personality traits as predictors of adherence in adolescents with type i diabetes

Personality Traits as Predictors of Adherence in AdolescentsWith Type I Diabetesjcap_329 66..74

Kathleen Wheeler, MA, Audra Wagaman, MA, and David McCord, PhD

Kathleen R. Wheeler, MA, is a doctoral candidate in counseling psychology, Ball State University, Muncie, IN; Audra L. Wagaman, MA, is a doctoralcandidate in counseling psychology at Indiana University of Pennsylvania, Indiana, PA; David M. McCord, MA, is Professor and Head, Department ofPsychology, Western Carolina University, Cullowhee, NC, USA.

Search terms:Five-factor model of personality, juvenilediabetes, medical adherence, personality traits

Author contact:[email protected], with a copy to the Editor:[email protected]

doi: 10.1111/j.1744-6171.2012.00329.x

TOPIC: Diabetes is a serious, chronic illness with long-term implications for healthand lifestyle. Significant differences in health outcome may be achieved as a result ofthe degree of adherence to recommended diabetes management regimens. Adher-ence is a particularly challenging issue with adolescents with diabetes.PURPOSE: The present study examined the association between primary persona-lity traits and adolescent adherence to prescribed diabetes management regimens.SOURCES: A measure of the five-factor model of personality was administered to asample of adolescents with insulin-dependent diabetes mellitus. Five self-reportedindicators of adherence were assessed: blood glucose monitoring, insulin adminis-tration, diet, exercise, and most recent glycosylated hemoglobin (HbA1c) level.CONCLUSIONS: Results revealed a pattern of significant correlations between theConscientiousness and Neuroticism personality domains and one or more self-reported adherence behaviors. In addition, correlations were also found betweenone facet of Extraversion and one facet of Agreeableness. These suggestive results, ifreplicated in larger studies, provide useful information to clinicians as they designand monitor individualized diabetes management regimens for adolescents.

Patient adherence is defined as active, voluntary behaviorsin which an individual engages so as to improve, maintain,or prevent further deterioration of his or her health status(Pidgeon, 1989; Sawyer & Aroni, 2003). Adherence to amanagement regimen is critical to the overall health ofpatients, slowing the harmful progression of chronic diseaseand avoiding future health complications (Lynch et al.,1992; Sawyer & Aroni, 2003; Stanton, 1987). Unfortunately,many patients do not engage in the necessary behaviorsrequired to maintain and promote health. In fact, noncom-pliance to prescribed treatments is a chronic problemamong many individuals suffering from chronic diseases,such as diabetes, asthma, renal disease, and coronary heartdisease (Kavanagh, Gooley, & Wilson, 1993; Mawhinneyet al., 1993; Sawyer & Aroni, 2003). Numerous studies haveshown that only 50% of the chronically ill populationadheres to their prescribed management regimen, whileother studies have reported even more dramatic noncompli-ance rates (Pidgeon, 1989; Sawyer & Aroni, 2003). Deter-mining which variable or variables predict adherence iscritical because it would allow primary care providers tointervene before patients become nonadherent and engagein risky health behaviors.

Many researchers have attempted to identify variables thatpredict adherence in chronically ill patients, such as cardiac,asthmatic, epileptic, and dialysis patients. Two of the mostcommonly used inventories to identify variables that predictadherence include the Minnesota Multiphasic PersonalityInventory (MMPI) and health locus of control inventories.Although a few studies have shown an association betweenMMPI scores and adherence behaviors (Blumenthal,Williams, Wallace, Williams, & Needles, 1982; Mawhinneyet al., 1993), in general, results from numerous studieseither show no relationship between MMPI scores andadherence behaviors or have not withstood replicationattempts (Dodrill, Batzel, Wilensky, & Yerby, 1987; Wiebe &Christensen, 1996).

