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R E S E A R C H A R T I C L E Open Access
A randomized controlled behavioral
intervention trial to improve medication adherence
in adult stroke patients with prescription tailored
Short Messaging Service (SMS)-SMS4Stroke study
Ayeesha Kamran Kamal
1*
, Quratulain Shaikh
2
, Omrana Pasha
3
, Iqbal Azam
4
, Muhammad Islam
4
, Adeel Ali Memon
5
,
Hasan Rehman
6
, Masood Ahmed Akram
6
, Muhammad Affan
5
, Sumaira Nazir
5
, Salman Aziz
5
, Muhammad Jan
1
,
Anita Andani
1
, Abdul Muqeet
7
, Bilal Ahmed
8
and Shariq Khoja
9
Abstract
Background: The effectiveness of mobile technology to improve medication adherence via customized Short
Messaging Service (SMS) reminders for stroke has not been tested in resource poor areas. We designed a
randomized controlled trial to test the effectiveness of SMS on improving medication adherence in stroke
survivors in Pakistan.
Methods: This was a parallel group, assessor-blinded, randomized, controlled, superiority trial. Participants were
centrally randomized in fixed block sizes. Adult participants on multiple medications with access to a cell phone and
stroke at least 4 weeks from onset (Onset as defined by last seen normal) were eligible. The intervention group, in
addition to usual care, received reminder SMS for 2 months that contained a) Personalized, prescription tailored daily
medication reminder(s) b) Twice weekly health information SMS. The Health Belief Model and Social Cognitive theory
were used to design the language and content of messages. Frontline SMS software was used for SMS delivery.
Medication adherence was self-reported and measured on the validated Urdu version of Morisky Medication
Adherence Questionnaire. Multiple linear regression was used to model the outcome against intervention and
other covariates. Analysis was conducted by intention-to-treat principle.
Results: Two hundred participants were enrolled. 38 participants were lost to follow-up. After 2 months, the
mean medication score was 7.4 (95 % CI: 7.2–7.6) in the intervention group while 6.7 (95 % CI: 6.4–7.02) in the
control group. The adjusted mean difference (Δ) was 0.54 (95 % CI: 0.22–0.85). The mean diastolic blood pressure in
the intervention group was 2.6 mmHg (95 % CI; −5.5 to 0.15) lower compared to the usual care group.
Conclusion: A short intervention of customized SMS can improve medication adherence and effect stroke risk factors
like diastolic blood pressure in stroke survivors with complex medication regimens living in resource poor areas.
Trial registration: Clinicaltrials.gov NCT01986023 last accessed at https://clinicaltrials.gov/ct2/show/NCT01986023
Keywords: Stroke, Medication adherence, SMS, Prevention, Non communicable disease, mHealth, IT technology, Lower
and middle income countries, Cost effectiveness
* Correspondence: ayeesha.kamal@aku.edu
Ayeesha Kamran Kamal and Quratulain Shaikh are joint first authors.
1
Stroke Services, Section of Neurology, Department of Medicine, The
International Cerebrovascular Translational Clinical Research Training Program
(Fogarty International Center, National Institutes of Health) and Aga Khan
University, Stadium Road, 74800 Karachi, Pakistan
Full list of author information is available at the end of the article
© 2015 Kamal et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Kamal et al. BMC Neurology (2015) 15:212
DOI 10.1186/s12883-015-0471-5
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Background
Stroke is the second major cause of death and third lar-
gest contributor to disability globally [1, 2]. Two thirds
of this burden is borne by low and middle income coun-
tries where they are more likely to be fatal or disabling
[3]. International comparison of stroke cost studies show
that on average, stroke care accounted for 3 % of total
health care expenditures [4]. In Pakistan, community
surveys suggest a lifetime stroke symptom prevalence of
approximately 19 % [5], with an estimated annual stroke
incidence of 250 per 100,000 population [6, 7].
Optimal adherence to medications may reduce the risk
of poor outcomes by 26 % [8]. However, a recent 50 year
(1948–1998) meta-analysis reported global adherence
rates around 75 % [9]. Local studies report adherence
rates to cardiac medicines ranging between 27–77 %
[10] and a 68 % compliance in stroke patients in the first
2 years after the event [11].
Interventions designed to overcome non-adherence
include drug diaries, pill counters, automated reminders,
patient counseling and improving social support [12–15].
