Article Text

Original research
Barriers and facilitators to using ophthalmic clinical health services following school vision screening: a mixed-methods study
  1. Pingping Lyu1,
  2. Jiaojiao Shi1,
  3. Jingwen Hu1,
  4. Jingjing Wang2,
  5. Xiangui He2,
  6. Huijing Shi1
  1. 1Department of Maternal, Child and Adolescent Health, School of Public Health, Fudan University, Shanghai, Shanghai, China
  2. 2Shanghai Eye Disease Prevention and Treatment Center, Shanghai, Shanghai, China
  1. Correspondence to Huijing Shi; hjshi{at}fudan.edu.cn

Abstract

Objective To identify determinants of the utilisation of ophthalmic clinical health services among students who failed school vision screening.

Methods This study employed a sequential explanatory mixed methods design, underpinned by Andersen’s Behavioural Model of Health Service Utilisation. Data were initially gathered through interviews with 27 stakeholders—comprising 5 ophthalmologists, 7 community doctors, 7 public health professionals and 8 teachers. The qualitative insights informed the construction of a questionnaire, which subsequently garnered responses from 6215 participants. Qualitative data underwent thematic analysis with NVivo V.12, while quantitative data were analysed using multivariable multinomial logistic regression in SAS V.9.4. Data integration was performed using the Pillar Integration Process for a deductive, evidence-based synthesis of findings.

Results The research revealed that students attending vision demonstration schools and receiving encouragement from schools or communities to access clinical ophthalmic services demonstrated higher adherence to referral (OR=1.66, 95% CI 1.30 to 2.12; OR=1.54, 95% CI 1.33 to 1.80). Conversely, older students and those from higher-income families exhibited lower adherence rates (OR=0.31, 95% CI 0.23 to 0.44; OR=0.34, 95% CI 0.25 to 0.46). Moreover, students with less urgent medical needs were more likely to adhere to referrals compared with those needing immediate referrals (OR=1.24, 95% CI 1.06 to 1.45).

Four pillars emerged: (a) adherence decreased with age, (b) financial constraints did not pose an obstacle, (c) public health services played a critical role, (d) referral urgency did not linearly correlate with adherence.

Conclusion The utilisation of ophthalmic clinical health services following vision screening failure in students is significantly influenced by public health services provided by schools or communities, such as prompting those with abnormal screening results to access ophthalmic clinical health services.

  • Adolescent Health
  • Health services research
  • Growth
  • Ophthalmology

Data availability statement

Data are available upon reasonable request.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

WHAT IS ALREADY KNOWN ON THIS TOPIC

  • Students who failed the school vision screening are mandated to pursue further assessment at a designated. Despite annual recommendations, adherence rate remains low.

WHAT THIS STUDY ADDS

  • Public health services were the primary determinants of referral adherence among students failing vision screenings, beyond sociodemographic characteristics such as age and family income, and perceived personal need.

  • Vision demonstration schools exhibited significantly higher adherence rates than other schools, and the active encouragement from schools or communities to adhere was a key factor in the utilisation of ophthalmic clinical health services.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

  • The determinants of individual clinical health service utilisation were multifaceted, with prior research focusing predominantly on sociodemographic factors and the availability and accessibility of clinical medical resources, often overlooking the influence of public health entities and their services. Further investigation in this area was warranted.

  • Similar to other health service utilisation surveys, investigations into ophthalmic clinical health service use among students with failed school vision screenings lacked standardised questionnaires and methodologies. However, employing the Andersen’s Model, incorporating mixed methods with both quantitative and qualitative analysis, and synthesising conclusions using the Pillar Integration Process were proven to be scientifically effective.

