowledge level (N = 300).

as having a high level of knowledge.

Table 3 presents the distribution of behavioral exposure and perceived harm scores. Daily bottled water consumption had the highest behavioral exposure mean (3.76 ± 1.22), followed by drinking hot beverages in paper cups (3.44 ± 1.23) and the use of single-use cutlery (3.40 ± 1.15). Heating food inside plastic containers had the lowest behavioral exposure mean (1.95 ± 1.16). Regarding perceived harm, participants showed the strongest agreement with the statement that microplastics are a health issue (3.81 ± 1.33), whereas the statement regarding potential effects on male reproductive health had the lowest mean score and the highest proportion of neutral responses.

Table 4 summarizes information sources, trusted sources, barriers, readiness to change, and intended behavioral changes. Social media platforms were the most common source of information about microplastics (40.7%), followed by participants who had not previously heard of microplastics (21.3%). Figure 1 illustrates the distribution of participants according to their primary information sources.

Table 3. Behavioral exposure and perceived harm scores (N = 300).

Table 4. Information sources, barriers, readiness to change, and intended behavior change.

Figure 1. Distribution of main information sources about microplastics (N = 300).

Official health bodies were identified as the most trusted source of information (68.0%). The most frequently reported barriers to reducing plastic use were lack of alternatives (34.7%) and time or convenience constraints (32.3%). Most participants reported readiness to change at least one plastic-related behavior during the following month (69.7%), as illustrated in Figure 2.

Figure 2. Distribution of readiness to reduce plastic use (N = 300).

Among participants willing to change their behavior, avoiding heating food inside plastic containers was the most frequently selected intended behavior change (30.6%), followed by choosing glass or stainless-steel containers (21.8%).

Table 5 presents the reliability, normality, and correlation analyses. Internal consistency was acceptable for the knowledge scale (KR-20 = 0.754), behavioral exposure scale (Cronbach’s alpha = 0.726), and perception scale (Cronbach’s alpha = 0.710). Shapiro-Wilk testing indicated significant non-normality for knowledge and perception scores, whereas behavioral exposure scores did not significantly deviate from normality.

Spearman correlation analysis revealed a moderate positive association between knowledge and perception (rho = 0.416, p < 0.001). No significant associations were observed between behavioral exposure and knowledge (rho = 0.020, p = 0.730) or between behavioral exposure and perception (rho = 0.031, p = 0.591).

Table 6 summarizes the inferential analyses and predictors of readiness to change. Knowledge scores differed significantly across readiness categories (p < 0.001), as did perception scores (p = 0.003), whereas behavioral exposure scores did not

Table 5. Reliability, normality, and correlations between core scores.

Table 6. Inferential analysis and predictors of readiness to change.

differ significantly between readiness groups (p = 0.170).

Knowledge scores were significantly higher among females than males (67.85% vs. 60.32%; U = 8231.5, p = 0.030), while behavioral exposure differed significantly across age groups (p = 0.003). Readiness to change was significantly associated with knowledge level (p < 0.001). The association between readiness and the main reported barrier remained significant using Monte Carlo inference (chi-square = 21.378, df = 10, Monte Carlo p = 0.020, Cramer’s V = 0.189).

Figure 3 illustrates the relationship between readiness to reduce plastic use and the main reported barriers. High levels of readiness were observed even among participants who reported lack of alternatives or time and convenience as barriers.

Figure 3. Readiness to reduce plastic use by main barrier to reducing plastic use (N = 300).

In the adjusted logistic regression model, higher knowledge and older age were independently associated with readiness to change. Each 10-point increase in knowledge score was associated with higher odds of readiness to change (OR = 1.323, 95% CI: 1.166 - 1.500, p < 0.001). Each one-category increase in age was also associated with higher odds of readiness to change (OR = 1.646, 95% CI: 1.330 - 2.037, p < 0.001). Behavioral exposure, perception score, gender, and education were not significant independent predictors.

This study has several limitations that should be considered when interpreting the findings. First, the use of a convenience sample recruited through social media platforms may limit the representativeness of the sample, as individuals with greater digital literacy or interest in environmental and health topics may have been more likely to participate. Second, females constituted a larger proportion of the sample (68.3%), which may limit the generalizability of the findings to the wider Saudi population. Third, all measures were self-reported and therefore subject to recall bias and social desirability bias, potentially leading participants to overestimate their knowledge or underestimate exposure-related behaviors. Fourth, the cross-sectional design does not permit causal inference, preventing conclusions regarding whether knowledge directly influences readiness to change or whether other unmeasured variables contribute to this relationship. Fifth, data collection was conducted over a relatively short period, which may not fully capture temporal variations in public awareness or behavioral patterns. Finally, the study relied on self-reported behavioral indicators as proxies for microplastic exposure and did not include objective biological or environmental measurements of exposure.