Skip to main content
Download PDF

Application of the information-motivation-behavioral skills model to improve medication adherence among older adults with type 2 diabetes: findings from a quasi-experimental study in Kermanshah, Iran

BMC Geriatrics volume 25, Article number: 328 (2025) Cite this article

Abstract

Introduction

Medication adherence is crucial for effective blood sugar control in diabetes patients. However, older adults face a higher risk of non-adherence. This study aims to evaluate the effectiveness of a theory-based program designed to enhance medication adherence among older adults with type 2 diabetes.

Methods

This quasi-experimental study involved 100 elderly individuals with type 2 diabetes in Kermanshah, Iran, in 2024. Participants were randomly assigned to an intervention (50) or control group (50). The intervention group attended six 40-minute sessions over six weeks, based on the Information-Motivation-Behavioral Skills (IMB) model. Data were collected via a questionnaire assessing demographics, IMB model components, and medication adherence. Data were analyzed using SPSS version 16, employing chi-square tests and t-tests for comparisons, moreover, effect sizes were determined using Cohen’s d.

Results

The intervention group showed significant improvements, especially in “Information,” with a very large effect size of 1.3 and an average change of 3.84 (p < 0.001). In contrast, the control group had minimal changes. Other components like “Attitude” and “Self-efficacy” also had large effect sizes (0.65 and 0.67). However, “Subjective Norms” showed a small effect size (0.11) with no significant changes. Additionally, the intervention group showed a significant improvement in medication adherence (effect size 1.15), increasing scores from 16.92 to 19.76, (p < 0.001) while the control group had minimal changes.

Conclusion

The program based on the IMB model significantly improved medication adherence among elderly individuals with type 2 diabetes. We also identified the key theoretical methods of behavior change for each determinant of the IMB model and recommend utilizing them in the development of similar future interventions.

Peer Review reports

Introduction

Diabetes has emerged as a significant public health challenge globally, exerting considerable pressure on healthcare systems [1]. The prevalence of this disease has surged in the 21st century, with reports indicating that in 2021; approximately 537 million adults worldwide were living with diabetes, a figure projected to escalate to 783 million by 2045, reflecting a 46% increase [2]. This rise correlates with increasing life expectancy and an aging population; the World Health Organization (WHO) estimates that by 2030, one in six individuals will be over 60 years old, with this ratio expected to approach one in four by 2050 [3]. In Iran, the Statistical Center reports that 6.3% of the population is currently over 60, projected to rise to 16.2% by 2036, highlighting a significant demographic shift [4].

Diabetes accounts for approximately 1.6 million deaths each year and places a heavy financial strain on healthcare systems worldwide, with global spending hitting an astonishing USD 966 billion in 2021; in Iran, the economic impact is particularly significant, with diabetes-related health expenditures per individual estimated at USD 1,354.8 in 2021, projected to rise to USD 1,839.2 by 2045 [5].

Older adults with diabetes face significant risks of complications, including hypoglycemia, kidney failure, and cardiovascular diseases [6]. The International Diabetes Federation reported that in 2019, one in five older adults worldwide had diabetes [7]. In Iran, research indicates that approximately one in three individuals over 60 is affected, highlighting the urgent need for attention to elderly diabetic patients in this context [4]. Effective self-management of type 2 diabetes involves challenges such as dietary adherence, regular exercise, medication compliance, foot care, glucose monitoring, and psychological support [8].

Long-term management of chronic diseases requires strict adherence to medication regimens to control symptoms and slow disease progression [9]. Medication adherence is vital for glycemic control in diabetic patients, but older adults often struggle with non-adherence due to multiple chronic conditions, polypharmacy, and cognitive decline [7]. Adherence, defined as following prescribed medication regimens [10], significantly impacts physiological outcomes and quality of life [11]. Actual adherence rates for type 2 diabetes vary widely, typically between 36 and 93% [12], with recent studies showing only 54% of adults adhering to therapies [13]. In Iran, about half of diabetic patients do not comply with treatment [14], leading to worse health outcomes and increased healthcare costs [15]. Poor adherence can worsen symptoms and complications, heightening the risk of both macrovascular and microvascular diseases [16, 17]. This global challenge not only accelerates disease progression but also inflates treatment costs [10, 18].

Current intervention strategies—ranging from patient education and counseling to simplifying medication regimens—have not sufficiently addressed the issue of non-adherence [19]. The complexities of medication adherence are influenced by various factors, some immutable (such as age), while others, particularly patient-related factors, can be modified through increased knowledge and altered beliefs about medications [20]. Current interventions aimed at improving medication adherence in diabetic patients are often insufficient due to several factors; many patients face barriers such as complex medication regimens, lack of understanding of their condition, and insufficient support systems; additionally, traditional approaches, may not address the underlying psychological and social determinants of health that influence adherence; thus, a more holistic approach is necessary to enhance adherence rates among diabetic patients [19,20,21].

Healthcare providers play a pivotal role in enhancing adherence by understanding the typical pathways influencing medication compliance among diabetic patients [22]. Evidence suggests that effective behavior change interventions must meet three criteria: they should target predictive factors of behavior, allow for modifications of those factors, and be practically applicable within the relevant cultural and contextual framework [23]. Various theoretical models have been proposed to elucidate health behavior changes. One such model is the information-motivation-behavioral skills (IMB) model, which facilitates the development and evaluation of diverse intervention strategies [24]. This model comprises three component: Information, which encompasses knowledge about the disease and its management; Motivation, reflecting an individual’s desire to engage in healthy behaviors and the social support received; and Behavioral Skills, which pertain to a person’s confidence and ability to perform health-related actions [25]. The IMB model is crucial in studies aimed at improving self-management among diabetic patients as it provides a comprehensive framework for understanding the factors that influence health behaviors; by ensuring that patients receive accurate information about diabetes management, fostering motivation through emotional and social support, and enhancing behavioral skills through practical training, healthcare providers can empower patients to take control of their condition; this holistic approach not only helps in improving adherence to treatment regimens but also encourages lifestyle changes that are essential for effective diabetes management, ultimately leading to better health outcomes and enhanced quality of life for patients [26,27,28,29,30,31,32]. The identified research gap is the lack of sufficient evidence regarding the application of the IMB model in promoting medication adherence among patients with type 2 diabetes in Iran, particularly elderly individuals. Despite the existence of various interventions aimed at improving adherence, many of these approaches fail to address the psychological, social, and cultural factors that influence adherence behavior. While the IMB model has shown potential in improving self-management and treatment adherence, its implementation and efficacy remain underexplored in the Iranian context. This study seeks to fill this gap by evaluating the effectiveness of an IMB model-based program tailored for elderly diabetic patients in Kermanshah, Iran, thus contributing to the development of more holistic and culturally relevant interventions.