Introduction

An estimated 1 billion cases of impaired vision or blindness out of 2.2 billion individuals could have been prevented or ameliorated but not handled.1 Vision impairment and blindness in children adversely impact their health, educational outcomes and future prospects.2 The omission of early diagnosis and intervention in paediatric populations can result in irreversible vision loss or blindness.3 Visual impairment manifests as a significant public health issue within developing nations, further compounded by insufficient healthcare services.4 Nevertheless, school-based eye care initiatives hold promise for delivering high-quality, cost-effective visual health services.5 The efficacy of vision screening programmes hinges on comprehensive follow-up care.6

In China, the lack of a standardised national protocol for vision screening and an established referral system has been noted.7 Often, children identified in vision screenings are asymptomatic or in early stages, thus post-screening clinical follow-up rates are often low.8 To improve compliance with clinical ophthalmic services post-screening, it is crucial to identify the underlying factors contributing to the persistently low adherence rates. Decision-making regarding medical consultations or treatments is intricate.9 The Andersen’s Model, established to elucidate healthcare access and utilisation,10 suggests that a convergence of predisposing characteristics, enabling resources and need factors drives healthcare usage.11 Contemporary research into post-vision screening compliance in children is limited,12 with existing studies primarily focusing on parental13 and healthcare system14 determinants.

Health services research demands the examination of multifaceted and multilevel systems, often necessitating both quantitative and qualitative data.15 Therefore, this study employs mixed methods to investigate the comprehensive determinants—spanning individual, familial, educational and healthcare-related factors—that influence the utilisation of ophthalmic services following school-based vision screenings, anchored by Andersen’s Model as the theoretical underpinning.

Methods

Study design

This research was conducted using a mixed-methods framework, incorporating both qualitative (individual in-depth interviews and focus group discussions) and quantitative (survey) methodologies. Mixed methods research synergistically combines the empirical precision of quantitative data with the nuanced context of qualitative insights, offering a robust approach for investigating complex healthcare systems and deepening the analysis in health services research.16

This study used a two-phase sequential explanatory mixed-methods approach, beginning with qualitative interviews to guide the creation of a quantitative survey in the absence of a pre-existing instrument for post-vision screening ophthalmic service utilisation. Subsequently, the survey was deployed to test hypotheses and achieve research goals. This process effectively merges qualitative insights with quantitative rigour, achieving a comprehensive methodological integration.17

Our study employed the validated mixed-method joint display technique known as the Pillar Integration Process (PIP) to effectively integrate quantitative and qualitative data, which was pivotal in deriving conclusions. The PIP consists of four stages—Listing, Matching, Checking and Pillar Building—to systematically reveal emergent themes.18

Phase 1

The study employed purposive sampling to select interviewees, such as ophthalmologists, community and public health centre physicians, and educators.

All included participants play crucial roles in the school eye health programmes. Teachers inform students and parents before the screening, providing student details to community physicians who carry out vision screenings at the school. Subsequently, the physicians send results and referral notifications to the school. Teachers communicate results to students and parents, issuing referrals as necessary. Referred students and parents proceed to designated hospitals for further examinations, with ophthalmologists recording and notifying outcomes to community hospitals. Following this, community physicians input follow-up data into Shanghai child and adolescent visual development records while public health physicians oversee database management and workflow coordination.

Participants must have at least 3 years of experience in their field, be actively involved in the management of eye health, and voluntarily participate. Data collection would be stopped, and interviews would be ended once thematic saturation is achieved. Focus group sessions were hosted at Disease Prevention and Control Centres, while offline individual interviews took place at the informant’s hospital. Online individual interviews were conducted via telephone. All participants provided informed consent prior to the interview, including the permission to be audio-recorded.

Phase 2

Teachers facilitated electronic questionnaires, which parents completed under supervision. This study has obtained consent from the guardians of the research subjects. Collected data were cross-referenced with the Minhang district’s child and adolescent visual development records in Shanghai, encompassing comprehensive demographic and ophthalmological assessment outcomes and physician’s advisement. Analysis identified students failing school vision screenings and recommended for referrals. Utilisation patterns of ophthalmic services among these students were investigated, differentiating between compliant and non-compliant groups. To discern factors influencing ophthalmic service usage, analytical variables were systematically categorised using the Andersen Model.