Each of these interventions, involves substantial cost, time
and effort with a variable response dependent on health
and prescription literacy and self-motivation [16]. These
are not feasible in settings like Pakistan due to poor health
literacy and awareness and severe resource limitations
[17, 18]. Short text message (SMS) is an inexpensive,
ubiquitous and culturally acceptable tool with poten-
tial for behavioral change. Mobile phone users in
Pakistan were recorded at greater than 137 million by
the Pakistan Telecommunication Authority and total
cellular density is reportedly 77 % [19]. We hypothe-
sized that our short intense SMS intervention would
be able to demonstrate its potential if we used the
Health Belief Model with Behavioural Change Theory
to design it and reach large numbers frequently due
to economic feasibility [20–22].
We sought to determine the effectiveness of custom-
ized SMS reminders plus Health information SMS in
addition to usual care in adult stroke patients compared
to usual care only in improving medication adherence at
a hospital stroke service in Pakistan. In addition we ex-
plored the biologic effects if any, on blood pressure for
those who received SMS and the scalability characteris-
tics of the innovation based on Rogers Diffusion of
Innovation Theory derived questionnaire that measures
intervention qualities such as Simplicity, Compatibility,
Observability and Relative advantage [23].
Methods
SMS for Stroke is a parallel-group, assessor-blinded, ran-
domized controlled single center superiority trial con-
ducted to assess the intervention of SMS reminders on
adherence [24]. The participants are randomized into
two parallel groups in a 1:1 ratio via block technique
with one group receiving the standard of care as per in-
stitutional guidelines while the parallel group receiving
SMS reminders for each dose of medicine in addition to
the standard of care. Following is a brief outline of the
methodology used in the study. For further details and
access to questionnaires and tools, please refer to our
paper on trial methods [23].
Study setting
The SMS for Stroke Study was conducted at the Clinical
Trials Unit (CTU); Aga Khan University which is a JCIA
(Joint Commission International Accreditation) accre-
dited hospital in Karachi, Pakistan. Stroke service is de-
livered at the center through a 24 h neurovascular team
on floor and ambulatory care clinics.
Participants
Participants were recruited from the Neurology and
Stroke Clinics at this tertiary care center. The average
daily volume of the center is 100+ Visits and annual vol-
umes are greater than 1500+ patients to the single stroke
clinic alone.
Eligibility criteria
Inclusion criteria
Age greater than 18 years old
History of stroke(s) confirmed by neuroimaging at
the time of the episode
>1 month since last episode of stroke
Use of at least two drugs such as (but not limited to)
anti platelets, statins, anti-hypertensives to control
risk factors of stroke.
Modified Rankin Score of 3 or less (so that they are
able to operate mobile phones)
Possession of a personal cell phone that the patient
has access to at all times. In the case of patients who
do not own or are unable to use mobile phones,
they must have a caregiver available at all times who
possesses a cell phone.
Ability to receive, comprehend and reply to an SMS
in English, Nastaleeq Urdu (local Urdu script) or
Roman Urdu. In the case of patients who themselves
are unable to receive, comprehend or reply to an
SMS, they must have caregivers available at all times
who could perform the above mentioned tasks.
Exclusion criteria
Biological impairment in reading or responding to
SMS in the caregiver such as (but not limited to)
loss of vision, visual field cuts, aphasia in case the
patient himself/herself is supposed to receive SMS
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Diagnosed organ dysfunction or malignancy such as
hepatic, renal or malignancy
Plans to travel outside the country inside the two
months following enrollment
Assignment of interventions
Centrally Randomised computer generated sequence
was used by the CTU and allocation concealed in
opaque white envelopes. Participants were assigned to
groups in a parallel fashion in a 1:1 ratio. Block
randomization technique was used with block size of 10
(not disclosed to field and research team that was dir-
ectly interacting with participants). This is to ensure
similarity between the two groups at all times permitting
interim analysis during the study.
Study procedures
Participants were invited after assessment of eligibility
and those who consented were interviewed in the CTU
regarding demographic information, medical and pre-
scription details. The baseline Morisky adherence score
for each patient was also recorded at this time followed
by the randomisation to either the treatment group A or
intervention group B. After allocation, the research
supervisor explained the details of the intervention to
the participants in group A and demonstrated by send-
ing one test SMS on his/her cell phone in the preferred
language for SMS. Since the participants were required
to respond via SMS, all participants were compensated
for the cost of sending the response by providing them
with prepaid credit in advance. In case of allocation to
usual care group, the participants were informed about
their date of follow up after 2 months. The staff who
randomized and those who assessed and those who de-
livered the intervention were separate.
