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

150 Pages·2013·1.43 MB·English

Computer-based diabetes self-management interventions for
adults with type 2 diabetes mellitus (Review)
Pal K, Eastwood SV, MichieS, Farmer AJ, Barnard ML, PeacockR, Wood B, Inniss JD,
Murray E
ThisisareprintofaCochranereview,preparedandmaintainedbyTheCochraneCollaborationandpublishedinTheCochraneLibrary
2013,Issue3
http://www.thecochranelibrary.com
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review)
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
TABLE OF CONTENTS
HEADER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
PLAINLANGUAGESUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
SUMMARYOFFINDINGSFORTHEMAINCOMPARISON . . . . . . . . . . . . . . . . . . . 2
BACKGROUND . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
OBJECTIVES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
METHODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Figure1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Figure2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Figure3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Figure4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Figure5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Figure6. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
AUTHORS’CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
CHARACTERISTICSOFSTUDIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
DATAANDANALYSES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Analysis1.1.Comparison1HbA1c,Outcome1HbA1c. . . . . . . . . . . . . . . . . . . . . . 68
Analysis1.2.Comparison1HbA1c,Outcome2Sensitivityanalysis-removingChristian2008. . . . . . . . 69
Analysis1.3.Comparison1HbA1c,Outcome3Sensitivityanalysis-removingLeu2005. . . . . . . . . . 70
Analysis1.4.Comparison1HbA1c,Outcome4Sensitivityanalysis-removingclusterrandomisedtrials. . . . . 71
Analysis1.5.Comparison1HbA1c,Outcome5Sensitivityanalysis-removeGlasgow2003. . . . . . . . . . 72
Analysis1.6.Comparison1HbA1c,Outcome6Subgroupanalysis-outcomesatlessthan6months. . . . . . . 73
Analysis1.7.Comparison1HbA1c,Outcome7Subgroupanalysis-outcomesatlaterthan6months. . . . . . 74
Analysis1.8.Comparison1HbA1c,Outcome8Subgroupanalysis-mobilephonebasedinterventions. . . . . . 75
Analysis1.9.Comparison1HbA1c,Outcome9Subgroupanalysis-interventionsbasedathome. . . . . . . . 76
Analysis2.1.Comparison2Dietarychange,Outcome1Fruitandvegetablescreenerscore. . . . . . . . . . 76
Analysis2.2.Comparison2Dietarychange,Outcome2Estimateddailyfatintake. . . . . . . . . . . . . 77
Analysis2.3.Comparison2Dietarychange,Outcome3Changeincalorificintake. . . . . . . . . . . . . 78
Analysis2.4.Comparison2Dietarychange,Outcome4Pooledeffectondiet. . . . . . . . . . . . . . . 78
Analysis3.1.Comparison3ImpactonweightorBMI,Outcome1PooledeffectonweightorBMI. . . . . . . 79
Analysis4.1.Comparison4Lipids,Outcome1Totalcholesterol. . . . . . . . . . . . . . . . . . . 80
Analysis4.2.Comparison4Lipids,Outcome2Changeintotalcholesterol. . . . . . . . . . . . . . . 81
Analysis4.3.Comparison4Lipids,Outcome3Highdensitylipoprotein(HDL). . . . . . . . . . . . . 81
Analysis4.4.Comparison4Lipids,Outcome4ChangeinHDL. . . . . . . . . . . . . . . . . . . 82
Analysis4.5.Comparison4Lipids,Outcome5Lowdensitylipoprotein(LDL). . . . . . . . . . . . . . 82
Analysis4.6.Comparison4Lipids,Outcome6ChangeinLDL. . . . . . . . . . . . . . . . . . . 83
Analysis4.7.Comparison4Lipids,Outcome7TC:HDLratio. . . . . . . . . . . . . . . . . . . . 83
Analysis4.8.Comparison4Lipids,Outcome8Changeintriglycerides. . . . . . . . . . . . . . . . . 84
Analysis4.9.Comparison4Lipids,Outcome9Pooledeffectoncholesterol. . . . . . . . . . . . . . . 84
ADDITIONALTABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
APPENDICES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
CONTRIBUTIONSOFAUTHORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
DECLARATIONSOFINTEREST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
SOURCESOFSUPPORT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
DIFFERENCESBETWEENPROTOCOLANDREVIEW . . . . . . . . . . . . . . . . . . . . . 147
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) i
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
[InterventionReview]
Computer-based diabetes self-management interventions for
adults with type 2 diabetes mellitus
KingshukPal1,SophieVEastwood1,SusanMichie1,AndrewJFarmer2,MariaLBarnard3,RichardPeacock4,BindieWood1,JoniD
Inniss1,ElizabethMurray1
1ResearchDepartmentofPrimaryCareandPopulationHealth,UniversityCollegeLondon,London,UK.2DepartmentofPrimary
CareHealthSciences,UniversityofOxford,Oxford,UK.3DepartmentofDiabetes,TheWhittingtonHospitalNHSTrust,London,
UK.4ArchwayHealthcareLibrary,London,UK
Contact address: Kingshuk Pal,ResearchDepartmentof Primary Care and Population Health,University College London, Upper
Floor3,RoyalFreeHospital,RowlandHillStreet,London,NW3PF,[email protected]@gmail.com.
