Using health action process approach to determine diet adherence among patients with Type 2 diabetes

Abstract

INTRODUCTION: Diet adherence may cause diabetes complications to be diminished. OBJECTIVES: This study aimed at identifying determinants of diet adherence among patients with Type 2 diabetes based on the health action process approach (HAPA). METHODS: In this cross-sectional study, 734 patients with Type 2 diabetes, attending to South Tehran health centers, were recruited during June–December 2018. The dietary regimen scale (nine items) and a researcher-designed questionnaire consisting of HAPA constructs were used to gather the data. Data were analyzed using the Mann–Whitney test, Pearson Chi-squared test, Fisher's exact test, and linear regression test. All statistical tests were assessed using SPSS (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY, USA: IBM Corp.). RESULTS: The level of nonadherence to diet was 91.1%. Diet adherence was significantly associated with family income ( P = 0.005), level of education ( P < 0.001), and age ( P = 0.009). The linear regression showed that 55% of the variance of diet adherence was determined by HAPA variables. Diet adherence was associated with intention ( P < 0.001), action planning ( P = 0.005), and barriers ( P = 0.003). CONCLUSION: Most of the patients did not adhere to their diet. Appropriate programs should be designed to promote diet adherence among the patients, especially those with low literacy and patients living in poor communities.

The Effect of Educational Intervention on Dietary Adherence among Type 2 Diabetics in Zahedan: Using the Health Action Process Approach

“…In our study, self-e cacy showed a signi cant difference in the test group one month and three months after the intervention. Other studies also showed an increase in self-e cacy after the intervention (10,30). Miller et al's study was not consistent with our study.…”

“…The results of this study showed that a signi cant percentage of patients did not follow a healthy diet, which may be due to their illiteracy, the socio-economic status of the studied community, and the lack of proper relevant planning among type 2 diabetes patients. Moreover, people with low income and low levels of education did not adhere to their diets, which is consistent with other studies (10,19).…”

“…Building positive self-care behaviors is essential for achieving the goals of diabetes treatment and maximizing the quality of life (9). Adherence to a healthy diabetic diet is fundamental to achieving healthy behaviors (10). Fruit and vegetable intake is an indicator of following a healthy diet (11); The design of educational interventions to create desirable behavioral changes is improved when all factors related to the determinants of the target behavior are considered.…”

The effectiveness of an intervention designed based on health action process approach on diet and medication adherence among patients with type 2 diabetes: a randomized controlled trial

“…The adherence rates among patients with type 2 diabetes in Iran explored in health centers were low [ 33 , 34 ]. It is important to encourage patients to monitor their own progress in order for long-term adherence to be successful [ 31 ].…”

“…The dimensions consisted of: (a) intention to diet and medications adherence (4 items), measured using seven-interval Likert scales, ranging from 1 (strongly disagree) to 7 (strongly agree); (b) task self-efficacy of diabetes diet and medications adherence (14 items); (c) copping self-efficacy (13 items); (d) recovery self-efficacy (6 items); (e) action planning (5 items); (f) copping planning (13 items), rated on a 4-point scale ranging from 1 (not at all true) to 4 (exactly true); (g) barriers to adherence (18 items); (h) resources and benefits (8 items), scores for this item ranged from 1 (strongly disagree) to 7 (strongly agree), higher scores represented a high level of barriers. Content validity and reliability for the HAPA-based questionnaire has been measured in the previous studies [ 33 , 34 ]. We transformed the scores of each item to 0–100 using the following formula: the new score of item = 100 × (Score of item − Minimum possible score)/Range of possible scores.…”