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Study protocol
Protocol for SAMS (Support and Advice for Medication Study): A
randomised controlled trial of an intervention to support patients
with type 2 diabetes with adherence to medication
Andrew J Farmer*
1
, A Toby Prevost
2
, Wendy Hardeman
2
, Anthea Craven
1
,
Stephen Sutton
2
, Simon J Griffin
3
, Ann-Louise Kinmonth
2
for The Support
and Advice for Medication Trial Group
Address:
1
Department of Primary Health Care, University of Oxford, Oxford, OX3 7LF, UK,
2
General Practice and Primary Care Research Unit,
Institute of Public Health, University of Cambridge, Cambridge, CB2 0SR, UK and
3
MRC Epidemiology Unit, Institute of Metabolic Science,
Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
Email: Andrew J Farmer* - andrew.farmer@dphpc.ox.ac.uk; A Toby Prevost - atp14@medschl.cam.ac.uk;
Wendy Hardeman - wh207@medschl.cam.ac.uk; Anthea Craven - anthea.craven@dphpc.ox.ac.uk; Stephen Sutton - srs34@medschl.cam.ac.uk;
SimonJGriffin-sjg49@medschl.cam.ac.uk; Ann-Louise Kinmonth - alk25@medschl.cam.ac.uk; The Support and Advice for Medication Trial
Group - sams@dphpc.ox.ac.uk
* Corresponding author
Abstract
Background: Although some interventions have been shown to improve adherence to
medication for diabetes, results are not consistent. We have developed a theory-based
intervention which we will evaluate in a well characterised population to test efficacy and guide
future intervention development and trial design.
Methods and Design: The SAMS (Supported Adherence to Medication Study) trial is a primary
care based multi-centre randomised controlled trial among 200 patients with type 2 diabetes and
an HbA1c of 7.5% or above. It is designed to evaluate the efficacy of a two-component motivational
intervention based on the Theory of Planned Behaviour and volitional action planning to support
medication adherence compared with standard care. The intervention is delivered by practice
nurses. Nurses were trained using a workshop approach with role play and supervised using
assessment of tape-recorded consultations. The trial has a two parallel groups design with an
unbalanced three-to-two individual randomisation eight weeks after recruitment with twelve week
follow-up. The primary outcome is medication adherence measured using an electronic medication
monitor over 12 weeks and expressed as the difference between intervention and control in mean
percentage of days on which the correct number of medication doses is taken. Subgroup analyses
will explore impact of number of medications taken, age, HbA1c, and self-reported adherence at
baseline on outcomes. The study also measures the effect of dispensing medication to trial
participants packaged in the electronic medication-monitoring device compared with conventional
medication packaging. This will be achieved through one-to-one randomisation at recruitment to
these conditions with assessment of the difference between groups in self-report of medication
adherence and change in mean HbA1c from baseline to eight weeks. Anonymised demographic data
Published: 11 April 2008
BMC Family Practice 2008, 9:20 doi:10.1186/1471-2296-9-20
Received: 3 March 2008
Accepted: 11 April 2008
This article is available from: http://www.biomedcentral.com/1471-2296/9/20
© 2008 Farmer et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 8
(page number not for citation purposes)
are collected on non-respondents. Central randomisation is carried out independently of trial co-
ordination and practices using minimisation to adjust for selected confounders.

BMC Family Practice 2008, 9:20 http://www.biomedcentral.com/1471-2296/9/20
Discussion: The SAMS intervention and trial design address weaknesses of previous research by
recruitment from a well-characterised population, definition of a feasible theory based intervention
to support medication taking and careful measurement to estimate and interpret efficacy. The
results will inform practice and the design of a cost-effectiveness trial [ISRCTN30522359].
Background
Diabetes is a major public health problem. The number of
people with diabetes is estimated to reach 330 million by
2030 [1]. There is a high clinical and economic burden
from the disease [2]: people with diabetes have a two-to-
four fold increased risk of cardiovascular disease com-
pared to the general population and increased incidence
of retinopathy, peripheral nerve damage and renal prob-
lems.
