Introduction
One of the most concerning global health issues is chronic diseases, particularly diabetes. Insulin resistance and relative insulin shortage are hallmarks of type 2 diabetes, a condition whose incidence is sharply increasing globally and placing a significant strain on healthcare systems around the world [1, 2]. There are currently 422 million people with diabetes globally, most of whom reside in low- and middle-income nations. Since this illness directly causes 1.5 million fatalities per year, its effects must be examined. As a result, the WHO set an ambitious objective of slowing the increase in diabetes and obesity by 2025 [3].
Diabetes in Egypt is higher than in the Middle East and North Africa (MENA) region in general, where an epidemic has been reported by the International Diabetes Federation (IDF). An estimated 15.6% of the population in Egypt aged between 20 and 79 years live with type 2 diabetes, and this is expected to continue increasing due to nutritional transition, physical inactivity, and urbanization. These factors highlight the need for management plans to be suitably devised for Egypt’s socio-economic and cultural setting [4‐6].
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Managing T2DM requires a multifaceted approach regarding lifestyle modifications, medication adherence, monitoring, and patient education. Nurses play a significant role because they are best positioned to educate, support, and empower patients. Evidence suggests that nursing interventions improve self-management behaviors and glycaemic control by facilitating patient involvement and knowledge acquisition [7‐11]. Global best practices, including the DPP in the United States and integrated care models in Europe and Australia, emphasize a comprehensive approach, combining education, behavioral support, and community engagement, providing strategies easily adapted to diverse cultural settings [12‐14].
Patient empowerment is also considered a vital part of diabetes management because it provides the required knowledge, skills, and confidence for the person involved in one’s care. Empowered patients are likelier to follow treatment recommendations, practice healthy behaviors, and experience better health outcomes [15‐20]. However, diabetes care is highly affected by socio-economic status in terms of income, education level, and access to health care. Low socio-economic patients typically face challenges to effective diabetes education and necessary supplies, negatively impacting self-management skills and health outcomes [21‐23].
Health promotion and wellness programs also have great potential to decrease diabetes complications. Because of frequent contact with patients, nurses can provide nutrition, physical activity, and stress management interventions [24, 25]. Furthermore, implementing coping strategies into diabetes management is critical since it often leads to psychological problems such as anxiety and depression. Good coping strategies enhance the psychological stability of patients and their self-management ability [26, 27].
Despite the immense evidence on the effectiveness of nursing interventions, gaps in implementing measures of effective strategy in managing diabetes still exist. Limited access to care and education, coupled with poor self-management support, continues to be challenging. Moreover, other socio-economic factors, cultural beliefs, and inadequacies of healthcare infrastructure add to these barriers in progress [28‐30]. This review evaluates an extensive nursing intervention program empowering T2D patients, including educational sessions, personalized support, and coping strategies to improve self-management skills with improved patient-centered outcomes.
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Aim of the study
This study evaluates the effectiveness of a structured diabetes self-management education program on patients’ self-management behaviors, empowerment, and activation levels.
Methods
Study design
This study used a quasi-experimental, single-group pre-test/post-test design. The design allowed for an effective comparison of results on diabetes management both before and after the nursing interventions to understand its effectiveness. A quasi-experimental design was used for several practical and ethical reasons. It was impossible to conduct a Research clinical trial (RCT) as it would involve denying some participants potentially beneficial interventions, which could be considered unethical. Also, practical problems such as the constraints of resources, time, and availability of participants within the healthcare setting made it impractical. Besides, the target population required a flexible approach to accommodate their needs. Because a quasi-experimental design allows for an examination into the real-world testing of the effects of the nursing interventions, the study’s internal validity positively contributes to valuable insights into the interventions’ effectiveness while prioritizing participant welfare.
Setting and sample size
The study was conducted in various healthcare centers in Zagazig City, Egypt, catering to a broad spectrum of patients with different access levels to healthcare. A sample size calculation was performed using G*Power software: power = 0.80, alpha level = 0.05, and medium effect size Cohen’s d = 0.5, leading to an estimated sample size of 80 participants. Considering the possibility of dropouts, the sample size was finalized at 100 participants to ensure adequate power was available to detect clinically important differences in diabetes management outcomes.
