Diabetes Paul

8/9/2019 Diabetes Paul

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July-August 2014 • Vol. 23/No. 4 231

Caralise W. Hunt, PhD, RN, CMSRN, is Assistant Professor, School of Nursing, AuburnUniversity, Auburn, AL.

Bonnie K. Sanderson, PhD, RN, is Professor, School of Nursing, Auburn University, Auburn,AL.

Kathy Jo Ellison, PhD, RN, is Associate Professor, School of Nursing, Auburn University,Auburn, AL.

Note: The corresponding author received the Academy of Medical-Surgical Nurses CeceliaGatson Grindel Evidence-Based Practice Research Grant Award to conduct this study.

Support for Diabetes Using Technology: A Pilot Study to Improve

Self-Management

A

ccording to the AmericanDiabetes Association (ADA,

2013a), 25.8 million peoplein the United States currently areliving with diabetes. Approximately90%-95% of these have type 2 dia-betes (T2DM). If not managed prop-erly, diabetes leads to multiple com-plications, including heart disease,stroke, high blood pressure, kidneydisease, blindness, and limb ampu-tation. Management of diabetesrequires participation in a multifac-eted program. The complex natureof diabetes treatment plans makes it

difficult for people living with dia-betes to understand and maintaindaily self-management (Sevick etal., 2008). Technology may assistwith processing the complexities of a self-management plan by provid-ing education and visual feedbackof self-management behaviors.

Review of Literature

People living with diabetes areencouraged to follow a healthy diet,monitor blood glucose, exercise,take prescribed medications, andmonitor for diabetes-related com-plications by daily inspecting skinand feet and obtaining an annualeye examination (ADA, 2013b).Self-care management interven-tions improve glycemic control inpeople living with T2DM, leadingto greater well-being and decreasedcomplications (Minet, Moller, Vach,Wagner, & Henriksen, 2010; Renderset al., 2009). Prior to study onset, aliterature review was conducted for

the years 2007-2012 using PubMed,

CINAHL, and PsycINFO databases.Search terms included diabetes self-management , diabetes self-manage-ment behaviors, diabetes and self-effi-cacy , and diabetes and technology .

Research indicates self-efficacy islinked closely to diabetes self-man-agement, with higher levels of self-efficacy being related to increased

participation in diabetes self-man-agement behaviors (King et al.,2010; Lanting et al., 2008; O’Hea etal., 2009). Methods to promote self-efficacy in persons with diabeteshave the potential to improve dia-betes self-management, therebyimproving overall disease control.Technology is being used increas-ingly to assist people living withdiabetes with self-management.New technological advances canimprove self-management by en-

couraging patients to participate inpractices and routines related totheir illness and providing educa-tional and motivational support forday-to-day diabetes management.

Technological interventions offerpromise for enhancing self-efficacyand support for diabetes self-man-agement. One study evaluated threedifferent methods of diabetes educa-tion delivery, including two differentweb interactive methods and a tradi-tional face-to-face education (Pacaud,Kelley, Downey, & Chiasson, 2012).

Improvements in diabetes knowl-edge, self-efficacy, and self-manage-ment were noted for all three meth-ods. Significant correlations werefound between higher websiteusage and higher diabetes knowl-edge, self-efficacy scores, and meta-bolic control. Researchers conclud-ed diabetes education deliveredelectronically can be as effective asthe traditional face-to-face deliverymethod and may offer options formeeting the increasing demands for

diabetes self-management educa-tion.

Another study evaluated the effectof a text message-based diabetesprogram on diabetes management

Research for Practice Research for Practice

Caralise W. Hunt

Bonnie K. Sanderson

Kathy Jo Ellison

Technology may assist people living with type 2 diabetes with self-

management. A pilot study that used Apple ® iPad ® technology tosupport diabetes self-management is described.


