INTRODUCTION
1. Background
Diabetes is a major public health concern in older adults. In Korea, over one-third of those aged ≥65 years have diabetes and nearly half have prediabetes [1]. Sustained self-management is essential to prevent complications and maintain quality of life [2], yet older adults often face cognitive/sensory decline and multimorbidity that hinder exercise and dietary adherence, along with motivation that wanes over long disease duration [3-5]. National data continue to show limited integrated outcomes in this population [1], indicating the need for further exploration of the various factors affecting self-management.
Insulin remains one of the most effective options for glycemic control and for curbing microvascular risk [6]. Nevertheless, many patients delay or avoid treatment because of psychological barriers, including fear of injections, concerns about complications, and a sense of personal failure. These barriers, collectively termed psychological insulin resistance (PIR) [7], are consistently linked with poorer treatment adherence and less engaged self-management behavior, which in turn compromise glycemic control and downstream outcomes [8]. In parallel, patients with diabetes often experience stress owing to the emotional burden of diagnosis, treatment, and the chronic nature of the disease [9], which negatively affects diabetes management and health behavior practice. Diabetes-related stress is closely associated with the degree of self-management and blood sugar control [10]. For older adults who must coordinate multiple regimens and routines, PIR and diabetes-related stress may co-occur and compound one another, elevating the likelihood of regimen fatigue and disengagement from recommended care.
Complementary and alternative medicine (CAM) use is common in diabetes, and dietary approaches are among the most frequently reported modalities [11-13]. Some CAM practices may be perceived to enhance self-efficacy or reduce stress; however, use without adequate evidence appraisal or communication with clinicians can compete with standard care and inadvertently weaken adherence [14,15]. Among older adults with type 2 diabetes, intention to use complementary and alternative diets (CAD) reflects personal health beliefs and attitudes that are shaped by social and cultural norms as well as access and past experiences [16]. Building on the Theory of Planned Behavior and self-determination/self-regulation perspectives, ‘intention’ is the proximal determinant of behavior, formed by attitudes (expected benefits/harms), perceived norms (family, peers, media), and perceived behavioral control (self-efficacy, barriers) [17].
In this study, the researchers examine PIR, diabetes-related stress, and intention to use CAD because each targets a distinct lever of self-management—PIR undermines perceived control and treatment attitudes, diabetes-related stress depletes motivation and self-regulation, and intention to use CAD can either complement or compete with recommended care—so assessing them together clarifies their relative contributions and identifies practical targets for intervention in older adults with type 2 diabetes. Despite a growing literature, most prior studies have examined PIR or stress in isolation, focusing on single barriers rather than their joint influence in older populations [8,9,18]. Likewise, CAD-related work has often been descriptive (types and frequencies) [13], leaving unclear whether intending to use CAD adds explanatory value for self-management above and beyond PIR and diabetes-related stress [11-13,17]. Evidence that simultaneously tests PIR, diabetes-related stress, and intention to use CAD in community-dwelling older adults with type 2 diabetes remains limited. Addressing this gap is timely, as researchers increasingly encounter older patients who balance complex diabetes treatments with strong preferences for dietary alternatives.
Therefore, this study examines how PIR, diabetes-related stress, and intention to use CAD are associated with diabetes self-management among older adults with type 2 diabetes. Clarifying these linkages can inform tailored education and supportive interventions that bolster evidence-based self-management while constructively addressing patients’ preferences for complementary dietary practices.
2. Purpose
This study aimed to identify the levels of PIR, diabetes-related stress, intention to use CAD, and self-management in older adults with type 2 diabetes. It also sought to examine differences in these variables according to participants’ general characteristics, explore correlations among them, and identify factors associated with self-management.
METHODS
Ethic statement: This study was approved by the Institutional Review Board (IRB) of Gyeongkuk National University (IRB No. 1040191-202403-HR-012-02). Informed consent was obtained from the participants.
1. Study Design
This cross-sectional descriptive study examined the associations between PIR, diabetes-related stress, intention to use CAD, and self-management among adults aged 65 years or older with type 2 diabetes mellitus. The study design followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Guidelines for Observational Research (https://www.strobe-statement.org).