Control of confounders
The potential confounding variables identified that may affect the outcome of diabetes management include age, gender, socio-economic status, comorbidities, psychological conditions, and medication adherence. Thus, stratified random sampling was conducted to ensure that there would be variable representations across different age groups, genders, and walks of life. Baseline measurements were obtained to gather data on education level, income, and health behaviors. Statistical controls included multivariable regression analyses during the data analysis to adjust for their influence on the outcomes of interest. This systematic approach enhances the stringency of the study and ascertains that the observed outcomes are more confidently attributed to the nursing interventions under evaluation.
Sampling technique
A stratified random sampling technique was used to ensure that a representative sample of patients with Type 2 diabetes was selected from different districts of Zagazig City, including Al-Qenayat, Al-Kawmeya, Al-Sharq, Al-Ahrar, and Al-Munira. Stratified sampling effectively represents every part of Zagazig City since the population comprises clearly defined subgroups. The first step involved the identification of important demographic variables that might affect diabetic management, such as district, age group (30–45 years, 46–55 years, and 56–65 years), and sex (males and females). Since it is a stratified study, each district was considered one stratum, ensuring full representation of the sample in Zagazig City.
Once the above stratigraphic sequences were established, a master list was made. Healthcare facility records were used to generate a master list of eligible patients diagnosed with Type 2 diabetes. The next stage of the process was stratification. Patients were classified into distinct categories based on the identified demographic characteristics, including district, age group, and gender. Subsequently, a random selection process was employed within each stratum. A random number generator or lottery method was used to choose participants from the lists of eligible patients in each district, ensuring that every subgroup was proportionately represented in the final sample. The selected participants were contacted to confirm their willingness to participate. In the case of refusal of a participant selected, a replacement was randomly selected from the same stratum until a target sample size was attained. This elaborate process of allocation enhances the transparency and replicability of the study by allowing future researchers to understand the sampling method used and replicate it. The stratified random sampling method increases the generalisability, reliability, and applicability of the study’s outcomes to similar urban settings in Egypt by ensuring that the sample is representative of the diverse population in Zagazig City.
Recruitment process
In order to ensure a representative sample from outpatient clinics and healthcare centers in Zagazig, several recruitment strategies were implemented. The first step involved informational sessions to update patients on the study’s purpose, procedures, and potential benefits while addressing any questions. Additionally, informational pamphlets and flyers detailing the study’s purpose and inclusion criteria were displayed in waiting and patient rooms to encourage participation. Physicians were also involved in referring eligible patients to the study. Informed consent was obtained from all participants, ensuring they understood their rights, the study’s objectives, and any associated risks or benefits. This approach facilitated effective recruitment while upholding ethical standards.
Inclusion and exclusion criteria
The study included adults aged 30–65 years with a confirmed diagnosis of Type 2 diabetes who were actively receiving treatment, such as medication, dietary modifications, or other management techniques. Participants needed to provide informed consent, reside within the study area, and be willing to attend intervention sessions. Exclusion criteria included individuals with severe comorbidities (e.g., advanced heart failure, cancer, or end-stage renal disease) or significant psychological conditions (e.g., severe depression, anxiety disorders, or schizophrenia) that could affect diabetes management or participation. Additionally, individuals with other chronic conditions requiring competing healthcare priorities, such as chronic obstructive pulmonary disease or autoimmune disorders, were excluded. Patients already involved in other diabetes management programs or research studies were also not eligible. Those with cognitive impairments preventing informed consent or participation, unstable living conditions, or frequent relocations were excluded, as well as those with smoking or alcohol dependence, as these factors could influence self-management behaviors. Finally, individuals with inadequate access to healthcare resources, such as lack of insurance or major travel barriers, were excluded to ensure consistent participation and exposure to the study’s interventions.
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Data collection tools
Demographic data
A comprehensive literature review was conducted to inform demographic data collection from respondents that provided the necessary contextual background of the study. The variables involved in the study included age, gender, level of education, employment status, marital status, and socio-economic status. Data on the duration of diabetes diagnosis, the current treatment status, and family medical history of diabetes were also collected. The rationale for choosing those specific demographic categories represents an effort to understand how they may interact with diabetes management and intervention outcomes. Stratification by socio-economic status is important because it could influence access to healthcare resources, adherence to treatment regimens, and health literacy skills integral to managing diabetes. The data are crucial for proper insight into the characteristics of the study population and understanding how these demographic factors may influence diabetes management and intervention outcomes.
