Adherence to IDDM Regimens Relationship to Psychosocial Variables and Metabolic Control

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A dherence to IDDM Regimens: Relationshipto Psychosocial Variables and Metabolic ControlLORRAINE C. SCHAFER, M.S., RUSSELL E. GLASGOW, Ph.D., KEVIN D. McCAUL, Ph.D., AND MARK DREHER, Ph.D.

Thirty-four adolescents (ages 12-14 yr) with IDDM completed a questionnaire assessing regimen ad-herence over the previous week and psychosocial measures potentially related to adherence. Four aspectsof the IDDM regimen were studied: insulin injections, dietary patterns, glucose testing, and exercise.Psychosocial variables included (1) Social Learning Th eory measures of diabetes-specific family b ehaviorsand barriers to adherence and (2) more general measures of family interaction. Glycosylated hemoglobinlevels were predicted accurately (R = 0.68) from a combination of three adherence measures. Thepsychosocial measures were not directly related to metabolic control, but they were associated withadherence. Degree of adherence to one aspect of the IDDM regimen was not related to adherence toothe r aspects of the regimen and different psychosocial variables predicted adh eren ce to different regimencomponents. The diabetes-specific measures were generally more predictive of adherence than werethe more global measures. Implications and limitations of this cross-sectional, correlational study weredi sC U SS ed . DIABETES CARE 6: 493-498, SEPTEMBER-OCTOBER 1983.T he short- and long-term complications associatedwith IDDM have been well documented. Inbrief,the disease produces detectable neuropathy andretinopathy,1and increases the risk of developingheart and kidney disease, blindness, and infection leading togangrene.2 Recent findings, however, suggest that such com-plications are not inevitable. Careful regimen management,producing good metabolic control, favors longevity 3and mayeven reverse the presence of short-term complications. 4

Given the importance of maintaining regimen adherenceand metabolic control, investigators have begun to searchfor factors, including psychosocial variables, that influenceadherence and control. The rationale for this search is thatif such factors (e.g., family discord, health beliefs) can beidentified, treatments to improve adherence and control canemphasize changes in those areas. Unfortunately, to date,the results of investigatio ns of psychosocial factors in diab eteshave produced, at best, mixed results.5 Studies designed todetect personality differences between persons with "good"versus "poor" control, for example, have been almost uni-formly unsuccessful.6'7 In one recent study, adolescents de-fined as having adequate versus inadequate blood glucoseregulation did not differ in terms of anxiety, locus of control,self-concept, or any of a variety of other personality dimen-

sions.8 Similar disappointing findings have been obtained forpsychosocial variables that emphasize environmental or fam-ily influences on adherence and control. 91 0Taken together, the results of studies concerned with therelationship between psychosocial variables and diabetes con-trol have been unimpressive." The guiding purpose of thepresent research was to improve the "fit" between psycho-social variables, regimen adherence, and metabolic control.We tested two assumptions about methods that have beenused to investigate the relationships among psychosocial var-iables, adherence, and control. One of these assumptions,behavioral specificity, was drawn from Social LearningTheory 1213 and the second from a distinction between theinfluence of psychosocial variables on regimen adherence asopposed to metabolic control.

Social Learning Theory stresses the reciprocal interactionbetween individual and environmental influences on behav-ior. Of particular interest here is the theory's emphasis onbehavioral specificity; that is, predicting a particular behaviordepends on m easurement of psychological and environm entalinfluences specific to that behavior. This notion suggests that"global" psychosocial measures (e.g., a general measure offamily functioning, overall self-concept) should show mini-mal relationships to specific diabetes regimen behaviors. It

DIABETES CAR E, VOL. 6 NO . 5, SEPTEMBE R-OCTOBER 1983 493


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ADHERENCE TO IDDM REGIMENS/L. C. SCHAFER. R. E. GLASGOW, K. D. McCAUL, AND M. DREHER