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(Nundy, Dick, Solomon, & Peek,2013). Participants received daily textmessages about taking medications,weekly reminders about foot care,and appointment reminders for dia-betes-related visits. They also could

request additional messages relatedto diabetes care, such as remindersabout glucose monitoring. Theintervention improved self-efficacyfor self-management by providingfeedback on self-management andrelating symptoms to self-manage-ment behaviors. Qualitatively, par-ticipants reported the text messag-ing intervention increased self-awareness and control, providedreinforcement and feedback, in-creased realization of the signifi-

cance of diabetes, and provided car-ing and support.

An online diabetes self-manage-ment program was evaluated byLorig and co-authors (2010). Par-ticipants accessed a website for edu-cational sessions and weekly learn-ing activities. They also formulatedan action plan for each week.Participants in the interventiongroup had significant improve-ments in self-efficacy for diabetesself-management compared to the

usual care control group.Research has been conductedusing handheld devices to promotediabetes self-management. A ran-domized controlled trial of 151 par-ticipants tested the use of personaldigital assistants (PDA) for improv-ing diabetes regimen adherence(Sevick et al., 2008). Researchersfound the PDA self-monitoringenhanced accuracy of estimatedcaloric intake and expenditure,enhanced vigilance to the dietaryregimen, allowed problem-solvingfor glucose control issues by exam-ining dietary intake and glucosevalues, and allowed positive rein-forcement and goal revision asneeded.

A qualitative study used a mobilephone and web-based collaborativecare intervention for patients withT2DM (Lyles et al., 2011). Smart-phones and other technology to sup-port diabetes self-management wereprovided to study participants. Mostparticipants appreciated email com-

munications with the nurse and

found it easy to upload glucose infor-mation from meters. However, mostparticipants found the smartphonesto be frustrating. These participantshad not used a smartphone previous-ly and had difficulty with basic oper-

ation of the phone. Participants andresearchers recommended using thetechnology with devices alreadyfamiliar to patients. Although partic-ipants found the smartphones frus-trating, most believed the programincreased awareness of their healthand helped them to be more focusedand accountable for self-managingdiabetes.

An experimental study was con-ducted to evaluate the effects of interactive multimedia on partici-

pants’ diabetes knowledge, abilityto control blood glucose, and self-care (Huang, Chen, & Yeh, 2009).Following the 3-month interven-tion, members of the experimentalgroup had significantly higher dia-betes knowledge levels than thosein the control group who received aroutine education program. Re-searchers found no significant dif-ferences between groups for glyco-sylated hemoglobin (A1C) values orself-care behaviors. A1C improved

for the experimental group, but notto a level of significance. Addi-tionally, the experimental groupshowed improvement in all self-carebehaviors except exercise for thestudy period; however, improve-ments again did not reach a level of statistical significance. Participantsin the experimental group were sat-isfied with the diabetes interactivemultimedia, indicating this may bean acceptable method for diabetesself-management education.

Diabetes self-management inter-ventions also are being deliveredusing the Internet. An Internetcomputer-assisted diabetes self-management intervention utilizedgoal-setting for medication adher-ence, physical activity, and foodchoices (Glasgow et al., 2012).Participants recorded progresstoward goals and created actionplans to address barriers to goalachievement. Health behaviorsimproved significantly for experi-mental group participants com-

pared to control group participants.

Researchers noted greatest improve-ments at 4 months with smalleffects at 12 months.

Tang and colleagues (2013) con-ducted a multicomponent random-ized controlled trial to evaluate an

online disease management systemto support people living withT2DM. The intervention includedwireless uploading of glucose read-ings with graphical feedback, nutri-tion and exercise logs, online mes-saging with the health care team,personalized text, and video educa-tion. At 6 months, A1C values forintervention group participantswere significantly lower comparedto control group participants. Thedifference was not significant at 12

months, however, possibly due tosignificant improvements in A1Camong control group participantsat this time. Intervention group par-ticipants also had significantly bet-ter low-density lipoprotein choles-terol values at 12 months, but nodifferences were seen for blood pres-sure or weight.