Results from studies examining the predictive ability ofhealth locus of control scores on adherence have been incon-sistent. Various studies, such as those conducted by Olden-burg, MacDonald, and Perkins (1988), Poll and De-Nour(1980), and Stanton (1987), have shown that chronically illpatients with an internal locus of control have greater adher-ence than patients without an internal locus of control.However, other research has found no such relationshipbetween the two variables. Such research includes studies

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Journal of Child and Adolescent Psychiatric Nursing ISSN 1073-6077

66 Journal of Child and Adolescent Psychiatric Nursing 25 (2012) 66–74© 2012 Wiley Periodicals, Inc.

conducted by Brown and Fitzpatrick (1988) and Witenberget al. (1983). The lack of consistency in the data and results oflocus of control research may exist because an individual’slocus of control possibly indirectly, rather than directly,affects adherence behavior (Wallston, 1992).

While many researchers have studied adherence in chroni-cally ill individuals that are not diabetic, numerous otherresearchers have attempted to discover a relationship betweenspecific predictive variables and adherence in diabeticpatients. Studies have been conducted examining Type Abehaviors, self-efficacy, family variables, and locus of control.Overall, the predominant pattern of results suggests a predic-tive association between self-efficacy and family values andadherence (Anderson, Auslander, Jung, Miller, & Santiago,1990; Cox et al., 1984; Eaton et al., 1992; Kavanagh et al.,1993; Rhodewalt & Fairfield, 1990). However, studies examin-ing the associations between Type A traits and locus ofcontrol have produced inconsistent results (Eaton et al., 1992;Murphy, Thompson, & Morris, 1997; Schlenk & Hart, 1984;Schneider, Friend, Whitaker, & Wadhwa, 1991).

Note that several of the predictor variables in the studiesreviewed above may be classified as personality traits, or trait-like personal characteristics (e.g., Type A behavior, locus ofcontrol, self-efficacy). Generally, these constructs refer tocharacteristics internal to the individual, rather than the situ-ation, and are broadly labeled “individual differences.” Thus,the research question becomes, “are there any individual dif-ferences that significantly predict adherence to a chronicdisease management regimen?” A major obstacle to research-ers (in many fields of study) has been the absence of a broad,comprehensive framework or theory of individual differencesin humans. Instead, psychology has offered a listing of varioushistorical personality theories, which have tended to be ratio-nal rather than empirical, most often sorely lacking in empiri-cal validity data, and conceptually disconnected from eachother. Consider the fact that the “psychodynamic” theories ofFreud and his followers, the humanistic theories of Maslowand Rogers and others, and the behavioristic theories ofWatson, Skinner, and others, despite being mutually incom-patible, tend to hold equal status in traditional textbooks ofpersonality theory. These unscientific“theories”of individualdifferences make entertaining reading but have had little tooffer the researcher interested in predicting important typesof behavior.

Fortunately, a paradigm shift has occurred within the fieldof psychology over the past 25 to 30 years, specifically, theemergence of a broad, comprehensive perspective on indi-vidual differences referred to as the five-factor model (FFM)of personality. The FFM is a trait approach that is very firmlygrounded in empirical data. Very briefly, the FFM is the cul-mination of work initiated with the “lexical hypothesis”(Allport & Odbert, 1936; Cattell, 1944), which is the idea thatany important personality trait must logically have some

verbal language representation; thus, to oversimplify a bit, allrelevant personality terms must be included in a comprehen-sive dictionary for a given language. Beginning with a full listof 17,953 individual trait terms drawn from the Oxfordunabridged English dictionary, researchers systematicallyreduced the list to manageable numbers of broad representa-tive terms, obtained ratings on thousands of subjects, andthen through numerous factor analytic studies over thedecades determined that in almost all cases, five broad factorsemerged from the data. These factors are all bipolar dimen-sions, with a high end and a low end, exhibiting a bell-shapednormal distribution in the population. The commonly usedtrait name, or letter, refers to the high end of the dimension,generally speaking. The first, strongest trait that accounts formost variance in human personality is Extraversion (versusintroversion); envisioning a bell-shaped distribution of thistrait, one can consider extreme extraverts to the right,extreme introverts to the left, with most people falling some-where near the middle of the distribution. This E factor mayalso be thought of as enthusiasm, or energy (Gosling & John,1999). Factor 2 (in terms of variance accounted for) is Agree-ableness (versus antagonism), which may also be thought ofas altruism or affection. The third factor is Conscientiousness(versus impulsivity), control or constraint. The fourth factoris N, for Neuroticism, nervousness, or, probably most accu-rate, negative affectivity. Finally, the fifth and least coherent,clear factor is Openness to Experience, also thought of asopen-mindedness or originality (Gosling & John, 1999).