Diabetes self-management questionnaire (DSMQ)
The Diabetes Self-Management Questionnaire (DSMQ) was developed by Schmitt et al. [31] as a validated tool for assessing self-management behaviors in individuals with diabetes, with a particular focus on those behaviors associated with glycemic control. The DSMQ comprises 16 items grouped into four principal domains: glucose management, dietary control, physical activity, and healthcare utilization. These items describe the relevant areas of diabetes self-care and whether the patients can look after themselves with diabetes. Rating for all items is done on a four-point Likert scale where 0 indicates the item does not apply, and 3 indicates that the item strongly applies to the respondent. The overall score ranges from 0 to 100, with higher scores indicating better diabetes self-management. Besides calculating an overall score, subscale scores for each domain can be calculated, allowing the targeted assessment of specific areas needing improvement. The DSMQ has been demonstrated to exhibit good psychometric properties, including internal consistency and validity. There is also a confirmed correlation between higher scores and better glycemic control, mainly as reflected by HbA1c levels.
Diabetes empowerment scale (DES)
The DES, developed by Anderson et al. [32], measures the level of empowerment of people with diabetes in their diabetes care and, more particularly, assesses the psychological aspects of self-management. This 28-item tool involves essential dimensions of diabetes care, such as managing psychosocial aspects of the disease, personal dissatisfaction with current self-management practices, and the capability to set and accomplish health-related goals. Respondents answer each item on a 5-point Likert scale, from 1 to 5, with total scores ranging between 28 and 140. Scores are higher for greater empowerment and confidence in managing diabetes. The DES has been extensively validated across various populations, ensuring its applicability in diverse clinical settings.
Patient activation measure (PAM)
The Patient Activation Measure (PAM), developed by Hibbard and Gilburt [33], represents a pivotal instrument for evaluating a patient’s knowledge, abilities, and assurance in navigating their health and healthcare. The measure concerns several dimensions of patient engagement, including understanding one’s health condition, making informed decisions, and the motivation to engage in health management activities. The PAM consists of statements to which participants respond on a 4-point Likert scale, representing their agreement or disagreement. The total score ranges from 0 to 100, with higher scores indicating greater patient activation and readiness to engage in health management. Research has demonstrated correlations between the PAM scores and health outcomes, which make the measure a useful tool in the assessment and development of strategies by which patient engagement is ensured within both clinical and research settings.
Validity and reliability
The validity and reliability of the instruments employed in this study were subjected to rigorous examination in order to ensure the accuracy and meaningfulness of the findings. A pilot study was conducted on 10% of the total sample of 100 participants prior to the main study to validate the Diabetes Self-Management Questionnaire (DSMQ), Diabetes Empowerment Scale (DES), and Patient Activation Measure (PAM). The sample was drawn carefully to ensure that the target population’s characteristics represent people of different ages, genders, and socio-economic backgrounds. Subsequently, participants completed the DSMQ, DES, and PAM, followed by the interview to comment on the clarity, relevance, and cultural appropriateness of the items of each of the tools. The participants reported that the items on each scale were understandable and related to their diabetes management experiences. This qualitative feedback identified doubts in the questions, allowing minor adjustments to enhance clarity and ensure instruments accurately measured the intended constructs. For further analysis of the tools, factor analyses were also conducted from the pilot study, confirming that the constructs being measured in the DSMQ, DES, and PAM reached their construct validity- self-management and empowerment for diabetes care. Notably, the pilot study participants were not included in the data analysis.
The reliability of the scales was measured using Cronbach’s alpha, which revealed a high internal consistency. In this case, DSMQ depicted a Cronbach’s alpha of 0.86 while DES was at 0.91, and PAM had a value of 0.84, with all values over the generally acceptable threshold of 0.70. These findings suggest a valid and reliable measurement of diabetes self-management and empowerment for this population, strengthening the research findings and ensuring the tools’ appropriateness for application in the main study.
Program structure: comprehensive 16-week nursing intervention program for diabetes self-management (April 2024 - August 2024)
The 16-week nursing intervention program from April 2024 to August 2024 was proposed to develop skills necessary for the self-management of Type 2 diabetes patients. The integrated framework incorporated four successive stages: assessment, formulation of plans, implementation, and review. The two-week pre-test period included the recruitment and baseline measurement of the program, which started in April 2024. The participants were selected by pinning information brochures on the bulletin boards at health centers and clinics within Zagazig City and by referrals through healthcare providers. For the baseline assessment of knowledge, self-management behaviors, and coping status, the instruments used were the DSMQ, DES, and PAM. In addition, every participant was provided with a specially developed Arabic-language booklet on managing diabetes.