Editorialgroup:CochraneMetabolicandEndocrineDisordersGroup.
Publicationstatusanddate:New,publishedinIssue3,2013.
Reviewcontentassessedasup-to-date: 14November2011.
Citation: PalK,EastwoodSV,MichieS,FarmerAJ,BarnardML,PeacockR,WoodB,InnissJD,MurrayE.Computer-baseddiabetes
self-managementinterventions foradultswithtype2diabetesmellitus.CochraneDatabaseofSystematicReviews2013, Issue3.Art.
No.:CD008776.DOI:10.1002/14651858.CD008776.pub2.
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
ABSTRACT
Background
Diabetes is one of the commonest chronic medical conditions, affecting around 347 million adults worldwide. Structured patient
educationprogrammesreducetheriskofdiabetes-relatedcomplicationsfour-fold.Internet-basedself-managementprogrammeshave
beenshowntobeeffectiveforanumberoflong-termconditions,butitisunclearwhat aretheessentialoreffectivecomponentsofsuch
programmes.Ifcomputer-basedself-managementinterventionsimproveoutcomesintype2diabetes,theycouldpotentiallyprovidea
cost-effectiveoptionforreducingtheburdensplacedonpatientsandhealthcaresystemsbythislong-termcondition.
Objectives
Toassesstheeffectsonhealthstatusandhealth-relatedqualityoflifeofcomputer-baseddiabetesself-managementinterventionsfor
adultswithtype2diabetesmellitus.
Searchmethods
Wesearchedsixelectronicbibliographic databases forpublishedarticlesandconferenceproceedingsandthreeonline databases for
theses(alluptoNovember2011).Referencelistsofrelevantreportsandreviewswerealsoscreened.
Selectioncriteria
Randomisedcontrolledtrialsofcomputer-basedself-managementinterventionsforadultswithtype2diabetes,i.e.computer-based
softwareapplicationsthatrespondtouserinputandaimtogeneratetailoredcontenttoimproveoneormoreself-managementdomains
throughfeedback,tailoredadvice,reinforcementandrewards,patientdecisionsupport,goalsettingorreminders.
Datacollectionandanalysis
Tworeviewauthorsindependentlyscreenedtheabstractsandextracteddata.Ataxonomyforbehaviourchangetechniqueswasusedto
describetheactiveingredientsoftheintervention.
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 1
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
Mainresults
Weidentified16randomisedcontrolledtrialswith3578participantsthatfittedourinclusioncriteria.Thesestudiesincludedawide
spectrumofinterventionscoveringclinic-basedbriefinterventions, Internet-basedinterventionsthatcouldbeusedfromhomeand
mobilephone-basedinterventions.Themeanageofparticipantswasbetween46to67yearsoldandmeantimesincediagnosiswas6to
13years.Thedurationoftheinterventionsvariedbetween1to12months.Therewerethreereporteddeathsoutof3578participants.
Computer-baseddiabetesself-managementinterventionscurrentlyhavelimitedeffectiveness.Theyappeartohavesmallbenefitson
glycaemiccontrol(pooledeffectonglycosylatedhaemoglobinA1c(HbA1c):-2.3mmol/molor-0.2%(95%confidenceinterval(CI)
-0.4to-0.1;P=0.009;2637participants;11trials).TheeffectsizeonHbA1cwaslargerinthemobilephonesubgroup(subgroup
analysis: mean difference in HbA1c -5.5 mmol/mol or -0.5% (95% CI -0.7 to -0.3); P < 0.00001; 280 participants; three trials).