Evidence supports the use of multiple medications to con-
trol blood glucose and cardiovascular risk among patients
with type 2 diabetes [3], and, this may lead to prescrip-
tions of eight or more medications a day. Up to half of this
medication may not be taken as prescribed [4,5], with
adherence to medication falling as dosage frequency rises
[6]. Failure to take medication has important conse-
quences. It not only reduces efficacy of the treatment, but
wastes healthcare resources in prescribed pills not taken,
extra consultations, referrals, investigations and hospital
admissions [7,8]. The availability of an effective interven-
tion to support patients with type 2 diabetes in taking
their medication regularly would make a major contribu-
tion to human health.
A variety of interventions to support adherence to medica-
tion have been tested for efficacy [9], and their clinical
application assessed [10]. Although some interventions
are effective in improving adherence, the results are incon-
sistent. These studies have used complex packages of care,
targeting multiple self-care activities and therefore limit-
ing identification of factors that lead to and might modify
non-adherence. Approaches to supporting behaviour
change are now informed by evidence about the psycho-
logical determinants of behaviour, and techniques to alter
them, and there is potential to apply these techniques in
the field of medication adherence [11,12].
Adherence to medication can be defined in many ways.
Our definition is the extent to which medicines are taken
regularly as prescribed. We argue that to understand the
determinants of adherence better and optimise the impact
of different intervention components upon them, we
need to design interventions based on clear conceptual
frameworks. We also need to test whether targeting deter-
minants of medication adherence (e.g., patient's beliefs)
People may not take their medication because of ambiva-
lence about pros and cons of adherence (intentional
lapse). Others, who intend to take their medications regu-
larly, may still forget to do so (non-intentional lapse).
Intentional and non-intentional lapses in adherence have
been identified as two important elements contributing to
overall non-adherence [14]. Drawing on psychological
theory and evidence [15,16], we have developed
approaches to address these two elements: to increase
patients' motivation to take their tablets regularly by tar-
geting underlying beliefs; and to help patients define spe-
cific action plans to facilitate the translation of intentions
into action and habit formation. The two components can
be defined as motivational – targeting the cognitive deter-
minants of intention – and volitional – defining action
plans to implement the target behaviour [15].
The motivational component of the intervention is based
on the Theory of Planned Behaviour (TPB) [16]. This the-
ory specifies beliefs which may be targeted to strengthen
intention. In particular techniques include reinforcement
of positive beliefs and problem solving approaches to
negative beliefs. The theory's constructs account for 35 to
50% of variance in intention and 26 to 35% of variance in
behaviour [17]. This illustrates a gap between intention
and behaviour. The use of action planning, also called
implementation intentions[15], is a promising approach
to bridge this gap. A range of studies has demonstrated
that explicit consideration of the circumstances under
which a behaviour will be enacted (action plans), pro-
motes clinically important change in specific health
related behaviours including consumption of vitamin C
tablets, attendance for cervical cytology screening and
breast self-examination [18].
In clinical trials evaluating medication taking, adherence
in the control group is often high. This may be because
patients willing to participate in trials are likely to be
adherent, because self-report measures may overestimate
true adherence, or because more objective measurement
focuses attention, on this target behaviour [7,10]. To
interpret the effects of interventions better, future trials
need to characterise the population from which partici-
pants have been recruited by collecting data about non-
responders, encouraging respondents who do not wish to
take part in the trial to complete baseline questionnaires,Page 2 of 8
(page number not for citation purposes)
results in greater levels of adherence [11,13]. and investigating the effect of measurement itself on
adherence and clinical risk.

BMC Family Practice 2008, 9:20 http://www.biomedcentral.com/1471-2296/9/20
In previous pilot work we have developed measures and
interventions [19] using the approach defined by the
Medical Research Council Framework for development of
interventions for evaluation in randomised trials [20,21].