The FFM also recognizes that there are, of course, nar-rower, more specific traits underlying these broad domains,and these are customarily referred to as “facets.” For example,the facets of Extraversion include friendliness, gregarious-ness, assertiveness, activity level, excitement seeking, andcheerfulness. Facets of Agreeableness include trust, morality,altruism, cooperation, modesty, and sympathy. Facets ofConscientiousness include self-efficacy, orderliness, dutiful-ness, achievement striving, self-discipline, and cautiousness.Facets of Neuroticism include anxiety, anger, depression, self-consciousness, impulsiveness, and vulnerability. Facets ofOpenness to Experience include imagination, artistic inter-ests, emotionality, adventurousness, intellect, and liberalism(Costa & McCrae, 1992).

The history of the FFM reveals roots in empirical datareported in the early 1900s (Garnett, 1919; Webb, 1915), withremarkably clear factor analytic results in the 1930s and 1940s(e.g., Cattell, 1944). However, the FFM did not rise to full vis-ibility until two psychologists at the National Institutes ofAging, Paul Costa and Robert McCrae, began a stunninglyprolific and productive research program around 1980. By theearly 1990s, the FFM was rapidly pervading many fields ofpsychological research, and at this point in time, there is vir-tually no debate that it has become the dominant, almost uni-versally accepted framework for the study of individual

Personality Traits as Predictors of Adherence in Adolescents With Type I Diabetes

67Journal of Child and Adolescent Psychiatric Nursing 25 (2012) 66–74© 2012 Wiley Periodicals, Inc.

differences in humans (Gosling & John, 1999; Marsh et al.,2010). A thorough review of the FFM is well beyond the scopeof this paper, as it would now involve thousands of publishedarticles. For readers wanting more, McCrae and John (1992)provide a formal, scholarly introduction to this importantmodel of personality. Alternatively, Gosling (2008) hasrecently published a book aimed at a popular audience that ishighly readable and entertaining, yet scientifically precise indescribing how one can discern the five-factor personalitytraits of other people by examining their “stuff” (e.g., dormi-tory room, office desk, bathroom cabinet, trash cans, musiccollection, Facebook page, etc.).

With the emergence of the FFM,this comprehensive frame-work of human personality has been used to guide research inhealth psychology in a number of recent research projects.However, studies focusing on the predictive value of the FFMfor adherence behaviors have thus far primarily researchedonly two domains, Conscientiousness and Neuroticism.

Results from many studies have demonstrated that theConscientiousness domain significantly and reliably pre-dicted the practice of wellness behaviors, health maintenance,and adherence (Booth-Kewley & Vickers, 1994; Brickman,Yount, Blaney, Rothberg, & De-Nour, 1996; Christensen &Smith, 1995; De-Nour & Czaczkes, 1972; Rosenbaum &Smira, 1986). However, studies examining the effect Neuroti-cism has on chronic illness adherence in the framework of theFFM have yielded less consistent results. In the study con-ducted by Christensen and Smith, Neuroticism was not a sig-nificant predictor of medication or dietary adherence. Incontrast, results from the study conducted by Brickman et al.showed that both high and low Neuroticism scores were cor-related with earlier diabetes-related renal deterioration, sug-gesting that individuals with moderate Neuroticism scoreswere more likely to adhere. Another study conducted byWiebe, Alderfer, Palmer, Lindsay, and Jarrett (1994) also sug-gests that a relationship exists between Neuroticism andadherence.

