The impact of vision care program on the mental health of migrant children in Eastern China: evidence from a cluster-randomized controlled trial.

The impact of vision care program on the mental health of migrant children in Eastern China: evidence from a cluster-randomized controlled trial - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Int J Equity Health . 2026 Apr 21;25:139. doi: 10.1186/s12939-026-02854-7 The impact of vision care program on the mental health of migrant children in Eastern China: evidence from a cluster-randomized controlled trial Yue Wang 1 , Cong Li 1 , Hanwen Zhang 2 , Yue Ma 2, ✉ Author information Article notes Copyright and License information 1 School of Economics and Finance, Xi’an Jiaotong University, Xi’an, Shaanxi 710049 China 2 Stanford Center on China’s Economy and Institutions, Stanford University, 616 Jane Stanford Way, Stanford, CA 94305−6055 USA ✉ Corresponding author. Received 2025 May 20; Accepted 2026 Apr 7; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13235173  PMID: 42015257 Abstract Background Vision impairment is common among children and is known to affect learning, but its impact on children’s mental health has received less attention, especially in low- and middle-income countries. This study aims to focus on a school-based vision care intervention for migrant children in China to examine how the intervention affect children’s mental health. Methods A randomized controlled trial was conducted to examine the causal impact of a vision care intervention on children’s mental health in 94 migrant schools. After baseline screening of 4,376 students, 682 children with visual impairments were assigned to either intervention or control groups. The intervention included distributing free eyeglasses, providing teacher incentives to encourage utilization, and offering informational education. Follow-up survey was conducted after six months. 309 children in the intervention group and 327 in the control group were included in the analysis. Intention-to-treat effects were estimated with standard errors clustered at the school level. Results Overall, the intervention resulted in a significantly higher risk of mental health issues among migrant children, particularly learning anxiety. The adverse effects disproportionately impacted children whose teachers did not support wearing glasses, whose parents or peers did not wear glasses, and who had moderate or severe vision impairment. The lack of support from teachers hindered students from developing positive perceptions of glasses use and acquiring knowledge about vision care, which subsequently negatively influenced their mental health. Conclusion Providing eyeglasses alone may not be sufficient to improve the well-being of migrant children. Without support from teachers, parents, and peers, vision care programs may lead to unintended increases in anxiety. School-based health programs should consider both physical and mental health needs and place greater emphasis on the social environment in which interventions are delivered. Supplementary Information The online version contains supplementary material available at 10.1186/s12939-026-02854-7. Keywords: Healthcare service, Mental health, Physical health, Vision care, Randomized controlled trial Introduction Recent global estimates indicate that childhood visual impairment is a substantial public health burden worldwide, with about 46.60 million children aged 0–14 experiencing mild impairment in 2020 [ 1 ], and it is highly prevalent in China, where an estimated 53.6% of all children and adolescents have poor vision [ 2 ]. Uncorrected visual impairment is associated with lower educational performance, reduced physical activity, and increased social difficulties [ 3 – 5 ]. Consequently, large-scale school-based vision care interventions—especially free eyeglass distribution—have been widely implemented in LMICs (low- and middle-income countries), with strong evidence of benefits for children’s academic performance [ 6 – 8 ]. Less is known about the mental health impacts of eyeglasses interventions, especially in contexts where eyeglasses wear carries negative stereotypes and incurs stigma. Stigma theory suggests that visible physical markers can become socially meaningful cues that elicit stereotyping, negative peer evaluations, and increased self-consciousness [ 9 – 11 ]. Research suggests that vision care may improve mental health by alleviating the psychological distress and inconveniences associated with poor vision [ 12 ]. However, studies in multiple contexts have found that young people worry that wearing eyeglasses negatively affects their appearance [ 13 , 14 ] and report peer victimization because of glasses wear [ 15 , 16 ]. The concern that one’s eyeglasses wear may be negatively judged by peers, family, and teachers can cause stress to perform for glasses-wearing children. When negative judgments by peers are internalized, they can lead to low self-esteem. A study of school-age children in Turkey further found that children who wear glasses reported lower self-esteem than their peers who do not [ 17 ]. Additionally, due to the common stereotype that people who wear glasses are more intelligent, glasses-wearing children could experience stereotype threat and feel pressured to perform well academically. Since academic performance is closely tied to identity and social comparison in classrooms [ 18 ], the association of glasses with academic performance could increase learning anxiety among glasses-wearing children. Supporting this, a study in China found that the distribution of free glasses had no significant effect on students’ mental health, and students with lower study intensity even experienced increased learning anxiety after receiving eyeglasses [ 19 ]. Both bullying from peers and expectations for academic ability from teachers can enhance the stereotype threat and performance-related anxiety [ 20 , 21 ], particularly among children with weaker academic performance. This conjecture calls for a thorough exploration of how home and school environments influence how children perceive eyeglasses and the subsequent impact of vision care on children’s mental health. If not addressed, the negative mental health impacts of vision care interventions may offset its positive effects on children’s development and academic performance. Anxiety and