TABLE 1Subject characteristics and

Age12121212121212121212131313131313131313131313131314141414141414141414

SexMMMFFFFFFFMMMMMMMFFFFFFFMMMMMFFFFF

Yearsdiagnosed411 '224781229

1010

123449111334678

HbA, levels

HbA,9.5

12.412.49.88.07.912.716.45.77.111.59.6

10.68.09.214.312.79.314.312.214.511.54.98.58.913.011.312.39.112.311.8

Barriers toadherence1815414138254824265027402750383554346352364733501849253337236115

Fam. beh. chklist:mother-negative121413261318211024161215710152224161522211814211471615141382315

' A "" indicates missing data.

would be preferable to construct psychosocial measures di-rectly related to the behaviors of interest (e.g., how does apatient's family participate in the diabetes regimen?).A second possible explanation for the minimal relation-ships obtained between psychosocial variables and control istha t investigators often att empt to predict measures of controldirectly from psychosocial variables. This approach is char-acteristic of much research in behavioral medicine; 1415 un -fortunately, it confuses outcome measures with adherencebehaviors. It is unlikely that psychosocial variables will im-pact directly on metabolic control (though stress may be anexce ptio n; see ref. 16). It is more likely that psychosocialvariables such as family beh avior w ill affect c ontro l indirectlythrough their influence on adherence behaviors.17The present study served as an initial attempt to test theabove assumptions. In a cross-sectional study, adolescentswith IDDM completed several psychosocial measures and

measures of adherence. In addition, blood samples were drawnfor glycosylated hemoglobin determinations of metaboliccon tro l. We comp ared a global measure of family functionin gto a scale assessing specific family behaviors relevant to thediabetes regimen and a specific measure of barriers to ad-herence. In addition, we compared the success of these psy-chosocial measures for predicting regimen adherence versusmetabolic control.

M ETHODSubjects and SettingA summer camp sponsored by the North Dakota affiliate ofthe American Diabetes Association was the site for collectingmeasures from adolescents with IDDM. The campers in-cluded 34 Caucasian adolescents (15 boys and 19 girls) from12 to 14 yr of age who had been diagnosed as having IDDMfrom 1 to 11 yr. Table 1 presents more detailed informationon individual subjects.ProcedurePrior parental consent for participation was obtained via themail from the p arents of all campers. During their orientatio nto camp, subjects were met individually and given instruc-tions on how to complete each of the questionnaires, whichwere administered in counterbalanced order. They were in-structed to answer questionnaires on the basis of their ex-periences over the week prior to camp. As each subject com-pleted the questionnaire measures, the camp nurse drew bloodsamples by venipuncture for HbA] analyses in vacuum bloodtubes containing EDTA.

MeasuresPsychosocial measures: barriers to adherence and problem solving. The Barriers to Adherence and Problem Solving Scalewas developed to measure (1) the extent that environmentalbarriers interfere with compliance to the recommendedself-care regimen and (2) one's ability to solve the problemscreated by such barriers. The instrument was constructedusing the three step Behavior Analytic Model (situationalanalysis, response enumeration, response evaluation) devel-oped by Goldfried and D'Zurilla.18 First, six persons (fourwomen, two men) who varied in age (range 14-55 yr) andduration of IDDM (range 11-21 yr since diagnosis) and twonurse educators who specialized in diabetes were assembledto assist in instrument developm ent. Participants were askedto generate as many problem situations as possible th at occurfor persons with IDDM. Instructions to the participants weretha t th ey should be as specific as possible and t ha t they shouldtry to think of problem situations interfering with each ofthe following regimen components: insulin injections, glu-cose monitoring, exercise and diet. Redundant items werethen eliminated and the remaining 36 items were rated forfrequency of occurrence and the difficulty of overcoming thebarrier. Items that were infrequent or not problematic were

