PLOS ONERESEARCH ARTICLE

Health education improves referral
compliance of persons with probable Diabetic
Retinopathy: A randomized controlled trial
Zara Khair ID1☯*, Md Moshiur Rahman ID1☯, Kana Kazawa1‡, Yasmin Jahan1‡, Abu S.
G. Faruque2☯, Mohammod Jobayer Chisti2☯, Michiko Moriyama1☯
1 Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan, 2 Nutrition
and Clinical Services Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr, b),
Dhaka, Bangladesh

a1111111111
a1111111111
a1111111111
a1111111111
a1111111111☯ These authors contributed equally to this work.
‡ These authors also contributed equally to this work.
* zara.oikee@gmail.com

Abstract
OPEN ACCESS

Objective

Citation: Khair Z, Rahman MM, Kazawa K, Jahan Y,
Faruque ASG, Chisti MJ, et al. (2020) Healtheducation improves referral compliance of persons
with probable Diabetic Retinopathy: A randomized
controlled trial. PLoS ONE 15(11): e0242047.
https://doi.org/10.1371/journal.pone.0242047

Lack of awareness about Diabetic Retinopathy (DR) is the most commonly cited reason
why many persons with type 2 diabetes are non-compliant with referral instruction toundergo retinal screening. The purpose of this study was to evaluate the efficacy of a culturally, geographically and socially appropriate, locally adapted five-month-long health education on referral compliance of participants.

Editor: Antonio Palazón-Bru, Universidad Miguel
Hernandez de Elche, SPAIN

MethodReceived: July 3, 2020
Accepted: October 22, 2020
Published: November 12, 2020
Peer Review History: PLOS recognizes thebenefits of transparency in the peer review
process; therefore, we enable the publication of
all of the content of peer review and author
responses alongside final, published articles. The
editorial history of this article is available here:
https://doi.org/10.1371/journal.pone.0242047
Copyright: © 2020 Khair et al. This is an open
access article distributed under the terms of theCreative Commons Attribution License, which
permits unrestricted use, distribution, andreproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: Data are available infigshare: https://doi.org/10.6084/m9.figshare.
13172837.v1 (10.6084/m9.figshare.13172837).

A prospective randomized, open-label parallel group study was conducted on persons with
type 2 diabetes who underwent basic eye screening at a diabetes hospital between September 2017 and August 2018. Participants who were noncompliant with referral instruction tovisit a hospital for advanced DR management were randomly divided into health educationintervention group (n = 143) and control group (n = 156). Both groups received information
regarding DR and referral instruction at the diabetes hospital. The intervention group wasprovided personalized education followed by telephonic reminders. The primary endpointwas ‘increase in referral compliance’ and the secondary endpoint was ‘increase in knowledge of DR’. Multivariate logistic regression model was used to identify significant predictorsof compliance to referral.

Results
A total of nine participants dropped and 290 completed the post intervention survey. The
compliance rate in intervention group was found to be significantly higher than the control
group (64.3% vs 28.2%; OR 4.73; 95% CI 2.87–7.79; p<0.001). Participants in the intervention group acquired better knowledge on DR (p<0.05). Apart from intervention, referral compliance rate was also found to be significantly associated with participants’ self-perception

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Funding: The author(s) received no specificfunding for this work.
Competing interests: The authors have declaredthat no competing interests exist.

Referral compliance and Diabetic Retinopathyof vision problem (OR 2.02; 95% CI 1.02–4.01; p = 0.045) and participants’ income (OR1.24; 95% CI 1.06–1.44; p = 0.008).

Discussion
Our results suggest that intensive health education on DR should be integrated with diabetes education as it may result in significantly improved referral compliance. Outcomes may
be sustainable if interventions are institutionalized at referral point.

Trial registration
Clinical Trials.gov (Registration # NCT03658980); https://clinicaltrials.gov/ct2/show/
NCT03658980.

