Knowledge Gaps, Primary Care Provider Counselling, and Barriers to Diabetic Retinopathy Screening Among Adults with Diabetes in Syria: A Multicenter Cross-Sectional Study

Abstract

Background

Diabetic retinopathy (DR) is a leading cause of preventable vision loss, yet retinal screening remains suboptimal in low-resource settings. This study assessed DR-related knowledge, risk perception, screening practices, and barriers among adults with diabetes attending selected healthcare facilities across multiple Syrian regions.

Methods

A multicenter cross-sectional study was conducted from December 2025 to February 2026 in public hospitals in Damascus, Latakia, Homs, and Aleppo. Adults aged ≥18 years with self-reported diabetes were recruited predominantly from diabetes/endocrinology clinics using non-probability sampling. An adapted Arabic questionnaire assessed knowledge (10-item score; adequate ≥6/10), screening, barriers, and provider communication. Bivariate analyses and hierarchical binary logistic regression identified factors associated with adequate knowledge and never screening.

Results

Among 375 participants, the mean knowledge score was 5.97 ± 2.40 and 60.0% had adequate knowledge. Only 57.6% recognized the need for screening despite controlled blood glucose. Although 62.9% reported ophthalmology advice, only 40.0% reported formal referral. Overall, 36.3% had never undergone diabetes-related eye screening; leading barriers were lack of clinician recommendation (47.1%) and absence of visual symptoms (39.0%). PCP counselling/advice was associated with higher odds of adequate knowledge (aOR 1.914, 95% CI 1.113–3.292) and lower odds of never screening (aOR 0.267, 95% CI 0.145–0.492). Adequate knowledge was also associated with lower odds of never screening (aOR 0.432, 95% CI 0.259–0.721), with substantial regional differences after adjustment.

Conclusions

Among adults with diabetes attending selected public hospital clinics in Syria, moderate overall knowledge coexisted with actionable misconceptions and screening gaps. The findings support evaluating interventions to strengthen patient education, clinician counselling, referral pathways, and equitable access to retinal assessment. Hospital-based non-probability sampling limits generalizability.

Introduction

Diabetes mellitus (DM) is a chronic non-communicable disease characterized by insulin dysregulation, resulting in elevated blood glucose levels and progressive multisystem injury. Type 1 and type 2 diabetes are the principal forms and differ in their pathophysiology, clinical course, and management requirements.¹

DM represents one of the most rapidly expanding global health challenges. In 2024, an estimated 589 million adults aged 20–79 years were living with diabetes worldwide, with approximately 43% remaining undiagnosed. The disease imposes a substantial burden through its microvascular and macrovascular complications, contributing to disability, reduced quality of life, premature mortality, and increased healthcare utilization. These consequences place major financial strain on individuals, families, healthcare systems, and governments, particularly in low-income countries.^2,3

Diabetic retinopathy (DR), a microvascular complication affecting the retinal circulation, is a leading cause of preventable vision loss among working-age adults. DR may remain asymptomatic during its early stages but can progress from non-proliferative retinopathy to proliferative disease, while diabetic macular oedema may occur at different stages and can independently threaten central vision. Advanced disease may therefore cause substantial and potentially irreversible visual impairment if not detected and treated promptly.³ Recent meta-analyses estimate that approximately 23% of people with diabetes have some form of DR, while 11% have sight-threatening disease. By 2045, the global burden is projected to reach 160.5 million cases of DR, including 44.82 million cases of sight-threatening DR.^2,4 Consistent with this, Meng et al reported that the number of people blind due to DR increased by 326% between 1990 and 2021, reaching an estimated 1.33 million in 2021, and is projected to rise further to approximately 1.95 million prevalent cases globally by 2035.⁵

Early detection through regular retinal screening is widely recognized as a cost-effective strategy to prevent DR-related vision loss. In parallel, optimizing systemic risk factors, including glycemic control, blood pressure and lipid profile, and preservation of renal function, can reduce diabetes-related complications and help limit retinopathy progression.⁶ Importantly, recommended retinal assessment is not simply symptom-triggered or uniformly annual for every patient. Current guidance recommends an initial comprehensive eye examination at the time of diagnosis for people with type 2 diabetes and approximately 5 years after the onset of type 1 diabetes. Subsequent screening intervals are individualized according to previous retinal findings and overall risk: intervals of 1–2 years may be considered after one or more normal examinations in appropriately controlled diabetes, whereas established, progressive, or sight-threatening retinopathy requires at least annual or more frequent ophthalmic assessment. Individuals with pre-existing diabetes who are pregnant or planning pregnancy require additional surveillance.⁷ This risk-based approach underscores why absence of visual symptoms or apparently good glycemic control should not be interpreted by patients as eliminating the need for retinal assessment.

Despite the availability of effective screening strategies, adherence to recommended retinal screening remains suboptimal worldwide. A recent systematic review reported markedly lower screening uptake in low- and middle-income countries (39.3%) compared with high-income countries (66.9%).⁸ Emerging evidence indicates that screening uptake is influenced by a complex interplay of factors across the patient-, provider-, and health-system-levels, including knowledge and risk perception, counselling and referral practices, and service accessibility and affordability.^8,9 In this context, general awareness that diabetes can affect the eyes should be distinguished from actionable knowledge, such as understanding that DR may be asymptomatic, that screening remains necessary despite apparently adequate glycemic control, and that effective treatments are available, and from the actual uptake of retinal screening. These related but distinct domains may help explain why relatively high awareness does not necessarily translate into preventive eye-care behavior. Interventions targeting these domains have shown meaningful improvements in attendance, highlighting the importance of identifying modifiable, context-specific barriers.⁹

In Syria, prolonged conflict has weakened continuity of healthcare and exacerbated geographic and financial barriers to chronic disease services. The International Diabetes Federation estimates that approximately 2.2 million adults aged 20–79 years in Syria were living with diabetes in 2024, with projections indicating a further increase by 2050.² A prior hospital-based study conducted in Damascus in 2017 reported reasonable general awareness of DR concepts, but low adherence to DR screening, underscoring an important awareness-to-preventive practice gap.¹⁰ However, that evidence was derived from a single-city hospital-based sample during an earlier phase of the Syrian crisis. Contemporary multi-region evidence examining actionable knowledge together with clinician counselling, formal referral, screening behavior, and patient-reported barriers remains limited. Therefore, this multicenter cross-sectional study aimed to assess DR-related knowledge, risk perception, and screening uptake among adults with diabetes across multiple Syrian regions and to examine patient-, provider-, and health-system factors associated with knowledge and diabetes-related retinal screening behavior.