Control group
In the control group, patients receive the usual standard
of care provided at the center for stroke patients. This
primarily consists of regular follow up visits (as advised
by their neurologist) with their stroke neurologist. In
general, these are at 1, 3, 5,9,12 months after a stroke.
Each patient is provided with a telephone number that
can be used to reach the stroke team in case of an emer-
gency and each patient is also reminded of their clinic
appointments 1–2 days prior via SMS and/or phone.
Intervention group
In addition to the usual care, intervention group re-
ceived automated SMS reminders customized to their
individual prescription. The participants were required
to respond to the SMS stating if they have taken their
medicines. Moreover twice weekly health information
SMS were also sent to the intervention group. Health
information SMS were customized according to med-
ical and drug profile of every patient by the research
team. The messages were designed in a weekly sched-
ule at preset days of the week for total 8 weeks e.g.,
Wednesday and Saturday week 1 for patient X. The
timings were decided according to the prescription so
that health messages do not collide with the reminder
messages for that day. Usually 5 pm was found feas-
ible for most participants. These messages did not ask
for a reply. These health information SMS were codi-
fied by Michie’s Taxonomy of Behavioural Change for
repeatability [25] (Fig. 1).
Follow up and outcome ascertainment
The subjects were required to follow up after 2 months
in the CTU. In order to improve the follow up rate par-
ticipants in both groups were sent SMS and reminded
about their due follow up 1–2 days earlier. If the partici-
pant was not able to report exactly after 2 months, a
period of ± 7 days was allowed for adjusting the follow
up. Those participants who did not appear for follow up
were contacted on phone up to 3 times and also
approached by other means like sending transport to aid
them or contacting them when they come for other
clinic visit, lab work, physiotherapy etc. All participants
were compensated for their travelling cost. Outcome as-
sessment was performed by trained study physicians
who were masked to the group that the participant was
assigned. In addition, separate assessors evaluated par-
ticipant response to SMS intervention. Enrollment began
on 5th December 2013 and the last patient was recruited
on 30th April 2014. The last followup was conducted on
28th June 2014.
Outcomes
Primary outcome measure
The primary outcome of interest was a change in medi-
cation adherence after 2 months of receiving the SMS.
Medication adherence was measured at recruitment
and after 2 months in both groups on the Morisky
Medication Adherence Scale (MMAS). The scale has
been used in a similar setting previously and it has
been translated and validated in Urdu [26]. The in-
strument consists of 8 questions and the response to
first 7 questions is scored as either 0 or 1. The eighth
question has a weighted response from 0.25 to 1. The
tool has a sensitivity of 46 % and specificity of 60 %
for the Urdu version which is the lingua franca of the
population, and this version has been validated [26].
Secondary outcome measures
Effect on biologic variables: blood pressure We ex-
plored the effect, if any, on blood pressure, even if
though the intervention was short term. Blood pressure
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was measured via Mindray Datascope Equator in the
CTU at registration visit and after interview to assess for
variability due to stress with the participant sitting and
relaxed.
SMS intervention assessment We also measured pa-
tient satisfaction and acceptability of using an innovation
such as the SMS to improve clinical outcome. This was
done through tools which identified the beneficial and
untoward attributes of using this technology. One of the
tools was a self-reported questionnaire originally de-
signed keeping in mind Roger’s factors from his theory
of Diffusion of Innovations and measured patient satis-
faction as a percentage [27, 28]. Another questionnaire
was designed based on previous literature which mea-
sured patient satisfaction and was also reported as pro-
portions [29].
Ethics and human subjects protection
All patients taking part in the trial were required to pro-
vide written informed consent at the time of recruit-
ment. Consent forms were available in English and
Urdu. Special care was taken to send the health promo-
tional texts twice weekly at times that do not cause dis-
comfort to the patient such as late at night. Our
messages did not contain identifying information and
the program sending the messages was secure at a single
site with limited access. All staff received requisite GCP
training and credentials. The participants were compen-
sated for their travel and phone expenses. A hotline was
created for patient queries and concerns. The study
was approved by the Ethical Research Committee,
Aga Khan University, Pakistan with approval number
2763-Med-ERC-13.