Introduction
Type 2 Diabetes Mellitus (T2DM) is on an alarming rise in the world [1]. In 2019, approximately 463 million adults (20–79 years) were living with diabetes and by 2045 this will rise to
700 million [2]. Bangladesh has been identified as one of the top ten countries worldwide interms of the number of people living with diabetes [3]. In 2019, there was an estimated 8.4 million people with diabetes in the age bracket 20–79 in Bangladesh, and this number is predicted
to increase to 15 million by 2045 [4].
Diabetic Retinopathy (DR) is the leading cause of vision loss in adults aged 20–74 years,
and the fifth leading cause of global blindness [5,6]. In Bangladesh, the national prevalence ofdiabetes is estimated to be 8.4% in population aged 20–79 years, with approximately 56% ofthem undiagnosed [4]. The estimated number of individuals with DR in Bangladesh is 1.8 million (21.6% of people with diabetes) [7]. Higher prevalence of DR has been reported in the
coastal areas compared to rural population from other areas of Bangladesh, according to a
study that was conducted in Barishal Division [8].
Since DR is initially asymptomatic, many people with diabetes are not aware that their eye
condition, if left unmanaged, may affect their vision and lead to blindness [9]. Screening andearly intervention is critical—it is more cost effective and may result in better health outcomes[10,11].
In Bangladesh, DR management is not yet integrated as part of mainstream public healthsystems and as such most registered persons with diabetes do not get their eyes routinely
examined [12]. DR management services are largely unavailable in facilities designated for
management of cases of diabetes, where other disease management is prioritized given limited
resources [12]. This may be because of low demand for DR management services possibly due
to lack of awareness about the disease, even among registered persons having diabetes. DR
management services can be very expensive [13]; therefore diabetes hospitals may not cater tothis service in limited-resource settings where demand for services is low.
A large proportion of persons with diabetes are non-compliant with referral to an Ophthalmologist [14] because of lack of awareness about eye complications of diabetes and lack of
information regarding where services are available [15,16]. Published systematic reviews
assessing RCTs found that providing health education regarding DR among persons with diabetes is a promising intervention that resulted in increased DR screening rate [17,18].
There does not exist any published RCT on said topic that has been conducted in a least
developed country (LDC) or in a low and middle-income country (LMIC), although RCT is

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considered the gold standard for evaluating effectiveness of health education interventions[19]. To the best of our knowledge, this is the first ever RCT conducted on said topic in an
LDC or an LMIC.
Health education interventions must be contextualized according to geographical, culturaland socioeconomic needs. For instance, home-based mail reminders may not be feasible inremote rural locations in Bangladesh given low literacy rates and because effectiveness of mailreminders has been found to be ‘quite modest and short-lived’ in previously published studies[20]. Printed education messages alone have at times failed to increase retinal screening
among persons with diabetes [11]. Interventions in limited-resource settings, where literacy
rates are low, perhaps require more personalized face-to-face connections and must be trialed
to study its effectiveness and scalability.
To address the challenge of suboptimal referral compliance, this study used an innovative
approach that comprised of comprehensive and multicomponent modalities such as interactive face-to-face education session using demonstrative flipchart, colorful pictorial leaflet andspecial referral card, and telephonic follow-ups. The purpose of this study was to evaluate theefficacy of a culturally, geographically and socially appropriate, locally adapted five-monthlong health education intervention on participants’ referral compliance. In our research wewere able to successfully evaluate the efficacy of the intervention and recommend behavior
change strategies as well.

Methods
Trial design
This was a prospective open-label parallel randomized controlled trial designed for non-compliant participants from December 2018 to May 2019. This study was registered with Clinical
Trials.gov (Registration # NCT03658980) and approved by Bangladesh Medical ResearchCouncil (Registration # 12512062018). Additionally, the study was undertaken in accordancewith the Declaration of Helsinki. All participants had been explained in detail about the purpose, risks and potential benefits of the research prior to voluntary consenting and recruitment
into the study. Participation was completely voluntary, and a written informed consent was
obtained from all participants (S1 and S2 Files).

Study sites
Barishal district under Barishal division of Bangladesh was selected as the study site for thisstudy. This was done to explore the existing referral modality between a private diabetes hospital and a public tertiary hospital. This divisional level public tertiary hospital was the first in
Bangladesh (outside of the capital Dhaka) to offer advanced DR management services (including eye screening using High Resolution Fundus camera, provision of treatment such as injections and laser surgeries) to the public at a very minimal cost.

Study population
The study population consisted of participants with T2DM, registered with a private diabetes
hospital and referred for advanced DR management to a public tertiary hospital.
Participants eligible for inclusion into study were adults (18 years or above) with T2DM
registered with a diabetes hospital, who had undergone preliminary screening for DR using
low-resolution fundus camera at the diabetes hospital between September 2017 and August
2018, were referred to a public tertiary level hospital for advanced DR management, did not

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undergo a Dilated Fundus Examination (DFE) in previous 12 months and had provided
informed written consent to be included in this study.
Participants who were excluded from this study were below the age of 18, persons with
T2DM registered with a diabetes hospital but not referred to the public tertiary level hospitalfor advanced DR management between September 2017 and August 2018, persons who had
undergone a DFE in previous 12 months and those who did not provide informed written consent to be included in this study.