Methods

Participants

This quasi-experimental study was carried out in 2024, involving 100 elderly individuals diagnosed with type 2 diabetes in Kermanshah city, located in western Iran. Kermanshah is recognized as one of the provinces with a high prevalence of diabetes in the Iran [33]. Participants were identified through health center records in the city and invited to join the study by a healthcare professional. They were then randomly divided into two groups: an intervention group (50 participants) and a control group (50 participants). Those in the intervention group were drawn from three health centers, where they received the educational intervention. Conversely, participants in the control group were selected from two separate health centers. Taking into account a confidence level of 95% and a power of 80%, and based on the findings of the previous study [34] which reported the mean treatment adherence scores among patients with type 2 diabetes in Iran as 61.22 for the intervention group and 58.91 for the control group, with standard deviations of 3.04 and 4.37 respectively, the minimum sample size required for the study is at least 42 individuals in each group. To account for potential sample rejection rate, 50 participants from each group were included in the study.

Inclusion and Exclusion Criteria

Inclusion criteria for the study encompassed individuals aged 60 years and above, without any mental disorders, possessing the physical and cognitive ability to answer questions, and providing consent to participate. All patients had a medical record at a health center located near their residence. They were evaluated by a physician and a healthcare specialist, who reviewed their medical records. Patients diagnosed with a mental or cognitive disorder by a physician and noted in their records were excluded from the study. Additionally, patients with comorbidities such as kidney failure or severe heart disease were also excluded. Moreover, exclusion criteria included a lack of willingness to participate, incomplete responses to the questionnaire, or missing attendance at two training sessions.

Content and educational intervention

The control group participants were provided with standard education and routine guidance on managing diabetes at healthcare facilities. In contrast, those in the intervention group attended six educational sessions designed around the IMB model. This IMB-focused intervention was tailored to promote medication adherence and was formulated using an intervention mapping strategy (Table 1) [23]. A session was conducted with the participation of a patient’s family member acting as a supporter. For each component of the information-motivation-behavioral skills model, a pamphlet and an educational video were developed, taking into account the results of a needs assessment that considered both desires and preferences, as well as input from the researchers. Two posters were also prepared for information purposes and placed in health centers under intervention.

Weekly sessions were conducted from 9 to 10 AM, each lasting roughly 40 min, over a six-week period. These sessions were facilitated and managed by a master’s student specializing in health education and promotion, who was also a research team member and an expert in healthcare. Around 20 min in each session were dedicated to open discussions, giving participants the opportunity to ask questions or share their experiences. To reinforce the material covered, participants received both a pamphlet and an educational video at the conclusion of each training session.

The initial two sessions emphasized the informational aspect. During these sessions, patients were instructed on the proper method and timing for taking their medication, the potential side effects of inconsistent use, and the appropriate dosage. The theoretical method used for this component was discussion [23]. At that time, the trainer engaged with the participants to review the topics covered. They were encouraged to seek clarification on anything they found unclear, and comprehensive explanations were provided.

Two sessions were dedicated to the motivation component as well. These sessions primarily aimed to foster motivation by emphasizing the development of positive attitudes, enhancing feelings of social support, and strengthening perceptions of subjective norms [35]. The needs assessment carried out in this study highlighted participants’ beliefs regarding the potential advantages of medication adherence. The key messages aimed at addressing these beliefs emphasized trust in recovery, confidence in preventing side effects, and assurance of an undisturbed lifestyle with medication adherence. Consequently, the design and approach for fostering theoretical change, particularly in relation to attitudes and self-appraisal reassessment [23], were carefully incorporated. In the motivation component, sessions progressed by applying the theoretical method of replacing “information about others approval” to enhance patients’ social motivation. Patients engaged in discussions about the consistency of medication use among individuals with type 2 diabetes, sharing insights and recognizing one another’s positive habits under the trainer’s guidance. Furthermore, to promote mental norms that support medication adherence, a dedicated session was organized, involving a family member as a supporter and caregiver to further encourage and reinforce this behavior. The final two sessions were designed to enhance patients’ behavioral skills. Research indicates that interventions targeting self-efficacy and teaching practical strategies, such as setting reminders like phone alert colors for medication adherence, can be effective [35]. In this context, we concentrated on boosting patients’ perceived self-efficacy by employing theoretical methods of change, including self-monitoring of behavior and planning coping responses [23].

The process of providing follow-up education on medication adherence has been reported to take up to a month [36]. According to American guidelines, a minimum period of six weeks is recommended for evaluating the response to treatment, while the American Diabetes Association suggests extending this period to two to three months [37, 38]. In the present study, we considered two months and data were collected before and two months after the implementation of the intervention. Creating educational materials such as videos, pamphlets, and posters focused on the practical application of IMB components. The approach also emphasized interpersonal engagement across all IMB components. Table 1 outlines the determinants, goals of change, message, theoretical method of change, and parameters, utilized in the current program, following the intervention mapping approach.