Self-management behavior track-ing, as well as improved access todiabetes education and health careproviders, can increase knowledge,

self-efficacy, and participation inself-management behaviors, andultimately may improve diabetesoutcomes (Pacaud et al., 2012).Health care professionals shoulddevelop and implement self-man-agement support technology pro-grams to meet the need to deliverindividualized, cost-effective carethat can reach into communitiesand homes (Fisher & Dickinson,2011). While literature supports theuse of technology to meet the needsof people living with diabetes, moreresearch is needed to determinewhich types of technological inter-ventions are most beneficial. Tech-nology should be evaluated formotivation for diabetes self-man-agement, user satisfaction, and dia-betes outcomes.

Purpose

The purpose of this pilot studywas to determine if the use of appli-cations on Apple® iPad® technology

that support diabetes self-manage-

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Support for Diabetes Using Technology: A Pilot Study to Improve Self-Management

ment will increase self-efficacy forself-management, increase participa-tion in self-management behaviors,and improve diabetes outcomes inpersons with T2DM in an employer-sponsored diabetes self-management

program. Specific aims for the proj-ect included the following:• Increase self-efficacy for diabetes

self-management.• Increase participation in diabetes

self-management behaviors, in-cluding monitoring blood glu-cose, taking medications, exer-cising, and following a recom-mended eating plan.

• Improve diabetes control (A1C).

Theoretical Framework

The study was guided by Self-Determination Theory, a general the-ory of human motivation which sug-gests people have three innate psy-chological needs: autonomy, comp-etence, and relatedness to others(Deci & Ryan, 2002). Autonomyinvolves self-regulation of behaviorsthrough experience and reflectiveself-endorsement. Competence refersto a person’s confidence in the abilityto self-manage and is similar to the

self-efficacy concept. Relatedness in-volves feeling meaningfully connect-ed to others. Feeling a partnershipwith health care providers increasesdesire to participate in self-manage-ment behaviors. Self-DeterminationTheory indicates support for thesethree needs will enhance both men-tal and physical health. People aremore likely to adopt healthy behav-iors when these basic needs are sup-ported. This intervention can in-crease autonomy by allowing self-management behaviors to be trackedand reviewed. This permits reflectionon self-management through visualrepresentation of how day-to-dayactivities affect outcomes such asblood glucose. The use of technologyto track self-management can in-crease competence when people liv-ing with diabetes see positive resultsbased on behaviors. Relatedness canbe accomplished through feedbackobtained from health care providersbased on documented self-manage-ment behaviors.

Methods

Design and Sample

This pilot study used a two-group,crossover, repeated-measures design.

Participants were recruited from theemployee health group of a diabetesand nutrition center at a local med-ical center in an urban area of theSoutheast. Representatives from theemployee health program postedstudy informational flyers at the cen-ter. An informational email blastdescribing the study and providingresearcher contact information wassent by a representative to allemployees enrolled in the healthprogram. Interested persons werereferred to the primary investigatorfor questions about study enroll-ment if they met the inclusion crite-ria. Inclusion criteria were people liv-ing with T2DM, age 19 or older, andable to read and write English. Thegoal was to enroll 20 employees inthe pilot study. Approximately 60people contacted the primary inves-tigator about study participation; 17met inclusion criteria and agreed toparticipate. The primary reasongiven by potential participants fornot enrolling in the study was a lackof time.

Procedures

The study proposal was reviewedand approved by the institutionalreview boards from the universityleading the study and the participat-ing hospital. The primary investiga-tor met with potential participants atthe diabetes and nutrition center.Study details were explained and awritten informed consent documentwas provided. Potential participants

were given the opportunity to askquestions. Those who were interest-ed in participating in the studysigned the consent document andwere given a copy. Following in-formed consent, participants com-pleted pre-intervention demograph-ic, self-efficacy, and diabetes self-management questionnaires. Base-line A1C values were collected bydiabetes and nutrition center staff and documented by researchers.