Statistical basis of sample size
To calculate the sample size for a statistical superiority design suitable for RCT, the formula{[(p1q1 + p2q2)/(p2—p1)2] X factor for alpha and beta} was used, where p1 is the percentageof the existing referral compliance, q1 is (1 –p1), p2 is the percentage of the expected referral
compliance from intervention, q2 is (1 –p2), alpha is type 1 error and beta is type 2 error, andfactor for alpha and beta with 90% power is 10.5.
It was assumed that the health education intervention would result in referral improvementfrom 35% to 55% (i.e. 20 percentage point improvement. The baseline referral rate of 35%(within control group) was assumed based on a previous published RCT conducted on persons
with T2DM who were provided with personalized follow-up with the aim to increase screeningfor DR [21]. In this study, which involved mailing a brochure and videotape followed by telephonic reminder a week later, the referral was 31% higher in the intervention group.
During sample size calculation, a more conservative 20% increase in referral rate improvement was assumed keeping in mind the health education intervention modality (home-based
health education session followed by telephonic reminders) and challenging sociodemographic and geographical context (lower education level compared to participants of aforementioned study [21], and typical barriers of accessing health care in Barishal which include
lack of awareness about disease, challenging road communication, distance to facility, cost,lack of accompanying person, household commitments of women particularly living in rural
areas, among others).
To detect a difference of 20% in the referral compliance using 2-tailed test with 90% power
and type 1 error 0.05, the sample would be 125 in each group. The dropout rate was assumed
to be 20% (more than standard 10%) because participants had already gone back home months
ago following referral, and it was thought to be difficult to convince them to make the journey(possibly with an accompanying person) to the tertiary care hospital given the access barriersin Barishal and costs involved in undertaking the journey with multiple transport modalities.
The total sample size was calculated to be 300 for the study.

Randomization
To maintain research quality and reduce investigators’ bias, randomization was conducted bya third person (an experienced researcher who was not related to this study). This person generated the random allocation sequence and distributed these in serially numbered sealed
opaque envelopes. Envelopes were provided with either of two interventions, ‘Standard Care’or ‘Health Education Intervention’. The sealed envelopes were directly couriered to the tertiary
hospital and were maintained in a locked cabinet under the supervision of an ophthalmic personnel. Twenty sealed envelopes were provided to field research team at a time, which was carried to participants’ home and opened sequentially once a field enumerator completed thebaseline in-depth interview. Envelopes were opened in a sequential manner (serial number inparticipant list and serial number mentioned on top of envelope was the same in all cases) in

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front of study participant and a witness (usually family member of the participant), and intervention allocation was implemented accordingly.

Outcomes
Primary endpoint. The primary endpoint was ‘increase in referral compliance’, i.e.
increase in referral completion. Referral compliance was defined as participants’ visit to thetertiary hospital during a six-month period (five months intervention period and one month
additional window period).
Secondary endpoint. The secondary endpoint was ‘increase in knowledge about DR’.
Increase in knowledge about DR was measured using pre and post intervention questionnaires(S3 and S4 Files) based on a previously published study [22]. A total of nine questions were
investigated to assess participants’ knowledge on DR. Knowledge questionnaire was administered by experienced Community Health Workers (CHWs) at participants’ homes. Study participants were asked the same questions during post-intervention survey.

Health education intervention package for the intervention group
The duration of the total health education package was 5 months and included one face-toface session and telephonic reminders. In case of participant being randomized to intervention
group, health education session was delivered by the CHWs who completed tertiary level education and had more than 5 years’ experience in disseminating eye health awareness in communities. The CHWs received orientation to deliver the intervention from the Principle
Investigator (first author) who is also a doctoral candidate of health sciences major. Interventions were delivered under the supervision of Principle Investigator. The health education contents are outlined in S5 File. The contents were examined and approved by Ophthalmologists
prior to field study. Telephonic reminders were delivered by the CHW who delivered the faceto-face intervention, so that participants could recognize and trust the caller as a result of rapport built during past interaction.
The face-to-face health education session was delivered in local (Bengali) language in about
30–40 minutes following an in-depth interview. It consisted of key information about Diabetes, DR, DR management options, and information about available services at the government
tertiary hospital. Communication materials used were a pictorial colorful portable flipchartused for demonstration purpose, colorful pictorial leaflet in native language (Bengali) and awaterproof referral card with important information which would help to measure primary
endpoint (referral compliance rate) accurately.
Telephone reminders followed this on Day 7, 30 and 90 where each reminder call lasted
about 15 minutes. Multiple reminders have previously been reported to be more effective thansingle reminder in improving DFE [23]. A similar past study had delivered face-to-face healtheducation session followed by monthly reminders [24]. Our study restricted telephonicreminders to three because evidence suggests that after a third patient reminder, there is no
incremental improvement in screening rates [23]. Telephonic reminders were discontinued
for participants who completed referral compliance prior to the next scheduled call. The contents of the face-to-face education session and telephonic sessions have been outlined in detail(S5 File).