Table 1 Outlines the determinants, goals of change, message, theoretical method of change, and parameters
Full size table

Questionnaire

In this study, we collected data from participants through interviews and a written questionnaire, which was divided into three sections.

The first section captured the demographic characteristics of participants, including age, duration since diabetes diagnosis, gender, education level, marital status, occupation, economic status, household size, smoking habits, type of treatment, family history of diabetes, health insurance coverage, and use of blood pressure-lowering medications.

The second section evaluated components of the IMB model. This part was developed based on prior research that utilized the IMB model to assess medication adherence among individuals with diabetes [26,27,28,29,30,31,32]. It included five items (e.g., “I know the right time to take my medication”) for information. The motivation component comprised two constructs: personal motivation and social motivation. The personal motivation segment included four items regarding attitudes towards medication adherence (e.g., “Thinking about taking diabetes medication every day for the rest of my life frustrates me”), while the social motivation segment contained two items reflecting subjective norms (e.g., “Most people important to me support my adherence to diabetes medication”).

Behavioral skills were assessed through two constructs: perceived self-efficacy and individual’s objective skills. Perceived self-efficacy included three items (e.g., “I am confident that I will continue taking my medication even when I feel unwell”), while individual’s objective skills comprised nine items (e.g., “I have set reminders for myself to take my diabetes medication”). A higher score in each construct indicated a more favorable situation. To facilitate participant responses, all items were rated on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). This study also evaluated the face validity, content validity, and reliability of the IMB model questionnaire components, with detailed explanations provided in subsequent sections.

Face validity evaluation

Face validity refers to the degree to which the measured elements appear suitable for assessing the intended concept. In simpler terms, it evaluates how well the items align with the subject in terms of appearance, logical coherence, proportionality, appeal, logical sequencing, practical usefulness, and overall significance. This evaluation particularly emphasizes the perspective of the target audience [39, 40]. The face validity of the questionnaire was assessed using qualitative methods. Individual face-to-face interviews were conducted with 12 experts, whose feedback was analyzed, leading to necessary modifications. The group of experts included professionals from various fields, such as general practitioners, health experts caring for diabetic patients, endocrinologists, health education specialists, and health policymakers.

Content validity evaluation

Content validity assesses the extent to which the selected items effectively represent the characteristics of the construct being measured. It ensures that the items included are appropriate and sufficient for capturing the essence of the concept [39, 40]. The content validity of the IMB model questionnaire was evaluated using both quantitative and qualitative approaches. Similar to the face validity evaluation, feedback was gathered from 12 experts regarding the difficulty, relevance, and clarity of the items. Their suggestions were carefully reviewed, and modifications were made accordingly. For the quantitative evaluation, a separate group of 12 experts classified each item as “essential,” “useful but not essential,” or “not essential.” The feedback collected was used to calculate the Content Validity Ratio (CVR) and Content Validity Index (CVI). The CVR ensured that the most critical content was retained, while the CVI assessed whether the questionnaire items were appropriately designed to measure the intended content. According to the Lawshe table, the minimum acceptable values for CVR and CVI were established at 0.62 and 0.79, respectively [39, 40]. All items were approved based on the CVA and CVR evaluations.

Reliability evaluation

Reliability refers to the consistency and stability of a measurement instrument. An instrument is considered reliable if it yields similar results under comparable conditions and with similar methods [41]. In our study, reliability was assessed using Cronbach’s alpha coefficient, with a value above 0.65 generally deemed acceptable [41]. A pilot study involving 30 participants from the target group was conducted prior to the main project. The Cronbach’s alpha coefficients for the constructs of information, attitude, subjective norms, self-efficacy, and objective skills were 0.85, 0.81, 0.75, 0.73, and 0.74, respectively.

The third section focused on evaluating patients’ medication adherence, using a standardized 5-item questionnaire that included statements such as “I sometimes forget to take one of my medications” [42]. In this study, the questionnaire demonstrated a Cronbach’s alpha of 0.79, indicating good reliability.

Data analysis

The data collected were analyzed using SPSS version 16 statistical software, employing appropriate statistical tests. The background and demographic variables of the intervention and control groups were compared through chi-square (χ2) tests and independent two-sample t-tests. To assess and compare the means of the studied variables, independent two-sample t-tests and paired t-tests were conducted. Additionally, mean changes before and after the intervention were reported. The effect size, calculated using Cohen’s d, was determined for the studied variables. This was done by subtracting the mean score of the control group from that of the intervention group and dividing the result by their pooled standard deviation. An effect size score ranging from 0 to 0.2 was categorized as small, 0.2 to 0.5 as medium, 0.5 to 0.8 as large, and above 0.8 as very large [43]. It is worth mentioning that the normality of the IMB components and medication adherence was assessed and confirmed using the Kolmogorov-Smirnov test.

Results

All participants remained actively engaged throughout the program, including the intervention phases, follow-up, and data collection, both before the program implementation and two months after the intervention.

The analysis shows that there are no statistically significant differences between the two groups across various demographic and health-related factors. For instance, the mean age of participants in the intervention group was 71.48 years, compared to 69.30 years in the control group, with a p-value of 0.102, indicating no significant age difference. In addition, the mean of diabetes duration participants in the intervention group was 9.68 years (SD: 6.71), compared to 8.64 years (SD: 5.78) in the control group, with a p-value of 0.409, indicating no significant diabetes duration difference. Table 2 presents a comparison of background variables between the intervention and control groups in the study. Variables such as sex, marital status, job status, education level, economic status, family size, health insurance coverage, type of treatment, family history of diabetes, smoking status, and use of blood pressure-lowering medications all yielded p-values greater than 0.05, suggesting comparable characteristics between the groups. These findings reinforce the validity of the study by ensuring that the intervention and control groups are similar in their baseline characteristics, which minimizes potential confounding variables. This homogeneity is crucial for attributing any observed effects on medication adherence specifically to the intervention implemented, rather than to pre-existing differences between the groups.