Currentinterventionsdonotshowadequateevidenceforimprovingdepression,health-relatedqualityoflifeorweight.Four(outof
10)interventionsshowedbeneficialeffectsonlipidprofile.
Oneparticipantwithdrewbecauseofanxietybuttherewerenootherdocumentedadverseeffects.Twostudiesprovidedlimitedcost-
effectivenessdata-withonestudysuggestingcostsperpatientoflessthan$140(in1997)or105EUROandanotherstudyshowed
nochangeinhealthbehaviourandresourceutilisation.
Authors’conclusions
Computer-baseddiabetesself-managementinterventionstomanagetype2diabetesappeartohaveasmallbeneficialeffectonblood
glucose control and the effectwas larger in themobile phone subgroup. There is no evidence to show benefits inother biological
outcomesoranycognitive,behaviouraloremotionaloutcomes.
PLAIN LANGUAGE SUMMARY
Usingcomputerstoself-managetype2diabetes
Diabetesisoneofthecommonestlong-termmedicalconditions,affectingaround347millionadultsworldwide.Around90%ofthem
havetype2diabetesandareatsignificant riskofdevelopingdiabetesrelatedcomplicationssuchasstrokesorheartattacks.Patient
educationprogrammescanreducetheriskofdiabetes-relatedcomplications,butmanypeoplewithtype2diabeteshaveneverattended
structurededucationprogrammestolearnhowtolookafterthemselves(self-management).Betteruseofcomputersmightbeoneway
ofhelpingmorepeoplelearnaboutself-management.
We identified 16 trialsinvolving 3578 adults thatmetour criteria. These studies included differenttypesof interventions usedin
differentplacesliketouchscreencomputersinhospitalclinics,computersconnectedtotheInternetathomeandprogrammesthat
communicatedwithmobilephones.Theaverageageofpeopletakingpartwasbetween46to67yearsoldandmostofthosepeople
hadlivedwithdiabetesfor6to13years.Participantsweregivenaccesstotheinterventions for1to12months,dependingonthe
intervention.Threeoutofthe3578participantsdiedbutthesedeathsdidnotappeartobelinkedtothetrials.
Overall,thereisevidencethatcomputerprogrammeshaveasmallbeneficialeffectonbloodsugarcontrol-theestimatedimprovement
inglycosylatedhaemoglobinA1c(HbA1c-along-termmeasurementofmetaboliccontrol)was2.3mmol/molor0.2%.Thiswas
slightlyhigherwhenwelookedatstudiesthatusedmobilephonestodelivertheirintervention-theestimatedimprovementinHbA1c
was5.5mmol/molor0.5%inthestudiesthatusedmobilephones.Someoftheprogrammesloweredcholesterolslightly.Noneofthe
programmeshelpedwithweightlossorcopingwithdepression.
Oneparticipantwithdrewbecauseofanxietybuttherewerenoobvioussideeffectsandhypoglycaemicepisodeswerenotreportedin
anyofthestudies.Therewasverylittleinformationaboutcostsorvalueformoney.
Insummary,existingcomputerprogrammestohelpadultsself-managetype2diabetesappeartohaveasmallpositiveeffectonblood
sugarcontrolandthemobilephoneinterventionsappearedtohavelargereffects.Thereisnoevidencetoshowthatcurrentprogrammes
canhelpwithweightloss,depressionorimprovinghealth-relatedqualityoflifebuttheydoappeartobesafe.