depression exert a substantial burden on affected children and adolescents, leading to decreased academic achievement, shortened years of education, and enduring adverse effects on adult health [ 22 , 23 ]. However, compared to the large body of research linking children’s mental health to various environmental, social, and psychosocial factors, the role of physical health conditions and interventions in children’s mental health has received much less attention [ 24 , 25 ]. Research has shown that schools and families influence children’s attitudes towards physical health interventions. Specifically, teachers’ support of health services trickles down to students and encourages them to model positive health behaviors [ 26 , 27 ]. At home, parents’ health knowledge and active engagement in healthy behaviors help children form perceptions of healthcare and take up daily health behaviors [ 28 – 30 ]. During adolescence, a period characterized by imitation and comparison of behaviors among peers, health-related behaviors can assume social and aesthetic connotations because of peer influence [ 31 ]. Children in low-resource communities with limited social support may be especially vulnerable to the potential negative impacts of vision interventions on mental health. For example, China’s rapid urbanization has led to a growing population of migrant children, who face higher risks of physical and mental health issues [ 32 , 33 ]. Because of a lack of social support networks, migrant children often experience low self-esteem, perceptions of discrimination, a low sense of belonging, and feelings of loneliness in cities. These challenges negatively affect not only their academic performance, but also their adaptation to the new environments [ 34 , 35 ]. Migrant households also have lower utilization of health services due to limited access to urban health providers [ 32 ], which could affect their knowledge of and attitudes towards vision care. In this study, we examine the mental health impacts of a randomized controlled trial of a school-based vision care service that combined free eyeglasses distribution with teacher incentives and vision-related information for parents. The intervention was implemented in 94 migrant schools across three cities in eastern China. We assess the overall effect of the intervention on migrant children’s mental health, with particular emphasis on heterogeneity across social contexts and potential pathways linking vision care to psychological outcomes. Specifically, we examine whether the mental health effects of the intervention differ according to teacher support for wearing eyeglasses, parental glasses wearing, peer glasses wearing, and the severity of visual impairment at baseline. We also explore mechanisms in several intermediate domains, including children’s perceptions of eyeglasses, vision-related knowledge, academic performance, and teacher-parent behavior regarding children’s vision status. Together, these analyses shed light on how school and family environments influence children’s psychological responses to physical health interventions and help identify groups that may be more vulnerable to unintended mental health consequences. The findings aim to inform the design of school-based health programs that promote physical health while protecting children’s mental well-being, especially among socially disadvantaged groups. Method Study setting and ethical considerations This cluster-randomized controlled trial was conducted in Shanghai, Suzhou, and Wuxi (twin cities near Shanghai). These cities were selected because of their large migrant populations: By the end of 2012, the migrant population in Shanghai exceeded 9.6 million, accounting for 40% of the total population [ 36 ], and migrants constituted 37.7% of the population in Wuxi and 26.6% in Suzhou in 2014 [ 37 , 38 ]. A large proportion of migrants in these cities do not have local residency (hukou) and thus have limited access to local public healthcare and schools. The baseline survey was conducted in September 2013, and the endline survey was conducted in May 2014. Both surveys included questionnaires for students, parents, and teachers. Students also completed a standard mathematics test, a mental health test (henceforth, MHT) and a visual acuity (henceforth, VA) screening as part of both surveys. In October 2013, after the baseline survey and before the intervention, optometric refraction was conducted with parental consent for students with uncorrected VA to provide them with safe and appropriate eyeglasses. Project staff then implemented the intervention and conducted two unannounced follow-up visits in December 2013 and April 2014. The trial was approved by the Institutional Review Boards of Stanford University (Palo Alto, California, USA; Protocol 28343) and Zhongshan Ophthalmic Center, Sun Yat-sen University (ZOC, Guangzhou, China). Permission was obtained from the local education bureau in each area and from the principals of all participating schools. Prior to each child’s participation, at least one parent provided written informed consent and the child gave verbal assent. The principles of the Declaration of Helsinki were adhered to throughout. The original trial was registered on Dec. 12, 2014 at http://isrctn.org under registration number ISRCTN16720066. Sampling, randomization, and masking We randomly selected 94 schools from a list of 135 migrant schools provided by the local bureaus of education, including 66 in Shanghai and 28 in Suzhou and Wuxi combined. A fifth-grade class consisting of children aged 10 to 12 was randomly chosen from each school and invited to participate. The baseline survey was administered to 4376 children. Only students diagnosed with visual impairment were eligible for randomization. Students without visual impairment were excluded from the study and did not receive any services. After removing these students and those with invalid baseline MHT scores, a total of 1,166 students remained eligible for randomization (see Flowchart in Fig. 1 ). Fig. 1. Open in a new tab Flowchart of enrollment and allocation of migrant children with refractive errors and mental health issues in the randomized trial Randomization was performed at Stanford University (Palo Alto, California, USA) using R software after the baseline survey and before refraction in October 2013. A priori sample size