2. Participants
Participants were individuals aged 65 years or older, diagnosed with type 2 diabetes, receiving oral hypoglycemic agents or insulin for at least 6 months, and able to respond to surveys without physical or mental impairments. Participants were recruited from a primary healthcare facility in A city, Gyeongsangbuk-do. Participants were included after providing voluntary informed consent following an explanation of the study purpose and content. Individuals with cognitive decline or psychiatric disorders affecting communication were excluded.
The sample size was calculated using the G*Power 3.1.9.7 program (University of Dusseldorf), based on multiple regression analysis (F-test). The minimum required sample size was 160 with a significance level of 0.05, power of 0.85, a medium effect size of 0.15, and 17 predictors. These 17 predictors consisted of 14 demographic and clinical variables and three main independent variables (PIR, diabetes-related stress, and intention to use CAD). In the final analysis, however, only 11 demographic and clinical variables were retained, as three items related to types and satisfaction of CAD use were excluded due to lack of direct relevance to the study purpose. Considering a 10% anticipated dropout rate [19], 183 participants were recruited, and after excluding three incomplete responses, data from 180 participants were analyzed.
3. Measures
A structured questionnaire consisting of 11 items on general characteristics, 18 items on PIR, 17 items on diabetes-related stress, one item on the intention to use CAD, and 15 items on self-management was used.
1) General Characteristics
The general characteristics consisted of 11 items, including age, sex, education level, living arrangements, and disease-related variables (e.g., duration of diagnosis and type of medication).
2) Psychological Insulin Resistance
PIR was measured using the Korean version of the Psychological Insulin Resistance Scale, developed by Song et al. [20]. It consists of 14 items in the cognitive–psychological domain and four items in the supportive domain, for a total of 18 items. Each item is rated on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating higher levels of PIR. Cronbach’s α was .91 in Song et al. [20], and .84 in this study.
3) Diabetes-Related Stress
Diabetes-related stress was measured using the Diabetes Distress Scale, developed by Polonsky et al. [21] and modified by Choi [22]. It consists of 17 items: five items on psychological burden, four items on stress related to healthcare providers, five items on treatment-related stress, and three items on interpersonal stress. Each item is rated on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating higher stress levels. Cronbach’s α was .86 in the Korean version [22], and .76 in this study.
4) Intention to Use Complementary and Alternative Diets
A single-item measure, such as behavioral intention, is useful because it allows respondents to quickly assess their intuitive level rather than dealing with more complex measurements [23]. Therefore, a single-item scale was used to assess the intention to use CAD. The question asked, “Do you intend to use complementary and alternative diets?” rated on a scale of 1 (I do not intend to use it) to 5 (I definitely intend to use it). This item was developed for the present study by the researchers. Several candidate items were initially generated based on expert consultation; however, considering the older population, the scale was simplified to a single item to minimize respondent burden and ensure clarity.
5) Self-Management
The level of self-management of older patients with diabetes was measured using the tool developed by Gu [24]. It consists of 15 items: nine on dietary practices, three on medication adherence, and three on physical exercise. Each item is rated on a Likert scale ranging from 1 (never) to 4 (always), with higher scores indicating a higher level of self-management adherence. Cronbach’s α was .84 in Gu [24], and .80 in this study.
4. Data Collection
Data were collected from March 8 to June 12, 2024, at a primary healthcare facility in A City, Gyeongsangbuk-do. Patients aged 65 and older who voluntarily agreed to participate in the study were asked to complete a written consent form and questionnaire in the outpatient counseling room. A trained nurse read the survey questions aloud to participants who responded accordingly. The time required to complete the survey was approximately 30 minutes. After completing the questionnaire, participants were given a small token of appreciation.
5. Data Analysis
The data collected were analyzed using the SPSS/WIN 28.0 program (IBM Corp.).
1) The general characteristics of the participants, PIR, diabetes-related stress, intention to use CAD, and self-management levels were analyzed using frequency, percentage, mean, and standard deviation.
2) Differences in PIR, diabetes-related stress, intention to use CAD, and self-management according to the general participant characteristics were analyzed using t-tests and one-way analysis of variance, with post-hoc analysis conducted using Scheffé’s test.
3) The correlations between PIR, diabetes-related stress, intention to use CAD, and self-management were calculated using Pearson’s correlation coefficient.
4) Factors affecting self-management were analyzed using multiple regression analysis.
6. Ethical Considerations
The study was approved by the Institutional Review Board (IRB) of Gyeongkuk National University (IRB No. 1040191-202403-HR-012-02). Written informed consent was obtained after explaining the study purpose, voluntary participation, and data confidentiality. All data were coded, securely stored, and scheduled for disposal after publication.
