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Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus

  1. Kingshuk Pal1,*,
  2. Sophie V Eastwood1,
  3. Susan Michie1,
  4. Andrew J Farmer2,
  5. Maria L Barnard3,
  6. Richard Peacock4,
  7. Bindie Wood1,
  8. Joni D Inniss1,
  9. Elizabeth Murray1

Editorial Group: Cochrane Metabolic and Endocrine Disorders Group

Published Online: 28 MAR 2013

Assessed as up-to-date: 14 NOV 2011

DOI: 10.1002/14651858.CD008776.pub2


How to Cite

Pal K, Eastwood SV, Michie S, Farmer AJ, Barnard ML, Peacock R, Wood B, Inniss JD, Murray E. Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. Cochrane Database of Systematic Reviews 2013, Issue 3. Art. No.: CD008776. DOI: 10.1002/14651858.CD008776.pub2.

Author Information

  1. 1

    University College London, Research Department of Primary Care and Population Health, London, UK

  2. 2

    University of Oxford, Department of Primary Care Health Sciences, Oxford, UK

  3. 3

    The Whittington Hospital NHS Trust, Department of Diabetes, London, UK

  4. 4

    Archway Healthcare Library, London, UK

*Kingshuk Pal, Research Department of Primary Care and Population Health, University College London, Upper Floor 3, Royal Free Hospital, Rowland Hill Street, London, NW3 PF, UK. k.pal@ucl.ac.uk. drkpal@gmail.com.

Publication History

  1. Publication Status: New
  2. Published Online: 28 MAR 2013

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Characteristics of included studies [ordered by study ID]
Christian 2008

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

1. Latin/Hispanic in ethnicity with a language preference of either English or Spanish

2. Aged 18 to 75 years with a diagnosis of type 2 diabetes
3. A BMI of 25 or greater

4. Uninsured, Medicaid eligible or Medicare beneficiaries.

Exclusion criteria:

1. Substance use or abuse

2. Severe arthritis or other medical condition limiting physical activity

3. Recent MI or stroke or PVD

4.Undergone or scheduled for gastric bypass surgery.


InterventionsNumber of centres: 2

Country: USA

Setting: Outpatient clinic settings at 2 large urban community-based health centres - the Denver Health and Hospital Authority's Sandoz Westside Neighbourhood centre in Denver and the Pueblo Community Health Center Pueblo.


OutcomesPrimary end point: weight loss, expressed as mean weight loss and the fraction of participants in each group achieving a clinically meaningful weight loss defined as a 5% reduction in body weight.

Secondary end points: change in physical activity estimated in metabolic equivalent task minutes, change in energy intake, change in lipids and HbA1c levels


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Supported by grant 5R44DK060272-3 from the US National Institute of Diabetes and Digestive and Kidney Diseases to PHCC LP Pueblo Colorado

Publication status: Peer reviewed journal


Stated aim of study"To test the effect of physicians providing brief health lifestyle counselling to patients with type 2 diabetes mellitus during usual care visits"


NotesAuthors contacted: Blinding of outcome assessment - there was some blinding but not for all cases.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Low risk"Assignments to 1 of these 2 groups were based on a computer-generated random number sequence"

Allocation concealment (selection bias)Low risk"Assignment was concealed to the RA by a padded envelope that also contained a kit of baseline enrolment materials"

Blinding (performance bias and detection bias)
All outcomes
High risk"Neither physicians nor patients could be blinded to the intervention assignment"

Comment: Authors contacted: no blinding for outcome assessment.

Incomplete outcome data (attrition bias)
All outcomes
Low risk"Analyses were tied to a priori hypotheses. We conducted intention-to-treat analyses using a “last-record-carried-forward” method in which the last available data from dropouts were used when analysing 12-month data"

Follow-up rates: Intervention: 141/155 = 91%. Control: 132/155 = 85%.

Selective reporting (reporting bias)Unclear riskInsufficient information to permit judgement.

Other biasUnclear risk"Ninety-eight percent of patients were taking antihyperglycaemic medications, and 51% of patients had changes in their medication regimen during the study.We were not able to determine the independent effects of changes in medication regimens on HbA1c levels. However, there was a significantly greater reduction in HbA1c level for control patients who had their dosage of antihyperglycaemic drugs increased or the type of medication changed—a −0.9 reduction in HbA1c level vs a −0.04 reduction for intervention patients who also had changes in their anti-diabetes drug regimen"

Comment: The effect of the intervention on HbA1c is likely to be smaller than the effects of changes in anti-hyperglycaemic medication.

Glasgow 1997

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

1. Having type 1 or type 2 diabetes

2. aged 40 or older

3. Primarily responsible for one's own diabetes dietary self-management (not institutionalised).

Exclusion criteria:

Not stated


InterventionsNumber of centres: 2

Country: USA

Setting: Offices of 2 Internists


OutcomesDietary measures including the Kristal Food Habits Questionnaire and 4-day food record; BMI, cholesterol and HbA1c; Patient satisfaction and cost assessment


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Supported by grant 3DK-R01-35524 from the National Institutes of Diabetes, Digestive, and Kidney Diseases

Publication status: Peer reviewed journal


Stated aim of studyThe primary purpose of the study was to evaluate the effectiveness of a brief medical office-based intervention in helping adult diabetes patients follow a healthy low-saturated fat eating plan. Secondary purposes were to 1) evaluate the impact of intervention on physiological (cholesterol; GHb) and quality-of-life outcomes and 2) evaluate the effectiveness of the intervention for different patient subgroups.


NotesWe requested further information about allocation concealment, any blinding of outcome assessors, raw means and SDs for outcome measures but received no response


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Low risk"Two hundred and six patients were randomised within physician practice, using a table of random numbers, to either Usual Care or to Brief Intervention"

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement. No comment on blinding of outcome assessors.

Incomplete outcome data (attrition bias)
All outcomes
Unclear risk"Sixteen percent of participants could not be contacted for the one year follow-up. Attrition was not differential across condition (16.7% vs 15.3% for intervention vs. control)"

Comment: No reasons for missing data.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Glasgow 2003

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

All participants were living independently; had a telephone; read and wrote English; were diagnosed with type 2 diabetes for at least 1 year, and were not planning to move out of the area during the next year. Those patients taking insulin met the Welborn criteria for type 2 diabetes based on age at diagnosis, BMI, and age of insulin initiation

Exclusion criteria:

Not type 2, under 40 or over 75 years, incapacitated or too ill, diagnosed less than 1 year, moving or not in area, can not read or write English and Other


InterventionsNumber of centres: Patients recruited from 16 physicians at 6 different medical offices

Country: USA

Setting: At home


OutcomesEffectiveness was evaluated by improvement from baseline to the final assessment 10 months later using multiple measures within each of three different domains: behavioural, biological, and psychosocial outcomes.

Dietary outcomes were assessed by improvements on the Kristal Fat and Fiber Behavior (FFB) scale and the Block/ NCI Fat Screener.

Diabetes care was measured by a composite of care recommendations from the American Diabetes Association Provider Recognition Program.

Physical activity was measured by the Physical Activity Scale for the Elderly.

Biological outcomes were evaluated by changes in HbA1C and lipid ratios

Psychosocial outcomes were measured by the Diabetes Support Scale and the Center for Epidemiologic Studies–Depression scale (CES-D)

Delivery of intervention components and participant usage of the website


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Supported in part by Grant RO1-DK-51581 from the National Institute of Diabetes, Digestive, and Kidney Diseases

Publication status: Peer reviewed journal


Stated aim of study"To report on the longer-term implementation across interventionists, on program usage over time and across conditions, on 10-month follow-up results on behavioral, biologic, and psychosocial outcomes, and on generalization of results across patients from the different clinics participating in the study"


NotesWe contacted the authors requesting more information on: Method of sequence generation and allocation concealment, any blinding of participants or assessors, need to know numbers in each condition, details of participants. Contacted author, no response.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear riskInsufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement.