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ADHERENCE TO IDDM REG1MENS/L. C. SCHAFER, R. E. GLASGOW, K. D. McCAUL, AND M. DREHER

eliminated. A list of the 18 remaining items was mailed tothe eight people who had generated them, and they wereasked to write down as many possible solutions to each prob-lem situation as they could. Participants were instructed notto evaluate their solutions but to include both "good" and"bad" solutions.Five investigators on the project, trained in Goldfried andD'Zurilla's problem-solving techniques and knowledgeableabout diabetes self-care activities, rated the solutions for ef-fectiveness. The rating scale used had three major categoriesof effectiveness ranging from low (1) to high (3). A prelim-inary multiple-choice version of the scale was then devel-oped. For each of the 18 items, from four to six possiblesolutions were included. The solutions were those on whichjudges were able to achieve consensus on effectiveness ratingsand included at least one from each major category.This version of the scale was administered to both ado-lescents and adults at two ch apter meetings of the Am ericanDiabetes Association in different communities. Items thatwere confusing to participants, or that showed no variationacross subjects in frequency of occurrence or extent to whichthey were problematic, were discarded. The current versionof the scale contains 15 items. A Barriers score is calculatedby summing the frequency of occurrence of barriers acrossall items. Total barriers scores can range from 15 to 105. Aproblem solving score, which can range from 15 to 45, iscalculated by summing the effectiveness ratings of all solu-tions selected.

Diabetes Family Behavior Checklist. The Diabetes FamilyBehavior Checklist was developed to assess the frequency ofboth supportive and nonsupportive behaviors directed towarddiabetic persons by family members. This scale differs fromother scales of family interaction in that the items arespecific to the diabetes regimen. Drawing on the work ofinvestigators exploring the relationship between family sup-port and other chronic diseases, l9a Diabetes Family B ehaviorChecklist was developed to assess actions of family membersin the four specific regimen areas previously discussed. Aninitial 14-item scale was piloted in a study designed to in-crease adherence to the diabetic self-care regimen in threeadolescents with IDDM.20 Results from this study were en-couraging and the scale was then expanded to include ap-proximately four items for each of the regimen componentsdiscussed above and four general items. In addition, the for-mat was changed from a checklist format to a 5-point scaleranging from 1 (never) to 5 (at least once a day).The scale was then administered to adults and childrenwith IDDM and their family members at two chapter meet-ings of the American Diabetes Association in two separatecommunities. Items that were difficult to understand or wererated as occurring an average oflessthan once per week were

On a 7-point frequency scale, items were excluded if the meanrating was


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RESULTST his section is divided into three parts. We will firstpresent descriptive data on the measures of met-abolic control, adherence, and psychosocial fac-tors. Second, we will present a comparison of theadherence versus psychosocial variables for predicting met-abolic control. Finally, data will be presented comparing theability of the specific against the general psychosocial meas-ures to predict regimen adherence.The average HbA, level for diabetic subjects was 10.7%(SD across subjects = 2.7%). HbA, levels for nondiabeticsubjects ranged from 5.4 to 6.9%. The average standarddeviation from the duplicate analyses of the same sample was0.3%. Consistent with other reports,29 girls had high er H bAlevels tha n boys; Ms = 11.8 versus 9.4%; F (1,29) = 7.01 ,

P < 0.01.The campers reported generally high levels of adherencethe week prior to camp. They reported conducting an averageof 3.1 glucose tests per day, exercising for at least 20 min onan average of 4.7 days per week, "usually" following theirdiet and performing "most" of their insulin injections ontime. Fortunately, there was sufficient variability in thesereports to explore possible sources of variance and relation-ships with other measures. There were no reliable sex dif-ferences on the adherence measures although there were non-significant tendencies for boys to report conducting moreglucose tests (P < 0.10 ) and to use greater care in measuringtheir insulin doses (P < 0.10).On the Family Behavior Checklist, subjects reported moresupportive than negative interactions with both mothers(M = 25.2 supportive versus 15.9 negative) and fathers(M = 23.6 supportive versus 14-7 negative: P < 0.001 inboth cases). Similarly, scores on the FES were high relativeto national norms (which are standardized to produce meanscores of 50 on each scale) on the Cohe sion scale (M = 57.7)and low relative to national norms on the Conflict scale(M = 41. 8). All psychosocial measures except the problemsolving subscore on the Barriers questionnaire produced suf-ficient variability. This measure was excluded from furtheranalyses.There was only one sex difference on the psychosocialmeasures. Girls reported more negative interactions with theirmother on the Family Behavior Checklist than did boys,F( l,3 2) = 4-70, P < 0.05 (see Table 1).Predicting metabolic control. Three of the seven adherencemeasures, including a measure of each regimen componentexce pt exercise, were significantly associated with Hb A lev-els. As indicated in Table 2, the extent to which one's dietwas followed, reported care in measuring insulin doses, andnumber of daily glucose tests were each significantly corre-lated with glycosylated hemoglobin levels. Interestingly, thesethree measures of adherence were essentially unrelated to

'These comparisons were conducted after introducing adjust-ments to correct for the differential number of items on the positiveand negative scales.