calculation using Optimal Design (OD) software determined that at least one class (an average of 50 children, with 10 expected to have vision impairment) from each of 90 schools (45 per group) was needed to provide 90% power to detect the expected difference between groups with an alpha error of 0.05 and intraclass correlation of 0.15 [ 39 ]. Following the sample size calculation guidelines, eligible children were randomly assigned at the school level to the intervention (588 students in 47 schools) or the control group (578 students in 47 schools) (Fig. 1 ). The participating children, their parents, teachers, and enumerators were unaware of treatment assignment, and the study staff was masked to treatment assignment. Intervention Because interventions that only distribute eyeglasses to children often reported low utilization [ 40 – 42 ], the current intervention has three components: Children in the intervention group received suitable and safe free glasses, their parents attended vision information lectures, and homeroom teachers were rewarded based on students’ compliance rate. On the two unannounced follow-up visits, teachers of children in the intervention group received a tablet (worth about $450) if more than 80% of the children in their class wore glasses. In the control group, a prescription for glasses and a letter were sent to the parents to inform their child’s refractive status. No teacher incentive was provided. At the end of the study, children in the control group received free glasses, although this was not announced beforehand. This integrated strategy is in line with previous vision care trials conducted in China [ 4 , 43 ]. Data collection Student, parent, and teacher questionnaires Trained enumerators administered questionnaires to children, parents, and teachers. At baseline, children reported their age, gender, whether they and their peers wore glasses, and completed a timed, proctored standard math test (designed by the research team with assistance from county education bureaus to ensure alignment with the national curriculum). Test scores were standardized according to the distribution of scores in each grade. Parents reported their education level, whether they wore glasses, their place of work (local or elsewhere), and their attitude toward children wearing glasses. We calculated a family wealth index by summing ownership of 14 items as reported in the China Rural Household Survey Yearbook [ 44 ]. Families were categorized as upper- or lower-wealth based on whether the family wealth index was above or below the sample mean. Teachers reported their gender, education level, age, and attitude toward children wearing glasses. In addition to the baseline measures, the follow-up survey also assessed children’s perception of eyeglasses, knowledge about vision (detailed measurement questions were shown in Appendix A), parental support for wearing glasses and communication between teachers and parents regarding children’s vision status. Visual acuity assessment and refraction As part of the baseline survey, a two-step vision test was administered to all children in both treatment and control groups. First, a nurse and a trained assistant conducted visual acuity (VA) screenings for all children at their schools, separately testing each eye with and without existing glasses (if available) at 4 m using a child-appropriate Early Treatment Diabetic Retinopathy Study (ETDRS) tumbling-E logMAR chart (Precision Vision, La Salle, Illinois, USA) in an illuminated, indoor area at school. If at least four of five optotypes on the 6/60 line were correctly identified, children were then tested on the 6/30 line, the 6/15 line, and subsequently line by line down to 6/3. VA for an eye was defined as the lowest line on which four of five optotypes were read correctly. If the top line could not be read at 4 m, the test was repeated at 1 m, and the measured VA was divided by 4. Following the Refractive Error Studies in Children (RESC) protocol, students who failed the visual acuity screening test, where the cut-off is a VA of less than or equal to 6/12 in either eye, were considered to have visual impairment. Visual impairment categories were defined following the RESC protocol, which has been widely implemented in pediatric vision research in China and in prior analyses of this intervention [ 45 ]. Mild impairment was defined as uncorrected VA worse than 6/12 but ≥ 6/24; moderate impairment as VA < 6/24 but ≥ 6/48; and severe impairment as VA < 6/48 in the better-seeing eye. Although WHO classifications use 6/18 and 6/60 as thresholds [ 46 ], the RESC-based cutoffs allow finer differentiation of impairment severity in school-aged samples and ensure comparability with earlier studies. All severity categories were based on uncorrected VA, which was also the eligibility threshold for refraction (uncorrected VA ≤ 6/12 in either eye). The LogMAR, which is equal to the logarithm of the Minimum Angle of Resolution, is one of the most common continuous measures of visual acuity in optometry. It was also developed to intuitively describe children’s visual acuity. Higher LogMAR values indicate worse vision [ 39 ]. Prior to the intervention, the teachers, nurses, and enumerators received formal vision screening training from optometrists at Zhongshan Ophthalmic Centre (ZOC), Guangzhou, China. They also completed one week of supervised hands-on training in their home counties, which involved screening children from local schools and dispensing eyeglasses under the supervision of ophthalmologists. Additionally, a consultant from the Brien Holden Vision Institute (BHVI) provided management training, including inventory control and record keeping, to the research staff. As the second step of the vision test, refraction tests were performed at each school one to two days later to determine eyeglasses prescriptions for children who failed the VA screening test and were thus eligible for the treatment or control group. Those children received cycloplegia and automated refraction with subsequent refinement by a refractionist trained by pediatric optometrists from ZOC. Mental health test Children’s mental health was measured using the Mental Health Test (MHT) [ 47 ], which was adapted from the Children’s Manifest Anxiety Scale (CMAS) and used extensively in studies of primary school students in China [ 48 , 49 ]. The MHT