- Email: [email protected]
Diet self-management and readiness to change in underserved adults with type 2 diabetes
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
Contents lists available at ScienceDirect
Primary Care Diabetes journal homepage: http://www.elsevier.com/locate/pcd
Original Research
Diet self-management and readiness to change in underserved adults with type 2 diabetes Holly Knight, Barbara Stetson ∗ , Sathya Krishnasamy, Sri Prakash Mokshagundam University of Louisville, United States
a r t i c l e
i n f o
a b s t r a c t
Article history:
Aim: Dietary assessment in diabetes may be enhanced by considering patient-centered per-
Received 3 July 2014
spectives and barriers to change within IDF guidelines. Consideration of readiness to change
Accepted 28 September 2014
(RTC) diet in underserved samples may guide future interventions in high risk populations.
Available online 22 October 2014
This study assesses the utility of a rapid assessment of RTC diet in a medically underserved sample.
Keywords:
Method: Participants were 253 Black (43.7%) and White (55.1%) American adults with type
Diabetes
2 diabetes [M age = 57.93 (11.52); 60.5% female; 19% below the US poverty threshold]. Par-
Self-care
ticipants were recruited at medical clinics and completed validated self-report measures
Medically Underserved
assessing diabetes knowledge, self-efficacy and dietary behaviors and barriers by RTC.
Self-report measures
Results: Stage-based comparisons identified significant differences in diabetes and dietary domains: participants in the Action stage endorsed fewer behavioral dietary barriers (p < .001), more frequent dietary problem-solving (p < .001), and greater diabetes self-efficacy (p < .001) than participants in the Contemplation and Preparation stages. Women were more likely to be in the Preparation stage and beyond (p < .05). Conclusions: Findings highlight the clinical utility of a brief measure of RTC in understanding patient perspectives toward dietary behaviors in a medically underserved sample. The impact of gender on RTC diet warrants further exploration. © 2014 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.
1.
Introduction
Diabetes affects 347 million people worldwide [1] and is projected to be the 7th leading cause of global death by 2030 [2]. Type 2 diabetes disproportionately effects low-income and underserved populations and is associated with worse outcomes and higher comorbidity rates [3,4]. The trajectory
of type 2 diabetes is heavily determined by health behavior choices, with the International Diabetes Federation (IDF) global guidelines recommending the maintenance of HbA1c levels below 6.5%, dietary modification, exercise engagement and weight loss for the control and improvement of diabetic outcomes [5]. Enhancement of self-management behaviors plays an integral part in proper blood glucose control and has emerged as a focal point of care for health care providers.
∗ Corresponding author at: Department of Psychological and Brain Sciences, 317 Life Sciences Building, University of Louisville, Louisville, KY 40292, United States. Tel.: +1 502 852 2540; fax: +1 502 852 8904. E-mail address: [email protected] (B. Stetson).
http://dx.doi.org/10.1016/j.pcd.2014.09.007 1751-9918/© 2014 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.
220
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
Poor diet is one of the most preventable causes of death in the US and dietary dysregulation and barriers to healthy eating present major problems for the improvement of individual glycemic control [6]. The health care encounter offers opportunities to promote a healthy diabetes diet however, some patients may resist making dietary changes. Understanding receptivity to dietary self-management is particularly relevant in underserved samples who often have limited access to diabetes education and endorse poorer awareness of diabetesmanagement strategies [4,7]. While health providers may recommend dietary plans, individual patients may not be ready to accept or implement these changes at the time of the medical encounter. By understanding patient perspectives, promotion of diet changes may be enhanced. When assessing self-management behavior change, the IDF suggests use of a framework emphasizing knowledge about lifestyle modification, problem-solving, and individualization of self-management goals and needs [8]. However, research has yet to address how the IDF recommended components of knowledge, problem-solving barriers to change and self-management needs present within a diverse, medically underserved population. A wealth of research has focused on the application of multiple health behavior models to self-management behaviors [9,10]. One such model, the transtheoretical model (TTM), utilizes a staged approach to understand how individual differences in readiness to change health behaviors unfold [11]. This model offers substantial opportunities for understanding patient perspectives at the time of medical encounters. From this perspective, individuals move toward behavior engagement through five sequential stages of change: Precontemplation, defined by a lack of intention to make behavioral changes; Contemplation, a consideration of changing health behaviors; Preparation, preparing to and making small changes; Action, active engagement in behavior change and Maintenance, continuing behavior change over time [11]. The TTM conceptualizes individual
differences in readiness to change behaviors and incorporates self-efficacy (e.g., confidence to overcome barriers) as a prominent construct aiding movement between the stages [11]. An extensive literature supports the use of staged approaches to dietary interventions [12–14]. The present paper aims to assess underserved patient perspectives toward dietary change within the IDF selfmanagement framework. Brief, clinically focused measures assess factors influencing dietary change, including diabetes knowledge, current diet self-management practices, dietary problem-solving and perceived barriers to dietary change across the TTM stages of change. The contribution of diabetes self-efficacy, as emphasized within the TTM, to dietary change is assessed to better understand influential factors in individual readiness to change diet. A final goal is to determine the utility of brief clinical measures in the assessment of self-management behaviors and readiness to change, with the potential for guidance toward stage-based interventions in underserved clinical samples.
2.
Methods
2.1.
Study participants
Participants were recruited from health department diabetes education programs and university-based medical clinics in a large southeastern U.S. city. All recruitment sites are accessible to underserved, low-income adults. Eligibility requirements were met if the individual was an adult diagnosed with type 2 diabetes and was able to read, write and speak English and had received health department brochures or attended self-management classes. A brief screening either in person or over the phone was administered. See Fig. 1 for recruitment data.
Total Invited to Parcipate N=431
Not eligible
Declined parcipaon
N=34 (7.9%)
N=81 (18.8%)
Consented and given packet N=416 (73.3%)
Completed Study
Non completer
N=245
N=162 (32% of those consented)
(61% of those consented) (59% of total invited)
Fig. 1 – Study recruitment flow chart.
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
2.2.
Materials
The self-report assessment packet contained questions assessing demographics, diabetes history and knowledge, self-care, dietary behaviors and barriers and readiness to change dietary routine. Socioeconomic level was assessed using self-report questions on education, income, employment and household size. Community-level socioeconomic status was assessed using the United States Census tract information [15]. All procedures were approved by the University Human Subjects Protection Program.
2.2.1.