Incomplete outcome data (attrition bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement. Unclear reporting of numbers included in the trial.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasUnclear riskControl arm received automated dietary change goals.

Glasgow 2005

MethodsStudy design: cluster parallel randomised controlled trial


ParticipantsInclusion criteria: the only inclusion criteria were age > or = 25 years, ability to read English, and type 2 diabetes, confirmed using the Welborn criteria

Exclusion criteria: none stated


InterventionsNumber of centres: Patients recruited from 52 physicians, 30 clinics

Country: USA

Setting: Primary Care practices in Colorado


OutcomesTwo primary outcomes: number of recommended laboratory screenings and recommended patient-centred care activities completed from the National Committee on Quality Assurance/American Diabetes Association Provider Recognition Program (PRP).

Secondary outcomes were evaluated using the Problem Areas in Diabetes 2 quality of life scale, lipid and HbA1c levels, and the Patient Health Questionnaire-9 depression scale.


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Agency for Health, Research and Quality, grant HS-10123

Publication status: Peer reviewed journal


Stated aim of studyTo determine if a patient-centred, computer-assisted diabetes care intervention increased perceived autonomy support, perceived competence (from self-determination theory), and if these constructs mediated the effect of the intervention on ADA/NCQA recommended diabetes care outcomes.


Notes


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"Randomization was conducted by the project statistician..."

Comment: No details about method of randomisation were provided.

Allocation concealment (selection bias)Low risk"Randomization was conducted by the project statistician, who then notified research staff of condition assignment". Although the study was not blinded, research staff would not be at risk of introducing selection bias as allocation was done by the statistician.

Blinding (performance bias and detection bias)
All outcomes
High risk"Randomization was conducted by the project statistician, who then notified research staff of condition assignment". Research staff were aware of allocation.

Incomplete outcome data (attrition bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement. Follow-up rates: Intervention: 379/469 = 81%. Control: 354/417 = 85%.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Glasgow 2006

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

Eligible participants were at least 25 years old, diagnosed with type 2 diabetes for at least 6 months, and able to read and write in English.

Exclusion criteria:

Physicians had the option of excluding patients for whom they felt the intervention would not be appropriate.


InterventionsNumber of centres:multiple: Adults diagnosed with type 2 diabetes residing in the Denver, Colorado metropolitan area recruited from lists provided by 42 participating physicians (20% from mixed payer settings, and the remainder employed by Kaiser Permanente Colorado)

Country: USA

Setting: The primary intervention was conducted at a location external to the participant’s primary care setting. This was typically a central clinic or medical office not too distant from the participant’s home. including both mixed-payer, fee for-service and managed-care offices


OutcomesOutcomes were changes in dietary behaviours (fat and fruit/vegetable intake), haemoglobin A1c (HbA1c), lipids, weight, quality of life, and depression


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: National Institute of Diabetes & Digestive & Kidney Diseases, Grant #DK35524. Copic Insurance Company introduced the project to private physician offices

Publication status: Peer reviewed journal


Stated aim of studyThe primary purposes of this article are to report on (1) the short-term (2-month) dietary, biological and quality-of-life outcomes from tailored self-management, (2) the implementation and feasibility of the programme, and (3) implications for broader dissemination


NotesFurther information needed: Details of sequence generation and allocation concealment, any blinding, Increase in fruit and vegetable score given in text (para 1 pg 34) does not correspond with the table for intervention. Contacted author, no response.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear riskInsufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement.

Incomplete outcome data (attrition bias)
All outcomes
Low risk"Attrition was modest (10%) by the 2-month assessment, and not different across conditions. Because of this low attrition rate, we used complete-case analyses in the present investigation, but intention-to-treat analyses with baseline values substituted for missing cases produced identical conclusions"

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasUnclear riskPhysicians had the option of excluding patients for whom they felt the intervention would not be appropriate.

Glasgow 2010

MethodsStudy design: randomised controlled trial


ParticipantsInclusion criteria:

25–75 years of age, diagnosis of type 2 diabetes, body mass
index (BMI) of 25 kg/m2 or greater, and at least one other risk
factor for heart disease (hypertension, low-density lipoprotein [LDL] > 100 or on a lipid-lowering agent, haemoglobin A1c > 7%, or being a current smoker). Additional inclusion criteria were access to a telephone and at least biweekly access to the Internet, ability to read and write in English or Spanish, and to perform mild to moderate PA

Exclusion criteria:

1. Sharing same household as other participants 2. Physicians not approved 3. Do not speak either English or Spanish


InterventionsNumber of centres:The study was conducted in five primary care clinics within Kaiser Permanente Colorado (KPCO).

Country: USA

Setting: Clinics were selected based on variability in size, location, and socioeconomic status of neighbourhood, and to maximise percentage of Latino patients.


OutcomesBehavioural Outcomes:

Eating behaviours were assessed using the Ammerman et al “Starting The Conversation” scale. Estimated fat intake was assessed using the National Cancer Institute’s Percent Energy from Fat Screener. The Community Health Activities Model Program for Seniors (CHAMPS) Questionnaire was used to estimate total weekly caloric expenditure in PA. Adherence to diabetes, blood pressure, and cholesterol medications ere assessed through the medication-taking items of the Hill-Bone Compliance Scale.

Biological Outcomes:

Biologic variables included BMI, haemoglobin A1c, lipids, and mean arterial pressure.


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding:This study was supported by grant #DK35524 from the National Institute of Diabetes and Digestive and Kidney Diseases.

Publication status: Peer reviewed journal


Stated aim of studyInternet and other interactive technology-based programs offer great potential for practical, effective, and cost-efficient diabetes self-management (DSM) programs capable of reaching large numbers of patients. This study evaluated minimal and moderate support versions of an Internet-based diabetes self-management program, compared to an enhanced usual care condition.

The purposes of this paper were to (a) evaluate the feasibility of an Internet-based DSM program (MyPath/Mi Camino) using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) model19 (www.re-aim.org); (b) present the 4-month behavioural and biological outcomes from a practical randomised trial; and (c) experimentally investigate the incremental effects of adding support to a minimal-contact version of the Internet-based program.


Notes


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Low risk"Participants were individually randomised via a computer program developed by our computer programmer and statistician"

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement but the study design makes it unlikely that participants or staff were blinded.

Incomplete outcome data (attrition bias)
All outcomes
Low riskIntention-to-treat analysis done. Follow-up rates: Intervention: 130/169 = 77%. Control: 115/132 = 87%. Significant difference in retention between groups.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Leu 2005

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

Patients with HbA1c values between 8.0% and 9.4% at the time of recruitment, with either type 1 or type 2 diabetes.

Exclusion criteria:

Three participants were found to be ineligible (two had pacemakers, and one was trying to conceive).


InterventionsNumber of centres: 9 clinics, 20 primary care providers and two endocrinologists.

Country: USA

Setting: University of Washington Physician’s Network (UWPN) clinics located in Western Washington. This is a group of nine neighbourhood clinics, of which Belltown (near Downtown Seattle), Auburn, Federal Way, Factoria, and Kent/Des Moines participated (20 primary care providers and two endocrinologists).


OutcomesHbA1c was the primary outcome measure.
Blood pressure was a secondary outcome measure. Patients’ attitudes as self-reported by survey were another secondary outcome measure.


Study detailsNot terminated before regular end.