RESULTS
1. General Characteristics of the Participants
The mean age of the participants was 73.79±5.59 years; 35.6% were male and 64.4% were female. Most were married (61.7%), and the most common education level was elementary school graduation (38.9%). The mean duration of diabetes was 13.28±9.03 years, and 90.0% were using oral hypoglycemic agents (Table 1).
2. Levels of Psychological Insulin Resistance, Diabetes-Related Stress, Intention to Use Complementary and Alternative Diets, and Self-Management
The mean scores for PIR, diabetes-related stress, and intention to use CAD were 57.54±8.81, 41.62±7.65, and 3.56±1.32, respectively, out of the maximum scores of 90, 85, and 5 points. The mean self-management score was 38.11±5.98 out of a maximum of 60 points (Table 2).
3. Psychological Insulin Resistance, Diabetes-Related Stress, Intention to Use Complementary and Alternative Diets, and Self-Management According to General Participant Characteristics
The PIR was significantly higher in females than in males (t=-5.81, p<.001), in participants with no formal education compared with those with higher education (F=3.51, p=.009), and in those treated with oral agents only relative to those receiving combined oral and insulin therapy (F=6.40, p=.002). Participants with HbA1c <7.5% also demonstrated higher PIR than those with HbA1c ≥7.5% (t=2.14, p=.033). Diabetes-related stress did not differ significantly across demographic or clinical characteristics. Intention to use CAD was greater among participants with prior CAD experience than among those without such experience (t=8.03, p<.001).
Self-management differed significantly according to the type of cohabitants (F=4.78, p=.009) (Table 3).
4. Correlation Among Psychological Insulin Resistance, Diabetes-Related Stress, Intention to Use Complementary and Alternative Diets, and Self-Management
Self-management was positively correlated with PIR (r=.31, p<.001) but negatively correlated with diabetes-related stress (r=-.24, p=.001). PIR also showed a positive correlation with diabetes-related stress (r=.37, p<.001) and a weak positive correlation with intention to use CAD (r=.15, p=.043). These correlation coefficients were modest and did not indicate problematic multicollinearity among the predictors (Table 4).
5. Factors Affecting Self-Management Among Older Adults With Type 2 Diabetes Mellitus
Cohabitants were included as a control variable because they showed significant differences in self-management in this study (F=4.78, p=.009). PIR, diabetes-related stress, and intention to use CAD were included as independent variables as they represented the main conceptual factors of this study, and multiple regression analysis was conducted to identify factors influencing self-management (Table 5).
Tolerance and variance inflation factor analyses confirmed the absence of multicollinearity, with tolerance values ranging from 0.846 to 0.976 (>0.1) and VIF values ranging from 1.005 to 1.182 (<10). The regression model for diabetes self-management was significant (F=14.30, p<.001); PIR (β=.47, p<.001) and diabetes-related stress (β=-.41, p<.001) were identified as significant predictors. Intention to use CAD did not significantly affect self-management (β=-.07, p=.288). The total explanatory power of the regression model (R2) was 24.6%.
DISCUSSION
This study examined the associations of PIR, diabetes-related stress, and intention to use CAD with self-management in older adults with type 2 diabetes. PIR and diabetes-related stress were significantly associated with self-management, whereas no significant association was found between intention to use CAD and self-management.
The mean PIR was 57.54 out of 90 points, which was lower than the average scores reported in previous studies [8,18]. This lower score may be attributed to participant characteristics, as the mean age in this study was higher than in previous studies and 33.3% of participants were living alone. PIR tends to decrease with age [18], and limited family support has been shown to lower the supportive subscale score [25]. In particular, the relatively high proportion of older adults living alone in this study may be closely related to the decrease in supportive subscale scores, underscoring the importance of family support in fostering positive attitudes toward insulin treatment.
PIR showed significant differences based on sex and education level, with higher scores observed in females and those with lower education levels. The finding that females had a higher PIR than males is consistent with those of previous studies [18,20], suggesting that while males tend to view insulin as a form of treatment, females are more likely to perceive it as a form of punishment [26]. Additionally, the finding that lower educational levels were associated with higher PIR is similar to that reported in a previous study [27]. This finding may be attributed to a lack of understanding of the necessity and safety of insulin treatment and differences in access to information to alleviate anxiety. Therefore, tailored educational strategies using audiovisual materials appropriate for the participants’ level of understanding are required.