Plan of analysis and sample size
Based on literature, we estimated the mean MMAS score
to be 6 [30] in the control group and 7 in the intervention
group, giving a mean difference of 1 (SD = 2). Using these
values, a sample of at least 172 subjects was required
to achieve a power of 90 % and significance level of
5 % when testing a two tailed hypothesis of inequality
of means. This translated into 16 % effect size. Keep-
ing a 15 % attrition rate the sample size was inflated
so at least 100 subjects were needed in each group.
AnyimprovementintheMMASwouldtranslateinto
clinical improvement in the long run through effective
secondary prevention.
Pilot Testing was done on 10 % of the sample size i.e.,
20 participants and the intervention was also tested for
smooth application and any systematic errors. This
sample was excluded from the final analysis. These 20
participants were in addition to the 200 participants that
were included in the final study.
Data was entered on Microsoft Access database
through double entry. Analysis was performed using the
intention to treat principle at two stages: interim analysis
after 25 % of the sample had been reached (Additional
file 1) and final analysis after data had been collected
from all study participants. Descriptive statistics were
Fig. 1 Information flow diagram
Kamal et al. BMC Neurology (2015) 15:212 Page 4 of 11
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reported as Mean (SD) or Median (IQR) for continuous
variables like age, years of schooling, years since diagno-
sis, MMAS score etc. Proportions were reported for cat-
egorical variables like gender, marital status, area of
residence, employment status, proportion of patients
with depression etc. Multiple linear regression was per-
formed to estimate the adjusted mean difference in
MMAS between the two groups. Robust regression
was applied to the final model. Sensitivity analysis
were done by duration of intervention, SMS receiver
(patient/caregiver) and primary stroke physician (refer
to Additional file 1). The acceptability and patient
satisfaction of the intervention were reported as pro-
portions. Stata version 12 was used for analysis.
An interim analysis was performed to ensure that the
IT based technology was not causing any unexpected
outcomes that were not foreseen, in addition to ensure
that the program was being delivered with fidelity.
Results
Three hundred twenty six patients were approached for
enrollment where 126 were excluded due to ineligibility
or lack of consent (Fig. 2). One hundred participants
were randomised to each group. After 2 months, 21
were lost to followup in control group while 19 in inter-
vention group.
Baseline characteristics (Table 1)
A total of 200 participants were analyzed in the study
(100 in each group). Of these, 135 (67.5 %) were male
while 65 (32.5 %) were female. There were fewer males
(64) in the control group as compared to the interven-
tion group (71). The mean age in the intervention group
was lower (56 years. S.D 1.5 years) compared to
(57.6 years, S.D 1.3 years) in the usual care group. These
differences were not statistically significant.
Mean medication adherence
The baseline median Morisky medication adherence
score was similar in the two groups (6.6). After 2 months
of follow-up, the MMAS increased in both groups.
While the increase was minor in the control group
(+0.1), there was a much larger increase in the inter-
vention group (+0.8). This difference was found to be
statistically significant (Table 2). On univariate ana-
lysis the mean medication adherence score was 0.65
(0.0–1.0) points higher in the intervention group
compared to the usual care group (Table 3). It was
Fig. 2 Study flow chart. mRS-modified Rankin Scale. Out of Station =Not in the city and unable to report for follow up during the period that
outcome assessment was supposed to be performed. Discontinued Intervention = Withdrew from the study and were not sent SMS, they did not
want to have SMS sent to them
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observed that high number of pills prescribed daily,
high monthly cost of drugs, higher level of social sup-
port, missing physician appointments in the previous
year, ischemic stroke and presence of depression were
all inversely related with the level of medication ad-
herence. Since cost of drugs was skewed it was log
transformed to obtain linearity with the outcome. The
baseline Morisky adherence score, being unemployed
or retired, being educated and higher dosing fre-
quency were positively related to the level of medication
adherence. Multivariable analysis showed that mean
difference in adherence score between the intervention
group and the usual care group was 0.54 (95 % CI; 0.22–
0.85) (p= <0.01) adjusted for all other variables. (Table 2)
The model explains 30 % of variability in the outcome
(r
2
=0.3).