Study population

Figure 1 shows that in phase 1, the sample comprised 27 informants. In phase 2, a total of 15 615 students were surveyed by questionnaire, of whom 3535 were excluded due to the unavailability of screening records, while 210 were omitted due to duplication, incomplete or aberrant data entries. Hence, the dropout rate for this study was 24.0% (3745/15 615). Among those remaining, 6215 out of 11 870 (52.36%) were recommended for referral, and a total of 6215 students were finally included in the study.

Figure 1

Overview of study population and data integration.

Statistical analyses

Phase 1: qualitative thematic analysis

All the interviews were recorded and transcribed. A thematic analysis was used to systematically code and analyse transcribed interviews through NVivo V.12.

Analysis themes

The interviews adhered to a semi-structured format designed to meet the objectives of the project. The guiding framework included sections on: (a) existing practices in children’s vision health, encompassing screening and referral processes; (b) regional adherence following school vision screening; (c) implications for health service demand; and (d) potential strategies to enhance adherence rate. The 21 items checklist from the Standards for Reporting Qualitative Research was used to inform the qualitative approach of the research.

Phase 2: quantitative variable analysis

Analysis was conducted using SAS software (V.9.4). We summarised descriptive statistics as counts (n) and proportions (%). Distributional disparities in compliance were evaluated using the χ2 test or Fisher’s exact test, as appropriate. Influencing factors were examined across three separate multivariate multinomial logistic regression models. Model 1 exclusively incorporated predisposing factors, while model 2 added an enabling factor. Model 3 was comprehensive, assimilating predisposing, enabling and an additional need factor for analysis. Results are presented as ORs with 95% CIs and associated p values. Statistical significance was set at p<0.05 with two-tailed tests.

Analysis variables

The quantitative survey data were analysed using Andersen’s Behavioural Model, encompassing predisposing, enabling and need factors.19

Dependent variable

In this analysis, adherence to referral was the dependent variable classified into compliant and non-compliant groups. Compliance was defined as having sought ophthalmic evaluation at least once following a screening failure in 2020, with attendance records maintained in the database. Children lost to follow-up were considered non-compliant. The adherence rate was calculated as the number of patients for whom the conclusions of the ophthalmologist were received from the screening institution divided by the number of referred patients.

Independent variables

Predisposing factors encompass demographic characteristics and social structure elements relevant to healthcare utilisation.20 In this study, predisposing factors included age, gender, ethnicity, indigenous habitats and parental occupations.

Enabling factors are conditions that facilitate the reduction of financial and structural obstacles to healthcare access.20 In this investigation, the enabling factors encompassed the annual family income, vision demonstration school, and the public health services provided by schools or community hospitals. Family income (per year) was categorised into ‘low income’ (less than ¥100 000), ‘lower middle income’ (¥100 000–¥300 000), ‘upper middle income’ (¥300 000–¥500 000) and ‘high income’ (¥≥500 000) according to the local economic level.

Need factors pertain to individuals’ subjective healthcare necessities and personal health perception.21 As the questionnaire responses were provided by parents, direct assessment of students’ self-evaluated referral needs and health perceptions was infeasible. Objectively, the study used referrals determined by community doctors, based on vision screening outcomes, as a proxy for evaluating students’ referral requirements. Visual health status was stratified into four categories reflecting the urgency of impairment: (a) routine, (b) urgent, (c) emergency and (d) immediate referral. The specific criteria for these classifications are detailed in online supplemental table S1.

Supplemental material

Data integration

In our study, the first column delineated discrete sections of the questionnaire under investigation. Subsequent questionnaire outcomes were enumerated in the second column. The Matching stage involved columns four and five, where qualitative insights and coding were synchronised with the quantitative data from column two. A comparative analysis of the data across columns two, four and five was then conducted to unveil patterns of congruence, culminating in the Pillar Building stage, where synthesised inferences were consolidated in the third column as foundational themes.22

Results

Qualitative findings

Twenty-two informants engaged in two focus groups, two underwent face-to-face in-depth interviews at their respective hospitals, and another three were interviewed via telephone. The qualitative interviews predominantly featured female informants, comprising 85.2% (n=23) of participants. The predominant share of the cohort possesses senior professional designations.