Despite the existing research on the personality domains ofConscientiousness and Neuroticism, there is a paucity ofresearch on the remaining three personality domains: Extra-version, Openness, and Agreeableness. Furthermore, researchconsistently shows that individuals in the adolescent agerange adhere less frequently to their diabetes managementregimens than any other age group; therefore, it is critical todetermine what variables affect adolescent adherence in aneffort to improve quality of life and prevent health complica-tions (Anderson et al., 1990; Murphy et al., 1997; Pidgeon,1989). The purpose of the present study was to examine theassociations between broad personality traits and adolescentadherence to diabetes management regimens. Specifically,correlations were computed between all five personalitydomains (Neuroticism, Extraversion, Openness, Agreeable-ness, and Conscientiousness) and five frequently used mea-

sures of diabetic adherence: blood glucose monitoring,insulin administration, diet, exercise, and self-reported glyco-sylated hemoglobin (HbA1c) levels. Facet-level correlationswere also computed. Based on previous research, we expectedthat the Conscientiousness domain and its underlying facetswould be most strongly associated with the various adherencebehaviors, in the positive direction. We also anticipated anegative correlation between the Neuroticism domain and itsunderlying facets with adherence behaviors. Although theextant literature did not provide a basis for making predic-tions regarding the other domains, we did anticipate that ourexploratory analyses could reveal associations between Extra-version traits, and possibly Agreeableness traits, and adher-ence behaviors that might be unique to the adolescent stage ofdevelopment.

Method

Participants

Twenty-eight adolescents with insulin-dependent diabetesmellitus, ages 13–18, participated in the study. Of these 28participants, 20 (71%) were female and eight (29%) weremale. Twenty-five (88%) adolescent participants were Cauca-sian, while the three remaining participants identified them-selves as Asian/Asian American/Pacific Islander (4%),AfricanAmerican (4%), or Hispanic/Latino (4%). The adolescents’mothers also participated. The participants who volunteeredfor the study via the Internet were from 14 different statesthroughout the country, one American territory and oneforeign country.

Measures

Adolescent participants completed the M5-336 Question-naire (McCord, 2002), a measure of the FFM of personality.The items on this questionnaire are drawn from Goldberg’s(1999) International Personality Item Pool and provide aproxy for the Revised NEO Personality Inventory (NEO-PI-R; Costa & McCrae, 1992). The questionnaire contains 336items designed to assess the five domains of personality (Neu-roticism, Extraversion, Openness,Agreeableness, and Consci-entiousness) in an individual. The items also assess the sixspecific facets comprising each domain. Items are scored on a5-point Likert-type scale designed to reflect the participant’sopinion for each item with scores ranging from 1 (very inac-curate) to 5 (very accurate). The five domains and 30 facetscales of the M5-336 exhibit high internal consistency (meanCronbach’s a = 0.80 across all 30 facets) as well as very highcorrelations with the corresponding scales of the NEO-PI-R(mean corrected correlation between M5 facet and NEO-PI-R facet is 0.94). For more detailed reliability and validitydata, see International Personality Item Pool (2001). Valida-



tion studies support the usefulness of this measure across allfive personality domains (e.g., Hambrick & McCord, 2010;Proctor & McCord, 2009a, 2009b; Unruh & McCord, 2010).

The adolescent participants also completed an adherencequestionnaire, constructed by the investigators, whichassessed their adherence to their prescribed diabetes manage-ment regimen over the previous 6 months. The adherencequestionnaire is presented in its entirety in Table 1. The firstfour items on the questionnaire measured, respectively, fourcomponents of adherence: blood glucose monitoring, insulinadministration, diet, and exercise. Questions 5 through 7solicited qualitative data that might guide future research.Question 8 asked the respondent to enter their most recentHbA1c level. It was our original intent to use the quantitativeitems on this questionnaire to construct a scale yielding oneoverall adherence score, which would be very useful in statis-tical analyses. We had hoped to obtain data from over 100adolescents with diabetes, which could provide sufficient datafor at least a preliminary scale. However, with ultimately only28 sets of data, scale construction was not feasible. Forexample, our efforts to base a scale on the most clearly quan-tifiable items 1–4 yielded one with unacceptably low internalreliability. The exercise question (#4) did not correlate wellwith the first three, but removing it still resulted in animprovement in Cronbach’s a only to 0.34. On the otherhand, the first four items themselves have high face validityand are clearly the key components of adherence reflectedthroughout the literature on diabetes management. Thus, weproceeded with data analysis based on bivariate correlationsbetween our key personality variables and the quantitativeadherence variables as separate entities.