Publication detailsLanguage: English

Funding: American Diabetes Association (Medical Scholars Award), by the Warren G. Magnuson Institute for Biomedical Research and Health Professional Training (Magnuson Scholarship), and by an Alpha Omega Alpha Student Research Fellowship

Publication status: Peer reviewed journal


Stated aim of studyThis randomised, controlled study tested the effect of using a wireless two-way pager-based automated messaging system to improve diabetes control through facilitated self-management.


NotesFurther information needed: details of excluded cases, control conditions, definition of hypertension, method of sequence generation. Tried to contact author, unable to get contact details.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Low risk"Prior to enrolment, an Excel spreadsheet was created that randomised 60 patients in groups of six. A stack of envelopes was created, containing the results of the randomizations. The allocation sequence was generated by the investigator"

Allocation concealment (selection bias)Low risk"This collection of envelopes was randomly “cut” in the middle, and the envelopes were numbered from 1 to 60. The sequence was concealed until the interventions were assigned at enrolment"

Blinding (performance bias and detection bias)
All outcomes
High risk"There was no blinding in the study due to the nature of the intervention"

Incomplete outcome data (attrition bias)
All outcomes
Unclear riskReporting of cases of attrition does not provide details about all the participants excluded in the results section. 18% dropout rate in control and intervention arms.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Lim 2011

MethodsStudy design: block randomised controlled trial


ParticipantsInclusion criteria:

Age >= 60. All enrolled participants had been diagnosed with type 2 diabetes for at least 1 year, and their A1C level was 6.5%–10.5%

Exclusion criteria:

The study excluded patients with severe diabetes complications (e.g., diabetic foot or severe diabetic retinopathy), liver dysfunction (aspartate aminotransferase or alanine aminotransferase >2.5 times the reference level), or renal dysfunction (serum creatinine >132 μmol/L [1.7 mg/dL]), or other medical problems that could affect study results or trial participation. The study enrolment excluded patients without a text message function on their cellular phone or who were unable to use text messages for any reason.


InterventionsNumber of centres:1.

Patients were recruited from the outpatient clinic of the Seoul National University Bundang Hospital (SNUBH). Participants used the intervention from home.


OutcomesThe primary end point of the study was the proportion of patients achieving an A1C level of <7% without hypoglycaemia at 6 months.

Secondary outcomes included weight, BMI, serum lipids, frequency of blood glucose monitoring, and fasting/post-prandial blood glucose.


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: "This study was supported by a grant of the Korea Healthcare technology R&D Project, Ministry for Health, Welfare & Family Affairs, Republic of Korea (A090001), a research grant (02-2008-036) from the SNUBH, and the Korea Science and Engineering Foundation grants funded by the Ministry of Science and Technology (M10642140004-06N4214-00410)"

Publication status: Peer reviewed journal


Stated aim of study"To improve quality and efficiency of care for elderly patients with type 2 diabetes, we introduced elderly-friendly strategies to the clinical decision support system (CDSS)-based ubiquitous healthcare (u-healthcare) service, which is an individualized health management system using advanced medical information technology"


NotesDetails of randomisations - Contacted author, no response.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"Block randomizations was used to assign each patient"

Comment: No details given. Insufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High riskNo blinding of participants possible with this study design. No information provided about blinding of assessors.

Incomplete outcome data (attrition bias)
All outcomes
Low riskDropout rates were low. 2/51 (3.9%) dropout rate in the intervention group and 4/52 (7.3%) dropout rate in the control group. No imputation for missing data.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Lo 1996

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

People with T1 and T2 diabetes at the Lismore base hospital diabetic clinic, diagnosed between 2 months and 10 years prior to this study.

Exclusion criteria:

None stated


InterventionsNumber of centres: 1

Country: Australia

Setting: Community health centre office - Diabetes clinic at the Lismore base hospital


OutcomesKnowledge levels measured by multiple choice tests and glycated haemoglobin levels


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: IRG grant from the University of New England, Northern Rivers, New South Wales

Publication status: Peer reviewed journal


Stated aim of studyAn evaluation study of the CAL program was conducted to test the following propositions: - participants who complete the CAL program will achieve a greater increase in their knowledge of diabetes mellitus management than participants who complete a conventional diabetes program. - The CAL program will motivate patients to achieve greater improvements in their glucose levels than a conventional diabetes program. - It is feasible to develop a CAL diabetes education program for home computers.


NotesFurther information needed: details of allocation and reasons for attrition. Unable to find current contact details for author.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"Participants were randomly assigned"

Comment: No details given. Insufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High riskNo blinding of participants possible with this study design. No information provided about blinding of assessors.

Incomplete outcome data (attrition bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement.

No details provided about participants who did not complete the study. All patients who dropped out were from the control arm.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Lorig 2010

MethodsStudy design: parallel randomised controlled trial for 6 months.

After that a subset of American Indians/native Alaskans were part of a wait-list control trial and were given the opportunity to use the intervention.


ParticipantsInclusion criteria:

Participants were aged 18 years, were not pregnant or in care for cancer, had physician-verified type 2 diabetes, and had access to the Internet. Recruitment was largely via the Internet, although print and broadcast media were also utilised.

Specific recruitment of AI/AN minorities into a separate subgroup.

Exclusion criteria:

None stated


InterventionsNumber of centres: Online trial

Country: USA

Setting: Internet-based - all consents and questionnaires administered online and patients took HbA1C themselves with a postal blood-letting kit


OutcomesThe primary outcome measure was A1C, measured using capillary blood obtained with self-administered BIOSAFE kits.

Secondary outcomes:

Health-related distress was measured by the health distress scale

The activity limitations scale, which measures the impact of disease on role activities such as recreation and chores
Depression was measured by the Patient Health Questionaire (PHQ)-9
A physical activities scale measured total minutes per week of aerobic exercise

Tertiary outcomes:

Tertiary measures included the 13- item short-form Patient Activation Measure (PAM) and diabetes self-efficacy


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: The study was supported by National Institutes of Health Grant 1R18DK065729 and Robert Wood Johnson Foundation Grant 096223.

Publication status: Peer reviewed journal


Stated aim of study"We hypothesized that participants in the IDSMP, compared with usual-care control subjects, would demonstrate 1) reduced A1C at 6 and 18 months, 2) have fewer symptoms, 3) have increased exercise, and 4) have improved self-efficacy and patient activation.We also hypothesized that participants randomised to a follow-up list serve, peer-support group would have better 18-month outcomes than participants receiving no follow-up"


NotesFurther information required: details of allocation concealment. Contacted author, no response.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Low riskRandom numbers table.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High riskIt would not be possible to blind participants in this study design. Collection of data was self-reported so blinding of "assessors" was not necessary; however patients were not blinded and were responsible for data collection so the risk of bias cannot be described as low.

Incomplete outcome data (attrition bias)
All outcomes
Low risk"When intent-to-treat analyses were used, PAM and self-efficacy remained significant, while the P value for A1C increased to 0.060"

Comment: Intention-to-treat analysis used. Follow-up rates: Intervention: 395/491 = 80%. Control: 238/270 = 88%.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Quinn 2008

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

The study enrolled patients 18–70 years old who had a diagnosis of type 2 diabetes for at least 6 months. Study patients were required to have an A1c 7.5% and to have been on a stable diabetes therapeutic regimen for 3 months prior to study enrolment.

Exclusion criteria:

None stated


InterventionsNumber of centres: 3

Country: USA

Setting: One community endocrinology and two community primary care practices


OutcomesSummary of Diabetes Self-Care Activities (SDSCA) questionnaire and HbA1c


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Study was supported by LifeScan, Inc. and Nokia, Inc.

Publication status: Peer reviewed journal


Stated aim of studyThe primary study aim was to assess the impact on A1c of a cell phone-based diabetes management software system used with web-based data analytics and therapy optimisation tools. Secondary aims examined healthcare provider (HCP) adherence to prescribing guidelines and assessed HCPs’ adoption of the technology.