has a reliability of 0.84–0.88 and a retest reliability of 0.78–0.86, suggesting that it is a dependable tool for assessing general anxiety and that the result is stable over time. The project staff administered the MHT to the sample children in their classrooms. The instrument includes 100 yes/no items, 10 of which are response validation items. Of the 4376 children surveyed, 38 (0.9%) failed seven or more validation items and were excluded. The remaining 90 items are divided into eight sections that measure specific subdomains of anxiety: learning anxiety and physical anxiety, each with 15 items; interpersonal anxiety, lonely tendency, self-blame tendency, over-sensitive tendency, panic anxiety, and impulsive tendency, each with 10 items. Each item corresponds to one point in the child’s MHT score. Higher scores indicate a higher risk of anxiety. A score above 8 in a subscale suggests that the child is at risk of that subdomain’s anxiety. A total MHT score of 56 or more indicates an overall risk of anxiety, while 65 or more signifies high risk and the need for clinical intervention. Statistical approach Before conducting empirical analysis, we performed a balance test between the treatment group and control group. Table A1 provides a summary of the characteristics of children, families, and teachers in both the treatment and control groups, and these characteristics were found to be balanced between the two groups. Table A2 shows that overall attrition is low (about 5%) and is not significantly associated with treatment assignment or the interaction between treatment and baseline MHT score. Adjusted Ordinary Least Squares (OLS) regression models were used to evaluate the effect of the vision care intervention on migrant children’s mental health. All models include district fixed effects and use robust standard errors clustered at the school level to account for within-school correlation. The main estimation model for mental health outcomes is as follows: 1 Where subscript “1” denotes endline values and “0” denotes baseline values. MHT_Score 1ijk is the standardized total (or subdomains) MHT score for student i in school j in district k . Treatment ijk indicates assignment to the intervention group (1 = yes, 0 = no). X ’ ijk is a vector of child-, parent-, and teacher-level characteristics listed in Table A1 , including baseline MHT subdomain scores for the corresponding endline outcomes and δ k denotes District fixed effects. We estimate the effects of the treatment on potential intermediate outcomes using linear probability models (LPMs): 2 where in Eq. ( 2 ) denotes endline outcomes related to perceptions of eyeglasses, vision care knowledge, standardized math scores, and parent–teacher behaviors. These models are used to explore possible mechanisms and are interpreted as exploratory analyses, rather than formal causal mediation. Similarly, we used LPMs to estimate whether the effects of the treatment varied by parental glasses wear, peer glasses wear, teacher support for wearing glasses, or baseline visual impairment: 3 where represents indicators for parental glasses wear, peer glasses wear, teacher support for wearing glasses, or baseline severity of visual impairment, and the interaction term × captures whether the treatment effect differs across these subgroups. In Eqs. ( 1 , 3 ), the coefficient represents the average causal ITT effect of assignment to the intervention group. Missing baseline covariates were multiply imputed following procedures used in earlier evaluations of this intervention [ 39 , 50 ]. Results We first describe the mental health status of migrant children in the sample and the distribution of key anxiety subdomains. We then present the ITT effects of the vision care intervention on children’s mental health. Next, we report subgroup analyses to identify which children were most affected by the intervention. Finally, we examine four potential mechanisms that may explain why certain groups experienced larger increases in anxiety. Mental health status of migrant children Table A3 shows substantial variation in mental health risks among the children in our sample. Children with visual impairment were more likely to be classified as high-risk for overall anxiety than children with normal vision (9.26% vs. 6.82%). Consistent with previous studies of Chinese primary-school students [ 48 , 51 ], learning anxiety was the most common subdomain of anxiety for both groups (51.2% among children with visual impairment; 46.1% among those without), followed by self-blame tendency and physical anxiety. Because risks in the other five MHT subdomains occurred at low frequencies, our analysis focuses on four outcomes: general MHT score, learning anxiety, self-blame tendency, and physical anxiety. These subdomain analyses were not pre-specified in the original trial registration and are therefore reported as exploratory. Effects of the intervention on mental health Table 1 shows the intention-to-treat (ITT) estimates for the mental health outcomes of migrant children. Higher MHT scores indicate worse mental health. For the primary general mental health outcome, assignment to the intervention increased the total MHT score by 0.214 SD (95% CI − 0.01–0.44; p < 0.1). In raw-score terms, this corresponds to an increase of about 2.83 points. Applying this shift to the baseline distribution suggests that the proportion of children exceeding the clinical risk threshold of 56 points increased by approximately 3.5% points in the intervention group compared with the control group. For subdomain mental health outcomes, the intervention increased learning anxiety by 0.257 SD (95% CI 0.03–0.48; p < 0.01), equivalent to roughly 0.79 raw points. Effects on self-blame tendency and physical anxiety were positive but did not reach statistical significance. Table 1. Intention-to-treat effects of the vision care intervention on migrant children’s mental health Variables Endline standard score General MHT Learning anxiety Self-blame tendency Physical anxiety Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment (0 = no, 1 = yes) 0.214† 0.257* 0.178 0.122 [-0.010, 0.439] [0.030, 0.485] [-0.056, 0.413] [-0.055, 0.300] Baseline general MHT YES Baseline learning anxiety YES Baseline self-blame tendency YES Baseline physical anxiety YES Control variables YES YES YES YES District FE YES YES YES YES Observations 636 636 636 636 R-squared 0.389 0.268 0.189 0.334 Open in a new tab Notes: Higher scores indicate worse mental health. All models include district fixed effects and cluster-robust standard errors at the school level.*** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1 Heterogeneity analysis We next evaluated whether treatment effects differed by teachers, parents, peers, and the severity of visual impairment (Tables 2 , 3 , 4 and 5 ). Reference categories are coded as 0 in all interaction models. Interaction terms serve as the formal tests of heterogeneity, while subgroup-specific estimates are presented as exploratory patterns. In all models, higher MHT scores indicate worse mental health. Table 2. Heterogeneous effects of the vision care intervention on mental health by teacher support for wearing glasses Variables Endline standard score General MHT Learning anxiety Self-blame tendency Physical anxiety Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment (0 = no, 1 = yes) 0.378* 0.804*** -0.218 0.439† [0.010, 0.746] [0.358, 1.249] [-1.223, 0.786] [-0.032, 0.911] Teacher support (0 = no, 1 = yes) 0.143† 0.074 0.085 0.129† [-0.004, 0.290] [-0.192, 0.340] [-0.118, 0.289] [-0.022, 0.280] Treatment × Teacher support -0.300 -0.660** 0.276 -0.417† [-0.680, 0.080] [-1.120, -0.201] [-0.744, 1.296] [-0.890, 0.056] Baseline general MHT YES Baseline learning anxiety YES Baseline self-blame tendency YES Baseline physical anxiety YES Control variables YES YES YES YES District FE YES YES YES YES Observations 616 616 616 616 R-squared 0.424 0.272 0.215 0.351 Treatment effect among children with teacher support 0.079 0.143† 0.058 0.022 [-0.037, 0.195] [-0.000, 0.286] [-0.076, 0.191] [-0.096, 0.140] Open in a new tab Notes: Higher scores indicate worse mental health. Treatment effect among children with teacher support is calculated as the linear combination of the treatment coefficient and the interaction term. *** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1; Table 3. Heterogeneous effects of the vision care intervention on mental health by parental glasses wearing Variables Endline standard score General MHT Learning anxiety Self-blaming tendency Physical anxiety Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment (0 = no, 1 = yes) 0.232† 0.281* 0.197 0.162† [-0.008, 0.472] [0.038, 0.524] [-0.057, 0.451] [-0.027, 0.351] Parental wear (0 = no, 1 = yes) 0.230* 0.231† 0.171 0.422*** [0.036, 0.424] [-0.017, 0.478] [-0.062, 0.404] [0.240, 0.603] Treatment × Parental wear -0.099 -0.133 -0.104 -0.226 [-0.354, 0.155] [-0.423, 0.157] [-0.438, 0.230] [-0.501, 0.050] Baseline general MHT YES Baseline learning anxiety YES Baseline self-blame tendency YES Baseline physical anxiety YES Control variables YES YES YES YES District FE YES YES YES YES Observations 636 636 636 636 R-squared 0.389 0.269 0.190 0.336 Treatment effect among children with parent wear glasses 0.133 0.148 0.092 -0.063 [-0.131, 0.396] [-0.147, 0.443] [-0.225, 0.410] [-0.333, 0.205] Open in a new tab Notes: Higher scores indicate worse mental health. Treatment effect among children with parental glasses wearing is calculated as the linear combination of the treatment coefficient and the interaction term. *** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1; Table 4. Heterogeneous effects of the vision care intervention on mental health by peer glasses wearing Variables Endline standard score General MHT Learning anxiety Self-blaming tendency Physical anxiety Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment (0 = no, 1 = yes) 0.266* 0.326** 0.235† 0.207* [0.023, 0.508] [0.083, 0.568] [-0.036, 0.507] [0.011, 0.403] Peers wear (0 = no, 1 = yes) 0.058 -0.035 -0.007 0.151 [-0.075, 0.191] [-0.195, 0.125] [-0.163, 0.148] [-0.042, 0.344] Treatment × Peer wear -0.139 -0.162 -0.150 -0.220 [-0.360, 0.081] [-0.399, 0.074] [-0.402, 0.103] [-0.487, 0.047] Baseline general MHT YES Baseline learning anxiety YES Baseline self-blame tendency YES Baseline physical anxiety YES Control variables YES YES YES YES District FE YES YES YES YES Observations 633 633 633 633 R-squared 0.397 0.272 0.194 0.343 Treatment effect among children with peer wear glasses 0.127 0.163 0.085 -0.012 [-0.134, 0.387] [-0.108, 0.435] [-0.171, 0.342] [-0.266, 0.241] Open in a new tab Notes: Higher scores indicate worse mental health. Treatment effect among children with peer glasses wearing is calculated as the linear combination of the treatment coefficient and the interaction term. *** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1; Table 5. Heterogeneous effects of the vision care intervention on mental health by severity of visual impairment Variables Endline standard score General MHT Learning anxiety Self-blaming tendency Physical anxiety Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment (0 = no, 1 = yes) 0.147 0.200* 0.110 0.144† [-0.039, 0.332] [0.005, 0.396] [-0.104, 0.323] [-0.021, 0.308] Severity of visual impairment (0 = mild, 1 = moderate/severe) -0.267* -0.213 -0.290† -0.066 [-0.51, -0.019] [-0.474, 0.048] [-0.583, 0.003] [-0.326, 0.194] Treatment × Visual impairment 0.238† 0.201 0.241 -0.075 [-0.035, 0.510] [-0.074, 0.476] [-0.102, 0.585] [-0.389, 0.239] Baseline general MHT YES Baseline learning anxiety YES Baseline self-blame tendency YES Baseline physical anxiety YES Control variables YES YES YES YES District FE YES YES YES YES Observations 636 636 636 636 R-squared 0.396 0.273 0.197 0.336 Treatment effect among children with moderate/severe visual impairment 0.384* 0.401* 0.351† 0.069 [0.016, 0.753] [0.035, 0.767] [-0.395, 0.741] [-0.268, 0.406] Open in a new tab Notes: Higher scores indicate worse mental health. Treatment effect among children with moderate/severe visual impairment is calculated as the linear combination of the treatment coefficient and the interaction term. *** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1; Table 2 examines heterogeneity by homeroom teachers’ support for wearing eyeglasses. The interaction between treatment assignment and teacher support is statistically significant for learning anxiety (β = − 0.66 SD, 95% CI: −1.12–−0.20; p < 0.01), indicating differential effects across teacher-support groups. Among children whose teachers did not support glasses wear (reference category), the intervention increased learning anxiety by 0.804 SD (95% CI: 0.36–1.25; p < 0.001). For children whose teachers were