We therefore intend to estimate the efficacy of support for
medication adherence on medication taking behaviour
using motivational and action planning techniques; and
estimate the effect of monitoring medication-taking itself
on self-reported adherence and glycaemic control in a ran-
domised trial. The trial addresses important limitations in
the literature by recruitment from a well-characterised
population, definition of a feasible intervention to sup-
port medication taking, and careful measurement to esti-
mate and interpret efficacy.
Methods/Design
Trial design
This parallel group trial has two sequential randomisa-
tions. The main randomisation takes place eight weeks
after recruitment, is unbalanced and compares a two-com-
ponent intervention addressing motivation and action
planning with a control intervention in which patients
only take part in data collection (Figure 1). Unbalanced
randomisation is used to maximise experience with the
intervention across a range of patients with follow up at
twenty weeks. The measurement effect randomisation,
which takes place at the baseline recruitment visit, is bal-
anced and assesses the effect of dispensing medication in
a container that records opening compared with dispens-
ing medication in standard packaging: with follow up at
eight weeks.
Ethical approval
The London, multi-centre research ethics committee has
reviewed and approved the protocol (06/MRE02/3).
Setting
Recruitment of patients is from general practices in
Oxfordshire, Milton Keynes, Suffolk, Essex and Hunting-
donshire.
Patients
Patients are eligible for inclusion in the trial if diagnosed
aged 18 years or above with type 2 diabetes of at least
three months duration, able to give informed consent,
currently taking any oral glucose-lowering agent and with
a HbA1c ≥ 7.5%. Those approached are deemed by their
general practitioner able to complete a consent form,
independent in medication taking, and appropriate for
tight glycaemic control.
Flow of participants through studyigure 1
Flow of participants through study.
Recruitment
Randomisation to intervention or control
Control group
visit
Final follow upFinal follow up
0 weeks
8 weeks
20 weeks
Intervention
group visit
n=100 n=150
Randomisation to evaluate measurement effect
TrackCap†
n=125
No TrackCap†
n=125
† TrackCap electronic medication-monitoring device
8-week
outcome
n=125
8-week
outcome
n=125
Lost to
follow-upPage 3 of 8
(page number not for citation purposes)

BMC Family Practice 2008, 9:20 http://www.biomedcentral.com/1471-2296/9/20
Intervention
After an eight week period of initial observation, patients
are allocated to either an intervention visit to support
medication adherence, or to a control visit at which their
current medication regimen is recorded.
The intervention was developed and piloted after a
detailed study to identify beliefs held about diabetes [19].
The intervention visit is delivered by the practice nurse. In
the first, motivational component of the intervention, the
nurse elicits the patient's beliefs relevant to their intention
to take medication regularly as prescribed based on the
TPB. Nurses use scripts to guide the order and phrasing of
questions that elicit individual beliefs about benefits and
harms, views of important others and factors that may
facilitate or inhibit taking medication regularly as pre-
scribed. Positive beliefs are reinforced with provision of
tailored information and problem solving is applied in
relation to negative beliefs [16]. In the second, action
planning component, the nurse asks the patient to write
down the exact circumstances under which they will take
their medication (using an "if.then" formulation to elicit
where, when and how this will occur) [15]. In the control
visit, delivered by the practice nurses, none of the above
techniques are applied.
Intervention fidelity
Initial training is provided over one day for the practice
nurses delivering the intervention, using a workshop
approach with role-play led by a psychologist and inter-
vention facilitators involved in quality assurance of inter-
vention delivery. It includes explanation of the rationale
for the intervention, use of a detailed manual providing
information about the theoretical base and operationali-
sation of the different components, how to use the inter-
vention to establish agreement with the prescription plan,
and use of a 'script' to promote fidelity of intervention
delivery. Assessment of audiotapes of intervention ses-
sions is conducted to assess fidelity of delivery using
standardised forms. Subsequently, coaching and feedback
is provided to the nurses to optimise intervention deliv-
ery. Possible sources of bias in intervention delivery are
addressed with the practice nurses throughout training
and ongoing support. These include the need to avoid (i)
delivering the intervention to control group patients, (ii)
discussing the intervention techniques with other mem-
bers of the primary care team and (iii) using intervention
techniques not specified in the script.