NotesFurther information needed: details of sequence generation and allocation concealment. Contacted author, no response.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"Eligible patients gave consent and were randomised to either the control or intervention group"

Comment: Insufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High risk"This study was a non blinded, randomised controlled trial (RCT)"

Incomplete outcome data (attrition bias)
All outcomes
Unclear risk"Characteristics for drop-out subjects were not different from the remaining study subjects"

Comment: No details given about reasons for dropping out of study. Insufficient evidence to permit judgement.

Follow-up rates: Intervention: 13/15 = 87%. Control: 13/15 = 87%.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasUnclear risk"A convenience sample of 30 patients with type 2 diabetes was recruited"

Comment: Small convenience sample - insufficient detail about local population to determine the consequences of this.

Control group was expected to be quite pro-active: "They were asked to fax or call in their BG logbooks every 2 weeks to their HCPs until their BG levels were stabilized in the target ranges or until their HCPs changed testing frequency"

Quinn 2011

MethodsStudy design: cluster-randomised controlled trial


ParticipantsInclusion criteria:

Physician diagnosis of type 2 diabetes for ≥6 months;
Glycated haemoglobin ≥7.5% within 3 months;
Age 18–64 years.

Exclusion criteria:

Medicare or Medicaid beneficiaries;
Uninsured;
Insulin pump users;

Not currently managed by study physicians;
Pregnant;
Active substance, alcohol, or drug abuser (sober <1 year);
Psychotic or schizophrenic under active care;
Severe hearing or visual impairment; or
No Internet or e-mail access.


InterventionsNumber of centres: 26 primary care physicians enrolled and randomised

Country: USA

Setting: General practice physicians (internal medicine, family medicine) were recruited from four areas in Maryland, including urban, suburban and rural practices. Physicians in academic settings were not included


OutcomesThe primary outcome of the study was change in glycated haemoglobin (%) comparing UC and maximal treatment (CPDS) at baseline versus 12 months.

Secondary outcomes were:

The Patient Health Questionnaire-9 scores at baseline and at follow-up interviews to assess depressive symptoms.

The 9-item version of the Self-Completion Patient Outcome Instrument to assess patient-reported symptoms associated with diabetes

The 17-item Diabetes Distress Scale.

Clinical measurement related to diabetes complications (blood pressure, lipid levels)

Hypoglycemic events, hospitalisations, and emergency room visits


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: This study was funded through a contract between the University of Maryland Baltimore and WellDoc in addition to contributions by WellDoc, CareFirst Blue Cross/Blue Shield of Maryland, LifeScan, and Sprint. Additional funding was provided by the Maryland Industrial Partnerships program through the University of Maryland, an initiative of the A. James Clark School of Engineering’s Maryland Technology Enterprise Institute.

Publication status: Peer reviewed journal


Stated aim of studyTo test whether adding mobile application coaching and patient/provider web portals to community primary care compared with standard diabetes management would reduce glycated haemoglobin levels in patients with type 2 diabetes.


NotesDiabetes Distress scale scores seem too low to be on the full scale - are these from a sub scale? Contacted author, no response.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"We randomised at the physician practice level in order to prevent potential contamination of the study intervention, i.e., all participating physicians at a practice site were randomised to the same study group. When a physician practice is contacted, agreement of individual physicians within the practice is sought, and they are added to the study physician group"

Comment: Insufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High riskPatients and providers were not blinded.

Incomplete outcome data (attrition bias)
All outcomes
High riskSensitivity analysis using weighted estimating equations (WEE) to address any residual bias from missing data was done. However the dropout rate in the intervention group was high (15/38 = 39%). Dropout rate in control group was 10%.

Selective reporting (reporting bias)Low riskProtocol for the trial published prior to study completion.

Other biasUnclear riskThe exclusion criteria meant that only patients with private insurance and access to the Internet/ email took part in the trial. The characteristics of such patients might have influenced the efficacy of the intervention and its generalisability.

Smith 2000

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

Women who participated in the Women to Women Diabetes Project had to meet the following study inclusion criteria: have diabetes (type 1 or 2), be between the ages of 35 and 60 years, be able to read and write English, and possess the sight and dexterity to use a computer (but not necessarily be computer literate). In addition, participants were required to have a telephone in their homes and live at least 25 miles outside the 6 major cities of Montana.

Exclusion criteria:

None stated


InterventionsNumber of centres: n/a

Country: USA

Setting: From home


OutcomesOver the telephone: change in health status scale, a sources of support scale and self-reported HbA1c

Mail questionnaires for Personal Resource Questionnaire, Quality of Life index, Social Readjustment Rating Scale and the Psychosocial Adaptation to Illness Scale


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Financial support for this research was provided by the American Association of Diabetes Educators Foundation and US West.

Publication status: Peer reviewed journal


Stated aim of studyThe aims were to (1) test the effects of the computer intervention in providing support, information and education on selected outcomes, and (2) evaluate the women's attitudes toward and satisfaction with the intervention and the support provided.


NotesFurther information needed: Method of sequence generation and allocation concealment. Number of participants completing the study. QOL etc scores after adjustment and any statistics on whether differences were significant or not. Unable to contact author.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"The 30 women were randomised into two groups (computer vs non computer) of 15 each"

Comment: Insufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskNo details provided. Insufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High riskBlinding of participants was not possible. No details about blinding of assessors.

Incomplete outcome data (attrition bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement. Unclear reporting of numbers included in the trial.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasUnclear riskSmall sample size.

Wise 1986

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

Patients regularly attending the diabetic clinic who were seen over a 2 month period at Charing Cross Hospital in London. Diagnosis of type 1/2 diabetes for at least 2 years.


InterventionsNumber of centres: 1

Country: UK

Setting: Diabetic clinic at Charing Cross Hospital, London


OutcomesKnowledge status measured by knowledge-assessment program and HbA1c


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Supported by the British Diabetic Association and the Northe West Thames Regional Research Committee

Publication status: Peer reviewed journal


Stated aim of studyThe purpose of our study was to examine separately two programs recently developed in this department to define any effects on knowledge and diabetic control.


NotesDetails of allocation concealment and SD of outcome measures if available. Unable to find current contact details for author.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)High risk"Assignment to test groups was randomised by year and month of birth"

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement: no details of allocation concealment provided.

Blinding (performance bias and detection bias)
All outcomes
High riskControl group "unaware of the study" and no details about blinding of assessors - study design makes it likely that assessors were aware of allocation

Incomplete outcome data (attrition bias)
All outcomes
Unclear riskInsufficient evidence to permit judgement: details of number of patients recruited at the start not reported.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Yoo 2009

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria: between 30 and 70 years of age, who met the following criteria: (i) a diagnosis of both type 2 diabetes and hypertension at least 1 year previously by a physician; (ii) HbA1c 6.5%–10.0%; (iii) blood pressure > 130/80 mmHg; and (iv) BMI ‡ 23.0 kg m2 (overweight according to Asia-Pacific criteria)

Exclusion criteria: i) severe diabetic complications (e.g. diabetic foot or severe diabetic retinopathy); (ii) liver dysfunction with aspartate aminotransferase or alanine aminotransferase > 2.5 times the reference level, or renal dysfunction (serum creatinine > 132 micro mol/L); (iii) medical history of congestive heart failure, angina pectoris, MI, or stroke based on a physician’s diagnosis; (iv) pregnancy or lactation; or (v) other medical problems that could affect study results or trial participation or (Vi) excluded all participants with hsCRP ‡ 15.0 mg to rule out any occult inflammatory or infectious disorders.