Secondary outcomes
Biologic effects –blood pressure
We limited our exploratory outcomes to the change in
systolic and diastolic blood pressure of participants. This
was due to the fact that major biologic changes were not
Table 1 Baseline characteristics of the study participants
Intervention group Usual care group
n= 100
n= 100
n (%) n (%)
1 Age (years)
a
56.07 (1.5) 57.62 (1.3)
2 Male 64 (64) 71 (71)
3 Educated 90 (90) 88 (88)
4 Years of formal education
a
12.7 (0.4) 12.36 (0.4)
5 Urban residence 86 (86) 88 (88)
6 Number of pills prescribed daily
b
7 (4.5–9.5) 8 (6–10)
7 Distance from stroke physician
b
(km) 9.9 (7.2–16.7) 11.6 (7.8–18.6)
8 Monthly cost of drugs
b
(PKR) 12,000 (7500–18,000) 12,000 (7500–19,750)
9 Side effects 13 (13) 12 (12)
10 Use of alternate medicines 12 (12) 12 (12)
11 Missed physician appointments in last year 13 (13) 14 (14)
12 Dosing frequency once daily 5 (5) 4 (4)
Twice daily 60 (60) 66 (66)
Thrice daily 35 (35) 30 (30)
13 Use of pill boxes 15 (15) 16 (16)
14 Use of alarms as medication reminders 3 (3) 2 (2)
15 Baseline Morisky adherence score
b
7 (5.7–8) 7 (5.7–8)
16 Blessed dementia score
b
4.5 (2–7.2) 4 (2.5–7)
17 Social support scale
b
12 (7–18) 12 (6–18)
18 Ischemic stroke 83 (83) 84 (84)
19 Time since stroke
b
2(1–5) 2 (1–4)
There were no statistically significant baseline differences in the study participants
a
Mean (SD)
b
Median (IQR)
Table 2 Mean Morisky medication adherence score at baseline and 2-month follow-up in Intervention vs. usual care group
(multivariable analysis)
Intervention group
a
Usual care group
a
Adjusted difference
b
(95 % CI)
Baseline 2 months Baseline 2 months
Morisky medication adherence score 6.6 (0.17) 7.4 (0.93) 6.6 (0.16) 6.7 (1.32) 0.54 (0.22–0.85)*
*p< 0.01
a
Mean (SD)
b
adjusted for baseline adherence score, number of pills prescribed daily, dosing frequency, age, gender, employment status, education, use of alarms, missing
physician appointments in the previous year and block design
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reasonably expected with such limited exposure to inter-
vention. Although no major effect was observed on sys-
tolic blood pressure after the intervention (change of
1mmofHgp= 0.678), the diastolic blood pressure did
show a significant change over a 2 month period. The
mean diastolic blood pressure in the intervention group
was 2.6 mmHg (95 % CI; −5.5 to 0.15: p= 0.06) lower
compared to the control group after the intervention
(Table 4).
Acceptability of intervention
1. Patient satisfaction with intervention
The overall mean score for this tool was 12.5 out of 13
which is equivalent to a mean percentage of 96.07 %
(Table 5).
2. Diffusion characteristics of mHealth (mobile health)
intervention
The overall mean score for this outcome was 7.6 out of
8 which translates into an overall mean percentage
score of 95.6 % (Table 6). The four attributes of Roger’s
Diffusion theory were scored separately. The score for
Simplicity was 1.91/2, Compatibility was 1.91/2, Observ-
ability was 1.9/2 and Relative advantage was 1.95/2.
Discussion
This study is an early report of an SMS based inter-
vention for improving medication adherence in stroke
survivors based in a low resource setting. The results
show a significant increase in medication adherence
behavior which is encouraging and highlights the
possibilityofimprovingsecondarystrokeprevention
through a simple intervention. Additionally, a small
but significant difference in diastolic blood pressure
was observed in those who received SMS, who were
presumably more compliant in the intervention group.
Users of the SMS for stroke service reported a high
satisfaction and acceptability and the intervention it-
self showed good characteristics as an innovation that
may disseminate favorably.
We observed that the dosing frequency had a posi-
tively linear relationship with mean medication adher-
ence in the presence of intervention. This shows that the
intervention was effective in achieving high adherence
for participants with most difficult dosing regimens like
thrice daily frequency. This was possible because the
intervention was tailored to individual patient prescrip-
tion and reminders were sent according to dosing sched-
ule. On the other hand it was seen that mean adherence
was inversely related to total pill count prescribed per
day. This contrasts with previous findings from a study
in Pakistani hypertensive population [10], where increas-
ing number of pills increased the adherence scores.