Dietary behaviors and barriers
Personal Diabetes Questionnaire (PDQ). The PDQ is a brief, patient-centered self-report questionnaire assessing general diabetes self-care in four behavioral domains: (1) nutritional management, (2) blood glucose monitoring, (3) medication adherence and (4) physical activity. The PDQ also assesses perceptions and barriers related to diabetes self-care and readiness to change [16]. Total scores were assessed as a sum of scaled individual barrier scores for each dietary domain. In a validation study, the PDQ demonstrated good internal consistency (Cronbach’s ˛ = 0.650–0.834) across domains [16]. Significant correlations were observed between PDQ subscales, HbA1c levels and BMI (p ≤ 0.001) [16]. The Flesch–Kincaid Readability Test [17] demonstrated readability at a 6th grade level [16]. Dietary constructs measured using the PDQ included current level of dietary self-management, dietary problemsolving, and perceived barriers to dietary change. Dietary self-management practices were assessed using items such as “During the past 3 months, how often did you use sugar-free or reduced sugar products?” Dietary problem-solving assessment utilized items including “During the past 3 months, how often did you use information about the grams of carbohydrates in foods to make decisions about what or how much to eat?” and reflected behavioral choices that aid HbA1c control. Perceived dietary barriers incorporated items including “During the past 3 months, how often have you experienced eating problems because of hunger or food cravings?” and described barriers to healthy diet choices. Stage of change. Dietary stage of change was assessed using a single item on the PDQ to determine whether a brief indicator of stage of change can be integrated into assessments in clinical settings. The item “Are you currently trying to follow a diet plan in order to better control your blood glucose? If you are not currently following a diet plan or meal plan to better control your blood glucose, is this something you plan to do in the future?” was used to differentiate participants by their dietary stage of change. A description of the criteria for stage of change assessment using this item is presented in Fig. 2. For the purpose of analysis, individuals were categorized by dietary stage of change and group differences were assessed.
2.2.2.
Diabetes history
Diabetes History Questionnaire (DHQ). Basic medical and demographic information related to diabetes were assessed using the DHQ [18].
2.2.3.
221
Diabetes knowledge
Diabetes Knowledge Test (DKT). The DKT was used to assess general diabetes knowledge including the symptoms associated with low or high blood sugar and normal fasting blood sugar levels [19,20]. The test has been administered to clinical populations and demonstrates good internal consistency (Cronbach’s ˛ = .70). The total number of correct items on the DKT was utilized as an estimate of overall diabetes knowledge.
2.2.4.
Diabetes self-efficacy
Diabetes Self-Efficacy Scale (DSES). The DSES was used to assess self-efficacy related to diabetes self-management behaviors [21]. The DSES has been validated within clinical populations with good internal consistency (Cronbach’s ˛ = .828) [22]
2.3.
Socioeconomic indicators
Census tract data was obtained from the United States Census Bureau’s website and was based on 2000 census data [15]. These tracts or subdivisions of a county represent a cluster of approximately 4000 individuals who have similar characteristics such as income, status and living conditions.
2.4.
Statistical analyses
Analyses were conducted using SPSS® Version 21. Twotailed tests were used for all analyses with an alpha level of .05 used as the criterion for statistical significance. Demographic characteristics and readiness to change were defined using descriptive statistics. Between-group differences were assessed using one-way ANOVA and nonparametric Kruskal–Wallace tests. Tukey’s HSD post hoc tests were used to elucidate significant ANOVA findings and Bonferroni’s corrections were applied.
3.
Results
3.1.
Readiness to change diet
Demographic and stage of change characteristics are presented in Table 1. Given the small quantity of participants within the Precontemplation stage, these results were excluded from the analyses. In regard to the IDF recommendations; the most frequently endorsed self-management practice was substituting low-calorie sweetener for sugar at least 4–6 times per week, reported by 72.2% of participants. The most frequently reported problem-solving behavior was controlling portion sizes, with 59.6% engaging in this 4–6 times per week. The most common barrier to diet change was battling with daily cravings, with 32.1% of individuals experiencing this barrier at least 4–6 times per week. Non-parametric analysis of the PDQ item assessing diet readiness for change identified stage-based differences for gender. Women were further along the stages of change than men: 76.98% of women in preparation or beyond compared to 60.21% of men (2 = 8.197, p = .017). The remaining demographic variables and comorbid illnesses did not differ based on dietary stage of change.
222
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
“Are you currently trying to follow a diet plan in order to better control your blood glucose? If you are not currently following a diet plan or meal plan to better control your blood glucose, is this something you plan to do in the future?”
“No I have no plans right now for starting to follow a diet or meal plan”
Precontemplation
“I plan to start within the next 6 months”
Contemplation
“I plan to start within the next month”
Preparation
“I am already following a diet or meal plan”
Action
Maintenance
Fig. 2 – Stage of dietary change assessed using items from the Personal Diabetes Questionnaire (PDQ) [16].
Diet behaviors and type 2 perceptions by stage of change Univariate analyses were used to describe dietary selfmanagement, problem-solving, perceived barriers and diabetes self-efficacy and knowledge across each stage of change (see Table 2). Stage-based differences were observed in the frequency of reported dietary self-management practices (F = 19.26, p < .001), the frequency of dietary problem solving (F = 22.22, p < .001), the quantity of perceived dietary barriers (F = 8.71, p < .001) and self-efficacy toward diabetes self-management (F = 17.98, p < .001). Significant group differences were not observed for general diabetes knowledge (F = 2.10, p = .125). Tukey’s HSD post hoc analyses indicated that the individuals within the Action stage endorsed significantly higher engagement in dietary self-management practices than those in the Contemplation and Preparation stages (p < .001). Participants in the Contemplation and Preparation stages did not significantly differ in their use of dietary self-management (p > .05). The frequency of positive dietary problem-solving was significantly higher in individuals within the Action stage compared to those in the Contemplation and Preparation stages (p < .001). Participants in the Contemplation and Preparation stages did not significantly differ in their problemsolving (p > .05). The quantity of perceived barriers to dietary adherence was also significantly higher in individuals within the Preparation stage (p < .01), although individuals within the Action and Contemplation stages did not significantly differ in their perception of dietary barriers (p > .05). In addition, greater diabetes-related self-efficacy was observed in participants in
the Action stage, significantly above that of their Contemplation and Preparation stage counterparts (p < .001).
4.