Control group
Participants from the control group also received information regarding DR and referral
instruction from the eye health service providers at the diabetes hospital, as same as the intervention group. Participants of control group were not provided with any form of personalized

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health education (face-to-face home-based education session followed by telephonicreminders).

Statistical methods
Analysis was conducted by Intention-to-treat (ITT) method. We considered dropout participants to be those who did not receive our phone call or respond during the follow-up calls. All
participants including those who dropped-out were included in analysis.
Pearsons chi-square test was used to compare the referral compliance and changes inknowledge measures of the two groups. Univariate analysis was conducted to test associationof different variables with referral compliance as the primary endpoint. Subsequently, multivariate analysis with backward Likelihood Ratio (LR) binary logistic regression modeling was
performed to identify significant predictors of referral compliance after adjusting for potential
confounders. The significance level of association was set at p<0.05 for the univariate analysis
and regression analysis. The strength of association was evaluated by calculating odds ratio(OR) and their 95% confidence intervals (CI).
For the secondary outcome, we compared the proportion of participants who provided correct (or positive) responses during pre and post intervention surveys. This comparison was
done between the two study arms. In addition, chi-square test was performed for each knowledge related question. There were no participants who initially provided correct (or positive)
response at baseline and later incorrect (or negative) response during the post intervention
survey. Therefore, we conducted chi-square test only on those participants who initially provided incorrect (or negative) responses. The significance level of association was set at p<0.05
for analysis of the secondary outcome.
Statistical Software for Social Science (SPSS) Version 21.0 was used for data analysis (IBMCorp, 2012) [25].

Reliability and validity
Due to the nature of the study design (open label), it was not possible to withhold knowledge
about allocated intervention to participants. Therefore, to reduce bias, a data manager stationed at the tertiary hospital assessed outcome (compliance in both intervention and control
groups). In addition, the accuracy of the outcome assessment was checked every 2 weeks bydata manager and then by ophthalmic personnel at the tertiary hospital. This record was thenshared with Principle Investigator.

Results
Baseline characteristics of the participants
The CONSORT flowchart of this study is detailed in Fig 1. Three hundred and ninety-sevenpersons who were referred from the diabetes hospital to tertiary hospital and met inclusion criteria were checked for eligibility. Among them, 98 persons dropped out due to reasons shownin Fig 1, and the remaining 299 persons were registered and randomly allocated to the intervention group (health education) (N = 143) or the control group (standard care) (N = 156).
During study period, four and five persons dropped out from intervention and control groups
respectively as we were unable to follow-up. Therefore, 139 and 151 participants were analyzed, and completion rates were 97.2% and 96.8% in intervention and control groups respectively. The socio demographic and other characteristics of study participants, obtained duringbaseline survey, are shown in Table 1. There were no statistically significant differences in thebaseline characteristics between the two groups.

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Fig 1. CONSORT flowchart.
https://doi.org/10.1371/journal.pone.0242047.g001

Efficacy of health education
Health education was found to be a statistically significant determinant of compliance rate
(Table 2). When compared between two groups, it was observed that 64.3% participants who
attended the health education session visited the referred facility, compared to 28.2% participants from control group. The difference of referral compliance rate between these two groups
was 36.1% (p<0.001), which was higher than the anticipated 20% (OR 4.73; 95% CI 2.87–
7.79).
The number of participants in each intervention group who responded positively to knowledge measures (secondary outcome) during pre and post intervention has been reported inTable 3. The post-intervention difference in knowledge levels between both groups was also

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Table 1. Baseline differences between intervention and control group.
Variables

Intervention Group N (%)(N = 143)