Table 2 Comparison of background variables between intervention and control groups
Full size table

Table 3 presents a comparison of the IMB components’ scores among participants in both intervention and control groups before and after the implementation of the intervention. The intervention group exhibited significant improvements across several components, particularly in “Information,” where the effect size was very large (1.3) with a substantial average rate of change (3.84) and a paired sample t-test result of < 0.001. This indicates that the intervention had a profound impact on the participants’ information. In contrast, the control group showed minimal changes, with no significant improvements in the same component. Other components such as “Attitude” and “Self-efficacy” also demonstrated large effect sizes (0.65 and 0.67, respectively) in the intervention group, further underscoring the program’s effectiveness. However, “Subjective Norms” displayed a small effect size (0.11) with no significant changes in either group. Additionally, the intervention group for medication adherence demonstrated a very large effect size of 1.15, with an average rate of change of 2.84 and a paired sample t-test result of < 0.001, indicating a significant improvement in medication adherence from an average score of 16.92 (SD = 2.80) before the intervention to 19.76 (SD = 3.10) afterward. In contrast, the control group showed minimal change, with a slight increase in scores from 16.12 (SD = 2.47) to 16.50 (SD = 2.54) and a non-significant p-value of 0.252. This data highlights the efficacy of the intervention in enhancing medication adherence among intervention group participants compared to the control group, which remained relatively stable.

Table 3 Comparison of scores of components of the IMB among participants in the intervention and control groups before and after the implementation of the program
Full size table

Discussion

The results of our study demonstrated that implementing the intervention substantially improved the information scores in the intervention group. The calculated effect size for this improvement was 1.3, reflecting a very large impact. Supporting this observation, Nouri et al. similarly reported a very large effect size of 3.2 for knowledge construct among type 2 diabetes patients in Isfahan, Iran [44]. Moreover, Ahmed et al., in their study involving 100 patients with type 2 diabetes in Port Said, Egypt, found that the average knowledge score significantly increased from 2.69 before the intervention to 5.30 afterward [45]. The current study employed the theoretical approach of discussion-based change to address information construct. Similar to our findings, previous research has highlighted the efficacy of this method of change in enhancing information management among individuals with chronic illnesses [46, 47]. Based on the findings of our study, it is crucial for patients with type 2 diabetes to engage in educational programs that utilize discussion-based approaches to enhance their understanding of diabetes management. The substantial improvements in knowledge scores observed in our research, highlight the efficacy of interactive learning environments. Therefore, healthcare providers should prioritize the implementation of group discussions and peer-led sessions within educational frameworks, as these methods not only foster a deeper understanding of diabetes but also encourage patient engagement and motivation. Additionally, incorporating regular assessments of knowledge and self-management practices can help tailor educational interventions to meet individual needs. By actively involving patients in their learning process and promoting continuous dialogue about their experiences, healthcare professionals can empower individuals with type 2 diabetes to take control of their health, ultimately leading to improved clinical outcomes.

The mean attitude score among patients in the intervention group improved from 14.24 to 15.38 following the intervention, with the increase being statistically significant. The calculated effect size was 0.65, reflecting a large effect on the attitude construct. These results align with findings from multiple studies, which have reported significant improvements in attitude scores post-intervention. For instance, Ahmed et al. conducted a study with type 2 diabetes patients in Egypt and observed a notable rise in their mean attitude scores after the intervention was implemented [45]. A study conducted by Malathy et al. in India also demonstrated the beneficial impact of an educational intervention on enhancing the attitudes of patients with type 2 diabetes [48]. In this study, we adopted self-reevaluation as a theoretical framework for understanding attitude change. This method involves encouraging patients to evaluate themselves both cognitively and emotionally regarding their actions or inactions related to healthy behaviors—specifically in our study, medication adherence [23]. Our findings highlighted the effectiveness of this approach in fostering behavior change among individuals with type 2 diabetes. Based on the significant improvements in attitude scores observed following the intervention, it is essential for healthcare providers to implement structured educational programs that utilize self-reevaluation techniques for patients with type 2 diabetes. These programs should encourage patients to critically assess their own behaviors and beliefs regarding medication adherence and lifestyle choices. By facilitating a reflective process, patients can develop a deeper understanding of the consequences of their actions, ultimately leading to more positive attitudes towards their treatment plans. Regular follow-ups and assessments of patient attitudes should also be conducted to ensure that the educational interventions remain effective and responsive to individual needs, thereby optimizing adherence and improving overall health outcomes.