Discussion
This study highlights the connections between readiness to change behavior and IDF self-management recommendations for dietary barriers and behaviors. The findings demonstrate that the readiness to change approach distinguished participants by multiple health behaviors and perceptions, all of which are important to sustain dietary change over time. The frequency of perceived dietary barriers was significantly lower for participants in the Action stage. Greater endorsement of dietary self-management and positive dietary problem-solving practices was reported by individuals in the Action stage. Furthermore, it was observed that stage of change impacted self-efficacy toward diabetes self-management, with greater self-efficacy observed in individuals within the Action stage. Diabetes knowledge did not differ between stages and was not linked to dietary selfmanagement behaviors. This suggests that a lack of medical understanding of diabetes does not contribute to readiness to change diet. Individuals within the Preparation stage experienced a significantly higher frequency of perceived dietary barriers while the endorsement of perceived barriers was not significantly different between individuals within the Action and the Contemplation stage. This illustrates a perceptual shift in the belief about ease of dietary modification and may indicate
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
Table 1 – Demographic characteristics of the sample. Demographic
Mean (SD)
Age Duration of T2 DM (months) Total HCP visits in past year Female Ethnicity Non-Hispanic white African-American Other Married Education High school or above Partial high school Junior high or less Income < $10,000 Below poverty thresholda BMI Normal (BMI < 25) Overweight (BMI 25–29.9) Obese (BMI ≥ 30) Comorbidities/risk factors Hypertension High cholesterol Myocardial infarction Peripheral neuropathy Stage of readiness to change Action Preparation Contemplation Precontemplation Following a diet plan Carbohydrate gram count diet Carbohydrate exchange diet Total available glucose diet Healthy diet USDA pyramid diet Low-fat diet Other diet Seen a dietician
57.93 (11.52) 63.13 (88.45) 7.13 (6.20)
a
n (% of sample)
153 (60.5%) 139 (55.1%) 110 (43.7%) 3 (1.2%) 87 (34.7%) 206 (81.4%) 28 (11.1%) 18 (7.1%) 81 (34.0%) 50 (19.6%) 33.88 (8.00) 28 (11.0%) 63 (24.7%) 159 (62.3%) 198 (78.6%) 157 (64.1%) 33 (14.9%) 76 (31.0%) 130 47 74 3
(51%) (19%) (29%) (1%)
223
begin making progressive dietary decisions. Furthermore, the use of behaviorally focused measures of problem-solving at an initial assessment may explicate patient skills specific to diet change. Given that problem-solving behaviors permeate most self-care domains, interventions based on this initial assessment of individual problem-solving strengths can then be tailored to other self-management behaviors. Women were more likely to be in the Preparation stage or beyond than men. This finding corroborates previous studies suggesting that clinically underserved men are less willing or able to engage in dietary change and attend diabetes education less frequently than women [23]. As a result, our data reinforce the need for clinicians to provide additional education and dietary support for individuals, particularly men, in this demographic group. Given that other demographic variables, including BMI, age, ethnicity and duration of type 2 diabetes did not vary by stage of change, this demonstrates the complexity of individual intention to modify maladaptive dietary behaviors. Individuals within the Action stage of change had significantly greater diabetes self-efficacy than individuals who had not yet attempted dietary alterations. Confidence in one’s ability to engage in diabetes self-management behaviors may be tied to initiation of dietary change and coincides with a decreased perception of barriers to dietary change. These results provide further support for the use of self-efficacy as a predictive construct of adherence to positive health behaviors in underserved populations.
4.1.
Clinical applicability of stage of change model
50 (38.5%) 13 (10%) 1 (0.8%) 57 (43.8%) 16 (12.3%) 22 (16.9%) 11 (8.5%) 155 (61%)
Percent of sample living in census tract areas in which 20% residents live below poverty threshold.
that imminent dietary transitions trigger negative perceptions of change. Individuals within the Preparation stage may feel daunted by the task of dietary change and may choose to discontinue the transition to healthy diet adherence. Since the perception of dietary barriers decreases in the Action stage, it seems imperative for health care providers to provide counseling for individuals with an immediate dietary transition to ensure successful behavior change. It is perhaps not surprising that those in the Action stage of change were more frequently engaged in dietary self-management and positive dietary problem-solving. This suggests that involvement in dietary self-management and problem-solving practices does not gradually increase between stages of change however, there is an augmentation of these skills once healthy diet engagement has occurred. Diabetes care providers may focus on implementing strategies that encourage individuals in contemplative stages to
The results support the use of a readiness to change approach to dietary adherence in underserved clinical samples with type 2 diabetes. The use of the TTM as a framework with which to identify and adapt dietary needs in underserved individuals is illustrated. Further, brief self-report measures such as the PDQ can accurately assess stage of change and can identify engagement in or avoidance of health behaviors. The brevity of the PDQ measure of readiness to change allows for immediate assessment of movement between stages and may lead to the adaptation of dietary planning to meet the specific needs of individuals in differing stages of change. Given the small quantity of participants classified within the Precontemplation stage, these results were removed from the analyses. This finding is noteworthy as it suggests that the majority of individuals within our sample were at least considering dietary change. Extrapolation of this finding may suggest that additional factors, such as perceived dietary barriers, are more influential on actual dietary change (movement to the Action stage) than individual readiness to initiate dietary modifications. Furthermore, the low percentage of responders reporting adherence to a diet plan (43%) underscores the need for clinicians to provide self-management education in dietary change and to monitor diet adherence within underserved populations.
4.2.
Study strengths and limitations
The results of this study further the understanding of diabetes management in clinically underserved populations. First, the
224
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
Table 2 – ANOVA results by stage of change for dietary dependent variables. Variable
Contemplation (C) Mean SD
Preparation (P) Mean SD
Action (A) Mean SD
DSM scorea
2.966 1.186
3.105 1.245
3.937 1.130
19.257
<0.001
DPS scoreb
2.664 1.098
2.652 1.146
3.635 1.193
22.216
<0.001
Dietary barriersc
2.501 1.175
3.239 1.174
2.502 0.989
8.708
<0.001
DSES total scored
6.087 2.346
5.590 2.349
7.477 1.920
17.984
<0.001
14.051 3.045
14.152 4.071
13.690 3.050
2.098
0.125
DKT scoree a b c d e
F
p-Value
Dietary self-management practices – significant Tukey’s HSD post hoc: A × C, A × P: p < 0.001. Dietary problem solving – significant Tukey’s HSD post hoc: A × C, A × P: p < 0.001. Dietary barriers – significant Tukey’s HSD post hoc: P × C: p = 0.001; P × A: p < 0.001. Diabetes Self-efficacy Scale score – significant Tukey’s HSD post hoc: A × C; A × P: p < 0.001. Diabetes Knowledge Test score – Tukey’s HSD post hoc: no s.f.