Higher pill count may lead to patient fatigue and poorer
adherence. Patients with stroke are have relative cogni-
tive impairment leading to poorer adherence to a com-
plex prescriptions, however in spite of this setting the
Table 3 Factors associated with adherence to medications (univariate analysis)
βcoefficient 95 % CI p value
1 Intervention 0.65 0.3–1.0 0.00
2 Number of pills prescribed daily −0.0475 −0.09 to–0.03 0.04
3 Social support scale −0.01266 −0.03 to–0.01 0.21
4 Baseline Morisky adherence scale 0.2644 0.15 to 0.38 0.00
5 Educated 0.363 −0.25 to 0.97 0.24
6 Missed appointments in last year −0.518 −1.05 to 0.013 0.05
7 Dosing frequency of medicines once daily Ref
Twice daily 0.868 −0.03 to 1.76 0.06
Thrice daily 0.466 −0.46 to 1.39 0.32
8 Use of alarms 0.955 −0.40 to 2.31 0.16
9 Ischemic stroke −0.329 −0.821 to 0.161 0.19
Table 4 Effect on mean diastolic blood pressure
Mean DBP Mean DBP Mean
difference
95 %(CI)*
Pre-intervention Post-intervention
mmHg mmHg
Intervention
group
80 77.9 −2.6 −5.5 to 0.15
Usual care
group
80.6 80.5 −0.1
DBP diastolic blood pressure
*p= 0.06
Table 5 Patient satisfaction with intervention
Mean (SD)/total Mean %
Patient satisfaction with intervention 12.5 (1.5)/13 96.07 %
Kamal et al. BMC Neurology (2015) 15:212 Page 7 of 11
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intervention was effective and users became more
compliant.
mHealth (mobile Health) is a rapidly developing field
whose potential of leverage to improve medically im-
portant outcomes is great but is limited by a lack of
well-designed randomized controlled trials that measure
robust outcomes [31, 32]. Most SMS studies are focused
on communicable diseases with a recent shift towards
non-communicable diseases. SMS based interventions
have shown modest effect [33–41]. We feel that in
addition to robust RCT design the actual SMS wordings
of our intervention were designed on theories of behav-
ior change and may explain some effect as compared to
simple knowledge transfer messages [42]. Most IT inter-
ventions are not informed by theory or frameworks that
would explain the mechanisms of why a message would
work or not, and be replicable by other teams. We
used the Health Belief Model, as opposed to simple
knowledge transfer, which predicts influences on hu-
man behavior have 6 key determinants: Perceived sus-
ceptibility,Perceived seriousness,Perceived benefits of
taking action,Barriers to taking action, Cues to Action
and Self-efficacy [43, 44]. Thus participants were en-
abled to change their behavior via messages that
touched on these themes.
Adherence has two components namely: i) Intentional
non-adherence and ii) non-intentional non-adherence. It
is important to distinguish the contribution of both the
types in order to devise successful interventions [45].
We targeted both aspects by providing knowledge and
belief change messages and the other by cueing, nudging
and reminder behavior to take medications.
The major strength of this study is its RCT design,
with allocation concealment, blinded outcome ascer-
tainment, and use of validated tools and effort to re-
duce attrition. We used an open access software for
designing the intervention. Our intervention is clear,
designed and taxonomy coded and replicable. Further-
more, sensitivity analyses also reinforce the independ-
ent effect of intervention.
The main limitation of this trial is the use of self-
reported outcome measure the validated Morisky
Medication Adherence Scale (MMAS), which was chosen
due to the complex stroke medication regimen and popu-
lation characteristics. There have been comparative stud-
ies where self-reported adherence measures, like
questionnaires, are found to be acceptable compared to
more objective methods of measuring drug adherence like
electronic pill boxes, biomarkers [46–48]. We considered
the use of electronic pill boxes and biomarkers for out-
come assessment. However, stroke patients have diverse
prescriptions which vary in the type of drug classes, num-
ber and frequency of dosage, no single biomarker would
be applicable to all the study participants. Similarly, elec-
tronic pill boxes record the number of times a box is
opened. Since stroke patients are on multiple drugs at any
dosing time, it would be erroneous to believe that they
have consumed all the pills for that dose when they open
the box. It was logistically difficult to request disabled par-
ticipants to physically visit for repeated pill counts. So we
relied on self-reported scale as a measure of adherence.