Participants were assigned ran-

domly either to the intervention

(iPad) or control (journal) group. Theprimary investigator distributed theApple iPad devices and providedinstructions on using the diabetesself-management application to logbehaviors. Participants also were

instructed how to email logs to theprimary investigator once per weekusing a single GMail account estab-lished for the study. The controlgroup participants were giveninstructions on how to log diabetesself-management activities in theprovided journal. Participants inboth groups were asked to log dia-betes self-management behaviors inthe following categories: monitoringblood glucose, following a recom-mended eating plan, exercising, and

taking medications on a daily basis.Contact information for the primaryinvestigator was provided in caseparticipants required assistance orhad questions during the study peri-od. The initial meetings, which last-ed approximately 1 hour, were con-ducted either in groups or individu-ally according to participant prefer-ence.

Researchers met with participantsfrom both intervention and controlgroups 3 months following the ini-

tial meeting to complete mid-inter-vention assessments. At this time,participants in the iPad group weregiven a paper journal to log diabetesself-management activities for thenext 3 months. Participants in thepaper journal group were given aniPad to document diabetes self-man-agement behaviors for the next 3months. A final assessment wascompleted after this 3-month studyperiod. A diabetes educator from thediabetes and nutrition center wasavailable throughout the study peri-od to answer participant questionsrelated to their medical treatmentprograms.

Measures

Demographic information in-cluding age, sex, race, length of time diagnosed with diabetes, andhighest level of education was ob-tained prior to the study. Pre-inter-vention, mid-intervention, andpost-intervention measures of self-efficacy and diabetes self-manage-

ment were obtained. The Diabetes


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Management Self-Efficacy Scale(DMSES) (van der Bijl, Poelgeest-Eeltink, & Shortridge-Baggett, 1999)was used to measure self-efficacy.The 20-item instrument includesquestions about self-care activities

people living with T2DM must per-form to manage the disease, includ-ing eating a heart healthy diet, par-ticipating in physical activity, mon-itoring blood glucose, taking med-ications, and monitoring for com-plications. The 10-point Likert scaleassessed patients’ confidence intheir ability to manage their dia-betes, with higher scores indicatinghigher levels of self-efficacy. In-ternal consistency of the total scalemeasured by Cronbach’s alpha

ranged from 0.81 to 0.92 in previ-ous studies (Coffman, 2008; Hunt etal., 2012; van der Bijl et al., 1999).

Participation in diabetes self-management behaviors was meas-ured using the Summary of Diabetes Self-Care Activities-Revised(SDSCA) questionnaire (Toobert,Hampson, & Glasgow, 2000). Theinstrument contains 11 items toevaluate the frequency with whichparticipants engage in self-manage-ment behaviors, including diet,

exercise, medication use, blood glu-cose testing, and foot care. Re-spondents indicate the frequencywith which they participated in eachself-management behavior in thelast 7 days. Mean number of days iscalculated for each category of self-management behaviors, with higherscores indicating more frequentparticipation in self-managementbehaviors. Overall internal con-sistency as measured by Cronbach’salpha ranged from 0.65 to 0.84

in previous studies (Eigenmann,Colagiuri, Skinner, & Trevena, 2009;Hunt et al., 2012).

An iPad application (DiabetesBuddy®) was loaded on each deviceto track self-management behav-iors. Diabetes Buddy was chosenbecause it allows tracking of the rec-ommended diabetes self-manage-ment behaviors of glucose monitor-ing, eating a healthy diet, exercis-ing, and using medication. Theapplication also allows emailing of data from within the application aswell as unlimited logging of behav-

iors. Participants logged behaviorseach day and emailed a report of activities each week to the primaryinvestigator. Control group partici-pants logged the same behaviorsusing a paper journal.