supportive, the treatment effect—calculated as the linear combination of the treatment coefficient and the interaction term—was 0.143 SD (95% CI: 0.00–0.29; p = 0.05). Table 3 examines heterogeneity by whether at least one parent wore eyeglasses. Interaction terms were not statistically significant for any outcome ( p > 0.10). Subgroup-specific estimates indicate that the intervention increased general MHT score by 0.232 SD (95% CI: −0.01–0.47; p < 0.10) and learning anxiety by 0.281 SD (95% CI: 0.04–0.52; p < 0.05) among children whose parents did not wear glasses, whereas effects among children with glasses-wearing parents were small and not statistically distinguishable from zero. Table 4 examines heterogeneity by whether a child had peers who wore eyeglasses. Interaction terms again showed no statistically significant heterogeneity (all p > 0.10). As descriptive patterns, the intervention increased general MHT score (0.266 SD, 95% CI: 0.02–0.51; p < 0.05), learning anxiety (0.326 SD, 95% CI: 0.08–0.57; p < 0.01), self-blame tendency (0.235 SD, 95% CI: −0.04–0.51; p < 0.10), and physical anxiety (0.207 SD, 95% CI: 0.01–0.40; p < 0.05) among children whose peers did not wear glasses, whereas effects were nonsignificant among those with peers who wore glasses. Finally, Table 5 examines whether baseline severity of visual impairment moderated treatment effects. No interaction terms indicated statistical significance. Even though, as descriptive results, children with moderate-to-severe vision impairment showed increases in general MHT score (0.384 SD, 95% CI: 0.02–0.75; p < 0.05), learning anxiety (0.401 SD, 95% CI: 0.04–0.77]; p < 0.05), and self-blame tendency (0.351 SD, 95% CI: −0.39–0.74; p < 0.10), while children with mild impairment showed less statistically detectable effects. Mechanism analysis We explored four intermediate domains: children’s perceptions of eyeglasses, vision-care knowledge, academic performance, and parent–teacher behavior, to understand potential pathways through which the intervention may relate to mental health outcomes. These analyses are descriptive and do not constitute formal causal mediation. Table A4 shows the overall ITT effects on these intermediate outcomes. Children in the intervention group reported more positive perceptions of eyeglasses (e.g., greater agreement that glasses help with studying ( P < 0.001) and disagreement that vision worsens after wearing eyeglasses ( P < 0.001)) and demonstrated higher scores on all five vision-care knowledge items (all p < 0.05), along with increased parental support for glasses and teacher–parent communication regarding children’s vision. We further examined whether these intermediate outcomes differed by teacher support, parental glasses wear, peer glasses wear, or baseline severity of visual impairment. For teacher support (Tables 6 , 7 and 8 ), none of the interaction effects were statistically significant, indicating no detectable heterogeneous treatment effects. Nevertheless, subgroup-specific estimates suggest distinct descriptive patterns. Among children whose teachers supported glasses wear, the intervention was associated with more favorable perceptions (e.g., increased belief that glasses help studying and reduced worry about worsening vision; several p < 0.05) and greater vision-care knowledge and parental support (multiple p < 0.001). By contrast, children whose teachers did not support glasses wear showed little change across these domains. Table 6. The heterogeneity effect of vision care service on perception of glasses by teacher support for wearing Variables Endline perception of glasses Classmates be teased for wearing glasses Glasses help studying Easy to adapt to glasses Worry that vision worsens after wearing glasses Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment 0.051 0.043 0.073 -0.072 [-0.472, 0.573] [-0.383, 0.468] [-0.209, 0.355] [-0.344, 0.200] Teacher support (0 = no, 1 = yes) -0.004 0.065 0.214** -0.022 [-0.135, 0.126] [-0.097, 0.227] [0.054, 0.374] [-0.260, 0.216] Treatment × Teacher support -0.032 0.175 -0.034 -0.054 [-0.554, 0.489] [-0.256, 0.605] [-0.326, 0.258] [-0.371, 0.264] Baseline general MHT YES YES YES YES Control variables YES YES YES YES District FE YES YES YES YES Observations 616 616 401 400 Pseudo R-squared 0.060 0.135 0.068 0.080 Treatment effect among children with teacher support 0.018 0.217*** 0.039 -0.126* [-0.084, 0.121] [0.120, 0.315] [-0.067, 0.145] [-0.240, -0.012] Open in a new tab Notes: *** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1 Table 7. The heterogeneity effect of vision care service on knowledge of glasses by teacher support for wearing Variables Endline knowledge of glasses Eye exercise treats myopia Glasses correct myopia Glasses help one see clearly Glasses cause worse vision Pupils are too young to wear glasses Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment -0.188 0.209 -0.001 -0.048 -0.068 [-0.520, 0.145] [-0.286, 0.705] [-0.254, 0.253] [-0.289, 0.193] [-0.515, 0.380] Teacher support (0 = no, 1 = yes) 0.043 0.074 -0.049 -0.008 -0.027 [-0.128, 0.213] [-0.048, 0.195] [-0.156, 0.057] [-0.156, 0.141] [-0.136, 0.081] Treatment × Teacher support -0.118 0.007 0.137 -0.115 0.025 [-0.439, 0.204] [-0.488, 0.502] [-0.125, 0.400] [-0.363, 0.132] [-0.436, 0.487] Baseline general MHT YES YES YES YES YES Control variables YES YES YES YES YES District FE YES YES YES YES YES Observations 615 616 615 614 614 Pseudo R-squared 0.146 0.099 0.097 0.085 0.044 Treatment effect among children with teacher support -0.305*** 0.216*** 0.136*** -0.163*** -0.042 [-0.405, -0.205] [0.130, 0.302] [0.075, 0.198] [-0.229, -0.098] [-0.121, 0.037] Open in a new tab Notes: *** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1 Table 8. The heterogeneity effect of vision care service on math score and parents-teacher behavior by teacher support for wearing glasses Variables Endline standard math score Endline parents and teacher behavior Parental support for glasses Teacher and parent discuss child’s vision Coeff [C.I.] Coeff [C.I.] Coeff [C.I.] Treatment -0.361 0.134 0.017 [-1.369, 0.647] [-0.205, 0.473] [-0.320, 0.353] Teacher support (0 = no, 1 = yes) 0.171 0.069 -0.024 [-0.144, 0.485] [-0.038, 0.176] [-0.182, 0.135] Treatment × Teacher support 0.481 0.013 0.068 [-0.544, 1.506] [-0.324, 0.350] [-0.270, 0.406] Baseline general MHT YES YES YES Control variables