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 2
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
SUMMARY OF FINDINGS FOR THE MAIN COMPARISON [Explanation]
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus
Patientorpopulation:participantswithtype2diabetesmellitus
Interventions settings: clinic-based (touch screen or other clinic computer), home computer-based and mobile phone-based
interventions
Intervention:computer-basedsoftwareapplicationsthatrespondtouserinputandaimtogeneratetailoredcontenttoimproveoneor
moreofthecognitive,behaviourandskillsandemotionalself-managementdomainsthroughfeedback,tailoredadvice,reinforcement
andrewards,patientdecisionsupport,goalsettingorreminders
Comparison:standarddiabetescare,non-interactivecomputer-basedprogrammes,papereducationalmaterial,delayedstart/waiting
list,face-to-facediabetesself-managementeducation
Outcomes Relativeeffect Noofparticipants Qualityoftheevidence Comments
(95%CI) (studies) (GRADE)
Health-relatedqualityof Seecomment 2113 ⊕⊕⊕(cid:13) No study showed statis-
life (5) moderatea tically significant differ-
[follow-up: 2 to 18 ences between interven-
months] tionandcontrolgroups
Deathfromanycause Seecomment 3578 ⊕⊕⊕⊕ Atotal ofthreedeathsin
[follow-up: 2 to 18 (16) high the16studies. Twopar-
months] ticipantsdiedinonestudy
(Lorig2010)andonepar-
ticipant died in another
studyfromcomplications
of a cerebrovascular at-
tack (Leu2005). No fur-
therdetailswereprovided
inthestudyreports.
Depression Seecomment 2273 ⊕⊕⊕(cid:13) No study showed sta-
[follow-up: 2 to 18 (6) moderateb tistically significant dif-
months] ferences in depression
scores or incidence of
depression between in-
tervention and control
groups
Adverseeffects Seecomment 3578 ⊕⊕⊕⊕ Onestudyreportedapar-
[follow-up: 2 to 12 (16) high ticipant withdrawing due
months] to anxiety related to the
study
HbA1c[%] 1.-0.2(-0.4to-0.1) 1.2673 1.⊕⊕⊕(cid:13) 1.Computer-basedinter-
[follow-up: 2.-0.5(-0.7to-0.3) (11) moderatec ventions resulted in a 0.
1.2to12months 2.280 2.⊕⊕(cid:13)(cid:13) 2%greaterHbA1creduc-
2.3to12months] (3) lowd tion than control groups
(differenceinchangeand
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 3
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
finalvalues)
2. Subgroup mobile
phone interventions re-
sulted in a 0.5% greater
HbA1c reduction than
control groups (differ-
enceinfinalvalues)
Economicdata Seecomment 761 ⊕⊕(cid:13)(cid:13) One study looked at
[follow-up:18months] (1) lowe health behaviour and re-
source utilisation but
found no significant dif-
ferences between inter-
ventionorcontrolgroups
GRADEWorkingGroupgradesofevidence
Highquality:Furtherresearchisveryunlikelytochangeourconfidenceintheestimateofeffect.
Moderatequality:Furtherresearchislikelytohaveanimportantimpactonourconfidenceintheestimateofeffectandmaychange
theestimate.
Lowquality: Further research isverylikelytohaveanimportant impact onourconfidence intheestimate ofeffect and islikelyto
changetheestimate.
Verylowquality:Weareveryuncertainabouttheestimate.
aSeriousriskofbias
bSeriousriskofbias
cInconsistency,indirectness
dSubgroupanalysis,lownumberofparticipants,indirectness
eOnestudyonly,seriousriskofbias
BACKGROUND
Improving bloodsugar control inpatientswithdiabetescanre-
Theburdenofdiabetesisgrowingwith347millionpeoplecur- ducetheriskofdeathandmicrovascularcomplications(DCCT
rentlyaffectedworldwide(Danaei2011)andnumbersprojectedto 1993;UKPDS1998);however,achieving significant reductions
increaseto552millionby2030(InternationalDiabetesFederation inblood glucose levelscanbe difficultinpractice (Peters1996;
2011).IntheUK,thecosttotheNationalhealthService(NHS) Saaddine2002).Cardiovascularriskfactorssuchasraisedblood
related to diabetes in 2002 was estimated to be around “£1.3 pressure and lipids are also important and targeting these indi-
billionayear,withmostofthiscostarising fromthelong-term viduallyortogethercanbeeffectiveinreducingmortality(Gaede
complications resultingfromdiabetesnotbeing managedprop- 2003). There is a growing body of evidence that supports the
erly”(Wanless2002),whiletheInternationalDiabetesFederation notion thatimproving self-care improvesthebiological compli-
(IDF)suggeststhatinthedevelopedworldthecostofcaringfor cationsofdiabetes,aswellascognitiveandemotionaloutcomes
patientswithdiabetesisdoublethatofthebackgroundpopula- (Campbell2003).
tion. Complications of diabetes range fromanincreased risk of
heart attacks, strokes and amputations to blindness and kidney
damage:a60-yearoldmalenewlydiagnosedwithtype2diabetes
Diabetesandself-management
(withoutpre-existingcardiovasculardisease)canexpecttolose8
to 10 years of life if his diabetes is poorly controlled (National Corbin and Strauss (Corbin 1988) described three distinct ele-
CollaboratingCentre2008).Theneedforcost-effectiveimprove- mentsofcopingwithachronicillness.
mentsinmanagingdiabetesisevidentlyimportant.