TABLE 2Correlations between adherence reports and diabetes control

Adherence measure Correlation with HbA,Extent follow dietCare measuring insulinNumber daily glucose testsMultiple correlation of 3 adherence

measures with HbA,

0 . 350 . 44 t

0 . 50

0.68**P< 0.05. tP


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TABLE 3Correlations between psychosocial measures and adherence measures found to be predictive of HbA, levels

Adherence measuresPsychosocial measure Extent follow diet Care inmeasuring insulin Number dailyglucose tests

I. "General" measuresFES a: CohesionFES: ExpressivenessFES: ConflictFES: IndependenceFES: Organization

II. "Specific" measuresFBCb: Mother supportiveFBC: Mother negative1FBC: Father supportiveFBC: Father negative1Barriers to adherence'

0.030.200.040.00

-0.140.16

0.30t0.08

0.260.41*

0.110.020.10-0.050 .10

0.140.140.07-0.010 .29 t

0.000.03-0.35*-0.16-0.130.12-0.35-0.040.29t0.02

FES = Family Environment Scale. bFBC = Diabetes Family Behavior Checklist. cOne would expect negative correlations between these measures andadherence. For the remaining measures, positive relationships would be predicted.*P


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results. Finally, the magnitude of the relationship betweenpsychosocial measures and adherence was only moderate andmany different analyses were conducted. Still, there weremore significant findings than would be expected by chanceand the results followed a relatively consistent pattern. Spe-cific social learning measures of barriers to adherence andnegative family interactions appear to be related to level ofregimen adherence among adolescents with diabetes.

ACKNOWLEDGMENTS:Appreciation is expressed to the Nor thDakota Affiliate of the American Diabetes Association forallowing us to collect these data at their annual summer campfor children, and especially to Fran Schindler and Drs. AlKenien, Juan Munoz, and George Johnson.

This study was supported by funds from NIH grant 28318from the National Institute of Arthritis, Diabetes, and Diges-tive Diseases.

Fromth Departmentsof Psychology and Food and NutritionNorth Dakota State University Fargo, North Dakota.Address reprint requests to Lorraine Schafer Departm entofPsychology North Dakota State University Fargo North Dakota58105 .

REFERENCES1 Danowski,T. S.,Ohlsen, P., andFisher,E. R.:Diabetic com-plications and their prevention or reversal. Diabetes Care1980;3:94-99.2Crofford, O. B.:Reportof theNational Commission on Dia-betes, 1:Thelong-range planto combat diabetes. Pub. No. (NIH)76-1018. U.S.Dept. of Health, Education, and Welfare. PublicHealth Service, National Institutes ofHealth,1976.3Cochran, H. A., Jr.,Marble,A. ,and Galloway,J. A.:Factorsinthesurvivalofpatients with insulin-requiring diabetesfor 50 yr.Diabetes Care 1979; 2:363-68.4Whi te , N. H., Waltman, S. R., Krupin, T , andSantiago,J. V.: Reversal ofneuropathic and gastrointestinal complicationsrelatedtodiabetes mellitusinadolescents with improved metaboliccontrol. Pediatrics 1981; 99:4 1-45 .5 Dunn, S. M., and Turtle, J. R.: The myth of the diabeticpersonality. Diabetes Care 1981; 4:640-46.6 Fisher, E. B., Jr., Delamater, A. M., Bertelson, A. D., and