Our analysis revealed a notable difference in self-efficacy scores between the intervention and control groups following program implementation. While the change in the intervention group’s mean self-efficacy score before and after the program was not statistically significant, there was a 0.5-point increase in their mean score. The intervention’s estimated effect size for this construct was 0.67, reflecting a large effect size. Similarly, Nouri et al., in their clinical trial aimed at improving treatment adherence among patients with type 2 diabetes in Isfahan, reported an estimated effect size of 0.63 (also large) for the construct of perceived self-efficacy [44]. A study by Mirzaei-Alavijeh et al. [34] in Tehran found a large effect size of 0.78 for the intervention’s impact on self-efficacy related to treatment adherence behaviors among patients with type 2 diabetes. Similarly, research by Jalilian et al. reported a significant enhancement in self-efficacy for self-management behaviors in the same patient population [49]. Lee et al.‘s study conducted in South Korea also observed a meaningful rise in perceived self-efficacy scores among intervention group participants with type 2 diabetes [50]. Additionally, Toygar et al. identified an effect size of 1.233 for self-care self-efficacy in their research on patients with type 2 diabetes [51]. Furthermore, a systematic review by Alharbi et al. concluded that diabetes self-management education interventions substantially improve self-efficacy, empowering individuals with type 2 diabetes to better manage their blood glucose levels [52]. Self-efficacy encompasses an individual’s cognitive, social, and skill-based capabilities essential for carrying out a specific action. It refers to one’s assessment of their ability to plan and execute tasks that demand particular types of performance [53]. As the findings showed, following the implementation of the intervention, the mean individual’s objective skills score among patients in the intervention group showed a significant improvement. Consistent with this result, a study by Bakır et al. in Turkey demonstrated that an educational program significantly enhanced the behavioral skills of patients with type 1 diabetes [30]. In contrast to the current findings, Jeon and Park, in their single-group intervention study based on the information-motivation model and behavioral skills framework for patients with diabetes, reported that the intervention had no significant impact on enhancing the patients’ self-care behavioral skills scores [31]. The current study incorporated two theoretical approaches to facilitate change: self-monitoring of behavior and planning coping responses, both utilized as part of the behavioral skills component. In a related study, Choi et al. emphasized the importance of hands-on skills training paired with numerical benchmarks for enhancing behavioral skills among patients with type 2 diabetes [29]. The findings of a systematic review highlight the effectiveness of various methods in promoting behavioral self-management skills for chronic diseases. These methods include role-playing, psychoeducational techniques such as targeted instruction provided by healthcare professionals or peer mentors, and the use of customized modules or kits designed for specific diseases [35]. Based on the findings regarding self-efficacy and behavioral skills in patients with type 2 diabetes, it is crucial for healthcare practitioners to develop and implement comprehensive educational interventions that focus on enhancing self-efficacy and practical self-management skills. These programs should incorporate hands-on training methods, such as role-playing and scenario-based exercises, to allow patients to practice skills in real-life contexts. For instance, teaching patients how to set medication reminders or develop strategies for managing their health while traveling can significantly improve their confidence in adhering to treatment plans. Future research could explore and compare the impact of theory of change approaches on enhancing behavioral skills or other components of the IMB model. In general, it seems intervention content designed to help patients discover strategies for maintaining adherence in various situations, such as setting reminder alerts or managing medications while traveling, can enhance their behavioral skills for consistent medication adherence.

The results of this study revealed that the implemented intervention did not significantly enhance subjective norms associated with consistent medication adherence in patients with type 2 diabetes. Contrary to these findings, Burner et al. identified mHealth as a feasible, well-accepted, and potentially effective approach to strengthening social support among individuals with diabetes [54]. In alignment with this finding, Mirzaei-Alavijeh et al. noted in their study that the intervention carried out showed no significant impact on enhancing the social support scores among patients with type 2 diabetes [34]. Social support involves receiving technical guidance and help with health-related behaviors from friends, family members, colleagues, and healthcare professionals [55]. This study included not only an intervention for patients but also a session for the families of individuals with type 2 diabetes. The session emphasized the importance of ensuring elderly patients adhere to regular medication schedules. However, it did not lead to a noticeable improvement in the patients’ subjective norms scores. Future research is recommended to determine the primary sources of support for patients with type 2 diabetes in Iran and to develop targeted interventions aimed at enhancing subjective norms and social support for these individuals.

Our findings revealed a notable enhancement in medication adherence among patients in the intervention group. The estimated effect size for this improvement was 1.15, indicating a very large impact. This aligns with prior research demonstrating that self-care behaviors tend to improve following diabetes education programs. For instance, Mirzaei-Alavijeh et al. reported an estimated effect size of 0.62 (large) for adherence behaviors in their study involving patients with type 2 diabetes [34]. Similarly, Lee et al. highlighted the effectiveness of educational interventions in fostering self-care practices in their research on patients with type 2 diabetes in South Korea [50]. The findings of a systematic review by Nieuwlaat et al., indicated that only a few implemented interventions have led to improved medication adherence and more favorable clinical outcomes for patients. They stated that current methods for enhancing adherence to medication for chronic health issues are primarily complex and not very effective. The lack of improvement in treatment adherence following the implementation of programs can often be attributed to the absence of individualized strategies tailored to the specific needs of patients. This evidence highlights the complexity of behavior change and emphasizes the need to adopt comprehensive approaches that consider the psychological, social, and contextual factors influencing treatment adherence [56]. Given the findings that indicate a significant improvement in medication adherence among patients in the intervention group, it is essential for healthcare providers to refine and enhance diabetes education programs. To address the contradictory results reported in various studies, interventions should focus on personalized strategies that cater to the unique needs and circumstances of each patient. This could involve conducting thorough assessments to identify individual barriers to adherence and employing tailored educational materials that resonate with patients’ specific experiences and preferences. Moreover, incorporating behavioral change techniques such as motivational interviewing, goal-setting, and self-monitoring can further strengthen the effectiveness of these interventions. Engaging patients in their care by fostering a collaborative environment where they feel empowered to take ownership of their health can lead to more sustainable behavior changes. Additionally, integrating support systems, such as peer mentoring or follow-up consultations, may help reinforce learning and provide ongoing encouragement. By adopting a more holistic and individualized approach, healthcare professionals can improve the efficacy of interventions aimed at enhancing medication adherence in patients with type 2 diabetes.

This study was designed to address the research gap in the use of the IMB model to increase medication adherence in elderly diabetic patients in Iran. The use of a valid theoretical framework, the IMB model, increased the scientific validity of the study, and the comprehensive intervention design, including education, motivation, and behavioral skills improvement, provided a multifaceted approach for better effectiveness. Involvement of family members, use of diverse educational tools, interactive and structured sessions, and two-month follow-up assessment are other strengths that enhance the efficacy of the intervention. However, this study is not without its limitations. Reliance on self-reported measures may have led to recall bias and social desirability bias. Nonetheless, the use of questionnaires offers a practical and cost-effective approach to gathering valuable insights into individuals’ reasons for non-adherence [57]. It is worth noting, however, that objective methods for measuring adherence to regular medication were not employed, nor were patients’ clinical indicators assessed.