YES YES YES District FE YES YES YES Observations 616 616 616 Pseudo R-squared/R-squared 0.330 0.080 0.045 Treatment effect among children with teacher support 0.12 0.147*** 0.085† [-0.115, 0.355] [0.052, 0.243] [-0.011, 0.180] Open in a new tab Notes: *** p < 0.001 ** p < 0.01, * p < 0.05, † p < 0.1 Similarly, interaction terms were not statistically significant in parental, peer, or severity subgroups (Tables A5 – A7 ), providing no formal evidence of moderation. Within these constraints, descriptive estimates suggest that children with parental or peer modeling of glasses wear experienced comparatively larger improvements in perceptions, knowledge, and parental support, whereas children without these supports exhibited smaller changes. For children with moderate-to-severe visual impairment, subgroup differences were modest and broadly aligned with the null interaction tests. Robustness analysis Across a series of robustness checks, the direction and magnitude of the estimated treatment effects remained generally consistent with the main results shown in Table A8 . First, the unadjusted ITT models without covariates or district fixed effects (Columns 1–4) produced positive but imprecise estimates of the intervention’s effect on general MHT score and learning anxiety, with confidence intervals overlapping the main estimates. Second, when baseline mental health scores were included as controls (Columns 5–8), the treatment coefficients for general MHT score and learning anxiety stayed positive and similar in size (0.175 SD and 0.183 SD, respectively), though with wide confidence intervals. Finally, inverse-probability-weighted regressions addressing potential attrition bias (Columns 9–12) showed larger treatment effects, particularly for general MHT score (0.316 SD, 95% CI: 0.012–0.620) and learning anxiety (0.355 SD, 95% CI: 0.045–0.665). Estimates for self-blame tendency and physical anxiety remained small and statistically nonsignificant across all analyses. Overall, these robustness checks suggest that the main findings are not affected by covariate adjustment, baseline controls, or differential attrition. Discussion This study evaluates the impact of a randomized controlled trial of a vision care program designed to improve visual acuity and academic performance on the mental health of migrant children in primary schools in eastern China. The results indicate that the intervention increased anxiety among migrant children, particularly learning anxiety. Although we did not find any statistically significant moderators, the program was associated with larger increases in anxiety among children whose teachers did not support wearing glasses, children whose parents did not wear glasses, children whose peers did not wear glasses, and children with moderate-to-severe visual impairment at baseline. These exploratory findings suggest that evaluations of physical health interventions should consider the sociocultural contexts in which they are implemented. Although large-scale vision interventions in low- and middle-income countries consistently report academic benefits [ 4 , 7 , 43 ], far fewer studies have examined factors that mitigate anxiety associated with eyeglasses wear. Considering the often intense peer competition and high expectations from teachers in Chinese classrooms, the common stereotype associating glasses with intelligence may cause stereotype threat and increase the pressure to perform well academically. For migrant children, who already face structural disadvantages in education, wearing glasses could further increase learning anxiety. Our study shows that the anxiety associated with wearing eyeglasses varied among children in different social environments. For instance, children who did not have eyeglasses-wearing peers experienced stronger anxiety after receiving eyeglasses, a finding consistent with stigma theory, which states that visible markers of difference can activate stereotypes, negative social evaluation, or increased self-consciousness [ 10 , 11 ]. Several studies report that school-age children worry about changes in appearance when wearing glasses and sometimes experience teasing or fear of being judged by peers or teachers [ 13 – 15 ]. These results also align with the social ecological model, which emphasizes that child development is shaped by interactions among family, school, and broader social contexts [ 52 ]. Our finding that support from teachers for wearing eyeglasses mitigated children’s anxiety after the intervention is consistent with literature showing that teacher expectations and support influence children’s confidence, perceived competence, and psychological safety [ 26 , 53 ]. Similarly, peer norms influence engagement in health behaviors and emotional adjustment [ 31 ]. Children whose peers or parents already wear glasses are more likely to view wearing glasses as normal, which could reduce uncertainty or fear of negative judgment. Migrant children in China have well-documented emotional and behavioral vulnerabilities compared with both urban registered children and left-behind children [ 33 , 34 , 54 , 55 ]. Our findings show that policies to improve access to health care are more effective when supported by information, education, and programs to strengthen social support networks for the recipients. Migrant, refugee, and internally displaced children often face disrupted social networks, limited access to health services, and stigmatization by others, which may influence their attitudes toward health programs [ 56 – 58 ]. The mechanisms identified in our study suggest that improving healthcare knowledge and awareness among teachers and parents could help children feel more comfortable wearing eyeglasses. Additionally, pairing optical correction interventions with anti-stigma education and peer champion programs could help reduce the stigma associated with wearing eyeglasses. These strategies could guide the delivery of other physical health interventions that involve visible markers of difference. Two alternative explanations for our results deserve mention. First, receiving glasses may have increased children’s perceived performance pressure if they believed teachers expected better academic results after correction. Second, the intervention itself might have raised children’s awareness of their vision problems, creating measurement reactivity that