InterventionsNumber of centres: 2

Country: South Korea

Setting: 1. University hospital setting (Korea University)

2. Community healthcare centre (Guro-Gu Public Health Centre


OutcomesBMI was calculated as weight ⁄ height2 (kg ⁄m2). Blood chemistry was analysed at the Korea University Guro Hospital laboratory (Seoul, Korea). The glucose oxidase method was employed to measure plasma glucose. A human insulin-specific radioimmunoassay kit (Linco Research Inc., St Charles, MO, USA) was used to measure insulin levels, with a coefficient of variation (CV) of 2.2%. This kit had a cross reactivity of < 0.2% with human proinsulin. Insulin resistance was calculated by the homeostasis model assessment. Serum total cholesterol, triglycerides, and high-density lipoprotein cholesterol were determined by enzymatic methods using a chemical analyser (Hitachi 747, Tokyo, Japan). HbA1c was analysed by high-performance liquid chromatography using a Variant II analyser (Bio-Rad Laboratories, Hercules, CA, USA). Plasma adiponectin levels were measured using an adiponectin enzyme immunoassay kit (Phoenix Pharmaceuticals, Belmont, CA, USA), with a CV of 3.2%. Plasma IL-6 levels were measured using a Quantikine kit (R&D Systems, Belmont, CA, USA) with a CV of 8.1%. Plasma high-sensitivity (hs) CRP levels were measured using a hsCRP kit (Immunodiagno, Benshaim, Germany) with a CV of 9.2%.


Study detailsNot terminated before regular end


Publication detailsLanguage: English

Funding: Seoul R & BD Project. The development of the HSA business model and technology was sponsored by the Ministry of Commerce, Industry and Energy

Publication status: Peer reviewed journal


Stated aim of studyOur goal was to examine whether a Ubiquitous Chronic Disease Care (UCDC) system using both the Internet and cellular phones could facilitate chronic disease self-management and improve multiple metabolic parameters in overweight patients with both type 2 diabetes and hypertension better than conventional health care in out-patient clinics.


NotesFurther information needed: clarify data for BPs - need clarification re. inconsistencies between tables and text re HbA1C, Full details of randomisation needed. Contacted author, no response.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"We recruited patients for this open-label, randomised, controlled, prospective study from both a university hospital setting"

Comment: No details provided of randomisations procedures. Insufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskNo details provided about allocation concealment. Insufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High risk"Open-label" study.

Incomplete outcome data (attrition bias)
All outcomes
Unclear risk"Five patients (8.1%) dropped out of the intervention group and seven (10%) out of the control group. The characteristics of patients who did and did not drop out were similar in both the intervention and control groups"

Comment: No details provided about reasons for patients dropping out. No imputation of data or intention-to-treat analysis reported. Insufficient evidence to permit judgement.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

Zhou 2003

MethodsStudy design: parallel randomised controlled trial


ParticipantsInclusion criteria:

Selection criteria: diagnosed according to WHO diagnostic criteria 1985, age over 35 years, previously received glucose lowering medication, and the dosage of medication remained constant at least two weeks prior to the selection.

Exclusion criteria:

Diabetes with other severe or acute complications and those with other endocrine disorders, hypertension (diagnosed according to WHO/ISH Hypertension guidelines), hypercholesterolaemia (principles for prevention of dyslipidaemia) and glomerular disease (diagnosed according to Morgenson diagnostic criteria).


InterventionsNumber of centres: 1

Country: China

Setting: Endocrinology Department in Second Affiliated Hospital of Zhejiang University


OutcomesHbA1c, BMI, fasting blood glucose, 2-hour post prandial glucose, lipids, urinary albumin excretion


Study detailsNot terminated before regular end


Publication detailsLanguage: Chinese

Funding: Not stated

Publication status: Peer reviewed journal


Stated aim of studyWe developed ‘Diabetes diet advisor V1.0 (PC-DR Vision 1.0)’. It consists of more than 20 thousand common food types of Chinese people. The objective of this research is to evaluate the efficacy of this software in clinical uses.


NotesFurther information required: details of allocation concealment and sequence generation. Unable to find current contact details for author.


Risk of bias

BiasAuthors' judgementSupport for judgement

Random sequence generation (selection bias)Unclear risk"150 patients are randomly allocated to two groups"

Comment: Insufficient evidence to permit judgement.

Allocation concealment (selection bias)Unclear riskInsufficient evidence to permit judgement.

Blinding (performance bias and detection bias)
All outcomes
High riskInsufficient evidence in article. However study design makes blinding highly unlikely.

Incomplete outcome data (attrition bias)
All outcomes
Low riskNo missing data.

Selective reporting (reporting bias)Unclear riskInsufficient evidence to permit judgement.

Other biasLow riskNothing detected

 
Characteristics of excluded studies [ordered by study ID]

StudyReason for exclusion

Adams 2009The intervention was non-interactive and consisted of tailored reports that were mailed to participants prior to visits. The only interaction with participants was a telephone-based pre-visit questionnaire based on ADA guidelines. Did not match our criteria for a self-management intervention.

Albisser 1996Not interactive. Did not match our criteria for a self-management intervention.

Avdal 2011Did not match our criteria for a self-management intervention. Fitted more with our criteria for telemedicine (nurse-led case management) intervention.

Billiard 1991Participants had type 1 diabetes only.

Boaz 2009Did not match our criteria for a self-management intervention. Fitted more with our criteria for telemedicine intervention.

Bond 2007Did not match our criteria for a self-management intervention. Fitted more with our criteria for telemedicine intervention.

Bond 2010Did not match our criteria for a self-management intervention. Intervention was felt to be a nurse-led telemedicine intervention more than a computer-based self-management intervention.

Bujnowska-Fedak 2011Did not match our criteria for a self-management intervention. Fitted more with our criteria for telemedicine intervention.

Carter 2011Did not match our criteria for a self-management intervention. Fitted more with our criteria for telemedicine intervention.

Castelnuovo 2010This report described a protocol for telemedicine intervention.

Cho 2006Did not match our criteria for a self-management intervention. Fitted more with our criteria for telemedicine intervention.

Cho 2009Comparison between a mobile phone and Internet-based intervention. No control group.

Cleveringa 2007The intervention (Diabetes Care Protocol) was targeted at health professionals. Did not match our criteria for a self-management intervention.

Derose 2009The intervention was non-interactive and consisted of automated prompts with telephone calls and letters.

Earle 2010Did not match our criteria for a self-management intervention. Fitted more with our criteria for telemedicine intervention.

Edmonds 1998Was a feasibility study with no suitable outcome measures. Participants were "insulin-requiring diabetics".

Estrada 2010Did not match our criteria for a self-management intervention. The intervention was aimed at healthcare professionals.

Glasgow 1995This report describes a feasibility study not suitable for inclusion.

Glasgow 20002x2 factorial trial where all participants received a brief computer intervention. This study looked at the incremental effects of adding telephone follow-up support and community resources.

Glasgow 2002All participants received a computer-based intervention.

Glasgow 2005aBrief report of the findings of the Diabetes Priority Program.

Goldberg 2006Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (nurse-led) telemedicine intervention.

Graziano 2009Did not match our criteria for a self-management intervention. The intervention was not interactive and did not provide tailored information.

Handley 2008The intervention was a non-interactive telephone intervention with nurse care management. Did not match our criteria for a self-management intervention.

Harno 2006Did not match our criteria for a self-management intervention. Fitted more with our criteria for an Internet-based telemedicine intervention.

Holbrook 2009Did not match our criteria for a self-management intervention. Shared electronic decision-support system. The intervention was a colour-coded diabetes tracker providing sequential monitoring values for 13 diabetes risk factors and the primary outcome measure was a process composite score.

Izquierdo 2010Did not match our criteria for a self-management intervention. Fitted with our criteria for an Internet-based telemedicine intervention.