use of brief self-report measures in a community-based setting succinctly identified stage of change among participants. This knowledge can be applied to develop stage-based interventions that bolster diet adherence by reducing barriers to dietary change. Second, our results suggest that willingness to initiate dietary change is less heavily weighted by sample characteristics than previously assumed [24]. This emphasizes the need for diabetes care providers to utilize clinical assessments of readiness to engage in health behaviors in concurrence with demographic-based assessments of risk factors (i.e. age, SES, BMI etc.). Finally, results elucidate the feasibility of a brief, readiness to change measure in assessing IDF recommendations for underserved samples. Specifically, the lack of demographic differences between the stages of change illustrates that IDF recommendations may be applied to culturally diverse samples. Additionally, the stage of change approach differentiated the extent to which individuals endorsed completion of IDF recommendations. This suggests that the TTM may be used to determine the level to which individuals will engage in self-management behaviors and may aid IDF intervention strategies. A limitation of the study is the small sample size of individuals in the Precontemplation stage. This meant that direct assessment of the full spectrum of readiness to change stages could not be completed. Comparisons between individuals who are considering and implementing dietary change with those who are not considering dietary modifications could not be made however, this would be a fruitful area of research for future investigation. Another potential limitation is the use of self-report measures to assess readiness to change. While the PDQ is a validated assessment tool with clinical utility, self-report bias is inherently present. Future studies should attempt to incorporate the measurement of dietary adherence using food logs or tracking. A final limitation of the study is the wording of the single-item measure of readiness to change dietary patterns. This item does not assess past dietary habits
or readiness to change and this limits the measurement of dietary change to cross-sectional analyses. Furthermore, the item does not differentiate between individuals who are in the Action and Maintenance stage of change and may have confounded the experiences of individuals within either group.
5.
Conclusions
Study results emphasize the need for clinicians to assess potential barriers to dietary change in individuals within differing stages of change. In particular, the provision of support and resources to reduce perceived dietary barriers in individuals preparing to make diet changes is imperative. Clinical interventions to bolster self-efficacy may further contribute to movement toward dietary change. The utility of validated, brief clinical measures to predict and assess readiness for dietary change in underserved community populations was supported. Application of these measures should be used to determine the focus of an individual’s diabetes education and to assess movement between stages of change for intervention tailoring. Given the finding that diabetes knowledge does not impact diet selfmanagement behaviors, a shift in emphasis to the application of diabetes knowledge may be warranted.
Conflict of interest The authors state that they have no conflict of interest.
references
[1] G. Danaei, M. Finucane, Y. Lu, et al., National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
[2]
[3]
[4] [5] [6]
[7]
[8]
[9]
[10]
[11]
[12]
country-years and 2.7 million participants, Lancet 378 (2011) 31–40. World Health Organization, Global Status Report on Noncommunicable Diseases, 2010. World Health Organization Report, 2011. Centers for Disease Control and Prevention, National Diabetes fact Sheet, 2007, Dept. of Health and Hum. Services, Atlanta, GA, 2008. N. Abate, M. Chandalia, The impact of ethnicity on type 2 diabetes, J. Diabetes Complic. 17 (2003) 39–58. International Diabetes Federation, IDF Diabetes Atlas, 2013, available from: http://www.idf.org/diabetesatlas A.H. Mokdad, J.S. Marks, D.F. Stroup, J.L. Gerberding, Actual causes of death in the United States, J. Am. Med. Assoc. 291 (2004) 1238–1245. C. Wilson, R. Alam, S. Latif, et al., Patient access to healthcare services and optimisation of self-management for ethnic minority populations living with diabetes: a systematic review, Health Soc. Care Commun. 20 (2012) 1–19. American Association of Diabetes Educators, AADE guidelines for the practice of Diabetes Self-Management Education and Training (DSME/T), Diabetes Educator 35 (2009) S85–S107. G. Highstein, M. O’Toole, G. Shetty, et al., Use of the transtheoretical model to enhance resources and supports for diabetes self-management: lessons from the Robert Wood Johnson foundation diabetes initiative, Diabetes Educator 33 (2007) S193–S200. J.N. Harvey, V.L. Lawson, The importance of health belief models in determining self-care behaviour in diabetes, Diab. Med. 26 (2009) 5–13. J. Prochaska, C. DiClemente, Stages and processes of self-change of smoking: toward an integrative model of change, J. Consult. Clin. Psychol. 51 (1983) 390–395. H. Bawadi, A. Banks, F. Ammari, et al., Stage of change of 6 health-related behaviors among patients with type 2 diabetes, Prim. Care Diabetes 6 (2012) 319–327.
225
[13] J. Norcross, P. Krebs, J. Prochaska, Stages of change, J. Clin. Psychol. 67 (2011) 143–154. [14] C. Pullen, S. Noble Walker, Midlife and older rural women’s adherence to U.S. Dietary Guidelines across stages of change in healthy eating, Public Health Nurs. 19 (2002) 170–178. [15] U.S. Census Bureau, Poverty Thresholds, 2000, available from: http://www.census.gov/hhes/www/poverty/data/ threshld/index.html [16] B. Stetson, D. Schlundt, C. Rothschild, et al., Development and validation of The Personal Diabetes Questionnaire (PDQ): a measure of diabetes self-care behaviors, perceptions and barriers, Diabetes Res. Clin. Pract. 91 (2011) 321–332. [17] R. Flesch, A new readability yardstick, J. Appl. Psychol. 32 (1948) 221–233. [18] Michigan Diabetes Research and Training Center, Diabetes History Form, available from: http://www.med.umich.edu/ mdrtc/profs/survey.html#dmh (cited 2013). [19] Michigan Diabetes Research and Training Center, Diabetes Knowledge Test, available from: http://www.med.umich. edu/mdrtc/profs/survey.html#dmh (cited 2013). [20] J. Fitzgerald, M. Funnell, G. Hess, et al., The reliability and validity of a brief diabetes knowledge test, Diabetes Care 21 (1998) 706–710. [21] Stanford Patient Education Research Center, Diabetes Self-Efficacy Scale, available from: http://patienteducation. stanford.edu/research/sediabetes.html (cited 2013). [22] K. Lorig, P. Ritter, F. Villa, J. Armas, Community-based peer-led diabetes self-management: a randomized trial, Diabetes Educator 35 (2009) 641–651. [23] C. Graziani, M. Rosenthal, J. Diamond, Diabetes education program use and patient-perceived barriers to attendance, Fam. Med. 31 (1999) 358–363. [24] M. Vallis, L. Ruggiero, G. Greene, et al., Stages of change for healthy eating in diabetes: relation to demographic, eating-related, health care utilization, and psychosocial factors, Diabetes Care 26 (2003) 1468–1474.