Seven themes were identified, including referral criteria, adherence rates, workflow, recording and feedback of outcomes, medical resources, health service capacity and medical fees.

Quantitative findings

Characteristics of respondents

The overall screening yielded a referral rate of 52.4%. Among the students recommended for referral, only 16.8% used ophthalmic clinical health services. Table 1 details the demographic profiles of the respondents. A majority (72.7%) were enrolled in primary schools, ages 7–11. The gender distribution was nearly even, with boys constituting 51.6%, and a significant majority, 96.7% (n=6011), were of Han ethnicity, with 41.6% (n=2584) identifying as indigenous residents. Approximately half reported a family income within the ‘lower-middle income’ bracket. The parents of around two-thirds of the participants were in professional or managerial roles. Only a small fraction, 7.5%, attended vision demonstration schools. About 95% of respondents had received formal screening notification, eye health education and results disclosure provided by schools or community hospitals. Furthermore, 60.5% were notified to pursue referrals. Among those referred, 49.5% required routine referral, while 35.5% necessitated an emergency referral.

Table 1

Baseline characteristics of the study participants

Sex, ethnicity and status as indigenous residents were not determinative factors in the utilisation of ophthalmic clinical health services. Students with parents employed in physical labour and those enrolled in vision demonstration schools exhibited higher adherence rates. As family annual income increased, the adherence rate decreased (p<0.001). Additionally, the public health services rendered by school or local communities, alongside the urgency of referrals, were influential parameters in the referral process.

Factors associated with compliance

Table 2 delineates the ORs ascertained from both bivariate and multivariate logistic regression analyses. The results demonstrated a negative correlation between age and service adherence. The likelihood of adherence was higher among students whose parents were engaged in service/labour sectors relative. Enrolment in vision demonstration schools significantly increased the likelihood of adherence to referrals. Interestingly, adherence was inversely related to family annual income. Notification of vision screening from schools or communities, along with health education and adherence reminders, significantly influenced the likelihood of referral compliance. Compared with students requiring emergency referrals, those necessitating urgent referrals exhibited an increased likelihood of attending clinical visits.

Table 2

Multivariable logistic regression analyses of factors associated with adherence

The comprehensive model demonstrated that students enrolled in vision demonstration schools and who received encouragement from their schools or local communities showed increased adherence to referral (OR=1.66, 95% CI 1.30 to 2.12; OR=1.54, 95% CI 1.33 to 1.80). Additionally, older students and students from higher-income families showed lower rates of adherence (OR=0.31, 95% CI 0.23 to 0.44; OR=0.34, 95% CI 0.25 to 0.46). Finally, students with less urgent medical needs were more likely to adhere to referrals compared with those requiring immediate referrals (OR=1.24, 95% CI 1.06 to 1.45).

Integration of qualitative and quantitative findings

Four pillars emerged from the integrated qualitative and quantitative results of the PIP. These were: (a) adherence decreased with age, (b) financial constraints did not pose an obstacle, (c) public health services played a critical role, (d) referral urgency did not linearly correlate with adherence. Table 3 illustrates the integration of the findings and the resulting pillars.

Table 3

A joint display of the connections between the quantitative and qualitative data arising from the study

Discussion

This study employed Andersen’s Model to investigate the characteristics of students who adhere to referral posting school vision screening. The study disclosed an overall adherence rate of 16.80%. The prevalence of visual impairment among students in Shanghai is on a continuous rise.23 Our study’s referral rate was high at 60%, surpassing rates observed in Australia (10%),24 Canada (32.2%),25 Germany (27%),26 New Zealand (14%).27 However, the adherence rate in our setting was markedly lower than in Israel (54.3%),13 Canada (69.9%)25 and Yunnan Province, China (37.4%).7 Vision screening, a pivotal public health intervention, is aimed at the early detection of high-risk individuals and early-stage diseases. Ensuring timely and adequate follow-up is critical for the success of disease prevention and control efforts. To bolster referral adherence, the study identified critical factors, including age, family annual income, public health services and referral urgency based on the student’s individual condition.