Kirkley,B. G.:Psychological factors indiabetesand itstreatment.J. Consult. Clin. Psychol. 1982; 50:993 -1003.7 Hauser,S. T., andPollets, D.: Psychological aspects of diabetesmellitus:a critical review. Diabetes Care 1979; 2:227-32.8 Simonds,J. ,Goldstein, D.,Walker, B., andRawlings,S.: Therelationship between psychological factors and blood glucosereg-ulation in insulin-dependent diabetic adolescents. Diabetes Care1981; 4:610-15.9A nderson,B., andAuslander, W.:Researchondiabetesman-

agement and the family: a critique. Diabetes Care 1980; 3:696702.10Johnson, S. B.: Psychosocial factors in juvenile diabetes: areview.J. Behav. Med.1980; 3:95-116.11Skyler, J. S.: Psychological issues in diabetes. Diabetes Care1981; 4:656-57.12 Bandura, A. :Social Learning Theory . Englewood Cliffs,NewJersey, Prentice-Hall,1977.13Parcel,G. S., andBaranowksi,T : Social learning theoryandhealth education. Health Educ. 1981; 12:14-18.14Leventhal, H.: Behavioral medicine: psychology in health care.In Handbook of Health, Health Care, and Health Professions. Inpress. M echanic, D., Ed. New York, Free Press.15Dunbar, J. M., andStunkard, A. J.: Adherence todietanddrug regimen. n Nutrition, Lipids, andCoronary Heart Disease.Levy,R., Rifkind, B.,Dennis, B., andErnst,N.,Eds. New York,Raven Press,1979.

16Surwit,R. S.,Scovern,A. W., andFeinglos,M.N .:Theroleof behavior in diabetes care. Diabetes Care 1982; 5:337-42.17Williams, T. F, Martin, D. A., Hogan, M. D., Watkins,J. D., and Ellis, E. V.: The clinical picture of diabetic control,studied infour settings. Am. J. Public Health 1967; 57:4 41-5 1.18Goldfried, M. R., andD'Zurilla,T. J.: A behavioral-analyticmodelforassessing com petence. nCurrent TopicsinClinicalandCommunity Psychology, Vol. 1.Sp ielberger,C. D.,Ed. New York,Academic Press,1967.19Baranowski, T , Nader, P. R., Dunn, K., and Vanderpool,N . A.:Family self-help: promoting changes inhealth behavior.J.Comm un. 1982; 32:161-72 .20Schafer, L. C.,Glasgow,R. E.,and McCaul,K.D.: Increasingthe adherence of diabetic adolescents.J.Behav. Med. 1982; 5:3 53 -62 .21Moos,R., andMoos, B.:Atypologyof family social environ-ments. Fam.Process 1976; 15:35 7-72.22Moos,R., andMoos, B.:Family Environm ent Scale M anual.Palo Alto, California, Consulting Psychologists Press, 1981.23Anderson, B.,Miller,J. P.,A uslander,W., andSantiago,J.:Family characteristics of diabetic adolescents: relationshiptoinsulincontrol. Diabetes Care 1981; 4:586-94.24 Marquis, K. H., andWare, J. E., Jr.:Measures of diabeticpatient knowledge, attitudes and behavior regarding self-care: Sum-mary report. (Contract No. 200-77-0722) Santa Monica, Califor-nia: RAND, August,1979."Golds t e in , D. E., Peth, S. B.,England, J. D., Hess, R. L,and DaCosta,J.:Effects of acu te cha ngesinblood glucose on Hb Alc .Diabetes 1980; 29:623-28.26Bio-Rad. HemoglobinA lby Column Test. Bulletin 4224 (April)1-14,1982.27Bio-Rad. Hemoglobin A1 by Column Test. Bulletin 4234 (Au-gust) 1-7, 1981.28Hammons,G.T., Junger,K.,McDonald, J.M.,and Ladenson,J. H.: Evaluation of three minicolumn procedures for measuringhemoglobin A,. Clin. Chem. 1982; 28:1775-78.29Goldstein, D. E., et al.: Clinical application ofglycosylatedhemoglobin measurements. Diabetes 1982;31 (Suppl. 3):7O78.

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Adherence to IDDM Regimens Relationship to Psychosocial Variables and Metabolic Control