Diabetes-related stress had an average score of 41.62, similar to that of a previous study [28]. Stress levels showed no significant differences based on blood sugar control or disease duration, which may be associated with the generally stable blood sugar levels and high disease awareness among the participants in this study. Among the subdomains of stress, “interpersonal stress” was the highest, which can be interpreted as the result of social isolation or the absence of family for older individuals, contributing to their emotional burden [3]. Therefore, intervention strategies are needed to strengthen social support and stress management. Diabetes-related stress was positively correlated with PIR and negatively correlated with self-management, which is consistent with previous studies indicating that lower stress levels are associated with better self-management [10].
The experience of using CAD was reported by 76.7% of the participants, and the intention to use CAD was scored at an average of 3.56. Notably, those who had previously used CAD had significantly higher intentions to use it (t=8.03, p<.001), consistent with the tendency of continued use among those with prior experience with CAM [11]. This finding suggests that the intention to use CAD may reflect self-directedness and satisfaction with treatment, consistent with the results of Chang et al. [16].
However, the intention to use CAD was not significantly associated with self-management in this study. It showed a weak positive correlation with PIR (r=.15, p=.043), suggesting that it may remain at the level of interest or an adjunctive behavior rather than an active strategy for self-management [29]. Given the high utilization rate and continued intention to use CAD, further research to systematically verify the effectiveness and safety of CAD is warranted.
The mean self-management score was 38.11 out of 60, indicating a moderate level. The subdomains included dietary control, medication adherence, and physical exercise. Among these, medication adherence was relatively high, whereas dietary control and exercise were low. This pattern is consistent with previous studies [30], which found relatively higher medication adherence than lifestyle behaviors. Targeting modifiable barriers—long-standing habits, cognitive/sensory changes, and physical constraints—while acknowledging that many older adults maintain healthy routines and seek complementary approaches to preserve autonomy and well-being [3,4,11] can facilitate effective self-care. Accordingly, nursing interventions should emphasize individualized dietary education using the food exchange table, specific and attainable step-count goals matched to functional capacity, and group-based programs that leverage peer support for continuity.
In this study, the PIR was significantly positively correlated with self-management, and multiple regression analysis identified it as a positive predictor. This finding suggests that resistance to insulin treatment may not hinder self-management, but may motivate individuals to practice more thorough self-management to avoid insulin treatment. Although the intention to use CAD did not directly affect self-management behavior, it may be chosen as an alternative strategy to satisfy the psychological desire to participate in self-care [29]. A weak correlation (r=.15, p=.043) was identified between the intention to use CAD and PIR, suggesting that patients with higher PIR may be more likely to opt for CAD. Previous studies have also reported an association between CAD use and self-management motivation [16], indicating that patients with stronger motivation tend to show greater intention to use CAD. These findings highlight the psychological factors underlying CAD use, yet further empirical research is needed to determine whether CAD intention translates into effective self-management behaviors.
This study is significant in that it identifies PIR as a positive motivator for self-management, addresses the limitations of previous research, and suggests novel directions for research. This finding supports the need for future studies on the development and effectiveness of psychological resistance reduction programs and stress management interventions for older patients with diabetes. Additionally, understanding the intention to use CAD can serve as foundational data for future research exploring the various factors influencing the health behaviors of older individuals.
This study has several limitations. CAD intention was measured with a single item, limiting its reliability and ability to capture multidimensional attributes. In addition, the generalizability of the findings is limited due to the recruitment of participants from primary care clinics in a single region. Future research should include larger and more diverse samples and adopt longitudinal or experimental designs to examine causal mechanisms and confirm the generalizability of the results.
CONCLUSION
This study confirmed that PIR and diabetes-related stress were significantly associated with self-management. Notably, in contrast to previous studies, PIR was positively associated with self-management, suggesting that psychological resistance to insulin treatment may potentially act as a motivator for self-management. Diabetes-related stress was negatively associated with self-management, highlighting the need for targeted interventions. Although intention to use CAD was not significantly associated with self-management, its weak correlation with PIR suggests it may function as an adjunctive choice.
These findings suggest the need for tailored interventions targeting PIR and diabetes-related stress and underscore the importance of further research to clarify the role of intention to use CAD in self-management.
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