Contents lists available at ScienceDirect
Primary Care Diabetes journal homepage: http://www.elsevier.com/locate/pcd
Original Research
Diet self-management and readiness to change in underserved adults with type 2 diabetes Holly Knight, Barbara Stetson ∗ , Sathya Krishnasamy, Sri Prakash Mokshagundam University of Louisville, United States
a r t i c l e
i n f o
a b s t r a c t
Article history:
Aim: Dietary assessment in diabetes may be enhanced by considering patient-centered per-
Received 3 July 2014
spectives and barriers to change within IDF guidelines. Consideration of readiness to change
Accepted 28 September 2014
(RTC) diet in underserved samples may guide future interventions in high risk populations.
Available online 22 October 2014
This study assesses the utility of a rapid assessment of RTC diet in a medically underserved sample.
Keywords:
Method: Participants were 253 Black (43.7%) and White (55.1%) American adults with type
Diabetes
2 diabetes [M age = 57.93 (11.52); 60.5% female; 19% below the US poverty threshold]. Par-
Self-care
ticipants were recruited at medical clinics and completed validated self-report measures
Medically Underserved
assessing diabetes knowledge, self-efficacy and dietary behaviors and barriers by RTC.
Self-report measures
Results: Stage-based comparisons identified significant differences in diabetes and dietary domains: participants in the Action stage endorsed fewer behavioral dietary barriers (p < .001), more frequent dietary problem-solving (p < .001), and greater diabetes self-efficacy (p < .001) than participants in the Contemplation and Preparation stages. Women were more likely to be in the Preparation stage and beyond (p < .05). Conclusions: Findings highlight the clinical utility of a brief measure of RTC in understanding patient perspectives toward dietary behaviors in a medically underserved sample. The impact of gender on RTC diet warrants further exploration. © 2014 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.
1.
Introduction
Diabetes affects 347 million people worldwide [1] and is projected to be the 7th leading cause of global death by 2030 [2]. Type 2 diabetes disproportionately effects low-income and underserved populations and is associated with worse outcomes and higher comorbidity rates [3,4]. The trajectory
of type 2 diabetes is heavily determined by health behavior choices, with the International Diabetes Federation (IDF) global guidelines recommending the maintenance of HbA1c levels below 6.5%, dietary modification, exercise engagement and weight loss for the control and improvement of diabetic outcomes [5]. Enhancement of self-management behaviors plays an integral part in proper blood glucose control and has emerged as a focal point of care for health care providers.
∗ Corresponding author at: Department of Psychological and Brain Sciences, 317 Life Sciences Building, University of Louisville, Louisville, KY 40292, United States. Tel.: +1 502 852 2540; fax: +1 502 852 8904. E-mail address: [email protected] (B. Stetson).
http://dx.doi.org/10.1016/j.pcd.2014.09.007 1751-9918/© 2014 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.
220
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
Poor diet is one of the most preventable causes of death in the US and dietary dysregulation and barriers to healthy eating present major problems for the improvement of individual glycemic control [6]. The health care encounter offers opportunities to promote a healthy diabetes diet however, some patients may resist making dietary changes. Understanding receptivity to dietary self-management is particularly relevant in underserved samples who often have limited access to diabetes education and endorse poorer awareness of diabetesmanagement strategies [4,7]. While health providers may recommend dietary plans, individual patients may not be ready to accept or implement these changes at the time of the medical encounter. By understanding patient perspectives, promotion of diet changes may be enhanced. When assessing self-management behavior change, the IDF suggests use of a framework emphasizing knowledge about lifestyle modification, problem-solving, and individualization of self-management goals and needs [8]. However, research has yet to address how the IDF recommended components of knowledge, problem-solving barriers to change and self-management needs present within a diverse, medically underserved population. A wealth of research has focused on the application of multiple health behavior models to self-management behaviors [9,10]. One such model, the transtheoretical model (TTM), utilizes a staged approach to understand how individual differences in readiness to change health behaviors unfold [11]. This model offers substantial opportunities for understanding patient perspectives at the time of medical encounters. From this perspective, individuals move toward behavior engagement through five sequential stages of change: Precontemplation, defined by a lack of intention to make behavioral changes; Contemplation, a consideration of changing health behaviors; Preparation, preparing to and making small changes; Action, active engagement in behavior change and Maintenance, continuing behavior change over time [11]. The TTM conceptualizes individual
differences in readiness to change behaviors and incorporates self-efficacy (e.g., confidence to overcome barriers) as a prominent construct aiding movement between the stages [11]. An extensive literature supports the use of staged approaches to dietary interventions [12–14]. The present paper aims to assess underserved patient perspectives toward dietary change within the IDF selfmanagement framework. Brief, clinically focused measures assess factors influencing dietary change, including diabetes knowledge, current diet self-management practices, dietary problem-solving and perceived barriers to dietary change across the TTM stages of change. The contribution of diabetes self-efficacy, as emphasized within the TTM, to dietary change is assessed to better understand influential factors in individual readiness to change diet. A final goal is to determine the utility of brief clinical measures in the assessment of self-management behaviors and readiness to change, with the potential for guidance toward stage-based interventions in underserved clinical samples.
2.
Methods
2.1.
Study participants
Participants were recruited from health department diabetes education programs and university-based medical clinics in a large southeastern U.S. city. All recruitment sites are accessible to underserved, low-income adults. Eligibility requirements were met if the individual was an adult diagnosed with type 2 diabetes and was able to read, write and speak English and had received health department brochures or attended self-management classes. A brief screening either in person or over the phone was administered. See Fig. 1 for recruitment data.
Total Invited to Parcipate N=431
Not eligible
Declined parcipaon
N=34 (7.9%)
N=81 (18.8%)
Consented and given packet N=416 (73.3%)
Completed Study
Non completer
N=245
N=162 (32% of those consented)
(61% of those consented) (59% of total invited)
Fig. 1 – Study recruitment flow chart.
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
2.2.
Materials
The self-report assessment packet contained questions assessing demographics, diabetes history and knowledge, self-care, dietary behaviors and barriers and readiness to change dietary routine. Socioeconomic level was assessed using self-report questions on education, income, employment and household size. Community-level socioeconomic status was assessed using the United States Census tract information [15]. All procedures were approved by the University Human Subjects Protection Program.
2.2.1.