Control Group N (%) (N = 156)

Mean age in years ± SD

51.5±11.4

51.0±10.8

Women

72 (50.3)

82 (52.6)

Education � Grade 10

102 (71.3)

110 (70.5)

Income � BDT 9999

87 (60.8)

99 (63.5)

4.8±5.6

5.4±6.5

Demographic

Diabetes
Mean years of registration with diabetes hospital ± SD
Eye Care
Vision problem (self-perceived)

120 (83.9)

126 (80.8)

Duration of self-perceived eye problem < 5 years

105 (73.4)

105 (67.3)

135 (94.4)

150 (96.2)

ReferralClear about referral instruction
SD, Standard Deviation.
https://doi.org/10.1371/journal.pone.0242047.t001

found to be statistically significant as reported in Table 4. Participants who belonged to theintervention arm and who responded negatively during pre-intervention (n = 127), were significantly more likely to respond positively to the same knowledge measures during post-intervention, when compared to the control group (n = 125).
Univariate analyses were conducted to identify sociodemographic and other factors,
obtained during baseline survey, which may have had important relationship with the primary
endpoint. The dependent variable was referral compliance (yes/no) including all registeredparticipants (n = 299). The independent variables or possible predictors of compliance areshown in Table 5. Results show that in addition to the health education intervention itself,‘education’ and ‘income’ were found to be statistically significant determining factors of participant’s referral compliance. No other independent variables were found to be significantly
associated with the primary endpoint.
All thirteen variables shown in Table 5 were included in the adjusted model during backward Likelihood ratio (LR) binary logistic regression analysis (cut-off value was 0.5). Thisrevealed the most significant predictors of participants’ compliance with referral instruction to
the tertiary hospital. Results from the final backward logistic regression model are shown in
Table 6. The most important predictor of compliance was health education intervention (OR4.73; 95% CI 2.87–7.79; p<0.001). Next, compliance rate was positively and significantly
affected by participants’ self-perception of vision problem (OR 2.02; 95% CI 1.02–4.01;
p = 0.045) and participants’ income (OR 1.24; 95% CI 1.06–1.44; p = 0.008). The Hosmer andLemeshow test result was non-significant which indicated that the model is a good fit(p = 0.151) and can significantly predict outcome.

Table 2. Comparison of primary outcome between intervention and control group.
Variables

Intervention N (%) (N = 143)

Control Group N (%) (N = 156)

P-value<0.001aPrimary Outcome (Increased referral compliance, i.e. return to tertiary hospital)
Referral compliance

92 (64.3%)

44 (28.2%)

Referral non-compliance51 (35.7%)

112 (71.8%)aPearson chi-square test.

https://doi.org/10.1371/journal.pone.0242047.t002

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Table 3. Number of participants who responded positively to knowledge measures (secondary outcome) during pre and post intervention.
Knowledge related measures

Study arm

Intervention Group N (%)
N = 139

Control Group N (%)
N = 151

Knows that long-term uncontrolled diabetes might be a cause for a vision
problem known as DR

Pre-intervention

12 (8.6)

20 (13.2)

Postintervention

139 (100)

59 (39.1)

Knows the symptoms of DR

Pre-intervention

12 (8.6)

17 (11.3)

Postintervention

139 (100)

28 (18.5)

Pre-intervention

22 (15.8)

26 (17.2)

Postintervention

131 (94.2)

21 (13.9)

Pre-intervention

111 (79.9)

136 (90.1)

Postintervention

136 (97.8)

136 (90.1)

Knows that the onset of DR can be delayed

Knows that DR can be treatedCorrectly indicated one of the symptoms of DR

Correctly indicated one of the treatment option for DR

Understands impact of non-compliance on vision

Pre-intervention

11 (7.9)

14 (9.3)

Postintervention

134 (96.4)

50 (33.1)

Pre-intervention

18 (12.9)

33 (21.9)

Postintervention

131 (94.2)

35 (23.2)

Pre-intervention

132 (95.0)

128 (84.8)

Postintervention

136 (97.8)

129 (85.4)

Knows that a trained Eye Consultant at tertiary hospital provides eye care services Pre-intervention

30 (21.6)

32 (21.2)

139 (100)

68 (45.0)

Pre-intervention

31 (22.3)

30 (19.9)

Postintervention

133 (95.7)

30 (19.9)

Postintervention
Knows the days and times when Eye Consultant at tertiary hospital provides eye
care services