Data Analysis

Descriptive statistics were used toanalyze demographic data and A1Cvalues. Pre-test and post-test meas-urements of self-efficacy and dia-betes self-management behaviorswere analyzed using a mixed modelanalysis of variance with the group(monitoring method) as the be-tween-subjects factor, and self-effi-cacy and diabetes self-managementbehaviors as the repeated factors. A

repeated measures analysis also wasused to determine changes in self-management behaviors over time.

Results

Demographic Characteristics

During the first phase of thestudy, 3 of the 17 participants with-drew due to time constraints orfamily issues; the final sample was14 participants (see Table 1 for

demographic characteristics). Tenparticipants (59%) were female and11 (65%) were over age 50. Thirteen(77%) of the participants had beendiagnosed with T2DM less than 10years.

Hemoglobin A1C

The sample for this pilot studyhad good glycemic control at base-line with an average A1C of 6.59%.No additional A1C values wereavailable during the study period.

Self-Efficacy

The mean and standard deviation(SD) self-efficacy score for the entiresample as measured by the DMSESwas high at 8.55 (+/- 0.89). This self-efficacy mean score falls within the“certain can do” for the DMSES. Thegroup using iPads in the first arm of the study had significantly higherbaseline self-efficacy scores than thesecond group with means (SD) at 9.1(+/- 0.76) and 8.1 (+/- 0.43), whichcontinued throughout the study.Self-efficacy scores for the first iPad

group (n=6) remained relatively thesame from baseline to mid-interven-tion and post-intervention (9.1, 9,and 9.2). Self-efficacy scores for thesecond iPad group (n=8) decreasedslightly from baseline to mid-inter-

vention after logging using the jour-nal and increased after using theiPads, but not to a level of signifi-cance (8.1, 7.9, and 8.7). Analysis of t -tests revealed no statistically signif-icant change in either group withiPad use, indicating the interventiondid not impact self-efficacy in thissample.

Diabetes Self-Management

The mean diabetes self-manage-ment score for the sample as meas-

ured by the SDSCA was 5.1 (+/-0.89) at baseline. For the groupusing iPads first, SDSCA scoresremained the same, but decreasedslightly after using the journals tolog behaviors (5.4, 5.3, and 5). Forthe group using iPads for the sec-ond half of the study, SDSCA scoresdecreased after journal use, but sig-nificantly increased at post-inter-vention after using the iPads (4.8,4.6, and 5.2). Analysis of t -testsrevealed no significant differences

between groups.

Activity Logs

A comparison of self-manage-ment behavior activity logs betweeniPad use and journal use revealedmixed results. Some participantslogged more self-management be-haviors when they used the iPadand others logged more activitiesusing the journal. This may indicatethe process of tracking self-manage-ment behaviors may be more

important than the method used totrack behaviors. Personal prefer-ences must be considered.

Discussion

Results revealed no difference inself-efficacy scores between the iPadand journal study groups; however,self-efficacy scores were very high atbaseline, making it difficult to iden-tify improvement. A larger, morevaried sample is needed for addi-tional evaluation. Additionally, theaverage A1C of 6.5% for the sample

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Support for Diabetes Using Technology: A Pilot Study to Improve Self-Management


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C o p y r i g h t o f M E D S U R G N u r s i n g i s t h e p r o p e r t y o f J a n n e t t i P u b l i c a t i o n s , I n c . a n d i t s c o n t e n t

m a y n o t b e c o p i e d o r e m a i l e d t o m u l t i p l e s i t e s o r p o s t e d t o a l i s t s e r v w i t h o u t t h e c o p y r i g h t

h o l d e r ' s e x p r e s s w r i t t e n p e r m i s s i o n . H o w e v e r , u s e r s m a y p r i n t , d o w n l o a d , o r e m a i l a r t i c l e s f o r

i n d i v i d u a l u s e .

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