Jones 2006Non-randomised controlled trial.

Kalten 2000The report described the intervention but provided no results. The intervention required motivational interviewing to be provided by healthcare professionals, it did not match our criteria for a self-management intervention.

Keuthage 2008Commentary on another article (Christian 2008).

Kim 2005Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (mobile phone-based) telemedicine intervention.

Kim 2006Targeted at healthcare professionals, did not match our criteria for a self-management intervention.

Kim 2007Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (mobile phone-based) telemedicine intervention.

Kim 2007aDid not match our criteria for a self-management intervention. Fitted more with our criteria for a (mobile phone-based) telemedicine intervention

Kim 2008Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (mobile phone-based) telemedicine intervention.

Kim 2010All patients were started on glargine. The intervention looked at the effect of SMS messages on titration of insulin.

King 2006The primary outcome measures included community health activities model program for seniors questionnaire, diet and psychosocial assessments. HbA1c or quality of life were not included as outcomes.

Kwon 2004Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (mobile phone-based) telemedicine intervention.

Laffel 2007Over 70% patients with type 1 diabetes.

Lee 2007Did not match our criteria for a self-management intervention. The intervention was not interactive and it was managed by a health professional.

Liebreich 2009The primary outcome measures included measured physical activity, social cognitive variables. HbA1c or quality of life were not included as outcomes.

MacLean 2004Did not match our criteria for a self-management intervention. The intervention was decision support software and it was aimed at health professionals.

McMahon 2005Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (nurse-led) telemedicine intervention.

Mollon 2008Did not match our criteria for a self-management intervention. The intervention was an automated telephone reminder. This report was also just a feasibility study with no clinical outcome measures.

Morrish 1989Participants had type 1 diabetes.

Noel 2004Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Oh 2003Purely telephone-based intervention, not computer-based.

Palmas 2010Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Persson 2000Not a randomised controlled trial.

Peters 1991Participants had type 1 diabetes.

Piette 2000Did not match our criteria for a self-management intervention. Non-interactive automated calls and telephone follow-up from a nurse.

Piette 2001Did not match our criteria for a self-management intervention. Non-interactive automated calls and telephone follow-up from a nurse.

Quinn 2009Did not match our criteria for a self-management intervention. The intervention was a diabetes communication system, using mobile phones and patient/physician portals to allow patient-specific treatment and communication.

Ralston 2009Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (care-manager led) telemedicine intervention.

Robertson 2007Not a randomised controlled trial.

Rodríguez-Idígoras 2009Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (call-centre protocol managed) telemedicine intervention.

Ross 2006The only outcomes measured were characteristics of and usage by patients.

Ryff-de 1992Participants had type 1 diabetes.

Sarkar 2008Did not match our criteria for a self-management intervention. A non-interactive telephone intervention.

Schillinger 2009Automated telephone messages or nurse telephone intervention. Did not match our criteria for a self-management intervention.

Schrezenmeier 1988Participants had type 1 diabetes.

Shea 2006Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Shea 2007Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Shea 2009Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Sherifali 2011Not an interactive intervention. Intervention was a mail out of a tailored letter. Did not fit our criteria for a self-management intervention.

Shultz 1991Did not match our criteria for a self-management intervention. Modem data transfer to clinicians only.

Smith 2004Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (nurse case management) telemedicine intervention.

Song 2009Not a randomised controlled trial.

Stone 2010Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Tildesley 2011Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Tjam 2006Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (Internet-based) telemedicine intervention.

Trief 2007Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Tsang 2001Participants had type 1 diabetes.

Turnin 199270% of participants had type 1 diabetes.

van Bastelaar 2011Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention as not fully automated and significant interaction with health professionals.

van Bastelaar 2011aDid not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention as not fully automated and significant interaction with health professionals

Vespasiani 2008Participants had type 1 diabetes.

Wakefield 2011Did not match our criteria for a self-management intervention. Fitted more with our criteria for a telemedicine intervention.

Yeh 2006Did not match our criteria for a self-management intervention. Aimed at health professionals, not an interactive patient focused intervention.

Yoo 2008The study compared 2 types of blood glucose monitoring.

Yoon 2008Did not match our criteria for a self-management intervention. Fitted more with our criteria for a (mobile phone) telemedicine intervention.

 
Characteristics of studies awaiting assessment [ordered by study ID]
Faridi 2008

MethodsStudy design: parallel randomised control trial

ParticipantsInclusion criteria:

Patients meeting the following inclusion criteria were included in the study:

(i) age ≥ 18 years; (ii) type 2 diabetes diagnosed by a health professional at least 1 year prior and confirmed by other clinical laboratory data (Fasting Plasma Glucose> 126 mg/dL and/or 2-hour 75-g oral glucose tolerance test OGTT > 200 mg/dL);

(iii) controlled by either diet or oral medications for at least 3 months;

(iv) BMI > 25;

(v) no exogenous insulin use;

(vi) a glycosylated haemoglobin (HbA1c) < 8% reflecting fair to good glycaemic control; and

(vi) serum creatinine <1.5 mg/dL.

Exclusion criteria:

None stated.

InterventionsNumber of centres: 2

The study was conducted in collaboration with a primary care network in Connecticut (Community Health Centers – CHC). Two of the seven CHC clinics with similar demographic characteristics in the network elected to participate.

Country: US.

Setting: community and at home.

Outcomes1) Feasibility was assessed as utilisation of the system by community health centre patients and consistent use of the system by patients over the 3-month intervention period. Utilisation was measured in the intervention group by mining the data collected by the NICHE server to obtain information about the utilisation of separate components. Additionally, post-intervention focus groups were held with intervention patients to illuminate patients’ barriers when utilising the technology.
2) Utility in enhancing diabetes management: assessed as pre- and post-intervention change in clinical measures and surveys relevant to diabetic self-care in the intervention and control group. Clinical measures included HbA1c levels, trend analysis of glucometer readings between groups, and BMI. Additionally, physical activity levels were measured both by pedometers and self-report using the Yale Physical Activity Scale (YPAS). Patients’ self-efficacy was assessed as via the Diabetes Self-efficacy Scale (DSES). Patrticipants’ diabetes management was recorded using the Diabetes Self-care Activities (SDSCA).

Study detailsNot terminated before regular end.

Publication detailsLanguage: English

Funding: Small Business Technology Transfer Resarch Program, grant number IR21DKK072321-01

Publication status: Peer reviewed journal

Stated aim of study"The primary aim of the study is to examine the feasibility of utilizing this technology to assist with diabetes self care in a clinic population as well as its impact on clinical outcomes"

NotesPilot study in preparation for a phase II trial. Unable to contact author.

Lorig 2006

MethodsStudy design: parallel randomised control trial

ParticipantsInclusion criteria:

Participants met all of the following criteria:

1) at least 18 years of age;

2) a physician’s diagnosis of heart disease, chronic lung disease or type 2 diabetes;

3) in addition to one of these diagnoses, partlcipant could have other chronic conditions but could not have been in active treatment of cancer for 1 year;

4) not participated in the small-group Chronic Disease Self-Management Program;

5) access to a computer with Internet and email capabilities;

6) agreed to 1–2 hours per week of log on time spread over at least 3 sessions/wk for 6 weeks;

7) are able to complete the online questionnaire.

Exclusion criteria:

None separately stated.

InterventionsNumber of centres: 1

Country: US

Setting: Participants used the Internet from home

OutcomesThere were 7 health-related quality of life measures or health indicators. Visual numeric scales (VNS) were used to measure pain/physical discomfort, shortness of breath, and fatigue.
The Illness Intrusiveness Scale measured the impact of disease on role activities such as work, recreation, and social activities.

The Health Distress Scale was adapted from the Medical Outcome Study.