Conclusion

We developed a program to enhance medication adherence among older adults with type 2 diabetes, based on the IMB model, achieving a very large increase in adherence. Our findings highlight the effectiveness of specific theoretical approaches to behavior change, offering valuable insights for future interventions. Researchers and healthcare providers should prioritize clear guidance on medication routines through lectures, educational videos, pamphlets, and interactive discussions. To boost motivation, health educators can foster positive attitudes and emphasize social support and shared norms. Additionally, employing change theory techniques like self-monitoring and coping strategies can enhance patients’ self-efficacy, further improving treatment adherence. Future studies should explore the long-term effects of these interventions and investigate the impact of personalized strategies tailored to individual patient needs.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Teo V, Weinman J, Yap KZ. Systematic review examining the behavior change techniques in medication adherence intervention studies among people with type 2 diabetes. Ann Behav Med. 2024;58(4):229–41.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Shi H, Liu C, Luo HY. Impact of community public health care on treatment effect, health cognition, and self-management in patients with type 2 diabetes. World J Clin Cases. 2025;13(5):95183.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Panahi N, Ahmadi M, Hosseinpour M, Sedokani A, Sanjari M, Khalagi K, Mansourzadeh MJ, Farhadi A, Nabipour I, Larijani B, Fahimfar N. The association between quality of life and diabetes: the Bushehr elderly health program. BMC Geriatr. 2024;24(1):267.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Fotouhi F, Rezvan F, Hashemi H, Javaherforoushzadeh A, Mahbod M, Yekta A, Jamshididana Z, Khabazkhoob M. High prevalence of diabetes in elderly of Iran: an urgent public health issue. J Diabetes Metabolic Disorders. 2022;21(1):777–84.

    Article  CAS  Google Scholar 

  5. Jalilian H, Heydari S, Imani A, Salimi M, Mir N, Najafipour F. Economic burden of type 2 diabetes in Iran: A cost-of‐illness study. Health Sci Rep. 2023;6(2):e1120.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Sayyed Kassem L, Aron DC. The assessment and management of quality of life of older adults with diabetes mellitus. Expert Rev Endocrinol Metabolism. 2020;15(2):71–81.

    Article  CAS  Google Scholar 

  7. Lim D, Woo K. Medication adherence and related factors among older adults with type 2 diabetes who use home health care. Geriatr Nurs. 2025;61:270–7.

    Article  PubMed  Google Scholar 

  8. Wong SK, Lew J, Soon W, Griva K, Smith HE, Lim SC. Profiles of knowledge, self-efficacy, psychological and physical health in type 2 diabetes and its association with outcomes. Patient Educ Couns. 2025;130:108482.

    Article  PubMed  Google Scholar 

  9. Worrall C, Shirley D, Bullard J, Dao A, Morrisette T. Impact of a clinical pharmacist-led, artificial intelligence–supported medication adherence program on medication adherence performance, chronic disease control measures, and cost savings. J Am Pharmacists Association. 2025;65(1):102271.

    Article  Google Scholar 

  10. Khardali A, Syed NK, Alqahtani SS, Qadri M, Meraya AM, Rajeh N, Aqeely F, Alrajhi S, Zanoom A, Gunfuthi S, Basudan W. Assessing medication adherence and their associated factors amongst type-2 diabetes mellitus patients of Jazan Province, Saudi Arabia: A single-center, cross-sectional study. Saudi Pharm J. 2024;32(1):101896.

    Article  PubMed  Google Scholar 

  11. Kwakye AO, Kretchy IA, Peprah P, Mensah KB. Factors influencing medication adherence in co-morbid hypertension and diabetes patients: A scoping review. Exploratory Res Clin Social Pharm. 2024:100426.

  12. Krass I, Schieback P, Dhippayom T. Adherence to diabetes medication: a systematic review. Diabet Med. 2015;32(6):725–37.

    Article  PubMed  CAS  Google Scholar 

  13. Piragine E, Petri D, Martelli A, Calderone V, Lucenteforte E. Adherence to oral antidiabetic drugs in patients with type 2 diabetes: systematic review and meta-analysis. J Clin Med. 2023; 12(5).

  14. Kooshyar H, Shoorvazi M, Dalir Z, Hosseini M. Health literacy and its relationship with medical adherence and health-related quality of life in diabetic community-residing elderly. J Mazandaran Univ Med Sci. 2013;22(1):134–43.

    Google Scholar 

  15. DiBonaventura M, Wintfeld N, Huang J, Goren A. The association between nonadherence and glycated hemoglobin among type 2 diabetes patients using basal insulin analogs. Patient Prefer Adherence. 2014:873–82.

  16. Presley B, Groot W, Pavlova M. Pharmacy-led interventions to improve medication adherence among adults with diabetes: a systematic review and meta-analysis. Res Social Administrative Pharm. 2019;15(9):1057–67.

    Article  Google Scholar 

  17. Jüngst C, Gräber S, Simons S, Wedemeyer H, Lammert F. Medication adherence among patients with chronic diseases: a survey-based study in pharmacies. QJM. 2019;112(7):505–12.

    Article  PubMed  Google Scholar 

  18. Gow K, Rashidi A, Whithead L. Factors influencing medication adherence among adults living with diabetes and comorbidities: a qualitative systematic review. Curr Diab Rep. 2024;24(2):19–25.

    Article  PubMed  Google Scholar 

  19. Chong CJ, Makmor-Bakry M, Hatah E, Tahir NA, Mustafa N, Capule FR, Hermansyah A. A qualitative study of type 2 diabetes mellitus outpatients’ perspectives on readiness, acceptance and barriers of mobile apps for medication adherence. Patient Educ Couns. 2025;131:108547.

    Article  PubMed  Google Scholar 

  20. Teo V, Weinman J, Yap KZ. A cultural adaptation and validation study of the intentional nonadherence scale (INAS) among people with type 2 diabetes in Singapore. J Psychosom Res. 2025;188:111969.