could temporarily boost anxiety. Although our study primarily focuses on mental health outcomes, the intervention could also affect refractive error correction and academic performance, which might then influence children’s mental responses. Previous studies have demonstrated that providing corrective eyeglasses improves visual acuity and reduces learning barriers, especially in subjects like mathematics that rely heavily on blackboard work and visual engagement [ 4 , 7 ]. Better academic performance and fewer learning difficulties may help decrease certain types of school-related stress and enhance overall mental well-being [ 59 ]. However, neither of these explanations accounts for why increased anxiety occurred only among children without supportive teachers, parents, or peers, suggesting that social-contextual mechanisms, rather than optical correction alone, may more plausibly to be involved. Migrant families in China also have limited access to healthcare services and public schools in cities [ 32 , 60 ]. This means that, compared with children born in urban areas, migrant children are less likely to get regular health examinations, receive suggestions to wear eyeglasses from ophthalmologists, or attend public schools with trained nurses and primary care physicians. Without active intervention from health professionals, they may be especially influenced by peer norms and teachers’ expectations regarding wearing glasses. Although this study took place a decade ago, the social challenges migrant children face still exist, and the implications regarding equity and psychosocial support remain highly relevant. Taken together, the findings suggest a need to rethink school-based vision care. The main issue is not whether glasses cause anxiety but how the social environment influences the psychological consequences of wearing them. This highlights the importance of considering social and emotional factors when designing school-based physical health programs. Policy and practice implications The findings are directly relevant to designing school-based healthcare programs in LMICs. First, teacher engagement is essential. Teachers act as key gatekeepers for school health initiatives. Brief, scalable teacher training modules that explain refractive error, the importance of glasses, and strategies to prevent unintentional stigma could significantly reduce psychosocial harm. Second, include anti-stigma and anti-bullying components. Vision health programs could incorporate class discussions, peer-champion campaigns, or guided activities that portray glasses as normal, positive, and academically helpful tools. Third, enhance light-touch parental engagement. Parent information sheets, short workshops, or messaging campaigns may reinforce positive role modeling and lessen children’s worries about appearance or academic expectations. Fourth, add psychosocial measures to future trials. Routine monitoring of glasses adherence, comfort, teasing or bullying, and stigma would allow early detection of unintended harms and better understanding of underlying mechanisms. Overall, these recommendations highlight that improving children’s vision requires not only optical correction but also a socially supportive environment. Strengths, limitations, and future research Several limitations should be acknowledged. The six-month follow-up period restricts understanding of long-term mental health trajectories. The study did not include direct measures of teasing, stigma, adherence, or lens comfort, which limits conclusions about specific mechanisms. Although the setting is relevant for migrant children, it may differ from current urban schools in China or other countries. Future research should include process measures, track children over longer periods, evaluate programs with psychosocial components, and explore how teacher-student and parent-child relationships influence mental health responses to health interventions. Conclusion This study shows that school-based vision care programs can unintentionally increase anxiety among visually impaired migrant children, especially when they lack support from teachers, parents, or peers. The findings reveal that physical health interventions operate within social systems, and their psychological effects depend on how children interpret the intervention in these contexts. Effective health programs for children therefore need to address both optical correction and the social factors that influence how children experience the treatment. Supplementary Information Below is the link to the electronic supplementary material. Supplementary Material 1 (74.1KB, docx) Acknowledgements We would like to acknowledge the great effort of the enumerators who joined this project. We give special thanks to the staff from Zhongshan Ophthalmic Center at Sun Yat-sen University for their invaluable guidance and advice. Author contributions Y. W. conducted the statistical analysis and drafted the manuscript. C. L. supervised the analyses and writing processes. H. Z. reviewed the draft and edited the entire manuscript. Y. M. contributed to data analysis and the interpretation of results. All authors read and approved the final manuscript. Funding The free eyeglasses used in this study were supplied by OneSight, Luxottica-China, producers of frames and lenses in China, who also provided financial support for the study. We are also grateful for financial and technical support from Essilor, Caterpillar, BHVI and CLSA, which do not have award/grant numbers. Data availability Data are available on reasonable request. Declarations Ethics approval and consent to participate The trial in this paper was approved by the Institutional Review Boards of Stanford University (Palo Alto, California, USA) and Zhongshan Ophthalmic Center, Sun Yat-sen University (ZOC, Guangzhou, China). At least one parent provided written informed consent for each child to participate. The principles of the Declaration of Helsinki were adhered to throughout. Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Burton MJ, Ramke J, Marques AP, Bourne RRA, Congdon N, Jones I, et al. The Lancet Global Health Commission on Global Eye Health: vision beyond 2020. Lancet Glob Health Elsevier. 2021;9:e489–551. 10.1016/S2214-109X(20)30488-5. [ Google Scholar ] 2. National Health Commission of China. 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