Materials and Methods

Study Design and Setting

This multicenter cross-sectional study assessed the knowledge, risk perception, and practices of adults with diabetes regarding regular eye examinations for diabetic retinopathy (DR), and explored the main barriers that may prevent adherence to diabetes-related eye screening. Data were collected between 2 December 2025 and 3 February 2026 in selected major public hospitals providing diabetes and endocrinology outpatient care in Damascus, Latakia, Homs, and Aleppo. The study is reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies; the completed checklist is provided as a Supplementary File 1.¹¹

Sampling Strategy

A multistage non-probability sampling approach was used. First, governorates were purposively selected to ensure geographic representation and feasibility of coordination. Second, within each included governorate, high-volume public hospitals were selected purposively because of their central role in providing diabetes care to patients from diverse demographic and socioeconomic backgrounds. Third, eligible adults with diabetes attending endocrinology and diabetes outpatient clinics were recruited consecutively during clinic hours throughout the study period; thus, eligible patients presenting in sequence were invited to participate. A very small supplementary convenience component was recruited electronically through the investigators’ personal networks using the same eligibility criteria and questionnaire; the great majority of participants were recruited through the participating clinics.

The target sample size was approximately 384 participants. This was estimated using a conservative single-population proportion approach assuming a 95% confidence level, a 5% absolute margin of error, and a population proportion of 50%, which maximizes the required sample size when the expected prevalence is uncertain. Given the large population of adults living with diabetes in Syria, finite-population correction had a negligible effect on the resulting estimate.

Because governorates and hospitals were purposively selected and recruitment was non-probability based, selection bias could not be completely eliminated. Geographic inclusion of multiple regions and consecutive recruitment within participating clinics were used to broaden participant representation and reduce discretionary selection within sites.

Study Population

The target population comprised Syrian adults aged 18 years or older with self-reported diabetes mellitus (type 1, type 2, or unknown type). Individuals with gestational diabetes, diabetes duration of less than 6 months, and those with cognitive impairment that precluded informed consent or reliable questionnaire completion were excluded. An initial screening item was used to confirm diabetes status.

Across the merged data-collection sources, 387 questionnaire responses were recorded before final data cleaning. All responses underwent eligibility and data-quality screening using the same criteria. Twelve records were excluded because of failure to meet eligibility requirements, duplicate submission, or substantial response inconsistencies or incompleteness that precluded reliable analysis, leaving a final analytic sample of 375 participants.

Study Variables and Measurements

A self-administered questionnaire was used to collect data. The instrument consisted predominantly of closed-ended items and was culturally adapted from a previously validated questionnaire used in a published cross-sectional Saudi study.¹² Most of the original content was retained, while a small number of questions and response options were added or expanded to reflect the objectives of the present study and the Syrian healthcare context.

Questionnaire wording was translated and reviewed by bilingual medical students, and several members of the research team independently cross-checked the wording to ensure linguistic clarity and preservation of the intended conceptual meaning. Discrepancies or unclear wording were resolved through discussion within the research team. The adapted questionnaire was subsequently reviewed by the senior academic supervisor for clarity, relevance, and contextual appropriateness. A separate formal validation or pilot sample was not undertaken; instead, questionnaire comprehensibility and response quality were monitored continuously during field data collection, and minor wording clarifications were made where necessary without altering the underlying constructs being assessed.

Study measures included sociodemographic characteristics, diabetes-related factors (including type and duration of diabetes, self-care practices, and comorbidities), and eye-related variables focused on diabetes-related eye screening practices. Eye-related measures included self-reported eye disease and its type, history of any eye examination (ever), diabetes-related eye screening status, time interval from diabetes diagnosis to the first diabetes-related eye visit, and eye-screening frequency since diabetes diagnosis.

Perceived barriers to diabetes-related eye screening were assessed among participants who reported never having diabetes-related eye screening using a list of potential reasons (multiple responses allowed). Perceived need for DR screening was assessed using two items evaluating participants’ beliefs about the need for an eye check-up under conditions of good vs poor glycemic control.

Provider communication was assessed using four items on whether the primary care provider (PCP) discussed diabetes-related eye complications and follow-up, advised an ophthalmology visit, and/or provided a formal referral; these were also summarized into a composite indicator of any PCP counselling/advice.

Knowledge about DR and screening was assessed using 10 statements with Yes/No/do not know responses; correct answers were summed to generate a knowledge score (0–10), with higher scores indicating better knowledge. Adequate knowledge was defined a priori as a score of ≥60% correct (≥6/10 correct). Internal consistency of the 10-item knowledge scale was evaluated using Cronbach’s alpha, and the score was moderate (Cronbach’s α=0.698).

For descriptive presentation and figures, the time interval from diabetes diagnosis until the first diabetes-related eye visit was collapsed into never screened, <1 year, and ≥1 year.

Data Collection Process

The questionnaire was distributed primarily in paper form by trained data collectors. For clinic-based recruitment, data collection took place face-to-face in a private room during clinic hours within each participating facility. The small supplementary electronic component used the same questionnaire wording and eligibility criteria as the clinic-based survey.

All participants were informed about the study’s objectives and the academic use of the data, and any questions regarding the study were addressed before questionnaire completion. The questionnaire was primarily self-administered; however, for illiterate or visually impaired participants, trained data collectors read the items verbatim and recorded the responses without interpretation.

Participation was voluntary, and participants were informed that they could withdraw at any time without affecting the quality or continuity of their medical care. Written or verbal informed consent was obtained from all participants before enrollment. The questionnaire was anonymous, and no personal identifiers were collected to ensure confidentiality.

To minimize interviewer influence and improve data quality, data collectors followed a standardized protocol across all sites and were instructed not to influence participants’ responses. Data quality was monitored throughout the collection period, with responses reviewed for eligibility, completeness, internal consistency, and obvious data-entry problems before creation of the final analysis dataset. The use of standardized wording, verbatim assistance when required, anonymous data collection, and uniform eligibility criteria was intended to reduce interviewer and information bias across recruitment settings.

The questionnaire required approximately 10–15 minutes to complete.

Statistical Analysis

Analyses were performed using IBM SPSS Statistics for Windows, version 30.0 (IBM Corp., Armonk, NY, USA). Categorical variables were summarized as n (%), whereas the knowledge score was summarized using mean (SD) and median (IQR), alongside theoretical and observed ranges. For region-based figures, percentages were calculated within each region. The variables included in the final analyses were complete for all 375 participants; therefore, no statistical imputation for missing data was required.

Bivariate associations between predictors and (1) adequate knowledge and (2) never having diabetes-related eye screening were examined using Pearson’s χ² tests, with effect sizes reported as Cramer’s V.

Two hierarchical binary logistic regression models were fitted. Candidate predictors and their hierarchical ordering were selected according to the study objectives, conceptual relevance, temporal interpretability, and model parsimony rather than solely according to statistical significance in the bivariate analyses.

For the adequate-knowledge model, predictors were entered in three blocks: sociodemographic characteristics (age group, sex, and region), followed by presence of any chronic disease, and then main information source and PCP counselling/advice.