Measurement effect
At the baseline visit patients are randomised to be dis-
pensed their metformin tablets in a container with a lid
that records the occurrence and timing of opening (Track-
If participants are not taking metformin, another of their
usual oral hypoglycaemic medication is dispensed in the
electronic medication-monitoring device.
Randomisation
Randomisation of patients to assess intervention and
baseline measurement effects is carried out independently
of trial co-ordination and intervention by the trial statisti-
cian. A partial minimisation procedure is used to dynam-
ically adjust randomisation probabilities to balance the
baseline stratification variables. For measurement effect,
randomisation at baseline includes practice, duration of
diabetes, HbA1c result from the practice record and
patient baseline measure of self-report adherence. For
intervention, randomisation at eight weeks includes the
baseline measurement-effect randomisation group alloca-
tion, and baseline HbA1c is included instead of the prac-
tice record. Staff receiving and downloading the data from
the electronic medication-monitoring device are blind to
allocation, as are laboratory staff measuring HbA1c.
Study procedures
Baseline data collection and randomisation to electronic medication
taking measurement
Eligible patients registered with the practice are identified
by the practice nurse. Baseline data from the notes is
recorded by the practice nurse and anonymised to provide
data from which to characterise the population from
which participants were recruited. Eligible patients are
sent a letter from the practice including study details, a
questionnaire asking about basic demographics, medica-
tion regimen, self-reported medication adherence, and
beliefs about taking diabetes medicines without missing a
day (Table 1 and Table 2). If willing to help further, a
phone call is made by the practice nurse to the patient to
arrange a study appointment.
Willing patients attend a baseline recruitment consulta-
tion of 40 minutes with their practice nurse. In advance of
the visit patients are allocated to be dispensed medication
in the electronic medication-monitoring device or in
standard packaging. Informed consent is obtained and
additional clinical data collected. Blood tests are taken,
and questionnaires completed. For those allocated to the
electronic medication-monitoring device, its use is
explained, and the practice dispenser or pharmacist dis-
penses the patient's usual prescription for metformin or
alternative oral glucose lowering agent in the device. For
those allocated to standard packaging, the practice dis-
penser or pharmacist dispenses medication in standard
blister-packs. A follow-up visit is arranged in eight weeks
and, in advance of the visit, the patient is randomised to
be allocated to receive the intervention or control visit.Page 4 of 8
(page number not for citation purposes)
Cap, Aardex, Zurich, Switzerland), or to continue taking
their medication in standard packaging as before the trial.

BMC Family Practice 2008, 9:20 http://www.biomedcentral.com/1471-2296/9/20
Intervention and control visit
Prior to the eight-week study visit patients are sent a ques-
tionnaire to be completed at home and returned to the
coordinating centre in a sealed envelope by post. At the
eight-week visit, patients allocated to the intervention take
part in a 50 minutes interview with the practice nurse
including the intervention and data collection. The con-
trol visit lasts approximately 20 minutes in which the data
are collected. All patients at the eight week visit have
blood samples taken and inquiry made about any possi-
ble adverse events including hypoglycaemia. A postal
questionnaire is completed one week after the eight week
visit.
Follow up to 20 weeks
Final follow up for all patients at 20 weeks involves a visit
to the practice nurse and includes a blood sample for
measurement of HbA1c and drug concentrations, and a
final questionnaire.