    Article  PubMed  Google Scholar 

  21. Lekha PP, Abdul Azeez EP. Psychosocial facilitators and barriers to type 2 diabetes management in adults: A meta-synthesis. Curr Diabetes Rev. 2024;20(8):110–23.

    Article  PubMed  Google Scholar 

  22. Seo S, Kim CJ, Kang HS, Kim DJ, Schlenk EA. Medication-Taking Trajectory and Its Correlates in Patients With Diabetes: Based on the Information–Motivation–Behavioral Skills Model. The Science of Diabetes Self-Management and Care. 2024: 26350106241293120.

  23. Kok G, Gottlieb NH, Peters GJ, Mullen PD, Parcel GS, Ruiter RA, Fernández ME, Markham C, Bartholomew LK. A taxonomy of behaviour change methods: an intervention mapping approach. Health Psychol Rev. 2016;10(3):297–312.

    Article  PubMed  Google Scholar 

  24. Fisher JD, Fisher WA. Changing AIDS-risk behavior. Psychol Bull. 1992;111(3):455.

    Article  PubMed  CAS  Google Scholar 

  25. Park NY, Jang S. Effects of mHealth practice patterns on improving metabolic syndrome using the Information–Motivation–Behavioral skills model. Nutrients. 2024;16(13):2099.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Akbari M, Seydavi M, Rowhani NS, Nouri N. Psychological predictors of treatment adherence among patients with diabetes (types I and II): modified information–motivation–behavioural skills model. Clin Psychol Psychother. 2022;29(6):1854–66.

    Article  PubMed  Google Scholar 

  27. Gao J, Wang J, Zhu Y, Yu J. Validation of an information–motivation–behavioral skills model of self-care among Chinese adults with type 2 diabetes. BMC Public Health. 2013;13:1–6.

    Article  CAS  Google Scholar 

  28. Osborn CY, Egede LE. Validation of an Information–Motivation–Behavioral skills model of diabetes self-care (IMB-DSC). Patient Educ Couns. 2010;79(1):49–54.

    Article  PubMed  Google Scholar 

  29. Choi S, Song M, Chang SJ, Kim SA. Strategies for enhancing information, motivation, and skills for self-management behavior changes: a qualitative study of diabetes care for older adults in Korea. Patient preference and adherence. 2014: 219– 26.

  30. Bakır E, Çavuşoğlu H, Mengen E. Effects of the information–motivation–behavioral skills model on metabolic control of adolescents with type 1 diabetes in Turkey: randomized controlled study. J Pediatr Nurs. 2021;58:e19–27.

    Article  PubMed  Google Scholar 

  31. Jeon E, Park HA. Experiences of patients with a diabetes self-care app developed based on the information-motivation-behavioral skills model: before-and-after study. JMIR Diabetes. 2019;4(2):e11590.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Dai Z, Jing S, Liu X, Zhang H, Wu Y, Wang H, Xiao W, Huang Y, Fu J, Chen X, Gao L. Development and validation of the diabetic self-management scale based on information-motivation-behavioral skills theory. Front Public Health. 2023;11:1109158.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Perseh L, Peimani M, Ghasemi E, Nasli-Esfahani E, Rezaei N, Farzadfar F, Larijani B. Inequalities in the prevalence, diagnosis awareness, treatment coverage and effective control of diabetes: a small area Estimation analysis in Iran. BMC Endocr Disorders. 2023;23(1):17.

    Article  Google Scholar 

  34. Mirzaei-Alavijeh M, Hosseini SN, Niksirt M, Hashemian AH, Khashij S, Jalilian F. The efficacy of theory driven treatment adherence promotion program among type 2 diabetic patients: application of intervention mapping and mHealth. J Diabetes Metabolic Disorders. 2023;22(2):1609–15.

    Article  Google Scholar 

  35. Chang SJ, Choi S, Kim SA, Song M. Intervention strategies based on information-motivation-behavioral skills model for health behavior change: a systematic review. Asian Nurs Res. 2014;8(3):172–81.

    Article  Google Scholar 

  36. Atolagbe ET, Sivanandy P, Ingle PV. Effectiveness of educational intervention in improving medication adherence among patients with diabetes in Klang Valley, Malaysia. Front Clin Diabetes Healthc. 2023;4:1132489.

    Article  Google Scholar 

  37. American Diabetes Association. Standards of medical care in diabetes—2011. Diabetes Care. 2011;34(Supplement1):S11–61.

    Article  PubMed Central  Google Scholar 

  38. Sidorenkov G, Haaijer-Ruskamp FM, de Zeeuw D, Denig P. A longitudinal study examining adherence to guidelines in diabetes care according to different definitions of adequacy and timeliness. PLoS ONE. 2011;6(9):e24278.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health. 2007;30(4):459–67.

    Article  PubMed  Google Scholar 

  40. Lawshe CH. A quantitative approach to content validity. Pers Psychol. 1975;28(4):563–75.

    Article  Google Scholar 

  41. Vaske JJ, Beaman J, Sponarski CC. Rethinking internal consistency in Cronbach’s alpha. Leis Sci. 2017;39(2):163–73.

    Article  Google Scholar 

  42. Lin CY, Ou HT, Nikoobakht M, Broström A, Årestedt K, Pakpour AH. Validation of the 5-item medication adherence report scale in older stroke patients in Iran. J Cardiovasc Nurs. 2018;33(6):536–43.

    Article  PubMed  Google Scholar 

  43. Goulet-Pelletier JC, Cousineau D. A review of effect sizes and their confidence intervals, part I: the Cohen’sd family. Quant Methods Psychol. 2018;14(4):242–65.

    Article  Google Scholar 

  44. Nouri K, Nazari M, Kaveh MH, Hosseini FS. Effectiveness of a Health Belief Model-based Educational Intervention on Treatment Adherence among Type 2 Diabetic Patients: Insights from a Randomized Controlled Trial in Iran. changes. 2024; 1:3.