For the never-screening model, a deliberately parsimonious four-block structure was used to limit model complexity and reduce the risk of overfitting: sociodemographic characteristics (age group, educational level, and region), followed by diabetes duration, PCP counselling/advice, and adequate knowledge. The final model contained 13 slope parameters for 136 never-screening events, corresponding to approximately 10.5 events per parameter. Variables with greater temporal ambiguity, conceptual overlap with retained predictors, or comparatively peripheral relevance to the primary screening outcome were not included in the final parsimonious model.

Categorical predictors were entered using indicator coding with prespecified reference categories. Multicollinearity among candidate predictors was assessed before final model estimation using tolerance and variance inflation factor diagnostics.

Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were reported. Block-wise improvement was assessed using likelihood-ratio χ² change, and final model performance was evaluated using the Omnibus test, −2 log-likelihood, Nagelkerke R², and the Hosmer–Lemeshow goodness-of-fit test, with overall classification statistics reported for the final models. Cronbach’s alpha was calculated to assess the internal consistency of the 10-item knowledge scale.

Two-sided p-values <0.05 were considered statistically significant.

Results

Among 375 participants, the most common age groups were 50–59 years (25.9%), 18–39 years (25.6%), and 60–69 years (24.0%). Males comprised 53.9% of the sample, and most participants were married (68.5%). Nearly half reported no formal/basic education (45.9%) and a moderate economic status (48.0%). Participants were most commonly from the Coastal region (32.0%) and Damascus and Rural Damascus (30.1%). Type 2 diabetes was the most frequently reported diabetes type (53.6%), while 20.3% did not know their diabetes type. Diabetes duration was less than five years in 115 participants (30.7%), five to ten years in 91 (24.3%), and more than ten years in 169 (45.1%). A first-degree family history of diabetes was reported by 58.9%, and 42.7% were current smokers. More than half reported at least one chronic disease (56.8%); hypertension (44.3%) was the most common comorbidity. Regarding diabetes management, 48.0% reported lifestyle-based control (diet/exercise), 59.5% used oral medications, and 39.7% used insulin. Most participants reported low-frequency blood glucose monitoring (62.4%) (Table 1).

Table 1.

Sociodemographic and Diabetes-Related Characteristics, Comorbidities, and Self-Care (N=375)

Characteristic	Category	n (%)
Age group (years)	18–39	96 (25.6)
	40–49	71 (18.9)
	50–59	97 (25.9)
	60–69	90 (24.0)
	≥70	21 (5.6)
Gender	Male	202 (53.9)
	Female	173 (46.1)
Marital status	Single	76 (20.3)
	Married	257 (68.5)
	Previously married (divorced/widowed)	42 (11.2)
Educational level	No formal/Basic	172 (45.9)
	High school	87 (23.2)
	University or higher	116 (30.9)
Economic status	Low	78 (20.8)
	Moderate	180 (48.0)
	Good/Excellent	117 (31.2)
Region	Damascus and Rural Damascus	113 (30.1)
	Coastal (Latakia/Tartus)	120 (32.0)
	Central (Homs/Hama)	93 (24.8)
	Other (North/East/South)	49 (13.1)
Diabetes type	Type 1 diabetes	98 (26.1)
	Type 2 diabetes	201 (53.6)
	Do not know	76 (20.3)
Duration of diabetes	<5 years	115 (30.7)
	5–10 years	91 (24.3)
	>10 years	169 (45.1)
Family history of diabetes	No	68 (18.1)
	Yes (first-degree relatives)	221 (58.9)
	Yes (other relatives)	86 (22.9)
Current smoking	No	215 (57.3)
	Yes	160 (42.7)
Any chronic disease	No	162 (43.2)
	Yes	213 (56.8)
Hypertension	Yes	166 (44.3)
Dyslipidemia	Yes	86 (22.9)
Heart disease	Yes	73 (19.5)
Kidney disease	Yes	32 (8.5)
Rheumatologic disease	Yes	39 (10.4)
Lifestyle control (diet/exercise)	Yes	180 (48.0)
Oral medications	Yes	223 (59.5)
Insulin	Yes	149 (39.7)
Blood glucose monitoring	Low (unwell/monthly)	234 (62.4)
	Weekly	71 (18.9)
	≥Daily	70 (18.7)

Notes: Data are n (%); percentages use N=375.

Almost half of participants reported having an eye disease (48.3%). Most had ever undergone an eye examination for any reason (75.5%). Diabetes-related eye screening was reported by 63.7%, while 36.3% had never been screened due to diabetes. Similarly, 36.3% reported never visiting an eye doctor due to diabetes; among those who did, the time to first diabetes-related eye visit was most commonly within 1–3 years (20.0%) or <1 year (18.7%), with 17.3% reporting a delay of >5 years. Since diabetes diagnosis, 36.3% reported never having a diabetes-related eye examination, and 19.2% reported a single examination. Primary care engagement was variable: 69.6% reported being informed by their PCP that diabetes can affect the eyes, 62.9% reported receiving advice to visit an ophthalmologist, and 40.0% reported a formal referral for an eye examination. Most participants agreed that eye check-ups are needed when glucose is poorly controlled (79.5%), while 57.6% agreed they are still needed when glucose is well-controlled (Table 2).

Table 2.

Eye Status, Eye Examinations, Diabetes-Related Eye Screening, and Provider Interaction (N=375)

Characteristic	Category	n (%)
Self-reported eye disease	No	194 (51.7)
	Yes	181 (48.3)
Eye disease types*	Refractive error	94 (25.1)
	Cataract	48 (12.8)
	Glaucoma	22 (5.9)
	Diabetic retinopathy	34 (9.1)
	Unspecified/unknown	16 (4.3)
Ever had an eye examination	No	92 (24.5)
	Yes	283 (75.5)
Diabetes-related screening	Ever screened	239 (63.7)
	Never screened	136 (36.3)
Time to first diabetes-related eye visit	Never	136 (36.3)
	<1 year	70 (18.7)
	1–3 years	75 (20.0)
	4–5 years	29 (7.7)
	>5 years	65 (17.3)
Eye-exam frequency since diagnosis	Never	136 (36.3)
	Once	72 (19.2)
	Every few years	72 (19.2)
	About once per year	37 (9.9)
	More than once per year	33 (8.8)
	Do not remember	25 (6.7)
PCP mentioned need for DR follow-up	Yes	210 (56.0)
PCP informed that diabetes can affect eyes	Yes	261 (69.6)
PCP advised ophthalmology visit	Yes	236 (62.9)
Formal PCP referral	Yes	150 (40.0)
Need check-up with well-controlled glucose?	Agree	216 (57.6)
	Disagree	60 (16.0)
	Do not know	99 (26.4)
Need check-up with poorly controlled glucose?	Agree	298 (79.5)
	Disagree	22 (5.9)
	Do not know	55 (14.7)

Note: *Multiple responses allowed.