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 4
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
1. Medicalandbehaviouralmanagement:e.g.taking Newtechnologyofferssomeexcitingnewopportunitiestoexpand
medication,attendingfollow-up. onthesuccessaboveandcountersomeofthedifficulties(Griffiths
2. Rolemanagement:e.g.takingonthe’patient’role,the 2006;Tate 2004). Desktop, laptopor handheldcomputersand
effectonrelationships. mobilephoneshavetheprocessingpowerandconnectivitytoal-
3. Emotionalmanagement:dealingwiththefear,anger,guilt lowremoteaccesstoinformationandalgorithmsthatmaybeable
etc.thatoftenaccompanylivingwithachronicillness. totargetmostofthecomponentsofexistingface-to-faceDSME
LorigandHolmanusedtheworkofCorbinandStraussasabasis programmes.Theyalsohavethepotentialtoberelativelycheap,
todescribesixskillsrequiredforself-management(Lorig2003): easilydistributable,deliveredatmultiplelocations(clinical,com-
1)problemsolving, 2)decisionmaking,3)resourceutilisation,4) munity-based,athomeoronthemove)attimesconvenientfor
theformationofapatient-providerpartnership,5)actionplanning patients,offerpatientsasmanyinterventionsastheyneedorwant
andbehaviourchange,and6)patientstailoringmanagementplans andoffercontinuingsupport,sendoutautomaticremindersand
tosuittheirneeds. present information in an attractive, tailored format to suit pa-
Theseskillsdescribe themedical,behavioural androle-manage- tients’needs.Connectivitymentionedabovealsoallowseasyfor-
mentelementsofself-management,buttheabilitytocopewith mationofsocialnetworkingandpeersupportgroupsbeyondtra-
theemotionalburdenassociatedwiththeillnessisalsoneeded.Di- ditionalclinicalsettings.Diabetesself-managementinterventions
abetesself-managementeducation(DSME)isaformaltermused often show evidence of short-term benefits that may fade over
todescribetheongoingprocessoffacilitatingtheknowledge,skill time(Minet2010).Computer-basedinterventionshavethepo-
andabilitiesnecessaryfordiabetesself-care(Funnell2009),and tentialtoprovideongoingself-managementsupporttore-enforce
newtechnologyhasthepotentialtoimprovepatientoutcomesby thebenefitsovertime.
helpingpatientsimprovetheirabilitiesinallofthesedomains.
Descriptionofthecondition
Theevidencefordiabetesself-management Diabetesmellitusisametabolicdisorderresultingfromadefectin
education insulinsecretion,insulinaction,orboth.Aconsequenceofthisis
chronichyperglycaemia(thatiselevatedlevelsofplasmaglucose)
Anumberofexistingevidence-basedprogrammestoimproveself-
with disturbances of carbohydrate, fat and protein metabolism.
carearealreadywidelyusedandexamplesofthesediabetesself-
Long-term complications of diabetes mellitus include retinopa-
management education programmes include: the diabetes edu-
thy,nephropathyandneuropathy.Theriskofcardiovasculardis-
cation and self-management for ongoing and newly diagnosed
ease is increased. For a detailed overview of diabetes mellitus,
(DESMOND)programmeforpeoplewithnewlydiagnosedtype
pleaseseeunder’Additional information’ intheinformation on
2diabetes(Davies2008),the’RethinkOrganizationtoiMprove
theMetabolicandEndocrineDisordersGroupinTheCochrane
EducationandOutcomes’(ROMEO)forpeoplewithtype2dia-
Library(see’About’,’CochraneReviewGroups(CRGs)’).Foran
betes(Trento2010),the’DiabetesX-PERTProgramme’(Deakin
explanationofmethodologicalterms,seethemainglossaryinThe
2006)for peoplewith type 2diabetes and the dose adjustment
CochraneLibrary.
for normal eating (DAFNE) for people with type 1 diabetes
(DAFNE 2002). Examples of general patient self-management
programmes include the chronic disease self-management pro-
gramme (CDSMP) (Lorig 2001) and the expert patient pro- Descriptionoftheintervention
gramme (EPP) (Department of Health 2001; Kennedy 2007).