Self-Rated Global Health was used as it is predictive of future health status.

The 20-item Health Assessment Instrument measures disability.
Four health-related behaviours were measured: stretching and strengthening exercise, aerobic exercise, use of cognitive symptom management techniques, and use of techniques to improve communication with healthcare providers.

Study detailsNot terminated before regular end.

Publication detailsLanguage: English

Funding: Not stated

Publication status: Peer reviewed journal

Stated aim of studyTo determine the efficacy of the Internet-based CDSMP

NotesNeed diabetes specific data - contacted author. Diabetes data not available separately and mixed diabetic population. Would require re-analysis of data.

Noh 2010

MethodsStudy design: parallel randomised control trial

ParticipantsInclusion criteria:

Patients 18– 80 years old with type 2 diabetes either drug naive or who had received prior drug therapy and had a glycated haemoglobin (A1C) level between 7% and 10% with stable glycaemic control were recruited. Stable glycaemic control was defined by no recent addition of hypoglycaemic medications or change in insulin dosing by >10% in the previous 3 months. Persons participating in this study had Internet assess in their homes, their own cellular phone, and the ability to access the Internet and mobile website.

Exclusion criteria:

Participants with severe medical illnesses including liver cirrhosis, end stage renal disease, and cancer were excluded.

InterventionsNumber of centres: 5 hospitals

Country: South Korea

Setting: Mobile and Internet-based intervention, patients recruited from hospital

OutcomesPrimary end points for the study were the changes in glycaemic control (A1C, fasting plasma glucose [FPG], and 2-h postprandial plasma [PP2] glucose).

Study detailsNot terminated before regular end

Publication detailsLanguage: English

Funding: This research was supported by a grant from the Korean Diabetes Association.

Publication status: Peer reviewed journal

Stated aim of studyThe aim of this study was to evaluate the effect of this computer- and cellular phone accessible web-based system on glycaemic control.

NotesNeed more details about intervention. Contacted author, no response.

 
Comparison 1. HbA1c

Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size

 1 HbA1c112637Mean Difference (IV, Random, 95% CI)-0.21 [-0.37, -0.05]

    1.1 Change in mean
3943Mean Difference (IV, Random, 95% CI)0.06 [-0.27, 0.39]

    1.2 Mean difference
81694Mean Difference (IV, Random, 95% CI)-0.32 [-0.52, -0.12]

 2 Sensitivity analysis - removing Christian 2008102364Mean Difference (IV, Random, 95% CI)-0.25 [-0.40, -0.10]

 3 Sensitivity analysis - removing Leu 2005102600Mean Difference (IV, Random, 95% CI)-0.23 [-0.39, -0.07]

 4 Sensitivity analysis - removing cluster randomised trials92005Mean Difference (IV, Random, 95% CI)-0.22 [-0.39, -0.05]

 5 Sensitivity analysis - remove Glasgow 2003102477Mean Difference (IV, Random, 95% CI)-0.21 [-0.38, -0.04]

 6 Subgroup analysis - outcomes at less than 6 months5842Mean Difference (IV, Random, 95% CI)-0.32 [-0.58, -0.07]

 7 Subgroup analysis - outcomes at later than 6months61795Mean Difference (IV, Random, 95% CI)-0.14 [-0.33, 0.05]

 8 Subgroup analysis - mobile phone based interventions3280Mean Difference (IV, Random, 95% CI)-0.50 [-0.74, -0.26]

 9 Subgroup analysis - interventions based at home41188Mean Difference (IV, Random, 95% CI)-0.25 [-0.47, -0.04]

 
Comparison 2. Dietary change

Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size

 1 Fruit and vegetable screener score1299Mean Difference (IV, Random, 95% CI)0.60 [-0.35, 1.55]

 2 Estimated daily fat intake2544Mean Difference (IV, Random, 95% CI)-3.44 [-7.93, 1.05]

 3 Change in calorific intake1Mean Difference (IV, Random, 95% CI)Totals not selected

 4 Pooled effect on diet3819Std. Mean Difference (IV, Random, 95% CI)-0.29 [-0.43, -0.15]

    4.1 Estimated daily fat intake
2546Std. Mean Difference (IV, Random, 95% CI)-0.32 [-0.49, -0.16]

    4.2 Change in weekly calorie intake
1273Std. Mean Difference (IV, Random, 95% CI)-0.23 [-0.46, 0.01]

 
Comparison 3. Impact on weight or BMI

Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size

 1 Pooled effect on weight or BMI5Std. Mean Difference (IV, Random, 95% CI)Subtotals only

    1.1 Weight
3507Std. Mean Difference (IV, Random, 95% CI)-0.05 [-0.22, 0.13]

    1.2 Change in weight
1273Std. Mean Difference (IV, Random, 95% CI)-0.14 [-0.38, 0.09]

    1.3 BMI
1245Std. Mean Difference (IV, Random, 95% CI)-0.06 [-0.31, 0.19]

 
Comparison 4. Lipids

Outcome or subgroup titleNo. of studiesNo. of participantsStatistical methodEffect size

 1 Total cholesterol4567Mean Difference (IV, Random, 95% CI)-0.19 [-0.41, 0.02]

 2 Change in total cholesterol1Mean Difference (IV, Random, 95% CI)Totals not selected

 3 High density lipoprotein (HDL)2446Mean Difference (IV, Random, 95% CI)-0.01 [-0.08, 0.05]

 4 Change in HDL1Mean Difference (IV, Random, 95% CI)Totals not selected

 5 Low density lipoprotein (LDL)1Mean Difference (IV, Random, 95% CI)Totals not selected

 6 Change in LDL1Mean Difference (IV, Random, 95% CI)Totals not selected

 7 TC:HDL ratio31466Mean Difference (IV, Random, 95% CI)0.05 [-0.07, 0.16]

 8 Change in triglycerides1Mean Difference (IV, Random, 95% CI)Totals not selected

 9 Pooled effect on cholesterol71625Std. Mean Difference (IV, Random, 95% CI)-0.11 [-0.28, 0.05]

    9.1 Total cholesterol
4567Std. Mean Difference (IV, Random, 95% CI)-0.22 [-0.48, 0.04]

    9.2 Change in total cholesterol
1273Std. Mean Difference (IV, Random, 95% CI)-0.27 [-0.50, -0.03]

    9.3 Total cholesterol:HDL cholesterol ratio
2785Std. Mean Difference (IV, Random, 95% CI)0.06 [-0.08, 0.20]

 
Summary of findings for the main comparison.

Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus

Patient or population: participants with type 2 diabetes mellitus

Interventions settings: clinic-based (touch screen or other clinic computer), home computer-based and mobile phone-based interventions

Intervention: computer-based software applications that respond to user input and aim to generate tailored content to improve one or more of the cognitive, behaviour and skills and emotional self-management domains through feedback, tailored advice, reinforcement and rewards, patient decision support, goal setting or reminders

Comparison: standard diabetes care, non-interactive computer-based programmes, paper educational material, delayed start/waiting list, face-to-face diabetes self-management education

OutcomesRelative effect
(95% CI)
No of participants
(studies)
Quality of the evidence
(GRADE)
Comments

Health-related quality of life

[follow-up: 2 to 18 months]
See comment2113

(5)
⊕⊕⊕⊝
moderatea
No study showed statistically significant differences between intervention and control groups.

Death from any cause

[follow-up: 2 to 18 months]
See comment3578

(16)
⊕⊕⊕⊕
high
A total of three deaths in the 16 studies. Two participants died in one study (Lorig 2010) and one participant died in another study from complications of a cerebrovascular attack (Leu 2005). No further details were provided in the study reports.

Depression

[follow-up: 2 to 18 months]
See comment2273

(6)
⊕⊕⊕⊝
moderateb
No study showed statistically significant differences in depression scores or incidence of depression between intervention and control groups.