Among participants who reported never having diabetes-related eye screening (n=136), the most frequently reported reasons were lack of doctor recommendation (47.1%) and absence of symptoms/visual problems (39.0%), followed by not enough time (16.9%), cost/financial barriers (16.9%), and perceiving screening as not necessary when glucose is well controlled (16.2%). Awareness of specific retinal examination modalities varied: 52.8% reported a dilated retinal exam, 23.2% fundus photography, and 10.7% OCT, while 17.9% reported never hearing of any specific examination. For treatment modalities, laser was most commonly reported (43.7%), followed by intravitreal injections (29.6%) and retinal surgery (22.9%); 30.4% reported not knowing any treatment. Recommended screening frequency among those without known eye disease most commonly clustered around every year (28.8%) or every six months (28.3%), while 22.1% endorsed screening only when symptoms occur (Table 3).

Table 3.

Information Sources, Awareness of Screening/Treatment Modalities, Recommended Exam Frequency, and Barriers to Screening (N=375)

Domain	Item/Response	n (%)
Main information source	Doctors/healthcare professionals	137 (36.5)
	Internet/social media	94 (25.1)
	Family/friends/self-learning	114 (30.4)
	No information source	30 (8.0)
Examination modalities*	Fundus photography	87 (23.2)
	OCT	40 (10.7)
	Dilated retinal exam	198 (52.8)
	Do not know/not sure	86 (22.9)
	Never heard of specific exam	67 (17.9)
Treatment awareness*	Laser	164 (43.7)
	Intravitreal injections	111 (29.6)
	Retinal surgery	86 (22.9)
	Eye drops only	106 (28.3)
	Do not know	114 (30.4)
Recommended exam frequency	Only with symptoms	83 (22.1)
	Every 2 years	20 (5.3)
	Every year	108 (28.8)
	Every 6 months	106 (28.3)
	Do not know	58 (15.5)
Reasons for never screening (n=136)*	No doctor recommendation	64 (47.1)
	No symptoms/visual problems	53 (39.0)
	Not enough time	23 (16.9)
	Cost/financial	23 (16.9)
	Difficulty accessing eye care	14 (10.3)
	Fear of exam/result/treatment	11 (8.1)
	Discomfort during exam	8 (5.9)
	Many other medical appointments	7 (5.1)
	Lack of knowledge about diabetic eye disease	17 (12.5)
	Lack of knowledge about retinal screening	18 (13.2)
	Perceived unnecessary with good glucose control	22 (16.2)
Barrier domains endorsed*	Lack of knowledge	200 (53.3)
	Cost/insurance	156 (41.6)
	Fear of bad findings	143 (38.1)
	Lack of time	107 (28.5)
	Difficulty accessing eye care	95 (25.3)
	Other	1 (0.3)

Note: *Multiple responses allowed.

Adequate knowledge differed significantly by economic status (p=0.002; V=0.186), region (p=0.013; V=0.170), family history of diabetes (p=0.003; V=0.174), main information source (p<0.001; V=0.270), and PCP counselling/advice (p<0.001; V=0.186). Adequate knowledge was highest among participants who cited doctors/healthcare professionals as their main information source (73.0%) and lowest among those reporting no information source (23.3%). Participants reporting PCP counselling/advice had higher adequate knowledge than those reporting none (64.7% vs 42.5%).

Never having diabetes-related eye screening differed by age group (p<0.001; V=0.241), educational level (p=0.035; V=0.134), region (p<0.001; V=0.231), diabetes duration (p<0.001; V=0.241), home blood glucose monitoring frequency (p=0.006; V=0.166), main information source (p=0.002; V=0.203), any PCP counselling/advice (p<0.001; V=0.257), and self-reported eye disease (p<0.001; V=0.351). Never screening was higher among those with shorter diabetes duration (53.0% for <5 years vs 26.0% for >10 years) and among those reporting no PCP counselling/advice (60.0% vs 29.8%). Regionally, never screening was lowest in Damascus and Rural Damascus (19.5%) and higher in the Coastal and Central regions (44.2% and 44.1%, respectively). Participants without self-reported eye disease had substantially higher never screening than those with eye disease (52.6% vs 18.8%).

Adequate knowledge was associated with a lower prevalence of never screening: 29.3% of participants with adequate knowledge had never been screened compared with 46.7% of those with poor knowledge (χ² =11.70, p<0.001; V=0.177) (Table 4).

Table 4.

Bivariate Associations with Adequate Knowledge and Never Having Diabetes-Related Eye Screening (N=375)

Predictor	Category	Adequate Knowledge n (%)	p (V)	Never Screened n (%)	p (V)
Age	18–39	54 (56.3)	0.693 (0.077)	37 (38.5)	<0.001 (0.241)
	40–49	47 (66.2)		39 (54.9)
	50–59	59 (60.8)		36 (37.1)
	60–69	54 (60.0)		21 (23.3)
	≥70	11 (52.4)		3 (14.3)
Gender	Male	112 (55.4)	0.052 (0.100)	78 (38.6)	0.307 (0.053)
	Female	113 (65.3)		58 (33.5)
Marital status	Single	43 (56.6)	0.133 (0.104)	26 (34.2)	0.639 (0.049)
	Married	162 (63.0)		97 (37.7)
	Previously married	20 (47.6)		13 (31.0)
Education	No formal/Basic	96 (55.8)	0.145 (0.101)	65 (37.8)	0.035 (0.134)
	High school	51 (58.6)		39 (44.8)
	University/higher	78 (67.2)		32 (27.6)
Economic status	Low	33 (42.3)	0.002 (0.186)	26 (33.3)	0.830 (0.032)
	Moderate	118 (65.6)		67 (37.2)
	Good/Excellent	74 (63.2)		43 (36.8)
Region	Damascus/Rural Damascus	62 (54.9)	0.013 (0.170)	22 (19.5)	<0.001 (0.231)
	Coastal	63 (52.5)		53 (44.2)
	Central	67 (72.0)		41 (44.1)
	Other	33 (67.3)		20 (40.8)
Diabetes type	Type 1	52 (53.1)	0.207 (0.092)	27 (27.6)	0.109 (0.109)
	Type 2	123 (61.2)		80 (39.8)
	Do not know	50 (65.8)		29 (38.2)
Diabetes duration	<5 years	69 (60.0)	0.475 (0.063)	61 (53.0)	<0.001 (0.241)
	5–10 years	50 (54.9)		31 (34.1)
	>10 years	106 (62.7)		44 (26.0)
Any chronic disease	No	96 (59.3)	0.798 (0.013)	61 (37.7)	0.626 (0.025)
	Yes	129 (60.6)		75 (35.2)
Eye disease	No	119 (61.3)	0.583 (0.028)	102 (52.6)	<0.001 (0.351)
	Yes	106 (58.6)		34 (18.8)
Current smoking	No	129 (60.0)	1.000 (0.000)	74 (34.4)	0.388 (0.045)
	Yes	96 (60.0)		62 (38.8)
Home BG monitoring	Low	142 (60.7)	0.864 (0.028)	96 (41.0)	0.006 (0.166)
	Weekly	43 (60.6)		26 (36.6)
	≥Daily	40 (57.1)		14 (20.0)
Family history	No	36 (52.9)	0.003 (0.174)	30 (44.1)	0.225 (0.089)
	First-degree	148 (67.0)		73 (33.0)
	Other relatives	41 (47.7)		33 (38.4)
Information source	Healthcare professionals	100 (73.0)	<0.001 (0.270)	33 (24.1)	0.002 (0.203)
	Internet/social media	53 (56.4)		43 (45.7)
	Family/friends/self-learning	65 (57.0)		45 (39.5)
	None	7 (23.3)		15 (50.0)
PCP counselling	No	34 (42.5)	<0.001 (0.186)	48 (60.0)	<0.001 (0.257)
	Yes	191 (64.7)		88 (29.8)
Knowledge status	Poor	—	—	70 (46.7)	<0.001 (0.177)
	Adequate	—	—	66 (29.3)