Dietary behaviors and barriers
Personal Diabetes Questionnaire (PDQ). The PDQ is a brief, patient-centered self-report questionnaire assessing general diabetes self-care in four behavioral domains: (1) nutritional management, (2) blood glucose monitoring, (3) medication adherence and (4) physical activity. The PDQ also assesses perceptions and barriers related to diabetes self-care and readiness to change [16]. Total scores were assessed as a sum of scaled individual barrier scores for each dietary domain. In a validation study, the PDQ demonstrated good internal consistency (Cronbach’s ˛ = 0.650–0.834) across domains [16]. Significant correlations were observed between PDQ subscales, HbA1c levels and BMI (p ≤ 0.001) [16]. The Flesch–Kincaid Readability Test [17] demonstrated readability at a 6th grade level [16]. Dietary constructs measured using the PDQ included current level of dietary self-management, dietary problemsolving, and perceived barriers to dietary change. Dietary self-management practices were assessed using items such as “During the past 3 months, how often did you use sugar-free or reduced sugar products?” Dietary problem-solving assessment utilized items including “During the past 3 months, how often did you use information about the grams of carbohydrates in foods to make decisions about what or how much to eat?” and reflected behavioral choices that aid HbA1c control. Perceived dietary barriers incorporated items including “During the past 3 months, how often have you experienced eating problems because of hunger or food cravings?” and described barriers to healthy diet choices. Stage of change. Dietary stage of change was assessed using a single item on the PDQ to determine whether a brief indicator of stage of change can be integrated into assessments in clinical settings. The item “Are you currently trying to follow a diet plan in order to better control your blood glucose? If you are not currently following a diet plan or meal plan to better control your blood glucose, is this something you plan to do in the future?” was used to differentiate participants by their dietary stage of change. A description of the criteria for stage of change assessment using this item is presented in Fig. 2. For the purpose of analysis, individuals were categorized by dietary stage of change and group differences were assessed.
2.2.2.
Diabetes history
Diabetes History Questionnaire (DHQ). Basic medical and demographic information related to diabetes were assessed using the DHQ [18].
2.2.3.
221
Diabetes knowledge
Diabetes Knowledge Test (DKT). The DKT was used to assess general diabetes knowledge including the symptoms associated with low or high blood sugar and normal fasting blood sugar levels [19,20]. The test has been administered to clinical populations and demonstrates good internal consistency (Cronbach’s ˛ = .70). The total number of correct items on the DKT was utilized as an estimate of overall diabetes knowledge.
2.2.4.
Diabetes self-efficacy
Diabetes Self-Efficacy Scale (DSES). The DSES was used to assess self-efficacy related to diabetes self-management behaviors [21]. The DSES has been validated within clinical populations with good internal consistency (Cronbach’s ˛ = .828) [22]
2.3.
Socioeconomic indicators
Census tract data was obtained from the United States Census Bureau’s website and was based on 2000 census data [15]. These tracts or subdivisions of a county represent a cluster of approximately 4000 individuals who have similar characteristics such as income, status and living conditions.
2.4.
Statistical analyses
Analyses were conducted using SPSS® Version 21. Twotailed tests were used for all analyses with an alpha level of .05 used as the criterion for statistical significance. Demographic characteristics and readiness to change were defined using descriptive statistics. Between-group differences were assessed using one-way ANOVA and nonparametric Kruskal–Wallace tests. Tukey’s HSD post hoc tests were used to elucidate significant ANOVA findings and Bonferroni’s corrections were applied.
3.
Results
3.1.
Readiness to change diet
Demographic and stage of change characteristics are presented in Table 1. Given the small quantity of participants within the Precontemplation stage, these results were excluded from the analyses. In regard to the IDF recommendations; the most frequently endorsed self-management practice was substituting low-calorie sweetener for sugar at least 4–6 times per week, reported by 72.2% of participants. The most frequently reported problem-solving behavior was controlling portion sizes, with 59.6% engaging in this 4–6 times per week. The most common barrier to diet change was battling with daily cravings, with 32.1% of individuals experiencing this barrier at least 4–6 times per week. Non-parametric analysis of the PDQ item assessing diet readiness for change identified stage-based differences for gender. Women were further along the stages of change than men: 76.98% of women in preparation or beyond compared to 60.21% of men (2 = 8.197, p = .017). The remaining demographic variables and comorbid illnesses did not differ based on dietary stage of change.
222
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
“Are you currently trying to follow a diet plan in order to better control your blood glucose? If you are not currently following a diet plan or meal plan to better control your blood glucose, is this something you plan to do in the future?”
“No I have no plans right now for starting to follow a diet or meal plan”
Precontemplation
“I plan to start within the next 6 months”
Contemplation
“I plan to start within the next month”
Preparation
“I am already following a diet or meal plan”
Action
Maintenance
Fig. 2 – Stage of dietary change assessed using items from the Personal Diabetes Questionnaire (PDQ) [16].
Diet behaviors and type 2 perceptions by stage of change Univariate analyses were used to describe dietary selfmanagement, problem-solving, perceived barriers and diabetes self-efficacy and knowledge across each stage of change (see Table 2). Stage-based differences were observed in the frequency of reported dietary self-management practices (F = 19.26, p < .001), the frequency of dietary problem solving (F = 22.22, p < .001), the quantity of perceived dietary barriers (F = 8.71, p < .001) and self-efficacy toward diabetes self-management (F = 17.98, p < .001). Significant group differences were not observed for general diabetes knowledge (F = 2.10, p = .125). Tukey’s HSD post hoc analyses indicated that the individuals within the Action stage endorsed significantly higher engagement in dietary self-management practices than those in the Contemplation and Preparation stages (p < .001). Participants in the Contemplation and Preparation stages did not significantly differ in their use of dietary self-management (p > .05). The frequency of positive dietary problem-solving was significantly higher in individuals within the Action stage compared to those in the Contemplation and Preparation stages (p < .001). Participants in the Contemplation and Preparation stages did not significantly differ in their problemsolving (p > .05). The quantity of perceived barriers to dietary adherence was also significantly higher in individuals within the Preparation stage (p < .01), although individuals within the Action and Contemplation stages did not significantly differ in their perception of dietary barriers (p > .05). In addition, greater diabetes-related self-efficacy was observed in participants in
the Action stage, significantly above that of their Contemplation and Preparation stage counterparts (p < .001).
4.