Thetermcomputer-baseddiabetesself-managementintervention
Group-basedtrainingforself-managementinpeoplewithtype2
includesanyapplicationthattakesinputfromapatientanduses
diabetesappearstoimprovediabetescontrol(glycatedhaemoglo-
communicationorprocessingtechnologytoprovideatailoredre-
binreducedby1.4%atsixmonths)andknowledgeofdiabetesin
sponsethatfacilitatesoneormoreaspectofdiabetesself-manage-
theshort-andlonger-termwithweakerevidencetoshoweffectson
ment,i.e.technologythatpromotes1)problemsolving, 2)deci-
bloodpressure,weightandhealth-relatedqualityoflife(Deakin
sionmaking,3)resourceutilisation,4)theformationofapatient-
2005). In contrast, theredoes not currently appear to be much
providerpartnership,5)actionplanning,emotionalmanagement
evidence to show thatindividual patienteducation significantly
orbehaviourchangeor6)self-tailoring,withoutneedingcontin-
improvesglycaemiccontrol, body mass index or blood pressure
uousprofessionalinput.
(Duke2009).
Adverseeffectsoftheintervention
Althoughdifficultieswiththeuptakeandreachofsuchinterven-
Thepotentialfornewtechnology
tions have beendocumentedin theliterature (Glasgow 2010a),
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 5
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
thereiscurrentlynogoodevidencedocumentingadverseeffects behaviourchange;2)theyonlypartiallyexplaintheobservedvari-
oftheseinterventions. Possible adverseeffectscouldincludethe anceseeninbehaviouraloutcomes;3)theyareheavilyfocusedon
following. motivatedorintentionalbehaviourwhilethebehavioursthatneed
• Patientsreceivingincorrectadviceormisinterpretingself- tobechangedtoimprovehealthareoftenautomatic,habitualpat-
managementguidance. ternsofbehaviour;and4)theydonotmodelmultiplebehaviour
• Patientsmakingdecisionsthatclinicianswoulddeem change(Munro2007).
’inappropriate’. Aninterventionbasedontheoryismorelikelytobeeffectivethan
• Frustrationatabsenceofservicestheinterventionsuggests onenotbasedontheory(Noar2008),andalsohastheadvantages
wouldbeuseful. ofageneralisableframework,thepossibilityofunderstandingwhy
• Senseoffailure,lossofself-esteemorself-worthamongst theinterventionsmightwork,andfacilitatingtheaccumulationof
patientswhostopusingitordonotfindithelpful. knowledge(Michie2008).However,thereisnoclearconsensuson
• Exclusionarisingfromdigitaldivideorinabilitytouse howtochooseoneormoretheoriesofhealthbehaviourinorder
technology. tocreateanintervention.Oneapproachistoassessthebehaviours
• Riskofhealthservicesystemonlyprovidinge-health thatneedtobechangedintermsoftheoreticaldomainsexplain-
intervention,leavingthoseunabletousesuchinterventions ing why current behaviours exist. Using a mapping framework
unserved.Breakdownorstrainonexistingdoctor-patient (Michie2008),thesedomainscanthenbeusedtoselectappro-
relationshipsifthereisadifferenceinadvicefromthe priatebehaviourchangetechniques(examplesshowninTable1).
interventionandhealthcareproviders. Theuseofintegrativetheoreticaldomainsallowsacomprehensive
• Clinicianinformationoverloadfromdatageneratedbyself- theoreticalassessmentratherthanstartingbyapplyingonlyoneor
managementrecording. twotheoriesandpotentiallymissingimportantexplanations.Part
• Increaseduseandstrainonhealthservicesfrommore oftheaimofthisreviewistodescribetheinterventionsinterms
engagedpatients. ofbehaviourchangetechniquesandtheories(aswellasmodeof
deliveryortechnologyused)therebyallowingatheory-basedra-
tionaleforgroupingorcombininginterventioncomponents.