Adverse effects

[follow-up: 2 to 12 months]
See comment3578

(16)
⊕⊕⊕⊕
high
One study reported a participant withdrawing due to anxiety related to the study.

HbA1c [%]

[follow-up:
1. 2 to 12 months
2. 3 to 12 months]
1. -0.2 (-0.4 to -0.1)

2. -0.5 (-0.7 to -0.3)
1. 2673

(11)

2. 280

(3)
1. ⊕⊕⊕⊝
moderatec

2. ⊕⊕⊝⊝
lowd
1. Computer-based interventions resulted in a 0.2% greater HbA1c reduction than control groups (difference in change and final values).

2. Subgroup mobile phone interventions resulted in a 0.5% greater HbA1c reduction than control groups (difference in final values).

Economic data

[follow-up: 18 months]
See comment761

(1)
⊕⊕⊝⊝
lowe
One study looked at health behaviour and resource utilisation but found no significant differences between intervention or control groups.

GRADE Working Group grades of evidence
High quality: Further research is very unlikely to change our confidence in the estimate of effect.
Moderate quality: Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.
Low quality: Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.
Very low quality: We are very uncertain about the estimate.

 aSerious risk of bias
bSerious risk of bias
cInconsistency, indirectness
dSubgroup analysis, low number of participants, indirectness
eOne study only, serious risk of bias
 
Table 1. Taxonomy of behaviour change techniques

Behaviour change techniques

1 Provide information on consequences of behaviour in general

2 Provide information on consequences of behaviour to the individual

3 Provide information about others' approval

4 Provide normative information about others' behaviour

5 Goal setting (behaviour)

6 Goal setting (outcome)

7 Action planning

8 Barrier identification/problem solving

9 Set graded tasks

10 Prompt review of behavioural goals

11 Prompt review of outcome goals

12 Provide rewards contingent on effort or progress towards behaviour

13 Provide rewards contingent on successful behaviour

14 Shaping

15 Prompt generalisation of target behaviour

16 Prompt self-monitoring of behaviour

17 Prompt self-monitoring of behavioural outcome

18 Prompt focus on past success

19 Provide feedback on performance

20 Provide information on where and when to perform the behaviour

21 Provide instruction on how to perform the behaviour

22 Model or demonstrate the behaviour

23 Teach to use prompts / cues

24 Environmental restructuring

25 Agree on behavioural contract

26 Prompt practice

27 Use follow-up prompts

28 Facilitate social comparison

29 Plan social support / social change

30 Prompt identification as a role model/position advocate

31 Prompt anticipated regret

32 Fear arousal

33 Prompt self-talk

34 Prompt use of imagery

35 Relapse prevention / coping planning

36 Stress management

37 Emotional control training

38 Motivational interviewing

39 Time management

40 General communication skills training

41 Stimulate anticipation of future rewards

 
Table 2. Overview of study populations

Characteristic

Study ID
Intervention(s) and control(s)[N] Screened[N] Randomised[N] ITT[N] Finishing study[%] Randomised
finishing study

Christian 2008I: computer expert system

C: printed information at baseline then usual care
T: 322I: 155

C: 155

T: 310
-I: 141

C: 132

T: 273
I: 91

C: 85

T: 88

Glasgow 1997I: computerised touchscreen assessment

C: touch screen assessment at baseline then usual care
-I: 108

C: 98

T: 206
No ITT analysis doneI: -

C: -

T: 161
I: -

C: -

T: 78

Glasgow 2003aI: D-NET Peer support

C: access to articles about diabetes
-I: 80

C: 80

T: 160
No ITT analysis done--

Glasgow 2005bI: DPP

C: touch screen assessment at baseline then usual care
T: 1187I: 469

C: 417

T: 886
No ITT analysis doneI: 379

C: 354

T: 733
I: 81

C: 85

T: 83

Glasgow 2006I: TSM

C: enhanced usual care - generic health risk appraisal then usual care
T: 2662I: 174

C: 161

T: 335
-I: 147

C: 152

T: 302
I: 84

C: 94

T: 90

Glasgow 2010cI: CASM

C: enhanced usual care - generic health risk appraisal then usual care
T: 544I: 169

C: 132

T: 301
-I: 130

C: 115

T: 245
I: 77

C: 87

T: 81

Leu 2005I: automated wireless messaging system

C: presumed usual care
T: 50I: 25

C: 25

T: 50
No ITT analysis doneI: 21

C: 21

T: 42
I: 82

C: 82

T: 82

Lim 2011I: U-healthcare

C: baseline face-to-face education followed by usual care
T: 180I: 51

C: 52

T: 103
No ITT analysis doneI: 49

C: 48

T: 97
I: 96

C: 92

T: 94

Lo 1996I: CAL

C: group diabetes education sessions
-I: 12

C: 20

T: 32
No ITT analysis doneI: 12

C: 16

T: 28
I: 100

C: 80

T: 88

Lorig 2010I: IDSMP

C: usual care
T: 1019I: 491

C: 270

T: 761
-I: 395

C: 238

T: 633
I: 80

C: 88

T: 83

Quinn

2008
I: WellDoc

C: provided blood glucose meters and encouraged participants to fax their results to their healthcare providers every two weeks until blood glucose was stabilised
-I: 15

C: 15

T: 30
No ITT analysis doneI: 13

C: 13

T: 26
I: 87

C: 87

T: 87

Quinn 2011I: group 2 coach only

C: usual care
T: 2602I: 38

C: 63

T: 101
-I: 23

C: 56

T: 79
I: 61

C: 90

T: 78

Smithd

2000
I: Firstclass software

C: hard copies of materials
T: 50I: 15

C: 15

T: 30
No ITT analysis done-I: 100

C: 100

T: 100

Wise 1986eI: ICT +KAP (IV)

C: presumed usual care
--No ITT analysis doneI: 21

C: 21

T: 42
I: 21

C: 21

T: 42

Yoo 2009I: UCDC

C: usual care
-I: 62

C: 61

T: 123
No ITT analysis doneI: 57

C: 54

T: 111
I: 92

C: 86

T: 90

Zhou 2003I: Diabetes diet advisor V1.0

C: fixed carbohydrate content
-I: 88

C: 62

T: 150
-I: 88

C: 62

T: 150
I: 100

C: 100

T: 100

Total fAll interventions19521476

All controls16261282

All interventions and controls35782922

 "-" denotes not reported
Where provided, data for analysis has used numbers provided for the specific outcomes. Where these data were not available, numbers in each group have been extracted from CONSORT diagrams or the text of the reports.
a Final numbers for each group were not included in study report. The numbers used in the analysis assumed equal allocation amongst experimental groups and made no allowance for attrition. As this would overpower the study in the meta-analysis, a sensitivity analysis was done removing this study - this had no significant impact on the results.
b The numbers for the final outcome data did not match the numbers completing the trial. The numbers for control and intervention groups were not provided, only a total n for number total cases providing outcome data. Numbers in each group were estimated as a proportion of the total cases using the ratio I : C = 379 : 354, e.g. for HbA1c total n = 560, n for the intervention group = (379/733)*560 = 290.
c The numbers for the final outcome data did not match the numbers completing the trial. The numbers for control and intervention groups were not provided, only a total n for number total cases providing outcome data. Numbers in each group were based on the CONSORT diagram as there were three groups - CASM, control and CASM+ and trying to estimate the numbers in each group based on the data provided was not feasible.
dThe number of participants completing the study was not reported.
eOnly 2/147 people dropped out of the whole study.
fRequested data from Glasgow 1997/2003; Smith 2000 and Wise 1986 but no response to queries.
C: control; I: intervention; ITT: intention-to-treat; T: total