The central component of the programme was a 12-week intervention phase scheduled between May and July 2024. Each week comprised a 90-minute educational session focusing on diabetes management. In the program’s third week, participants were introduced to the pathophysiology of Type 2 diabetes, its associated complications, and the importance of glycaemic control, employing various interactive methods, including lectures, multimedia presentations, and group discussions, to reinforce the knowledge acquired by participants. In the fourth week, the emphasis was placed on dietary control and physical activity, such as practical cooking demonstrations and personalized meal planning to promote healthy eating and exercise habits. The fifth week of the programme addressed coping strategies and stress management, including relaxation techniques, mindfulness practices, and stress management workshops.
In Week 6, medication adherence and health literacy were pursued. The participants were made to understand their medication regimen and the prevention of hypoglycemia. The seventh week emphasized empowerment through self-management, with participants taught to set realistic health goals and navigate the healthcare system effectively. Group discussions and peer mentoring sessions represented a pivotal part of this phase. The eighth week was reserved for review and reinforcement, allowing participants to synthesize their knowledge and skills, present their individualized self-management plans, and discuss the remaining questions.
Between weeks 9 and 12, follow-up activities were conducted to ensure that participants maintained their learned self-management behaviors. Nurses provided ongoing support through weekly telephone calls or clinic visits to monitor progress, address challenges, and reinforce the importance of sustained self-care. Furthermore, participants were encouraged to engage with their peers through WhatsApp groups for ongoing support and motivation. Continuous monitoring and peer support were paramount to maintaining participant engagement and commitment. The programme concluded with a two-week post-test phase in August 2024, during which post-intervention assessments were conducted using the same tools as the initial assessments (DSMQ, DES, PAM). Furthermore, physiological measures were collected to evaluate the intervention’s clinical outcomes, including HbA1c levels, blood pressure, and BMI.
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The programme employed a variety of accessible and pertinent educational materials, including an Arabic-language booklet and multimedia presentations, throughout its duration. The combination of educational sessions, practical demonstrations, peer support, and ongoing follow-up sessions was designed to foster the development of sustainable self-management behaviors and improve overall health outcomes for participants. The programme aims to empower patients with Type 2 diabetes to take control of their health and enhance their quality of life by integrating culturally tailored content and continuous reinforcement (Table 1).
Table 1
Final summary table of the 16-week program
Phase | Week | Activity | Key Focus |
|---|---|---|---|
Pre-test phase | Week 1–2 | Recruitment and baseline assessments | DSMQ, DES, PAM, clinical measures (HbA1c, BMI, BP) |
Intervention phase | Week 3 | Introduction and diabetes basics | Understanding diabetes and complications |
Week 4 | Dietary management | Nutrition education and meal planning | |
Week 5 | Physical activity | Exercise routines and the importance of physical activity | |
Week 6 | Medication adherence | Medication management, understanding regimens | |
Week 7 | Stress management | Mindfulness, relaxation, coping strategies | |
Week 8 | Empowerment through self-management | Goal setting and healthcare system navigation | |
Week 9 | Review and reinforcement | Recap, group discussions, self-management plans | |
Week 10–12 | Follow-up and continuous support | Ongoing peer and nurse support | |
Post-test phase | Week 13–14 | Post-intervention assessments and clinical evaluations | DSMQ, DES, PAM, clinical measures (HbA1c, BMI, BP) |
Evaluation | Final Phase | Statistical analysis and thematic analysis of feedback | Comparison of pre-and post-test results, feedback evaluation |
Ethical considerations
Ethical considerations were paramount throughout this study to ensure that the rights and welfare of the participants were protected. Ethical approval was obtained from the Research Ethics Committee, Faculty of Nursing, Zagazig University, Egypt (ID/Zu. Nur. REC#: 00212). All participants provided informed consent before participation in this study, which attested to their understanding of the purpose of the study, research procedures, risks, and expected benefits. The confidentiality of the data was strictly maintained to protect participants’ identities securely. Moreover, respondents were free to withdraw at any point. The study followed strict ethics according to relevant national and international standards, so ethical considerations were considered in esteem for every person’s dignity.