Howtheinterventionmightwork
Computer-based interventions to improve diabetes self-care are
complexinterventions(MedicalResearchCouncil2008),andthey
canbejudgedontheirabilitytoimprovebiological,cognitive,be-
haviouralandemotionaloutcomes.Forthistohappen,interven-
Whyitisimportanttodothisreview
tionsneedtohelppatientsimprovetheirknowledgeandunder-
standingofdiabetesandchangetheirpatternsofeating,physical Thereisevidencethatlow-intensitybriefinterventionsforsimple
activityandadherencetotreatmentregimens.Thetheorybehind behaviourchange(e.g.smokingcessation)areeffectiveevenwhen
theeducationalcomponentofinterventionscanbebasedonprin- deliveredbycomputer-basedapplications(Portnoy2008),while
ciples of adult learning and education (Collins 2004) although higher-intensityface-to-faceinterventions(grouporone-to-one)
thetheoreticalbasisofdiabeteseducationalinterventionsisoften setthecurrentstandardforself-managementtraining.Thefunda-
poorly described (Brown 1999). Knowledge and understanding mentalquestioniswhetherthereisacost-effectivenicheforcom-
arethoughttobeimportantcognitionsthatcaninfluencehealth puter-based‘intermediate’interventions(i.e.interventionsthatare
behaviourandtheyarecomponentsofsomeofthetheoriesmen- morecostlyandtimeconsumingthanthebriefinterventionmodel
tionedbelow. butcheapertoimplementthanface-to-facecontact)forthemore
Therearecurrentlyanumber ofdifferenttheoriesthatareused complex(multiple)behaviourchangerequiredinchronicdisease
tomodelhealthbehaviourwhichoftenoverlapandmayusedif- self-management,inthisparticularcase,type2diabetesmellitus.
ferenttermstodescribe similar concepts (Noar 2005). Some of Therearesomeimportantquestionsaboutcomputer-basedinter-
themostcommonlycitedmodelsforhealthbehaviourfocuson ventions for diabetes self-managementthatneedanswering and
cognitiveconstructssuchasattitudes,beliefsandexpectations(re- havenot beenfullyanswered by previous reviews in theareaas
latedtooutcomes,self-belieforwhatotherpeoplemightthink) therehasbeeninsufficientevidenceinthepast.
andexamplesof suchmodelsinclude the’HealthBeliefModel’ 1. Unknownefficacy-dotheyreallywork?
(Rosenstock1966),’TheoryofReasonedActionandPlannedBe- 2. Uncertaintyaboutactivecomponents-howdotheywork?
haviour’(Ajzen2001),’SocialCognitiveTheory’(Bandura1986) 3. Whatistheclinicalsignificanceofanyreportedbenefitsof
and’ProtectionMotivation Theory’(Rogers1975).Usingthese theseinterventions?
theoriesasabasisfordesigningself-managementprogrammeshas 4. Aretheycosteffective?
a number of challenges: 1) the theories focus on predicting be- 5. Whatharmcancomefromcomputer-basedinterventions?
haviour and were not primarily created as theories for enabling 6. Whichpopulationsandsub-populationsdotheybenefit?
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 6
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
OBJECTIVES Behaviourandskills
• Incorporatingappropriatenutritionalmanagement.
Toassesstheeffectsonhealthstatusandhealth-relatedqualityof
• Incorporatingphysicalactivityintolifestyle.
lifeofcomputer-baseddiabetesself-managementinterventionsfor
• Utilisingmedications(ifapplicable)fortherapeutic
adultswithtype2diabetesmellitus.
effectiveness.
• Monitoringbloodglucose,urineketones(when
appropriate),andusingtheresultstoimprovecontrol.
METHODS • Accessingservicesandpreventing,detectingandtreating
acutecomplications.
• Preventing(throughriskreductionbehaviour),detecting,
andtreatingchroniccomplications.
Criteriaforconsideringstudiesforthisreview
Emotional
Typesofstudies • Integratingpsychosocialadjustmenttodailylife.
• Managinganxiety,depressionandstress.
Randomisedcontrolledclinicaltrials.
• Providingsocialsupportforpatients.
Typesofparticipants
Control
Adultpatientswithtype2diabetesmellitus.Adultpatientswere • Standarddiabetescare.
definedaspatientsaged18andover. • Non-interactivecomputer-basedprogramme.
• Papereducationalmaterial.
• Delayedstart/waitinglist.
Diagnosticcriteria • Face-to-facediabetesself-managementeducation.