Notes: Data are n (row %). P-values are Pearson χ² tests; V denotes Cramer’s V. Adequate knowledge = ≥6/10.

Hierarchical binary logistic regression was used to identify factors associated with adequate knowledge (≥6/10). The demographic block containing age, sex, and region was not statistically significant overall (χ² (8)=14.540, p=0.069; Nagelkerke R² =0.051), and addition of chronic disease produced essentially no improvement (Δχ² (1)=0.012, p=0.913). Addition of information source and PCP counselling/advice substantially improved the model (Δχ² (4)=34.571, p<0.001). The final model was significant overall (χ² (13)=49.123, p<0.001), with Nagelkerke R² =0.166 and acceptable calibration (Hosmer–Lemeshow χ² (8)=7.188, p=0.516). Overall classification accuracy was 66.4%.

In the fully adjusted model, participants residing in the Central region (aOR 2.339, 95% CI 1.217–4.494, p=0.011) and Other regions (aOR 2.144, 95% CI 1.020–4.509, p=0.044) had higher odds of adequate knowledge than those in Damascus and Rural Damascus. Compared with participants citing doctors/healthcare professionals as their main information source, those relying primarily on the internet/social media (aOR 0.483, 95% CI 0.266–0.876, p=0.017), family/friends/self-learning (aOR 0.495, 95% CI 0.282–0.868, p=0.014), or reporting no information source (aOR 0.117, 95% CI 0.044–0.310, p<0.001) had lower odds of adequate knowledge. PCP counselling/advice was associated with higher odds of adequate knowledge (aOR 1.914, 95% CI 1.113–3.292, p=0.019). Age, sex, and chronic disease were not independently associated with adequate knowledge (Table 5).

Table 5.

Hierarchical Binary Logistic Regression for Adequate Knowledge (N=375)

Predictor	Reference	Block	aOR (95% CI)	p
Age 40–49	18–39	1	1.244 (0.594–2.606)	0.563
Age 50–59	18–39	1	1.087 (0.556–2.127)	0.807
Age 60–69	18–39	1	1.010 (0.492–2.072)	0.978
Age ≥70	18–39	1	0.746 (0.252–2.206)	0.596
Female	Male	1	1.338 (0.847–2.114)	0.212
Coastal	Damascus/Rural Damascus	1	1.138 (0.649–1.996)	0.651
Central	Damascus/Rural Damascus	1	2.339 (1.217–4.494)	0.011
Other region	Damascus/Rural Damascus	1	2.144 (1.020–4.509)	0.044
Any chronic disease	No	2	1.027 (0.607–1.738)	0.921
Internet/social media	Healthcare professionals	3	0.483 (0.266–0.876)	0.017
Family/friends/self-learning	Healthcare professionals	3	0.495 (0.282–0.868)	0.014
No information source	Healthcare professionals	3	0.117 (0.044–0.310)	<0.001
PCP counselling/advice	No	3	1.914 (1.113–3.292)	0.019

Notes: Final model: −2LL=455.636; Omnibus χ² (13)=49.123, p<0.001; Nagelkerke R² =0.166; Hosmer–Lemeshow χ² (8)=7.188, p=0.516; overall classification=66.4%.

A parsimonious hierarchical binary logistic regression was used to identify factors independently associated with never having diabetes-related eye screening. Predictors were entered in four blocks: sociodemographic factors (age, education, and region), diabetes duration, PCP counselling/advice, and adequate knowledge. The final model contained 13 slope parameters for 136 never-screening events. The model was significant overall (Omnibus χ² (13)=92.043, p<0.001), explained 29.8% of the variance on the Nagelkerke scale, and showed acceptable calibration (Hosmer–Lemeshow χ² (8)=8.528, p=0.384). Overall classification accuracy was 74.1%.

In the fully adjusted model, participants aged 60–69 years (aOR 0.427, 95% CI 0.188–0.968, p=0.042) and ≥70 years (aOR 0.157, 95% CI 0.035–0.707, p=0.016) had lower odds of never screening than those aged 18–39 years. Compared with Damascus and Rural Damascus, never-screening odds were higher in the Coastal (aOR 3.258, 95% CI 1.683–6.311, p<0.001), Central (aOR 3.804, 95% CI 1.745–8.292, p<0.001), and Other regions (aOR 3.848, 95% CI 1.701–8.705, p=0.001). Diabetes duration of 5–10 years, compared with <5 years, was associated with lower odds of never screening (aOR 0.384, 95% CI 0.198–0.743, p=0.004), whereas the >10-year category was not independently significant (aOR 0.545, 95% CI 0.282–1.052, p=0.071). PCP counselling/advice was strongly associated with lower odds of never screening (aOR 0.267, 95% CI 0.145–0.492, p<0.001). Adequate knowledge remained independently associated with lower odds of never screening (aOR 0.432, 95% CI 0.259–0.721, p=0.001). Educational level was not independently associated with never screening in the final model (Table 6).

Table 6.