Statistical analysis
The statistical analysis in the present study was done using the SPSS statistical software, version 26. Descriptive statistics were first measured to summarize demographic characteristics among the participants by frequencies and percentages for categorical variables. In order to examine the intervention effect, paired t-tests were conducted with normally distributed scores before and after the intervention with the Diabetes Self-Management Questionnaire (DSMQ) and the Diabetes Empowerment Scale (DES); both questionnaires showed statistically significant improvements (p < 0.05) in all the domains measured. Changes in Patient Activation Measure levels were explored using a Chi-square test for categorical outcomes; significant differences between the pre- and post-intervention periods were shown. Moreover, correlation analyses were performed on DSMQ, DES, and PAM scores, which were all positive and supported the interrelation of self-management and empowerment. Lastly, multiple regression analysis was done to identify the key predictors of post-intervention scores by taking the baseline measurements of demographic variables like age and gender into account.
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Results
The demographic characteristics of the participants in this study are summarized in Table 2. The sample included 100 individuals who had representative age distribution. The highest proportion belonged to the age group of 41–50 years, at 21.3%, followed by the 30–40-year age group, with a proportion of 12.0%, and then the 51–60-year age group, with a proportion of 18.7%. The gender distribution indicated a predominance of females (44.0%) over males (22.7%). The most significant proportion of participants had obtained a college education or higher (27.0%) in education level. Regarding employment status, it was observed that 48.0% of the participants were unemployed, which may be indicative of the socio-economic challenges they were facing. Most respondents were married (32.0%), while their socio-economic status was largely middle class (32.0%). In addition, 29.3% of the respondents had a family history of diabetes, which may imply a genetic causation of the disease in this group.
Table 3 explains the scores from the Diabetes Self-Management Questionnaire (DSMQ) prior to and following the intervention. The results demonstrate notable enhancements across all components, with the total DSMQ score increasing from a pre-intervention mean of 64.5 (SD = 10.4) to a post-intervention mean of 68.6 (SD = 9.8), yielding a statistically significant test value of 3.98 (p < 0.001). Notably, the Glucose Management component exhibited the most significant improvement, with a mean increase from 70.2 (SD = 11.0) to 75.4 (SD = 10.5), which was supported by a significant test value of 3.45 (p < 0.001). Figure 1 illustrates the pre-and post-intervention scores across each DSMQ component, visually highlighting these improvements.
The results of the Diabetes Empowerment Scale (DES) scores are presented in Table 4. The mean score prior to the intervention was 65.4 (SD = 11.9), which significantly increased to 70.0 (SD = 11.2) following the intervention, with a test value of 3.27 (p = 0.001). All dimensions of the DES, including psychosocial aspects and goal setting, showed clinically significant improvements, thus reflecting that the intervention was associated with increased empowerment of patients. For example, the goal-setting aspect of the intervention improved significantly, from a pre-intervention score of 70.0 (SD = 11.5) to 75.1 (SD = 10.9) post-intervention (t-value = 3.63, p < 0.001). The latter is an illustration that the intervention was effective in enhancing the confidence of the patients in managing their diabetes.
Table 5 summarises the PAM scores for the pre-and post-intervention periods. Positive patient activation is noted, as reflected in the significant decrease in the numbers falling into Level 1 (0–49) from 55 pre-intervention to 40 post-intervention (χ² = 7.45, p = 0.024). On the contrary, the number of participants who reached Level 4 (80–100) increased from 30 to 50, giving a significant chi-square value of 8.25 (p = 0.016). These two findings reflect that the intervention successfully improved patients’ activation levels toward becoming more active players in their health management. Figure 2 presents the distribution of PAM levels before and after intervention by visual, with the statistical findings reinforcing it.
The correlation between the DSMQ, DES, and PAM scores before and after the intervention is shown in Table 6. In all the variables studied, statistically significant positive correlations showed interlinks among improvements in self-management behaviors, empowerment, and patient activation. To illustrate, the correlation of the DSMQ total score with the DES total score was 0.58 before and 0.65 after the intervention (p ≤ 0.001). This means that as the self-management ability of patients developed, so did their level of empowerment, which shows the effectiveness of the intervention.