Additionally, to counter check our measure, we docu-
mented day to day adherence with return SMS from the
participant. There are no ideal measures for reporting ad-
herence, the MMAS itself is a reliable measure of self-
reported adherence as it corresponds well to pharmacy
refill rates [49, 50]. We are exploring phone based adher-
ence measures to improve our adherence measurement
outcomes in future studies, such as unannounced pill
counts and capsule photographs [51, 52]. Another limita-
tion is that the duration of this study did not allow
measurement of definite biologic outcomes like stroke
recurrence after the intervention. It may be argued
that the patient population for this study had minimal
disability (MRS < 3), but it is this high risk group
which should be saved from recurrent disability by
stroke recurrence. Moreover, our eligibility data show
that 77 % of the stroke patients coming to our clinic
were eligible for this intervention and only 11 % were
excluded due to disability (Fig. 2). An inherent limita-
tion of the study is the performance bias of an educa-
tional intervention; participants were not blinded to
the reception of SMS and were well instructed and
probably motivated to medication adherence than the
control group. This motivation may be partially re-
sponsible for some of the adherence behavior. Al-
though our population may have poor literacy and
health literacy skills overall, we used a short text mes-
sageservicetoimproveadherenceduetothefactthat
Roman Urdu (easily legible) and Bolo SMS (Verbal
SMS) options were used in the study to send messages
to participants and this is what helped with acceptabil-
ity and reach. Pakistanis have exchanged 301.7 billion
SMS with 317 million users during 2014, covering
92 % of the land area. In this study, there was an ex-
pected limitation for those who would not possess a
cell phone, based on the eligibility criteria and review,
Table 6 Acceptability of mHealth intervention
Mean (SD)/total Mean %
Acceptability of mHealth intervention 7.6 (1.1)/8 95.6 %
Components
Simplicity 1.91 (0.35)/2 95.5 %
Compatibility 1.91 (0.35)/2 95.5 %
Observability 1.90 (0.40)/2 95 %
Relative advantage 1.95 (0.21)/2 97.5 %
Kamal et al. BMC Neurology (2015) 15:212 Page 8 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
6 of the 326 potential participants (1.8 %) were ex-
cluded on this basis and we found that at least based
on mobile infrastructure related basis, we were able to
reach out to 98 % of the population at our center.
Despite our efforts to keep the loss of follow up min-
imal, we did experience a 20 % loss to follow up due
to hesitation and limitation of disabled persons to
travel for follow up. In future interventions, we are
planning Skype™assisted teleconference follow ups to
measure functional status and other outcomes of inter-
est in disabled persons.
Some operational difficulties with the intervention
were faced when the SMS service was blocked in the
country for security reasons. There were 3 separate
occasions when this happened, each lasting 24 h. We an-
ticipated such events and informed our participants
about the possibility of not being able to send reminder
messages that day and that they should manage their
medications themselves to avoid anxiety. After set up it
was very easy to operate the system.
The effect on diastolic blood pressure needs to be
strengthened by improving study power and duration of
exposure. We believe this tool has the potential to bring
such changes if used over a significant duration.
The potential impact of using SMS to cue chronic dis-
ease desirable behavior is immense. SMS is incredibly
popular and acceptable, with Pakistani mobile phone
users exchanging a staggering 315.7 billion text messages
during July 2012 to June 2013 or 865 million SMS mes-
sages a day and prefer this mode of communication [39].
There are 135 million registered phone users in Pakistan
whose data are biometrically verified, in addition there is
a national electronic database where all users are linked
and registered and potentially able to receive SMS [19].
The cost of SMS is cheap including bundles for business
and social marketing, and the software used to deploy
mass messages is open access and freely available. Stroke
happens a decade earlier in LMIC countries like Pakistan
and the population at risk is using cell phones. Addition-
ally, since the stroke survivor and primary caregiver res-
ide in communities, the primary caregiver often has
access to a mobile phone and it is possible to make the
intervention effective in a relatively older population.
Additionally, although the population has literacy chal-
lenges a text based reminder system works even in those
who have had minimal schooling due to the widespread
understanding of Roman Urdu (which we also used to
send our messages).
Although it is not known how SMS would affect ter-
minal outcomes like recurrent strokes, death or disabil-
ity, it is known that the effect size itself is modest. In
spite of these acknowledged limitations, in population
dense regions, in absolute numbers, millions of lives
could be reached and positively influenced regardless of
geopolitical strife, chaos, socioeconomic differences and
access inequities.