Hierarchical Binary Logistic Regression for Never Having Diabetes-Related Eye Screening (N=375)

Predictor	Reference	Block	aOR (95% CI)	p
Age 40–49	18–39	1	1.462 (0.699–3.056)	0.313
Age 50–59	18–39	1	0.788 (0.387–1.604)	0.511
Age 60–69	18–39	1	0.427 (0.188–0.968)	0.042
Age ≥70	18–39	1	0.157 (0.035–0.707)	0.016
High school	No formal/Basic	1	1.151 (0.611–2.169)	0.663
University/higher	No formal/Basic	1	0.544 (0.293–1.011)	0.054
Coastal	Damascus/Rural Damascus	1	3.258 (1.683–6.311)	<0.001
Central	Damascus/Rural Damascus	1	3.804 (1.745–8.292)	<0.001
Other region	Damascus/Rural Damascus	1	3.848 (1.701–8.705)	0.001
Diabetes duration 5–10 years	<5 years	2	0.384 (0.198–0.743)	0.004
Diabetes duration >10 years	<5 years	2	0.545 (0.282–1.052)	0.071
PCP counselling/advice	No	3	0.267 (0.145–0.492)	<0.001
Adequate knowledge	Poor knowledge	4	0.432 (0.259–0.721)	0.001

Notes: Final model: −2LL=399.160; Omnibus χ² (13)=92.043, p<0.001; Nagelkerke R² =0.298; Hosmer–Lemeshow χ² (8)=8.528, p=0.384; overall classification=74.1% (specificity=86.6%; sensitivity=52.2%).

Figure 1 displays the collapsed time interval from diabetes diagnosis until the first diabetes-related eye examination across Syrian regions (never screened, screened within <1 year, and screened after ≥1 year). Percentages were calculated within each region. The distribution differed significantly by region (Pearson χ² (6)=28.312, p<0.001; Cramer’s V=0.194). Never screening was lowest in Damascus and Rural Damascus (19.5%) and higher in the Coastal (44.2%), Central (44.1%), and Other regions (40.8%). Screening within <1 year was highest in Damascus and Rural Damascus (29.2%) and lowest in the Central region (7.5%) (Figure 1).

Figure 1.

Regional differences in time interval from diabetes diagnosis until first diabetes-related eye examination (N=375).

Figure 2 shows the proportion of participants with adequate knowledge across Syrian regions. Adequate knowledge differed significantly by region (p=0.013; Cramer’s V=0.170), ranging from 52.5% in the Coastal region and 54.9% in Damascus and Rural Damascus to 67.3% in Other regions and 72.0% in the Central region (Figure 2).

Figure 2.

Regional differences in adequate knowledge about diabetic retinopathy and screening (N=375).

Figure 3 summarizes participants’ responses to the 10 knowledge statements related to diabetic retinopathy and eye screening. For each statement, the proportions responding Yes, No, or do not know are presented as percentages of the total sample (N=375).

Figure 3.

Responses to diabetic retinopathy knowledge items among participants (N=375).

Overall knowledge was moderate: the mean score was 5.97 (SD 2.40), the median was 6 (IQR 4–8), and the observed range was 0–10. Overall, 60.0% met the adequate-knowledge threshold (≥6/10). Knowledge was highest for recognition that diabetes can affect the retina (85.9% Yes), that good glycemic control can prevent diabetes-related eye damage (77.1% Yes), and that diabetes can lead to blindness (70.9% Yes). Misconceptions and uncertainty remained common for several items, including endorsement of the statement that eye examinations are needed only when symptoms appear (34.7% Yes) and limited awareness that treatments are available for diabetic retinopathy (42.9% Yes; 48.5% do not know) (Figure 3).

Discussion

In the Syrian context, within a health system affected by prolonged conflict and socioeconomic strain, this multicenter cross-sectional study identified important gaps between diabetic retinopathy knowledge and uptake of diabetes-related eye screening among adults with diabetes attending selected healthcare facilities. Overall knowledge was moderate: the mean score was 5.97/10, and 60.0% of participants met the predefined threshold for adequate knowledge (≥6/10). Nevertheless, 36.3% reported never having undergone diabetes-related eye screening, and important item-specific misconceptions remained. Primary care engagement also appeared incomplete: although 62.9% reported receiving advice to visit an ophthalmologist, only 40.0% reported a formal referral. Taken together, these findings suggest that general knowledge alone does not necessarily translate into preventive eye-care behavior and highlight potentially modifiable gaps in actionable knowledge, clinician counselling, and referral processes.

Knowledge Level and Comparison with the Literature

Overall knowledge about DR in our cohort was moderate, with 60.0% of participants meeting the predefined adequate-knowledge threshold. A Saudi study using a different knowledge instrument reported a median DR knowledge score of 4.5/11, below its designated adequate-knowledge threshold (≥5/11),¹³ while a study from Oman reported excellent awareness of diabetes-related eye complications among 72.9% of participants.¹⁴ Because instruments, scoring systems, populations, and definitions of adequate knowledge differ across studies, these figures should not be interpreted as direct numerical benchmarks. Rather, they illustrate substantial between-setting variation in DR-related knowledge and reinforce the importance of context-specific assessment.

When knowledge items were examined individually, basic awareness was relatively high: 85.9% recognized that diabetes can affect the retina and 70.9% recognized that diabetes can cause blindness. Similar patterns have been reported in Australia, where broad headline concepts were better recognized than specific preventive messages.¹⁵ However, important gaps persisted in actionable knowledge. Notably, 34.7% incorrectly believed that eye examinations are only necessary when symptoms occur, reflecting a clinically problematic symptom-driven approach to care-seeking. This misconception has also been documented in Saudi Arabia (38.3%)¹² and is important because early DR is frequently asymptomatic; relying on symptoms may delay detection until later stages. Limited knowledge of treatment options further reinforces this gap: only 42.9% of participants endorsed that treatments for DR are available, a finding comparable to Syrian crisis-era data (42.7%) and findings from Ethiopia (29.4%) and Hong Kong (17.5%).^10,16,17 Thus, the principal knowledge problem in our sample appears less related to recognition of the general diabetes–eye relationship and more to actionable understanding of asymptomatic disease, available treatment, and the rationale for preventive retinal assessment.

Source of Information and Provider Counselling

Our multivariable analysis suggests that knowledge is shaped not only by patient characteristics but also by healthcare-system contact and the credibility of information sources. Compared with participants who identified doctors or other healthcare professionals as their main information source, those relying on internet/social media, family/friends/self-learning, or reporting no information source had lower adjusted odds of adequate knowledge. Participants reporting PCP counselling/advice also had higher odds of adequate knowledge (aOR 1.914, 95% CI 1.113–3.292). This is consistent with evidence from a previous Damascus study and from Sri Lanka supporting the important role of clinicians, including doctors and nurses, in delivering accurate and actionable messages, improving patient knowledge and screening-related behaviors, and addressing common misconceptions.^10,18

These associations should, however, not be interpreted as demonstrating that counselling itself caused greater knowledge. Patients who have more frequent or higher-quality contact with healthcare services may simultaneously be more likely to receive counselling and to acquire information from professional sources. Provider counselling may therefore function partly as a marker of broader healthcare engagement.