Table 7 presents the findings of the multiple regression analysis. The analysis indicates that pre-intervention scores for DSMQ, DES, and PAM significantly predict post-intervention scores. The coefficient for the pre-DSMQ score was 0.45 (p ≤ 0.001), indicating a strong positive correlation. In addition, demographic factors such as age and sex were also identified as having a significant contribution to variation in post-intervention scores where age had a coefficient of 0.20 (p = 0.047), and gender had a negative coefficient about males, B = -1.00, p = 0.048. Thus, these findings identify both baseline self-management behaviours and demographic characteristics as predictors of the efficacy of the intervention on patient outcomes.
Table 2
Demographic characteristics of participants
Demographic Variable | Frequency (n) | Percentage (%) |
|---|---|---|
Age | ||
- 30–40 years | 18 | 12.0 |
- 41–50 years | 32 | 21.3 |
- 51–60 years | 28 | 18.7 |
- 61–65 years | 22 | 14.7 |
Gender | ||
- Male | 34 | 22.7 |
- Female | 66 | 44.0 |
Educational Level | ||
- Less than High School | 24 | 16.0 |
- High School | 36 | 24.0 |
- College or Higher | 40 | 27.0 |
Employment Status | ||
- Employed | 28 | 18.7 |
- Unemployed | 72 | 48.0 |
Marital Status | ||
- Married | 48 | 32.0 |
- Single | 24 | 16.0 |
- Divorced/Widowed | 28 | 18.7 |
Socio-economic Status | ||
- Low | 36 | 24.0 |
- Middle | 48 | 32.0 |
- High | 16 | 10.7 |
Family History of Diabetes | ||
- Yes | 44 | 29.3 |
- No | 56 | 37.3 |
Table 3
Diabetes self-management questionnaire (DSMQ) scores
Component | Pre-Intervention Mean Score (SD) | Post-Intervention Mean Score (SD) | Test Value (t) | p-value |
|---|---|---|---|---|
Glucose management | 70.2 (11.0) | 75.4 (10.5) | 3.45 | < 0.001 |
Dietary control | 65.0 (12.5) | 68.2 (12.0) | 2.87 | 0.005 |
Physical activity | 55.4 (13.8) | 58.7 (14.3) | 2.54 | 0.015 |
Health care use | 68.0 (11.2) | 72.1 (11.8) | 3.12 | 0.002 |
Total DSMQ Score | 64.5 (10.4) | 68.6 (9.8) | 3.98 | < 0.001 |
Fig. 1
Pre- and post-intervention DSMQ scores by component
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Table 4
Diabetes empowerment scale (DES) scores
DES Dimension | Pre-Intervention Mean Score (SD) | Post-Intervention Mean Score (SD) | Test Value (t) | p-value |
|---|---|---|---|---|
Psychosocial aspects | 65.2 (14.3) | 70.3 (15.2) | 2.98 | 0.003 |
Personal satisfaction | 61.0 (12.2) | 64.7 (12.6) | 2.57 | 0.012 |
Goal setting | 70.0 (11.5) | 75.1 (10.9) | 3.63 | < 0.001 |
Total DES Score | 65.4 (11.9) | 70.0 (11.2) | 3.27 | 0.001 |
Table 5
Patient activation measure (PAM) scores
PAM Level | Pre-Intervention Frequency (n) | Post-Intervention Frequency (n) | Chi-Square (χ²) | p-value | |
|---|---|---|---|---|---|
Level 1 (0–49) | 55 | 40 | 7.45 | 0.024 | |
Level 2 (50–64) | 75 | 60 | 3.45 | 0.063 | |
Level 3 (65–79) | 85 | 100 | 4.12 | 0.042 | |
Level 4 (80–100) | 30 | 50 | 8.25 | 0.016 | |
Fig. 2
Pre- and post-intervention distribution of PAM levels
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Table 6
Correlation between DSMQ, DES, and PAM scores
Variable Pair | Pre-Intervention Correlation Coefficient (r) | Post-Intervention Correlation Coefficient (r) | p-value |
|---|---|---|---|
DSMQ Total Score & DES Total Score | 0.58 | 0.65 | < 0.001 |
DSMQ Total Score & PAM Score | 0.55 | 0.58 | < 0.001 |
DES Total Score & PAM Score | 0.67 | 0.70 | < 0.001 |
Table 7
Multiple regression analysis results
Outcome Variable | Independent Variables | Coefficient (B) | Standard Error | t-value | p-value |
|---|---|---|---|---|---|
Post-DSMQ Score | Pre-DSMQ Score | 0.45 | 0.05 | 9.00 | < 0.001 |
Age | 0.20 | 0.10 | 2.00 | 0.047 | |
Gender (Male = 1, Female = 0) | -1.00 | 0.50 | -2.00 | 0.048 | |
Post-DES Score | Pre-DES Score | 0.38 | 0.06 | 6.33 | < 0.001 |
Education Level (College or Higher = 1) | 2.50 | 0.75 | 3.33 | 0.001 | |
Post-PAM Score | Pre-PAM Score | 0.32 | 0.07 | 4.57 | < 0.001 |
Socio-economic Status (Higher Status = 1) | 1.80 | 0.85 | 2.12 | 0.034 |
Discussion
The significant improvement in the scores on the Diabetes Self-Management Questionnaire following the intervention confirms the programme’s effectiveness in promoting self-management behaviors. This aligns with other studies indicating similar outcomes in managing diabetes interventions, especially regarding glucose control and medication adherence. The significant improvement in glucose management observed in this study agrees with the previous studies that focused on structured self-care education as an integral element in diabetes management. Such educational programs have been shown to positively affect blood glucose levels and reduce the complication risk associated with diabetes [34‐40].