Conclusions
In conclusion, we feel that the SMS intervention seems
feasible for clinical use in stroke survivors for improving
adherence. Further studies are needed to report on
meaningful biologic outcomes like recurrent stroke,
death and disability. Cost effectiveness, scalability char-
acteristics beyond what we have reported, are also areas
in need of further research exploration, as larger scale
policy informing analysis.
Additional file
Additional file 1: Interim Analysis. (DOC 37 kb)
Abbreviations
SMS: Short text message; AKUH: Aga Khan university hospital; JCIA: Joint
commission international accreditation; CTU: Clinical trials unit; MMAS: Morisky
medication adherence scale; mHealth: Mobile health.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
AKK conceived the study design, developed the intervention, wrote the
manuscript, QS directly overlooked all aspects of study design, logistics,
analysis, and follow up and wrote the manuscript with AKK, IA, BA, MI
assisted statistical design, OP reviewed the study for overall quality and
design robustness, MA assisted data base design and follow up issues, SN,
AAM intellectually contributed to the design and flow of the study, HR
contributed to all aspects of writing related to this protocol; MJ, AA worked
on data flow issues and contributed intellectually to the design and writing
of this paper, SA was IT 24/7 for all SMS AM provided all technical support
and solutions and contributed to the technical aspect of the study SK
provided intellectual support and oversight for all aspects of design with
emphasis on scale up and user interoperability and replicability. All authors
have contributed intellectually to this manuscript.
Authors’information
The authors are a group of Transdisciplinary investigators including IT,
neurovascular neurologists, biomedical engineers, epidemiologists and study
design experts working together in an LMIC setting to implement best
evidence for stroke in resource challenged settings.
Acknowledgements
We would like to acknowledge the tremendous support, cooperation,
respect, humor, hope, courage and grace of the families of stroke survivors
and caregivers in Pakistan, who continue to provide exemplary care, love,
affection to their loved ones and who inspire us every day. It would not
have been possible to do this study without their unstinting engagement.
Funding disclosures
Dr Ayeesha Kamran Kamal is the co-director and recipient of grant entitled,
“The International Cerebrovascular Translational Clinical Research Training
Program”(Fogarty International Center, National Institutes of Health).
Dr. Quratulain Shaikh is a neurovascular research fellow whose mentored
research practicum training is currently funded by Award Number
D43TW008660 from the Fogarty International Center and the National Institute
of Neurologic Disorders and Stroke. This work has been directly facilitated by
the above training and research grant.
Dr Ayeesha Kamran Kamal is also funded by Grand Challenges Canada- Bold
ideas with Big Impact, University Research Council Aga Khan University
(URC, AKU), Higher Education Commission (HEC), Gov. of Pakistan; She is
Kamal et al. BMC Neurology (2015) 15:212 Page 9 of 11
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
also collaboratively funded from Baylor College of Medicine, BCM Center
for Globalization on work on medical prescription literacy.
The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript. The content is solely
the responsibility of the authors and does not necessarily represent the
official views of the Fogarty International Center, National Institute of
Neurologic Disorders and Stroke or the National Institute of Health.
Author details
1
Stroke Services, Section of Neurology, Department of Medicine, The
International Cerebrovascular Translational Clinical Research Training Program
(Fogarty International Center, National Institutes of Health) and Aga Khan
University, Stadium Road, 74800 Karachi, Pakistan.
2
Fogarty Cerebrovascular
Research Fellow, The International Cerebrovascular Translational Clinical
Research Training Program (Fogarty International Center, National Institutes
of Health) and Aga Khan University, Karachi, Pakistan.
3
Epidemiology and
Biostatistics Program, Department of Community Health Sciences, Aga Khan
University, Karachi, Pakistan.
4
Department of Community Health Sciences,
Biostatistics, Aga Khan University, Karachi, Pakistan.
5
SMS4Stroke Study, The
International Cerebrovascular Translational Clinical Research Training Program
(Fogarty International Center, National Institutes of Health) and Aga Khan
University, Karachi, Pakistan.
6
Stroke Service, Aga Khan University, Karachi,
Pakistan.
7
eHealth Innovation, Global, eHealth Resource Center, Aga Khan
Development Network, Karachi, Pakistan.
8
Epidemiology and Biostatistics,
Department of Medicine, Aga Khan University, Karachi, Pakistan.
9
Tech4Life
Enterprises, and Technical Advisor-Evidence, Capacity & Policy mHealth
Alliance, United Nations Foundation, Washington, USA.
Received: 29 July 2015 Accepted: 8 October 2015
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