Design and Procedure

A brief synopsis of this study and the experimenter’s contactinformation were posted on http://www.childrenwithdiabetes.org. This Web site allows researchers to recruit partici-pants by posting summaries of clinical studies they are con-ducting. After viewing the synopsis, adolescents and parentsinterested in volunteering for this study contacted the experi-menter via email. The experimenter then mailed to the par-ticipants a packet containing an instruction sheet, a consentform, the adherence questionnaire, the M5-336 Question-naire, and a self-addressed and stamped return envelope.After completing the forms, the participants mailed thepacket back to the experimenter.

Analyses

Correlation coefficients were computed between each of thefive broad personality domains and each individual adher-ence item. In addition, correlations were computed for the sixfacets underlying each broad domain and all adherence mea-

sures. Due to the large number of correlations being calcu-lated, we adopted a more stringent level of p < .01 to assessstatistical significance. Even with this conservative probabilitylevel, the possibility of Type I error exists, and these resultsshould certainly be seen as preliminary, to be interpreted withcaution.

Results

As predicted, significant positive correlations were foundbetween the Conscientiousness domain and two of the fiveadherence variables, and a significant negative correlationwas found between the Neuroticism domain and one of theadherence variables. In addition, a significant correlation wasfound between Extraversion and one of the adherence vari-ables. At the facet level, significant patterns of associationsbetween adherence factors and personality traits were foundin four of the five major domains, as will be described below.See Tables 2 and 3 for the domain-level and facet-level corre-lations, respectively.

Conscientiousness

The Pearson correlation between the overall Conscientious-ness domain and the diet variable (AQ3) was significant andpositive (r = 0.521, p = 0.005). The correlation between Con-scientiousness and the insulin administration variable (AQ2)was also significant and positive (r = 0.488, p = .009) (seeTable 2).

At the facet level (see Table 3), three narrow personalitytraits were significantly associated with insulin admini-stration (AQ2), including C1—Self-efficacy (r = 0.480,p = .010), C5—Self-discipline (r = 0.482, p = .009), andC6—Cautiousness (r = 0.517, p = .005). In addition, two ofthe Conscientiousness facets were significantly correlatedwith the AQ3 diet variable, including C5—Self-discipline(r = 0.566, p = .002) and C6—Cautiousness (r = 0.509,p = .007).

Neuroticism

The correlation between the overall Neuroticism domainscore and the insulin administration variable (AQ2) was sig-nificant and negative (r = -0.505, p = .006). At the facet level,two facets were associated with insulin administration(AQ2), including N2—Anger (r = -0.542, p = .003) andN3—Depression (r = -0.498, p = .007). One Neuroticismfacet, N5—Impulsiveness, was significantly correlated withthe AQ3 diet variable (r = -0.528, p = .005).

Extraversion

The correlation between the overall Extraversion domainscore and the exercise variable (AQ4) was positive and



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significant (r = 0.520, p = .005). At the facet level,E3—Assertiveness was also significantly correlated with exer-cise (r = 0.516, p = .005).

Agreeableness

The overall Agreeableness domain score did not correlate sig-nificantly with any of the adherence variables using the strin-gent probability level selected for these analyses. At the facet

level, one significant correlation occurred, betweenA2—Morality and the insulin administration variable AQ2(r = 0.603, p = .001).

Discussion and Implications for Practice

Adherence to a medical regimen is critical to the overall healthof patients (Lynch et al., 1992; Sawyer & Aroni, 2003; Stanton,1987). Unfortunately, noncompliance to prescribed treat-

Table 2. M5 Domain-Level Correlations with Self-Reported Adherence Scores

Adherence measures N—Neuroticism E—ExtraversionO—Openness toexperience A—Agreeableness C—Conscientiousness

AQ1—Glucose Monitoring -0.012 0.327 0.101 -0.190 -0.084AQ2—Insulin Administration -0.505a 0.151 0.051 0.460 0.488a

AQ3—Diet -0.307 0.037 0.133 0.434 0.521a

AQ4—Exercise -0.267 0.520a 0.302 -0.028 0.051AQ8—HbA1c (Self-report) 0.289 0.081 0.038 -0.327 -0.337

aCorrelation is significant at the .01 level (two-tailed).