Symptom-Driven Risk Perception and Routine Screening Uptake

A key mismatch in our findings is that perceived need for screening was substantially higher when glucose was perceived as poorly controlled (79.5%) than when it was well controlled (57.6%), suggesting conditional risk appraisal that may delay preventive screening. This symptom- or risk-triggered decision-making is clinically problematic because early DR is commonly asymptomatic and vision loss tends to occur later in the disease course.^3,19 Current recommendations similarly emphasize that retinal assessment should not depend on symptoms alone; the timing and subsequent frequency of examinations instead depend on diabetes type, disease duration, previous retinal findings, pregnancy status, and overall clinical risk.⁷ Therefore, both absence of visual symptoms and apparently satisfactory glycemic control may create false reassurance if patients interpret them as reasons to defer eye assessment.

Screening Practices and Comparison with the Literature

Our screening results indicate a substantial shortfall in retinal screening uptake: 36.3% of participants reported never having undergone diabetes-related eye screening, and only 18.7% reported annual or more frequent examinations. Notably, this proportion is strikingly similar to the crisis-era Damascus hospital study reporting that 37% had never visited an ophthalmologist and only 21.5% had regular eye examinations. Rather than overstating discontinuity, our results suggest that the awareness-to-screening gap observed previously in Damascus may extend beyond a single city and remain relevant in a broader, more recent multicenter Syrian sample. In this sense, the novelty of the present study lies less in overturning earlier findings than in showing that these gaps are not confined to the capital and in identifying potentially modifiable correlates of screening uptake across multiple regions.¹⁰

Recent evidence describes the Syrian health system as fragmented, unevenly resourced, and affected by limited healthcare personnel and marked inequalities in access to care, all of which may weaken continuity of preventive services. In such a setting, retinal screening may be deferred in favor of more immediate medical priorities, even when patients are aware of its importance.²⁰ The broader global pattern is similar: a recent systematic review and meta-analysis reported markedly lower pooled screening adherence in low- and middle-income countries than in high-income settings.⁸ Although differences in screening definitions and outcome measures limit direct numerical comparison, the overall pattern supports the persistence of a screening shortfall in resource-constrained settings.^6,8

At the same time, our 36.3% estimate should not be interpreted as a national prevalence estimate for unscreened diabetes. Because recruitment occurred predominantly among patients already attending selected public diabetes/endocrinology clinics, participants were relatively engaged with healthcare services. Adults with diabetes who do not attend care or face the greatest geographic, financial, or structural barriers may be less likely to undergo screening; consequently, the true community-level screening gap could plausibly be larger than that observed in this clinic-enriched sample.

Factors Associated with Screening and Provider-Level Gaps

A central finding of our multivariable model was that primary care counselling/advice was strongly associated with lower odds of never being screened (aOR 0.267, 95% CI 0.145–0.492). This is consistent with regional evidence that clinician recommendation is an important correlate of screening attendance.^10,21 However, the observation that only 40.0% of participants reported receiving a formal referral despite 62.9% reporting advice to visit an ophthalmologist suggests an important gap between counselling and operational referral.²²

Adequate knowledge also remained independently associated with lower odds of never screening (aOR 0.432, 95% CI 0.259–0.721). This association remained after adjustment for age, educational level, region, diabetes duration, and PCP counselling/advice, supporting the relevance of actionable knowledge to screening behavior. Nevertheless, the cross-sectional design does not establish temporal direction: prior screening itself may expose patients to ophthalmic counselling and thereby improve subsequent knowledge. The relationship between knowledge and screening is therefore likely bidirectional rather than a simple causal pathway.

Age, diabetes duration, and region were also independently associated with screening behavior. Participants aged 60–69 years and ≥70 years had lower odds of never screening than those aged 18–39 years, while participants with diabetes for 5–10 years had lower odds of never screening than those with disease duration <5 years. These patterns may partly reflect accumulated opportunities for contact with diabetes and eye-care services over time. However, the >10-year duration category was not independently significant, indicating that duration alone does not fully account for screening behavior.

More broadly, screening should be conceptualized as a continuum involving recommendation, attendance, retinal assessment, appropriate interpretation, referral where required, and subsequent follow-up rather than as a single isolated event.^22,23 Pragmatic trial evidence suggests that increasing the availability of screening alone may not ensure referral adherence or follow-up completion without structured navigation and referral pathways.^22,23 Variation in healthcare professionals’ guideline knowledge, counselling practices, and referral behavior may further contribute to missed opportunities for early detection.^24–26

Barriers to Screening

The dominant barriers among never-screened participants were lack of physician recommendation (47.1%) and absence of symptoms (39.0%). This pattern closely mirrors findings from a tertiary diabetes center in Jordan²¹ and supports the interpretation that both provider-level missed opportunities and symptom-triggered beliefs contribute to non-attendance.

Importantly, financial and access-related barriers were present but were less frequently identified as immediate reasons for never screening than lack of clinician recommendation or absence of symptoms: cost/financial barriers were reported by 16.9%, and difficulty accessing eye care by 10.3% of never-screened participants. Thus, our findings should not imply that cost and access were the dominant barriers in this sample. Instead, the most commonly reported barriers were potentially modifiable failures of recommendation and symptom-driven perceptions, occurring within a broader environment in which financial and structural constraints remain relevant. In Syria, these constraints are likely intensified by prolonged conflict, economic deterioration, discontinuity of chronic disease follow-up, and documented deficits in ophthalmic infrastructure and subspecialty services.^27,28

Regional Disparities

Regional differences were among the most consistent findings in the screening analysis. After multivariable adjustment, participants from the Coastal, Central, and Other regions had approximately three- to four-fold higher odds of never having diabetes-related eye screening than participants from Damascus and Rural Damascus. These associations persisted after adjustment for age, education, diabetes duration, PCP counselling, and knowledge.

Our observed regional differences in screening uptake are consistent with evidence that screening adherence is socially and geographically patterned, with nonadherence clustering in areas characterized by socioeconomic disadvantage in Geographic Information Systems (GIS)-based analyses.²⁹ These patterns align with the broader concept that unequal access, differing service availability, and variations in care pathways can drive regional gradients in preventive care.^29,30

Notably, regional patterns in knowledge and screening did not move uniformly in the same direction. Participants in the Central and Other regions had higher adjusted odds of adequate knowledge than those in Damascus and Rural Damascus, yet these regions also had markedly higher odds of never screening. This discordance further supports the central theme of an awareness-to-practice gap: comparatively better knowledge within a region does not necessarily overcome structural, referral, or access-related barriers to screening. Because the study did not directly measure regional ophthalmology capacity, travel distance, facility availability, or health-system resources, the mechanisms underlying these geographic differences cannot be determined from our data and warrant further investigation.