Table 1: Trial measures and timing
Baseline visit Before 8 week visit At 8 week visit After 8 week visit Final visit at 20-weeks
Basic demographics x
Medication x x x
Co-morbidity x
Clinical measures
Weight x x
Blood pressure x x
HbA1c (Central laboratory) x x x
Adherence
Electronic medication monitor for preceding
period
x (50%) x
Self-report (MARS) Diabetes x x
Drug concentrations x x
Psychological
TPB† Direct measures and intention x x x
TPB† Indirect measures x x x
Time and location of taking medicines x
Communication with practice nurse x
Quality of Life
Short-Form 12‡ x x
Diabetes Treatment Satisfaction Questionnaire x
Hypoglycaemia x
‡
12-Item short form Medical Outcomes Study health survey questionnaire.
†
Theory of Planned Behaviour.
Table 2: Theory of Planned Behaviour measures of belief and intention towards taking oral glucose-lowering medications
Variable name Number of items† Sample question
Direct attitude 2 It is beneficial for me to take my diabetes medicines without missing a day
Direct subjective norm (injunctive) 2 Most people who are important to me think I should take my diabetes medicines
without missing a day
Direct subjective norm (descriptive) 1 If they were taking part in this study, most people who are important to me would
take their diabetes medicines without missing a day
Direct perceived behavioural control 3 It is difficult for me to take my diabetes medicines without missing a day
Indirect attitude 7 If I were to take my diabetes medicines without missing a day, it would keep my
diabetes under control
Indirect subjective norm (injunctive) 3 Members of my family or close relatives would approve of me taking my diabetes
medicines without missing a day
Indirect perceived behavioural control 4 Changes to my daily routine would make it more difficult for me to take my
diabetes medicines without missing a day
Intention 2 I intend to take my diabetes medicines without missing a dayPage 5 of 8
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†Each measured on a 7-point scale from 1 = strongly disagree to 7 = strongly agree

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Measurement
Primary outcome for intervention trial
The primary outcome for the intervention is the percent-
age of days on which the prescribed dose of main
hypoglycaemic medication is taken as prescribed, meas-
ured with the TrackCap electronic medication monitor
over a 12-week period from eight to twenty weeks.
Primary outcome for measurement-effect trial
The primary behavioural outcome for the measurement
effect of the use of an electronic medication-monitoring
device compared with standard packaging is change in self
reported adherence measured with the Medication Adher-
ence Report Schedule (MARS). The primary clinical out-
come for the measurement effect is mean HbA1c at eight
weeks.
Secondary outcomes for intervention trial
Secondary outcomes are HbA1c, well-being measured
with the 12-item Short Form Medical Outcomes Study
health survey questionnaire (Short Form-12) [22] and
treatment satisfaction measured with the Diabetes Treat-
ment Satisfaction Questionnaire (DTSQ) [23].
Additional measures of medication adherence
Other measures include serum drug concentrations and
self-reported measures of medication adherence (MARS)
[24], and dispensing records to complement electronic
medication-monitoring. Drug concentrations will be col-
lected to explore whether the electronic medication-mon-
itoring device records of timing of doses relate to the
presence of therapeutic concentrations at study visits.
Psychological and process measures
A questionnaire based on the Theory of Planned Behav-
iour is used to assess attitude, subjective norm, perceived
behavioural control, and intention to take diabetes medi-
cines without missing a day. The questionnaire also
assesses perceived consequences of taking diabetes medi-
cation (behavioural beliefs); perceived views of significant
others about taking diabetes medication (normative
beliefs); perceived factors that make taking diabetes med-
ication easier or difficult (control beliefs). These measures
are based on our earlier pilot work [19].