DR stands for Diabetic Retinopathy.
https://doi.org/10.1371/journal.pone.0242047.t003

Post-hoc sub-group analyses
Although more women than men presented in the baseline survey of this study (shown in S1
Table), more men were likely to visit referred facility (shown in Table 5). Of the total participants, 10.4% (N = 31) experienced physical disability as a result of their existing vision problems (‘Strongly agree’ and ‘Agree’ categories taken into account as shown in S1 Table). Of thetotal study participants, 8% (N = 24) said that they depended on someone’s assistance to perform day-to-day tasks as a result of vision problem (‘Strongly agree’ and ‘Agree’ categories
taken into account as shown in S2 Table). Out of the 24 participants who depended on someone else’s assistance, only 37.5% (N = 9) visited the referred facility (as shown in S2 Table).
However, it was found that among these compliant participants (N = 9), referral compliancewas better in participants who received the intervention (N = 6) compared to those who didnot (N = 3).

Discussion
Analysis of results
In our study, personalized health education intervention was found to be the most importantstatistically significant predictor of referral compliance rate. In this study the intervention

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Table 4. Comparison of number of participants who responded negatively to knowledge measures during pre-intervention.
Knowledge related measures

Responses (pre and postintervention)

Knows that long-term uncontrolled diabetes might be a cause
for a vision problem known as DR
Knows the symptoms of DR
Knows that the onset of DR can be delayed
Knows that DR can be treatedCorrectly indicated one of the symptoms of DR
Correctly indicated one of the treatment option for DR
Understands impact of non-compliance on visionIntervention Group N (%) Control Group N (%)
N = 127
N = 125

Negative to Positive

127 (100)

39 (29.8)

Negative to Negative

0 (0)92 (70.2)

Negative to Positive

127 (100)

11 (8.2)

Negative to Negative

0 (0)123 (91.8)

Negative to Positive

109 (97.2)

0 (0)Negative to Negative

8 (6.8)125 (100)

Negative to Positive

25 (89.3)

0 (0)Negative to Negative

3 (10.9)15 (100)

Negative to Positive

123 (96.1)

36 (26.3)

Negative to Negative

5 (3.9)101 (73.7)

Negative to Positive

113 (93.4)

2 (1.7)

Negative to Negative

8 (6.6)116 (98.3)

Negative to Positive

5 (71.4)

1 (4.3)

Negative to Negative

2 (28.6)

22 (95.7)

Knows that a trained Eye Consultant at tertiary hospitalprovides eye care services

Negative to Positive

109 (100)

36 (30.3)

Negative to Negative

0 (0)83 (69.7)

Knows the days and times when Eye Consultant at tertiary
hospital provides eye care services

Negative to Positive

102 (94.4)

0 (0)Negative to Negative

6 (5.6)121 (100)

Pvaluea<0.001<0.001<0.001<0.001<0.001<0.0010.001<0.001<0.001aPearson chi-square test.
DR stands for Diabetic Retinopathy.
https://doi.org/10.1371/journal.pone.0242047.t004

improved knowledge of DR among participants, consistent with other studies that had
reported that health education interventions have been successful in increasing screening rates
for retinopathy [26–28]. The face-to-face interaction with participants using easy local language and pictorial tools apparently helped to promote understanding among participants.
Participants most probably felt empowered to make informed decision to access DFE after
receiving specific information about where, when, how and from whom to seek advanced DR
management services at a very small cost. This apparently resulted in reduced perceived barriers and increased perceived benefits among participants. When coupled with cues to action(reminder and follow-up), this resulted in the uptake of health services, and this concept is
consistent with the Health Belief Model [29].
The second most important predictor of compliance was participant’ self-perception ofvision problem. Where participants felt that their vision was already affected, there seemed to
be a sense of urgency and possibly fear that vision may get worse without timely medical intervention. The perceived susceptibility and severity after the health education as per the HealthBelief Model [29], have probably led to increased compliance.
Another important predictor of compliance was participant’s income or ability to pay fortransportation and logistics required to attend the referred facility (possibly along with anaccompanied person). The better financially resourced participants were significantly more
likely to visit the referred hospital for further check-up.

Field experience
Health education, for it to be effective, must be focused, personalized and suitably adapted to
local context. It must be appropriate from cultural geographical and social perspectives [30].