Table 3. M5 Facet-Level Correlations with Self-Reported Adherence Scores

M5 FacetsGlucosemonitoring

Insulinadministration Diet Exercise HbA1c

N1—Anxiety -0.083 -0.441 -0.220 -0.092 0.190N2—Anger 0.285 -0.542a -0.400 -0.083 0.330N3—Depression -0.149 -0.498a -0.077 -0.143 0.200N4—Self-Consciousness -0.098 -0.133 -0.070 -0.428 0.056N5—Impulsiveness 0.208 -0.348 -0.528a -0.135 0.434N6—Vulnerability -0.196 -0.378 -0.211 -0.367 0.084E1—Friendliness 0.134 0.263 0.216 0.357 -0.058E2—Gregariousness 0.309 0.072 -0.084 0.448 0.108E3—Assertiveness 0.408 0.090 -0.008 0.516a 0.140E4—Activity Level 0.155 0.330 0.301 0.472 -0.115E5—Excitement Seeking 0.309 -0.146 -0.113 0.413 0.114E6—Cheerfulness 0.135 0.156 -0.066 0.170 0.140O1—Imagination 0.184 -0.183 -0.117 0.230 0.093O2—Artistic Interests 0.052 0.009 0.200 0.148 -0.042O3—Emotionality -0.185 0.128 0.376 0.176 -0.242O4—Adventurousness 0.045 0.089 0.120 0.426 0.022O5—Intellect 0.136 0.005 0.031 0.226 0.103O6—Liberalism 0.114 0.210 0.006 0.091 0.150A1—Trust -0.139 0.382 0.241 0.038 -0.334A2—Morality -0.065 0.603a 0.430 0.016 -0.229A3—Altruism -0.311 0.225 0.392 0.037 -0.216A4—Cooperation -0.159 0.324 0.462 -0.139 -0.343A5—Modesty -0.120 0.130 0.136 0.016 -0.308A6—Sympathy -0.009 0.205 0.122 -0.098 -0.002C1—Self-Efficacy -0.008 0.480a 0.394 0.069 -0.159C2—Orderliness -0.124 -0.018 0.087 -0.033 -0.088C3—Dutifulness -0.192 0.419 0.390 0.044 -0.315C4—Achievement Striving 0.093 0.382 0.484 0.324 -0.326C5—Self-Discipline -0.050 0.482a 0.566a -0.022 -0.214C6—Cautiousness -0.071 0.517a 0.509a -0.060 -0.329

aCorrelation is significant at the .01 level (two-tailed).



ments is a chronic problem among many individuals suffer-ing from chronic diseases, and the nonadherence rate isespecially alarming among adolescent diabetics, as most ado-lescents do not adhere to their prescribed diabetes manage-ment regimen (Anderson et al., 1990; Murphy et al., 1997;Pidgeon, 1989). An improved understanding of factorsrelated to compliance, and an ability to predict compliance ina given patient, can enhance the effectiveness of the patient’soverall health plan. This study examined the relation betweenthe “Big 5” personality domains (Neuroticism, Extraversion,Openness, Agreeableness, Conscientiousness), plus the sixnarrow facets underlying each domain, and adolescent adher-ence (blood glucose monitoring, insulin administration, diet,exercise, and self-reported HbA1c) to diabetic regimens.

Examination of each personality domain revealed interest-ing trends. Conscientiousness was shown to be most stronglyrelated to adolescents’ self-report of adherence. The moreconscientious an adolescent was, the more he or she adheredoverall to the diabetic regimen. These findings are most spe-cific with regard to dietary and insulin regimens. At the facetlevel, the subfactors of C1—Self-efficacy, C5—Self-discipline, and C6—Cautiousness exhibited strongest asso-ciations with adherence behaviors. These findings are quiteconsistent with our predictions as well as with other literaturein this area and highlight the fact that assessing an adolescentpatient’s level of Conscientiousness may yield importantinformation in the development of an individualized healthmaintenance regimen.