  45. Ahmed MM, Degwy HM, Ali MI, Hegazy NH. The effect of educational intervention on knowledge, attitude and glycemic control in patients with type 2 diabetes mellitus. Int J Community Med Public Health. 2015;2(3):302e7.

    Google Scholar 

  46. Illa L, Echenique M, Jean GS, Bustamante-Avellaneda V, Metsch L, Mendez-Mulet L, Eisdorfer C, Sanchez-Martinez M, Project ROADMAP. Reeducating older adults in maintaining AIDS prevention: a secondary intervention for older HIV-positive adults. AIDS Educ Prev. 2010;22(2):138–47.

    Article  PubMed  Google Scholar 

  47. Mirzaei-Alavijeh M, de Vries H, Hamzeh B, Mansouri F, Rahimi F, Jalilian F. Promotion of medication adherence program among AIDS patients: application of the I-Change model. Clin Med. 2022;29(2):110–9. (Persian Article).

    Google Scholar 

  48. Malathy R, Narmadha MP, Jose MA, Ramesh S, Babu ND. Effect of a diabetes counseling programme on knowledge, attitude and practice among diabetic patients in erode district of South India. J Young Pharmacists. 2011;3(1):65–72.

    Article  CAS  Google Scholar 

  49. Jalilian F, Zinat Motlagh F, Solhi M, Gharibnavaz H. Effectiveness of self-management promotion educational program among diabetic patients based on health belief model. J Educ Health Promot. 2014;3:14.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Lee SK, Shin DH, Kim YH, Lee KS. Effect of diabetes education through pattern management on self-care and self-efficacy in patients with type 2 diabetes. Int J Environ Res Public Health. 2019;16(18):3323.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Toygar İ, Hançerlioğlu S, Utku T, Şimşir IY, Çetinkalp Ş. Effect of an educational intervention based on Bandura’s theory on foot care self-efficacy in diabetes: a prospective quasi-experimental study. Int J Low Extrem Wounds. 2022;21(4):414–9.

    Article  PubMed  Google Scholar 

  52. Alharbi TA, Alhumaidi B, Alharbi MN, Ngo AD, Alasqah I, Alharbi HF, Albagawi B. Diabetes education self-management intervention in improving self-efficacy for people with type 2 diabetes in the Gulf Cooperation Council countries: a systematic review. Diabetes Metabolic Syndrome: Clin Res Reviews. 2023;17(12):102906.

    Article  CAS  Google Scholar 

  53. Bandura A. Self-efficacy mechanism in human agency. Am Psychol. 1982;37(2):122.

    Article  Google Scholar 

  54. Burner E, Lam CN, DeRoss R, Kagawa-Singer M, Menchine M, Arora S. Using mobile health to improve social support for low-income Latino patients with diabetes: a mixed-methods analysis of the feasibility trial of TExT-MED + FANS. Diabetes Technol Ther. 2018;20(1):39–48.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Shariful IM. Theories applied to m-health interventions for behavior change in low-and middle-income countries: a systematic review. Telemedicine e-Health. 2018;24(10):727–41.

    Article  Google Scholar 

  56. Nieuwlaat R, Wilczynski N, Navarro T, Hobson N, Jeffery R, Keepanasseril A, Agoritsas T, Mistry N, Iorio A, Jack S, Sivaramalingam B. Interventions for enhancing medication adherence. Cochrane Database Syst Reviews. 2014(11): CD000011.

  57. Stirratt MJ, Dunbar-Jacob J, Crane HM, Simoni JM, Czajkowski S, Hilliard ME. Self-report measures of medication adherence behavior: recommendations on optimal use. Transl Behav Med. 2015;5(4):470–82.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We want to express our gratitude to the elderly individuals who participated in the study. We also want to thank the Research Vice-Chancellor at Kermanshah University of Medical Sciences for their support in this project. Additionally, we are thankful for the collaboration of the Clinical Research Development Center at Motazedi Hospital in Kermanshah.

Funding

This research was carried out as part of a Master’s thesis (Code: 4020855) in the field of health education and promotion. It received support from Kermanshah University of Medical Sciences.

Author information

Authors and Affiliations

  1. Social Development and Health Promotion Research Center, Health Policy and Promotion Research Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Mehdi Mirzaei-Alavijeh & Shima Khashij

  2. Department of Health Education and Promotion, School of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Saba Yarmoradi

  3. Family Health and Population Growth Research Center, Health Policy and Promotion Research Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Farzad Jalilian

Authors
  1. Mehdi Mirzaei-Alavijeh
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Saba Yarmoradi
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Shima Khashij
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Farzad Jalilian
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

“M.M.A. and F.J. contributed to the idea of study interpretation. F.J. contributed to the data analysis. M.M.A. and F.J. contributed to the set-out of the first draft of the manuscript. S.Y. was involved in data collection and providing training. S.KH. contributed to the edit of the manuscript. All authors participate in the final approval of the revised manuscript for publication.”

Corresponding author

Correspondence to Farzad Jalilian.

Ethics declarations

Ethical approval

The study protocol (IR.KUMS.REC.1402.530) was approved by the research ethics committee at Kermanshah University of Medical Sciences. All procedures followed the ethical standards of the institution, national research committee, and the 1964 Helsinki Declaration along with its amendments. Participants were provided with detailed information about the study, including procedures, confidentiality of their information, and purpose before they agreed to participate. Informed consent for participation in the study was obtained from all participants. The participants were given the participant information statement and signed the consent form.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mirzaei-Alavijeh, M., Yarmoradi, S., Khashij, S. et al. Application of the information-motivation-behavioral skills model to improve medication adherence among older adults with type 2 diabetes: findings from a quasi-experimental study in Kermanshah, Iran. BMC Geriatr 25, 328 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-06000-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-06000-w

Keywords

BMC Geriatrics

ISSN: 1471-2318

Contact us