Adherence rate decreases with age

The adherence rate shows a marked decrease from preschoolers at 19.4%–18.5% in primary school students, and further to 7.9% in middle school students. Eye diseases such as myopia were considered untreatable and irreversible,28 and it is commonly believed that intervention is effective only prior to the onset of a disease, which leads to a gradual neglect of eye health as individuals age. However, visual development is a dynamic process, and the stage of young adulthood remains a crucial period for visual development.29

Poverty is not a deterrent to referral adherence

Hemptinne et al suggest that the expense is a crucial determinant for parental compliance.30 This study found an inverse relationship between family annual income and adherence rates. Although vision screening is state-funded in China, further ophthalmological evaluations carry additional costs. The study revealed that the expense of a single referral ranged from ¥100 to ¥300, an amount not prohibitive in the study’s regional context. Consequently, economic hardship does not account for low adherence rates; in fact, families facing financial constraints may prioritise their children’s vision health.

Public health services are crucial

Students attending vision demonstration schools or those encouraged to seek referrals by school or community hospitals exhibited notably higher adherence rates. Moreover, encouragement from teachers or community physicians significantly influenced student follow-up post-screening. This highlights the importance of public health to enhance adherence following school vision screenings.

Adherence does not linearly correlate with referral urgency

The adherence rate for immediate referrals was 13.8%, surprisingly lower than for emergency (17.1%), urgent (21.0%) and routine referrals (16.7%). Community doctors interviewed indicated that in practice, stratified management of students according to referral urgency is lacking. Students with rapidly deteriorating vision needing immediate referrals often are less aware than those with better vision, underscoring the importance of tiered management in student eye health.

The study findings indicate that adherence to referral is independent of gender, ethnicity and indigenous status. Likewise, familial financial standing and visual health status does not predict compliance. Consistent with other existing research,31 enhanced governmental, community or school vision health services are pivotal in improving adherence. These results underscore the critical role of public health in advancing vision health among children and adolescents. The public health services, including offering dedicated appointments,32 strengthening health education, conducting follow-up phone calls and involving school nurses in screening programmes, have been shown to boost post-screening referral adherence.7

This study has several limitations. In Shanghai’s school eye health programmes, community doctors refer children to designated hospitals. Only follow-up results from these hospitals are recorded in the database. Medical records from non-designated hospitals are not included. Survey results show that over 80% of revisits occur at designated hospitals, suggesting a 20% follow-up loss. Designated hospitals are public with lower costs, while non-designated hospitals are mostly private with higher expenses. This underlines the study’s conclusion that poverty does not hinder referral adherence. Therefore, despite some loss to follow-up, it does not affect the final conclusion of this study. Additionally, reliance on parental questionnaires may not accurately reflect children’s viewpoints, and a direct appraisal of the students’ self-assessed needs for referral and health perceptions was not possible. Instead, doctor’s recommendations were used to estimate the students’ actual referral needs.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Ethics approval

This study involves human participants and was approved by the Ethics Committee of the School of Public Health, Fudan University, approved this study (approval number IRB#2020-07-0836). Participants gave informed consent to participate in the study before taking part.

References

Supplementary materials

  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Footnotes

  • Contributors PL had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: HS, PL. Acquisition, analysis or interpretation of data: PL, HS, JW. Drafting of the manuscript: PL. Critical revision of the manuscript for important intellectual content: HS, PL, JS, JH. Statistical analysis: PL. Obtained funding: HS, XH. Administrative, technical or material support: HS, XH, JW. Supervision: HS.

  • Funding This study was funded by the Shanghai 3-year action plan to strengthen public health project (GWV-9.1); and Key Discipline Programme of Sixth Round of the Three-Year Public Health Action Plan (Year 2023–2025) of Shanghai, China (GWVI-11.1-32).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.