Discussion
This study highlights the connections between readiness to change behavior and IDF self-management recommendations for dietary barriers and behaviors. The findings demonstrate that the readiness to change approach distinguished participants by multiple health behaviors and perceptions, all of which are important to sustain dietary change over time. The frequency of perceived dietary barriers was significantly lower for participants in the Action stage. Greater endorsement of dietary self-management and positive dietary problem-solving practices was reported by individuals in the Action stage. Furthermore, it was observed that stage of change impacted self-efficacy toward diabetes self-management, with greater self-efficacy observed in individuals within the Action stage. Diabetes knowledge did not differ between stages and was not linked to dietary selfmanagement behaviors. This suggests that a lack of medical understanding of diabetes does not contribute to readiness to change diet. Individuals within the Preparation stage experienced a significantly higher frequency of perceived dietary barriers while the endorsement of perceived barriers was not significantly different between individuals within the Action and the Contemplation stage. This illustrates a perceptual shift in the belief about ease of dietary modification and may indicate
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
Table 1 – Demographic characteristics of the sample. Demographic
Mean (SD)
Age Duration of T2 DM (months) Total HCP visits in past year Female Ethnicity Non-Hispanic white African-American Other Married Education High school or above Partial high school Junior high or less Income < $10,000 Below poverty thresholda BMI Normal (BMI < 25) Overweight (BMI 25–29.9) Obese (BMI ≥ 30) Comorbidities/risk factors Hypertension High cholesterol Myocardial infarction Peripheral neuropathy Stage of readiness to change Action Preparation Contemplation Precontemplation Following a diet plan Carbohydrate gram count diet Carbohydrate exchange diet Total available glucose diet Healthy diet USDA pyramid diet Low-fat diet Other diet Seen a dietician
57.93 (11.52) 63.13 (88.45) 7.13 (6.20)
a
n (% of sample)
153 (60.5%) 139 (55.1%) 110 (43.7%) 3 (1.2%) 87 (34.7%) 206 (81.4%) 28 (11.1%) 18 (7.1%) 81 (34.0%) 50 (19.6%) 33.88 (8.00) 28 (11.0%) 63 (24.7%) 159 (62.3%) 198 (78.6%) 157 (64.1%) 33 (14.9%) 76 (31.0%) 130 47 74 3
(51%) (19%) (29%) (1%)
223
begin making progressive dietary decisions. Furthermore, the use of behaviorally focused measures of problem-solving at an initial assessment may explicate patient skills specific to diet change. Given that problem-solving behaviors permeate most self-care domains, interventions based on this initial assessment of individual problem-solving strengths can then be tailored to other self-management behaviors. Women were more likely to be in the Preparation stage or beyond than men. This finding corroborates previous studies suggesting that clinically underserved men are less willing or able to engage in dietary change and attend diabetes education less frequently than women [23]. As a result, our data reinforce the need for clinicians to provide additional education and dietary support for individuals, particularly men, in this demographic group. Given that other demographic variables, including BMI, age, ethnicity and duration of type 2 diabetes did not vary by stage of change, this demonstrates the complexity of individual intention to modify maladaptive dietary behaviors. Individuals within the Action stage of change had significantly greater diabetes self-efficacy than individuals who had not yet attempted dietary alterations. Confidence in one’s ability to engage in diabetes self-management behaviors may be tied to initiation of dietary change and coincides with a decreased perception of barriers to dietary change. These results provide further support for the use of self-efficacy as a predictive construct of adherence to positive health behaviors in underserved populations.
4.1.
Clinical applicability of stage of change model
50 (38.5%) 13 (10%) 1 (0.8%) 57 (43.8%) 16 (12.3%) 22 (16.9%) 11 (8.5%) 155 (61%)
Percent of sample living in census tract areas in which 20% residents live below poverty threshold.
that imminent dietary transitions trigger negative perceptions of change. Individuals within the Preparation stage may feel daunted by the task of dietary change and may choose to discontinue the transition to healthy diet adherence. Since the perception of dietary barriers decreases in the Action stage, it seems imperative for health care providers to provide counseling for individuals with an immediate dietary transition to ensure successful behavior change. It is perhaps not surprising that those in the Action stage of change were more frequently engaged in dietary self-management and positive dietary problem-solving. This suggests that involvement in dietary self-management and problem-solving practices does not gradually increase between stages of change however, there is an augmentation of these skills once healthy diet engagement has occurred. Diabetes care providers may focus on implementing strategies that encourage individuals in contemplative stages to
The results support the use of a readiness to change approach to dietary adherence in underserved clinical samples with type 2 diabetes. The use of the TTM as a framework with which to identify and adapt dietary needs in underserved individuals is illustrated. Further, brief self-report measures such as the PDQ can accurately assess stage of change and can identify engagement in or avoidance of health behaviors. The brevity of the PDQ measure of readiness to change allows for immediate assessment of movement between stages and may lead to the adaptation of dietary planning to meet the specific needs of individuals in differing stages of change. Given the small quantity of participants classified within the Precontemplation stage, these results were removed from the analyses. This finding is noteworthy as it suggests that the majority of individuals within our sample were at least considering dietary change. Extrapolation of this finding may suggest that additional factors, such as perceived dietary barriers, are more influential on actual dietary change (movement to the Action stage) than individual readiness to initiate dietary modifications. Furthermore, the low percentage of responders reporting adherence to a diet plan (43%) underscores the need for clinicians to provide self-management education in dietary change and to monitor diet adherence within underserved populations.
4.2.
Study strengths and limitations
The results of this study further the understanding of diabetes management in clinically underserved populations. First, the
224
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
Table 2 – ANOVA results by stage of change for dietary dependent variables. Variable
Contemplation (C) Mean SD
Preparation (P) Mean SD
Action (A) Mean SD
DSM scorea
2.966 1.186
3.105 1.245
3.937 1.130
19.257
<0.001
DPS scoreb
2.664 1.098
2.652 1.146
3.635 1.193
22.216
<0.001
Dietary barriersc
2.501 1.175
3.239 1.174
2.502 0.989
8.708
<0.001
DSES total scored
6.087 2.346
5.590 2.349
7.477 1.920
17.984
<0.001
14.051 3.045
14.152 4.071
13.690 3.050
2.098
0.125
DKT scoree a b c d e
F
p-Value
Dietary self-management practices – significant Tukey’s HSD post hoc: A × C, A × P: p < 0.001. Dietary problem solving – significant Tukey’s HSD post hoc: A × C, A × P: p < 0.001. Dietary barriers – significant Tukey’s HSD post hoc: P × C: p = 0.001; P × A: p < 0.001. Diabetes Self-efficacy Scale score – significant Tukey’s HSD post hoc: A × C; A × P: p < 0.001. Diabetes Knowledge Test score – Tukey’s HSD post hoc: no s.f.