We are using a measure to assess patients' ratings of com-
munication with nurses (covering the ability to tell the
nurse personal or troubling things and feeling under-
stood) [25], and ask open-ended questions about when
and where medications are usually taken. Tape recordings
of consultations are used to assess fidelity of intervention
delivery, using a-priori criteria. The intervention facilita-
tors record adherence to techniques specified in the inter-
Baseline measures to characterise participants
Socio-demographic and clinical measures include meas-
ures of duration of diabetes, overall drug regimen and
numbers of prescribed medication doses. For the pur-
poses of characterising the eligible population and ran-
domisation at baseline, the last practice-recorded HbA1c
is also recorded.
Sample size
The trial is planned to follow-up 200 patients, providing
80% power at the 5% significance level to detect a differ-
ence in means between randomised groups of 5% (1.5
days per month difference) in the percentage of days on
which the correct number of doses is taken. This was
based on an estimate of the standard deviation of this
measure of 13.5% in a pilot study for the trial conducted
in 2001 in Newmarket, Cambridgeshire (personal com-
munication Dr Simon Griffin). Assuming a follow-up rate
of 85%, a maximum of 250 participants would need to be
recruited.
For the measurement effect we can detect a difference of
one point in the MARS self-reported adherence measure
(a small to moderate effect size) [24], with 80% power
and a two sided test at the 5% level with a conservative
estimate of a 2.5% standard deviation. We will also detect
a 0.5% difference in HbA1c at eight weeks with 80%
power at the 5% level assuming a standard deviation of
1.25% for HbA1c.
Analysis
Intervention effect
Analysis will be by intention-to-treat using multiple
imputation for those with missing data by the method of
Rubin [26]. This will be supported by a sensitivity analysis
reporting all cases where the primary outcome is available
and using optimistic and pessimistic scenarios with the
imputed estimates for missing data [27]. The mean per-
centage of days on which the correct number of doses is
taken will be compared between the groups allocated to
intervention and control, using a non-parametric boot-
strap method to derive the difference in means with a 95%
confidence interval [28,29].
Measurement effect
The primary behavioural outcome for the assessment of
measurement effect is self-reported adherence (MARS) at
eight weeks compared between groups allocated to use of
the medication monitor compared to those allocated to
dispensing of medicines in standard packaging. The pri-
mary clinical outcome is HbA1c at 8-weeks compared
between groups. In order to increase the precision of esti-
mated intervention effects continuous measures will bePage 6 of 8
(page number not for citation purposes)
vention script on standardised forms. analysed with adjustment for the baseline covariate prior

BMC Family Practice 2008, 9:20 http://www.biomedcentral.com/1471-2296/9/20
to the first randomisation, if available, with missing base-
line data included by the missing indicator method [27].
Sub-group analyses
Subgroup analyses will be carried out to explore the
impact of number of medications, age, HbA1c, self-
reported adherence at baseline and prior randomisation
to the electronic medication-monitoring device on the
intervention effect.
Additional analyses
We will assess the impact of the intervention on beliefs
about taking diabetes medication, and test whether any
observed change in medication adherence is mediated by
the intervention's impact on beliefs. We will explore the
potential role of nurse communication style as a modera-
tor of effect. We will compare the differences between par-
ticipating and non-participating patients.
Discussion
This trial is designed to estimate the efficacy of a two-com-
ponent intervention targeting determinants of intentions
and action planning as possible mediators of improved
medication adherence. Measures and interventions have
been developed using the approach defined by the Medi-
cal Research Council Framework for development of
interventions for evaluation in randomised trials [20,21].
In addition to estimating efficacy the trial will provide
information on psychological mechanisms of increasing
medication adherence and assess the impact of trial meas-
urement on outcomes.
We are conducting this trial in a well characterised pri-
mary care population. The training of nurses to deliver the
intervention uses scripts and feedback from taped inter-
vention sessions to maximise delivery as planned and
consistent delivery across nurses and over time. We are
able to test impact of the communication style of the prac-
tice nurse by examining the relationship between patient
attitudes about communication and behavioural out-
comes. We have optimised clear communication of the
intervention through training and feedback to the nurses
delivering the intervention.