Also as predicted, Neuroticism was significantly related toadherence. The more neurotic an adolescent was, the less heor she adhered to his or her overall diabetes regimen.Although the correlation with insulin administration was theonly statistically significant correlation at the domain level,there were trends evident with regard to diet, exercise, andself-reported HbA1c. Strong correlations were foundbetween the anger and depression facets and the insulinadministration variable, and between impulsiveness and thediet variable. These findings are also consistent with other lit-erature, although, as noted earlier, there are some studies thatfailed to find associations between this domain and adherencebehaviors.

New to this study are results showing that both Extraver-sion and Agreeableness were related to adherence, with posi-tive correlations in both cases. With regard to Extraversion,the overall domain score was significantly correlated withAQ4, the exercise variable. Facet-level data showed that thiscorrelation appears to be based largely on the strong associa-tion between exercise and the E3—Assertiveness facet.Although none of the correlations between the overall Agree-ableness domain score and the five adherence variablesreached the level of statistical significance established for thisstudy, there was one significant positive facet-level associa-tion, between facet A2—Morality and the insulin administra-

tion variable (AQ2). Adolescents who were morestraightforward, honest, and cooperative were more likely tofollow their medication regimen.

In retrospect, one drawback to the present study is themethodology utilized to assess adherence. As noted above, wehad hoped to collect enough data to refine an adherence scaleas an aggregate variable, but we were unable to do so. Theadherence questionnaire items clearly need improvement.For example, Conscientiousness is highly correlated withinsulin administration, but not with blood glucose monitor-ing, although in reality these behaviors should be concordant.Development of a reliable, valid adherence assessment instru-ment, specific to diabetes management in adolescents, wouldbe valuable in future research.

Perhaps the single most significant weakness of the presentstudy is the disappointing sample size. Although over 100families provided initial indications of willingness to partici-pate, only 67 actually signed formal consent, and, ultimately,only 28 completed data packets were returned. Subsequentstudies should employ a much larger sample that is moregender-balanced and otherwise diverse. The data collectionmethod used in this study also introduced a selection bias,which should be avoided in future designs.

The present study is viewed as an initial foray into animportant area of research, and results should certainly beseen as preliminary, to be interpreted cautiously. Neverthe-less, these early findings have significant practical implica-tions for the understanding of adherence-related issues inadolescents with diabetes. Adolescents are less likely to adhereto their prescribed diabetes management regimen than at anyother stage of their life. As it is commonly understood thatadherence to a prescribed health regimen can improve, main-tain, or prevent further deterioration of one’s health, deter-mining which variables affect adolescent diabetic adherenceto a prescribed treatment regimen is paramount. Healthcareprofessionals should consider using five-factor personalityassessments when working with adolescents, especially thosediagnosed with chronic illnesses that require a rigorous man-agement regimen such as diabetes. Patients with lower thanaverage Conscientiousness scores are likely going to be lesscompliant and, thus, may need more monitoring, follow-up,and enhanced care advice, such as the use of electronic alarmsand reminders on their cell phones, and so forth. Adolescentswith higher than average N scores are also likely to be non-compliant, but for different reasons, having to do with anxietyand depression. They may need concomitant attention toemotional disorders in order to enhance adherence. The mostwidely used commercially available instrument measuringthe FFM is the NEO-PI-R (Costa & McCrae, 1992). An excel-lent public domain measurement tool has been developed byJohn A. Johnson at Pennsylvania State University; short andlong forms of this instrument, the International PersonalityItem Pool NEO (IPIP-NEO), are available through his Web



site (http://www.personal.psu.edu/j5j/IPIP/). Through thisWeb site, one could actually have an adolescent patient takethe test online, in about 15 min, and then interpretive resultsand personality domain and facet scores are immediatelyavailable.

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