use of brief self-report measures in a community-based setting succinctly identified stage of change among participants. This knowledge can be applied to develop stage-based interventions that bolster diet adherence by reducing barriers to dietary change. Second, our results suggest that willingness to initiate dietary change is less heavily weighted by sample characteristics than previously assumed [24]. This emphasizes the need for diabetes care providers to utilize clinical assessments of readiness to engage in health behaviors in concurrence with demographic-based assessments of risk factors (i.e. age, SES, BMI etc.). Finally, results elucidate the feasibility of a brief, readiness to change measure in assessing IDF recommendations for underserved samples. Specifically, the lack of demographic differences between the stages of change illustrates that IDF recommendations may be applied to culturally diverse samples. Additionally, the stage of change approach differentiated the extent to which individuals endorsed completion of IDF recommendations. This suggests that the TTM may be used to determine the level to which individuals will engage in self-management behaviors and may aid IDF intervention strategies. A limitation of the study is the small sample size of individuals in the Precontemplation stage. This meant that direct assessment of the full spectrum of readiness to change stages could not be completed. Comparisons between individuals who are considering and implementing dietary change with those who are not considering dietary modifications could not be made however, this would be a fruitful area of research for future investigation. Another potential limitation is the use of self-report measures to assess readiness to change. While the PDQ is a validated assessment tool with clinical utility, self-report bias is inherently present. Future studies should attempt to incorporate the measurement of dietary adherence using food logs or tracking. A final limitation of the study is the wording of the single-item measure of readiness to change dietary patterns. This item does not assess past dietary habits
or readiness to change and this limits the measurement of dietary change to cross-sectional analyses. Furthermore, the item does not differentiate between individuals who are in the Action and Maintenance stage of change and may have confounded the experiences of individuals within either group.
5.
Conclusions
Study results emphasize the need for clinicians to assess potential barriers to dietary change in individuals within differing stages of change. In particular, the provision of support and resources to reduce perceived dietary barriers in individuals preparing to make diet changes is imperative. Clinical interventions to bolster self-efficacy may further contribute to movement toward dietary change. The utility of validated, brief clinical measures to predict and assess readiness for dietary change in underserved community populations was supported. Application of these measures should be used to determine the focus of an individual’s diabetes education and to assess movement between stages of change for intervention tailoring. Given the finding that diabetes knowledge does not impact diet selfmanagement behaviors, a shift in emphasis to the application of diabetes knowledge may be warranted.
Conflict of interest The authors state that they have no conflict of interest.
references
[1] G. Danaei, M. Finucane, Y. Lu, et al., National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370
p r i m a r y c a r e d i a b e t e s 9 ( 2 0 1 5 ) 219–225
[2]
[3]
[4] [5] [6]
[7]
[8]
[9]
[10]
[11]
[12]
country-years and 2.7 million participants, Lancet 378 (2011) 31–40. World Health Organization, Global Status Report on Noncommunicable Diseases, 2010. World Health Organization Report, 2011. Centers for Disease Control and Prevention, National Diabetes fact Sheet, 2007, Dept. of Health and Hum. Services, Atlanta, GA, 2008. N. Abate, M. Chandalia, The impact of ethnicity on type 2 diabetes, J. Diabetes Complic. 17 (2003) 39–58. International Diabetes Federation, IDF Diabetes Atlas, 2013, available from: http://www.idf.org/diabetesatlas A.H. Mokdad, J.S. Marks, D.F. Stroup, J.L. Gerberding, Actual causes of death in the United States, J. Am. Med. Assoc. 291 (2004) 1238–1245. C. Wilson, R. Alam, S. Latif, et al., Patient access to healthcare services and optimisation of self-management for ethnic minority populations living with diabetes: a systematic review, Health Soc. Care Commun. 20 (2012) 1–19. American Association of Diabetes Educators, AADE guidelines for the practice of Diabetes Self-Management Education and Training (DSME/T), Diabetes Educator 35 (2009) S85–S107. G. Highstein, M. O’Toole, G. Shetty, et al., Use of the transtheoretical model to enhance resources and supports for diabetes self-management: lessons from the Robert Wood Johnson foundation diabetes initiative, Diabetes Educator 33 (2007) S193–S200. J.N. Harvey, V.L. Lawson, The importance of health belief models in determining self-care behaviour in diabetes, Diab. Med. 26 (2009) 5–13. J. Prochaska, C. DiClemente, Stages and processes of self-change of smoking: toward an integrative model of change, J. Consult. Clin. Psychol. 51 (1983) 390–395. H. Bawadi, A. Banks, F. Ammari, et al., Stage of change of 6 health-related behaviors among patients with type 2 diabetes, Prim. Care Diabetes 6 (2012) 319–327.
225
[13] J. Norcross, P. Krebs, J. Prochaska, Stages of change, J. Clin. Psychol. 67 (2011) 143–154. [14] C. Pullen, S. Noble Walker, Midlife and older rural women’s adherence to U.S. Dietary Guidelines across stages of change in healthy eating, Public Health Nurs. 19 (2002) 170–178. [15] U.S. Census Bureau, Poverty Thresholds, 2000, available from: http://www.census.gov/hhes/www/poverty/data/ threshld/index.html [16] B. Stetson, D. Schlundt, C. Rothschild, et al., Development and validation of The Personal Diabetes Questionnaire (PDQ): a measure of diabetes self-care behaviors, perceptions and barriers, Diabetes Res. Clin. Pract. 91 (2011) 321–332. [17] R. Flesch, A new readability yardstick, J. Appl. Psychol. 32 (1948) 221–233. [18] Michigan Diabetes Research and Training Center, Diabetes History Form, available from: http://www.med.umich.edu/ mdrtc/profs/survey.html#dmh (cited 2013). [19] Michigan Diabetes Research and Training Center, Diabetes Knowledge Test, available from: http://www.med.umich. edu/mdrtc/profs/survey.html#dmh (cited 2013). [20] J. Fitzgerald, M. Funnell, G. Hess, et al., The reliability and validity of a brief diabetes knowledge test, Diabetes Care 21 (1998) 706–710. [21] Stanford Patient Education Research Center, Diabetes Self-Efficacy Scale, available from: http://patienteducation. stanford.edu/research/sediabetes.html (cited 2013). [22] K. Lorig, P. Ritter, F. Villa, J. Armas, Community-based peer-led diabetes self-management: a randomized trial, Diabetes Educator 35 (2009) 641–651. [23] C. Graziani, M. Rosenthal, J. Diamond, Diabetes education program use and patient-perceived barriers to attendance, Fam. Med. 31 (1999) 358–363. [24] M. Vallis, L. Ruggiero, G. Greene, et al., Stages of change for healthy eating in diabetes: relation to demographic, eating-related, health care utilization, and psychosocial factors, Diabetes Care 26 (2003) 1468–1474.