Implications for Practice and Policy

Evidence indicates that quality-improvement interventions directed at patients, healthcare providers, and health systems can increase DR screening attendance by clinically meaningful margins.^8,9 The most direct implications of our data concern clinician recommendation, patient education, and referral processes. Given that lack of physician recommendation was the leading reported reason for never screening and that formal referral was reported substantially less often than ophthalmology advice, standardized counselling prompts and clearer referral pathways within routine diabetes care represent particularly relevant targets for evaluation.^9,25

Integration of retinal assessment into diabetes or primary care services may also reduce scheduling and access barriers and is supported by evidence from primary-care-based screening programs.^31,32 However, such models were not evaluated in the present study, and their feasibility, effectiveness, and cost-effectiveness in the Syrian healthcare context require prospective assessment.

Similarly, telemedicine, point-of-care retinal imaging, and AI-assisted screening have potential to reduce geographic and opportunity-cost barriers,^{22,23,32–34} but our study did not assess infrastructure, diagnostic performance, patient acceptability, workforce readiness, or implementation costs in Syria. These approaches should therefore be regarded as possible future strategies rather than direct recommendations arising from the current cross-sectional findings.

Overall, the present results most directly support evaluating interventions that combine actionable patient education with consistent clinician counselling and functioning referral and follow-up pathways, while adapting delivery models to regional service capacity and resource constraints.

Strengths, Limitations, and Generalizability

This study has several strengths. It provides one of the few multi-region assessments of DR-related knowledge and screening behaviors in Syria, includes simultaneous measurement of knowledge, screening-related risk perception, barriers, and provider counselling, and applies multivariable modelling to identify independent correlates of both adequate knowledge and never having been screened. The use of a corrected 10-item knowledge score with assessment of internal consistency, reporting of effect sizes in bivariate analyses, and deliberately parsimonious modelling of never-screening behavior further strengthen the analytical transparency of the study.

The findings should also be interpreted in light of limitations. First, the cross-sectional design does not permit causal inference; associations between counselling, knowledge, and screening could be bidirectional. For example, counselling may promote screening, but patients who are already more engaged with healthcare may also be more likely both to receive counselling and to attend eye examinations.

Second, the multistage non-probability sampling approach, including purposive selection of governorates and hospitals, limits external validity. Recruitment occurred predominantly among patients attending selected public hospital clinics, with only a very small supplementary convenience component recruited electronically. Consequently, the sample should not be considered nationally representative of all adults with diabetes in Syria. Because individuals who are disconnected from healthcare services or face the greatest access barriers were less likely to be captured, knowledge may have been overestimated and the prevalence of never screening underestimated relative to the wider diabetic population.

Third, key variables including diabetes status, clinician counselling, eye disease, and screening history were self-reported, which may introduce recall or social desirability bias. Misclassification of the timing or purpose of previous eye examinations is also possible.

Fourth, although the questionnaire was culturally adapted, linguistically reviewed by bilingual members of the research team, and reviewed by the senior academic supervisor, a separate formal Syrian psychometric validation study or multidisciplinary expert-panel content-validation process was not conducted. Internal consistency of the final 10-item knowledge scale was moderate (Cronbach’s α=0.698), but further validation in independent Syrian samples would strengthen confidence in the instrument’s measurement properties.

In addition, diabetic retinopathy severity was not clinically assessed through retinal examination, imaging, or grading, limiting our ability to relate knowledge and screening behavior to objective retinal disease status.

The regression models were designed primarily to identify explanatory associations rather than to serve as clinical prediction tools. In particular, the adequate-knowledge model explained a modest proportion of outcome variability (Nagelkerke R² =0.166) and had moderate overall classification performance, indicating that relevant determinants of knowledge were likely not fully captured. Residual confounding from unmeasured factors such as healthcare utilization intensity, distance to ophthalmic services, insurance or payment mechanisms, and facility-level availability therefore remains possible.

Finally, differences across studies in healthcare systems, screening definitions, knowledge instruments, and outcome measures constrain direct numerical comparisons; therefore, our comparisons emphasize patterns and plausible mechanisms rather than exact benchmarking.

Conclusion

Among adults with diabetes attending selected public hospital clinics across several Syrian regions, knowledge of diabetic retinopathy was moderate overall, with 60.0% meeting the predefined adequate-knowledge threshold; however, clinically important misconceptions persisted, and 36.3% reported never having undergone diabetes-related eye screening. Lack of physician recommendation and absence of symptoms were the most commonly reported reasons for never screening, while financial and access barriers were present but less frequently cited as immediate reasons.

PCP counselling/advice and adequate knowledge were independently associated with lower odds of never screening, while substantial regional differences remained after multivariable adjustment. The gap between ophthalmology advice (62.9%) and formal referral (40.0%) further suggests an operational discontinuity between counselling and access to eye care. These associations should not be interpreted causally because of the cross-sectional design and the possibility that greater healthcare engagement influences both counselling and screening behavior.

The findings support the need to evaluate interventions that strengthen actionable patient education, standardize clinician counselling, improve referral and follow-up pathways, and reduce regional barriers to retinal assessment within routine diabetes care. Because the study used hospital-based non-probability sampling, the findings should not be generalized to all adults with diabetes in Syria. Prospective and implementation-focused research is needed to determine which screening-delivery strategies are feasible, effective, and sustainable in the Syrian healthcare context.

Funding Statement

No funding was received for this research.

Data Sharing Statement

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Ethics Approval and Consent to Participate

Ethical approval for this study was obtained from the Biomedical Research Ethical Committee at Damascus University (approval No. MD-261125-560), which covered all participating sites. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki (1975, revised 2008). Participants were informed of the study objectives, procedures, voluntary nature of participation, and their right to withdraw at any time without consequence. Confidentiality was maintained by collecting anonymous data and storing study files in a password-protected drive accessible only to the principal investigator and authorized research personnel.

Consent for Publication

Not applicable. The manuscript contains no identifiable personal data from any participant.

Author Contributions

Ahmad Al Malla: Conceptualization, Methodology, Investigation, Writing – original draft, Writing – review & editing.

Ahmad Bishr Nasra: Methodology, Formal analysis, Visualization, Writing – review & editing.

Shahd Almansour: Validation, Writing – review & editing.

Mohammad Alaa Aldakak: Validation, Writing – review & editing.

Mohammad Al Saleh: Investigation, Data curation, Writing – original draft, Writing – review & editing.

Joudi Alkhateeb: Investigation, Data curation, Writing – review & editing.

Lama Bashar Salman: Investigation, Data curation, Writing – review & editing.

Youssef Latifeh: Methodology, Supervision, Validation, Writing – review & editing.

All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

The abstract of this paper was presented as a poster at the Syrian American Medical Society (SAMS) 24^th International Conference in Aleppo, Syria, on June 27, 2026. The results presented in the poster were preliminary and were subsequently updated during manuscript revesion. No publication link or DOI for the poster abstract is currently available.