Tobeconsistentwithchangesinclassificationanddiagnosticcri-
Thereisno equivalentof aplacebo-controlledtrial asallof the
teriaofdiabetesmellitusthroughtheyears,thediagnosisshould
controlshavepatientswithachronicillnesswhowillhaveongo-
havebeenestablishedusingthestandardcriteriavalidatthetime
ingclinicalinputthatcouldhaveaneffectonthetargetpopula-
ofthebeginningofthetrial(forexampleADA1999;ADA2008;
tion.Somewouldarguethatanyeffectofstandardcareisdesir-
WHO 1998). Ideally, diagnostic criteria should have been de-
able asitcounteracts theeffectof theselectionbias inherentin
scribed.Wherenecessary,authors’definitionofdiabetesmellitus
choosingvolunteersfortrialswhoaremorelikelytobemotivated
wereused.
andconcernedabouttheirhealthanditprovidesamorerealistic
estimateofanyadvantage ofthetreatmentoverexistingclinical
care.However,inthecaseofbehaviouralinterventions,’standard
Typesofinterventions
care’mayinvolveanumberofthebehaviouraltechniquesthatare
beingtestedandtheirpresenceinthecontrolgroupcouldmake
theresultsdifficulttointerpret.Wehavethereforetriedtoanalyse
Intervention any ’standard care’ providedto comparison groups and implicit
interventionortechniquethatmightbepartofthecomparison
Computer-basedsoftwareapplicationsthatrespondtouserinput
group(deBruin2009).
andaimtogeneratetailoredcontenttoimproveoneormoreofthe
following self-management domains through feedback, tailored
advice,reinforcementandrewards,patientdecisionsupport,goal Setting
settingorreminders.
Therewerenorestrictionsbasedonsettingortechnologyusedto
delivertheintervention.
Cognitive
• Knowledgeaboutthediabetesdiseaseprocess, Exclusions
complicationsandtreatmentoptions. Anyprogram,websiteorapplication.
• Goalsettingtopromotehealth. • Targetedonlyatpatientswithtype1diabetes
• Self-efficacyandconfidenceinownabilitytomanage • Involvingparticipantsagedundertheageof18(including
diabetes. studiesonmixedpopulationsofadultsandchildren)
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 7
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.
• Usedonlyforcommunicationbetweenpatientsand Typesofoutcomemeasures
professionals
• Targetedexclusivelyathealthprofessionals
Studiescarriedoutonmixedpopulationsofpatientswithtype1 Integrating all the factors contributing to diabetes self-manage-
andtype2diabeteswereincludedinthereviewaslongasmore ment into a unified model to describe how they might affect
than50%ofthepatientshadtype2diabetes.Wherepossible,data outcomesischallenging.Adeliberatelysimplifiedschematicthat
forpatientswithtype2diabeteswereextractedandthedataforpa- couldaidthisprocessisshowninFigure1.Asmanyofthehealth
tientswithtype1diabetesdiscarded.Whenthatwasnotpossible, outcomes take many years to develop, it is not practical to use
dataforthemixedpopulationwereused.Four studiesincluded themasprimaryoutcomemeasuresforthisreviewasfollow-upin
inthereviewhadmixedpopulations(Leu2005;Lo1996;Smith thestudieswouldnotbelongenoughtodemonstratedifferences
2000;Wise1986).Oneofthesestudies(Leu2005)providedsuf- inthese.However,moreproximalvariablessuchasglycosylated
ficientdatatoincludeitinthemeta-analysis.Asubgroupanalysis haemoglobin A1c (HbA1c, representing an average measure of
was undertaken to examine the impact of removing studies on bloodsugars),bodymassindex(BMI),depressionoranxietymay
mixedpopulations. showchangesoversuitabletimescales.
Figure1. Amodeltodemonstratehowself-managementinterventionsmightaffectoutcomesintype2
diabetes
Primaryoutcomes
Cognitions
• Health-relatedqualityoflife
• Changeinknowledgeandunderstanding
• Deathfromanycause
• Self-efficacy
• HbA1c
Behaviours
Secondaryoutcomes
• Physicalactivity
Computer-baseddiabetesself-managementinterventionsforadultswithtype2diabetesmellitus(Review) 8
Copyright©2013TheCochraneCollaboration.PublishedbyJohnWiley&Sons,Ltd.