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Table 5. Association of primary outcome with other variables.
Variables

Compliant N (%) N = 136

Non-compliant N (%) N = 163

P-value

Health Education Intervention

92 (67.6)

51 (31.3)<0.001aStandard Care44 (32.4)

112 (68.7)

Women

62 (45.6)

92 (56.4)

Men

74 (54.4)

71 (43.6)

�29

2 (1.5)5 (3.1)

30–39

19 (14.0)

19 (11.7)

40–49

40 (29.4)

43 (26.4)

50–59

36 (26.5)

42 (25.8)

60+

39 (28.7)

54 (33.1)

Grade 10 or below

65 (47.8)

88 (54.0)

Passed Grade 10 or has higher qualification

68 (50.0)74 (45.4)

Vocational or others

3 (2.2)1 (0.6)0–499971 (52.2)

97 (59.5)

5000–9999

7 (5.1)

11 (6.7)
27 (16.6)

Intervention GroupSex
0.061aAge Group
0.476b

Education
0.029bIncome Range (BDT)

10,000–14,999

12 (8.8)

15,000–19,999

15 (11.0)

5 (3.1)

20,000–49,999

26 (19.1)

23 (14.1)

50,000 +5 (3.7)0 (0)� 60 mins

68 (50.7)

71 (43.6)

0.044bTravel time in minutes (home to tertiary hospital)
61–90 mins

23 (16.9)30 (18.4)

91–120 mins

21 (15.4)

35 (21.5)

� 121 mins

23 (16.9)

27 (16.6)

Yes

118 (86.8)

128 (78.5)

No

18 (13.2)

35 (21.5)

Strongly agree

2 (1.5)3 (1.8)0.296bVision problem (self perception)
0.063aExperiences disability as a result of vision problem
Agree

11 (8.1)

15 (9.2)

Neutral

2 (1.5)3 (1.8)Disagree121 (89.0)

142 (87.1)

0 (0.0)0 (0.0)Strongly disagree

0.625bRequires someone else’s assistance to perform day to day activities as a result of vision problem
Strongly agree

0 (0.0)1 (0.6)Agree9 (6.6)14 (8.6)

Neutral

1 (0.7)3 (1.8)Disagree125 (91.9)

144 (88.3)

1 (0.7)1 (0.6)Strongly disagree

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Table 5. (Continued)
Variables

Compliant N (%) N = 136

Non-compliant N (%) N = 163

P-value
0.207b

Waiting time
<30 minutes

31 (22.8)

46 (28.2)

30–60 minutes

96 (70.6)

110 (67.5)>60 minutes

9 (6.6)7 (4.3)0.623bEye screening duration at diabetes hospital<20 minutes

60 (44.1)

72 (44.2)

20–40 minutes

58 (42.6)

78 (47.9)>40 minutes

18 (13.2)

13 (8.0)
0.234bCounsel time
<10 minutes

81 (59.6)

108 (66.3)

10–20 minutes

53 (39.0)

53 (32.5)>20 minutes

2 (1.5)2 (1.2)

Referral
0.840aOverall referral clarity
Yes

130 (95.6)

155 (95.1)

No

6 (4.4)8 (4.9)aPearson chi-square test.

b

Mann-Whitney U test.

https://doi.org/10.1371/journal.pone.0242047.t005

In our experience, participants were found to be very pleased to participate in an interactive
personalized learning session, as they felt ‘cared-for’.
Telephonic reminder system was the most preferred mode of reminder since all study participants owned or had access to a personal cell phone. Participants were more likely torespond eagerly and provide verbal commitment (by confirming a date) to visit the tertiary
hospital during the first telephonic reminder on Day 7 compared with reminders provided on
Day 30 and 90. Timely intervention is particularly vital for priority patients such as those suffering from a disability. In our study, the health education resulted in increased DFE among
those who faced physical disability as a result of vision problem and required someone else’s
assistance to perform day-to-day tasks.
In countries with limited resources and high DR prevalence rates, ensuring customized
home-based personalized health education even for people with advanced DR maybe costly
and challenging. A more cost-effective solution may be to utilize the existing network of
CHWs to provide information about DR, and where when and how to access nearby DR management services.
Table 6. Multivariate binary logistic regression of the predictors of participants’ referral compliance.
Variable

B

OR

Intervention type

1.553

4.73

2.89

Self-perception (vision problem)

0.703

2.02

1.02

Monthly income

0.211

1.24

1.06

P-value

Nagelkerke R2

7.79<0.001

0.21�

4.01

0.045

1.44

0.008

Results at final step 95% CI
for OR Lower Upper

Hosmer and Lemeshow Test result indicates that model is non-significant (p = 0.151).
Prediction percentage correct for above model = 68.2%.
�The Nagelkerke R2 is 0.21 for this model.
https://doi.org/10.1371/journal.pone.0242047.t006