This trial has been designed to address the weaknesses of
previous work in the area of medication adherence. It
approaches medication taking as a discrete behaviour and
uses psychological theory and evidence in the design of
intervention to address intentions and the step from
intention to actions, and in measurement of the process.
It will therefore be possible to explore the extent to which
interventions that address these components of medica-
tion adherence might improve outcomes. Additional
intention and action planning. The trial will explore the
extent to which previous trials may have failed to show
efficacy as a result of the kind of people who participate in
such trials, and the kinds of measures of adherence used,
including the impact of measurement itself on adherence
and HbA1c.
This trial will provide one of the first evaluations of an
intervention developed using psychological theory to sup-
port patients in adherence to diabetes medication. If the
trial provides evidence of efficacy, it will add to the clinical
approaches for medicines education currently in use.
If the two-component intervention shows evidence of effi-
cacy, we propose to compare it with the action-planning
only intervention in a future trial. Future research in this
area will also need to incorporate detailed health eco-
nomic assessments to assess cost-effectiveness. However,
because of the large numbers of people with diabetes,
even very small effects of an intervention on adherence
offer potential for major public health gains.
Competing interests
The author(s) declare that they have no competing inter-
ests.
Authors' contributions
A-LK and AF led the grant-writing group. All authors were
involved in the development and application of the pro-
tocol. The contributions of other members of the SAMS
study team are gratefully acknowledged and listed above.
AF is the guarantor of this paper.
Funding
This trial is supported by the Medical Research Council
and through National Health Service R&D support fund-
ing.
The SAMS Team
Writing group: A Farmer, AT Prevost, W Hardeman, A Cra-
ven, S Sutton, S Griffin, A-L Kinmonth. Coordinating Cen-
tre: A Craven, J Oke, D White. Trial Statistician: AT Prevost.
Intervention Development: A Farmer, W Hardeman, I Kellar,
Y Kim, M Selwood, S Sutton. Measures: A Farmer, S Griffin,
D Hughes, I Kellar, S Sutton. Practices: Suffolk; The Rook-
ery Medical Centre Newmarket, Woolpit Health Centre;
Huntingdonshire; Rainbow Surgery Ramsey, Ramsey
Health Centre, The Surgery Papworth Everard, Spinney
Surgery St. Ives, Eaton Socon Health Centre; Essex; John
Tasker House Surgery Great Dunmow; Oxfordshire;
Woodcote Surgery, Horse Fair Surgery Banbury, Islip Med-
ical Practice; Milton Keynes; Parkside Medical Centre,
Stantonbury Health Centre. Pharmacies: Lloyds PharmacyPage 7 of 8
(page number not for citation purposes)
analyses will estimate the extent to which any observed
effects of the intervention on behaviour are mediated by
Ramsey, Cox & Robinson Banbury; Yogi Pharmacy Great
Dunmow; P & I Smith Bletchley, Cox & Robinson Bletch-

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BMC Family Practice 2008, 9:20 http://www.biomedcentral.com/1471-2296/9/20
ley, Lloyds Pharmacy Eaton Socon, McLaren Pharmacy
New Bradwell. Nurse training and intervention co-ordination:
S Boase, Y Kim. Fidelity assessment: J Argles, S Boase, P
Gash, Y Kim, M Selwood. Primary care network liaison: J
Graffy. Pharmaceutical adviser: S. Ashwell.
Acknowledgements
We are grateful to the patients; practice nurses; general practitioners and
pharmacists for taking part in this trial. We are grateful to Professor R
Horne for permission to use the MARS scale and Professor C Bradley for
permission to use the DTSQ. The Departments of General Practice at the
Universities of Oxford and Cambridge are partners in the NIHR National
School of Primary Care Research. The SAMs study is a component of the
MRC co-operative on the development and evaluation of innovative strat-
egies for the prevention of chronic disease in primary care. The opinions
expressed in this paper are not necessarily those of the Department of
Health.
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