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Referral compliance and Diabetic Retinopathy

Similarity with other global studies
Our findings are consistent with the findings of similar studies trialed in developed countries[17, 18] where increase in DFE was reported as a result of health education intervention. Our
multicomponent and locally adapted intensive health education intervention succeeded toattain a referral compliance rate that was 36.1% higher (in other words, this is equivalent to128% increase in interventions group compared to control group). Several RCTs based indeveloped countries that used varied health education modalities to increase DFE reported alower compliance rate [21, 31–37].
Apart from the fact that a multicomponent intervention was used in our study, there may
be other reasons why it was possible to attain higher compliance rate compared to other global
studies. It may be easier to achieve a higher change in intervention group where baseline referral compliance rates are relatively low [17] such as in countries with limited health resources.
On the other hand, despite lower education level among participants, and social and infrastructural barriers to accessing health care generally expected in limited resource settings, thecompliance rate among intervention group was more than what was initially expected during
study design.

Future implications
To sustain increased DFEs among persons with T2DM, personalized multicomponent behavior change strategies used in this trial may be tested and provided at the institutions where DR
management services are either available within the hospital or in the community. Additional
demonstrative strategies such as using audio-visual modalities within hospital premises may
be explored and adopted. Further studies may be conducted in LMICs to understand social
infrastructural and other systemic barriers to accessing DR management services, so as todevise and trial other effective interventions to increased referral compliance.

Study limitations
This study may not be generalized for the entire population who are suffering from diabetes.
Participants of this study were registered with a diabetes hospital and therefore generally
aware about diabetes mellitus.
Furthermore, in this study, the referred facility was located in the same district as participant’s residence as well as the diabetes hospital. In areas where participants live further away,or where referred facility is further away, the referral compliance rate may not improve significantly among those who have been provided with health education.

Supporting information
S1 Table. Baseline characteristics of study participants according to subgroups.
(DOCX)S2 Table. Effect of intervention on referral compliance for patients who require someone
else’s assistance.
(DOCX)
S1 File. Informed consent form in English.
(PDF)
S2 File. Informed consent form in Bengali.
(PDF)

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S3 File. Questionnaire in English.
(PDF)
S4 File. Questionnaire in Bengali.
(PDF)
S5 File. Health education content.
(DOCX)
S6 File. CONSORT checklist.
(DOC)
S7 File. Trial protocol.
(PDF)
S8 File. Approved protocol of ethics committee.
(PDF)

Acknowledgments
The authors are grateful for the support provided during the study by Dr. Yoshiaki Kiuchi,
Professor, Department of Ophthalmology and Visual Sciences, Hiroshima University, Japan,
Dr. Md. Shafiqul Islam, Assistant Professor, Department of Ophthalmology, Sher-e-Bangla
Medical College & Hospital, Barishal, Bangladesh, and Dr. Md. Ataur Rahman (Chunnu),
Senior Eye Consultant, Advocate Hemayet Uddin Ahmed Diabetic & General Hospital, Barishal, Bangladesh. Community health workers have been tremendously supportive in visiting
participants’ homes given the challenging climate and transportation infrastructure in hardto-reach areas in Barishal district.

Author Contributions
Conceptualization: Zara Khair, Md Moshiur Rahman, Michiko Moriyama.
Data curation: Zara Khair.
Formal analysis: Zara Khair, Kana Kazawa, Abu S. G. Faruque.
Investigation: Zara Khair.
Methodology: Zara Khair, Md Moshiur Rahman, Mohammod Jobayer Chisti, MichikoMoriyama.
Project administration: Zara Khair, Abu S. G. Faruque, Michiko Moriyama.
Resources: Zara Khair, Md Moshiur Rahman, Abu S. G. Faruque, Mohammod Jobayer Chisti,
Michiko Moriyama.
Supervision: Zara Khair, Md Moshiur Rahman, Michiko Moriyama.
Validation: Zara Khair, Mohammod Jobayer Chisti.
Visualization: Zara Khair, Yasmin Jahan.
Writing – original draft: Zara Khair.
Writing – review & editing: Md Moshiur Rahman, Kana Kazawa, Yasmin Jahan, Abu S. G.
Faruque, Mohammod Jobayer Chisti, Michiko Moriyama.

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