The observed improvements in the Diabetes Empowerment Scale (DES) demonstrate the efficacy of the intervention in improving patient confidence and goal-setting abilities. It is crucial to empower patients with diabetes to facilitate their active participation in managing their condition. Evidence indicates that empowerment-based interventions significantly improve patients’ psychosocial adjustment to diabetes, concerning improved goal setting and self-efficacy [41‐46]. These interventions can help build patient confidence and thus promote longer-term behavioral changes and a more active approach to self-care.
Furthermore, the Patient Activation Measure (PAM) results provide additional evidence of the intervention’s efficacy, with notable increases in patient activation levels. This positive shift indicates participants’ increasing willingness and capacity to assume responsibility for their health management. Several studies indicate a strong relationship between patient activation and better health outcomes. More active patients tend to exhibit healthier behaviors and have better disease management. The decrease in participants at the lowest activation level and the increase at the highest level reflects prior research showing that tailored interventions effectively increase patient activity [47‐50].
The correlations between the DSMQ, DES, and PAM scores reinforce the interrelation of self-management, empowerment, and activation, indicating a synergistic effect where those who have gained confidence in managing their condition are most likely empowered and more active regarding their health management. Further, empowered and active patients have been demonstrated to be more likely to engage in proactive health behaviors, underscoring the relevance of these constructs within the context of diabetes care [21, 50‐53].
Furthermore, the multiple regression analysis shows that self-management and empowerment at baseline have predictive values for post-intervention outcomes. The results are thus consistent with the literature indicating that baseline levels of self-management and empowerment are a critical determinant of the long-term success of such interventions [20, 54‐59]. Of interest was that demographic predictors also strongly influenced outcome prediction, with older age and females showing more significant improvements, reflecting a tendency for older patients to engage more vigorously in health-promoting behaviors in response to cumulative health risks, with a tendency of females to show stronger responses to empowerment-based interventions [60‐65].
However, while the short-term results are promising, it would be prudent to explore the long-term sustainability of these effects in future studies. This study’s relatively short follow-up period limits our understanding of whether the observed improvements in self-management, empowerment, and patient activation are maintained over time. Further research is needed to show how long such changes are maintained, especially without continuous interventions or booster sessions. Moreover, the extent to which such effects can be sustained would be better understood by investigating external factors that either facilitate or hinder the persistence of these effects, such as social support, access to health care, or technology integration.
In conclusion, the observed enhancements in empowerment and activation have significant implications for the long-term management of diabetes. As patients become more empowered and active, they will probably experience sustained improvements in self-management behaviors and health outcomes. It would be valuable for future research to focus on longitudinal studies to explore the sustainability of these changes and their impact on long-term health trajectories. Incorporating empowerment and activation strategies into diabetes management programmes enables healthcare providers to assist patients more effectively in attaining optimal health outcomes.
Study implications
The study’s findings underscore the importance of integrating personalized and targeted interventions into managing diabetes. The demonstrated improvements in self-management behaviors, empowerment, and patient activation indicate that healthcare professionals should adopt a dual approach, placing equal emphasis on clinical care and patient education and support mechanisms that facilitate patient independence. The significant correlation between self-management, empowerment, and patient activeness indicates that an improvement in one domain positively impacts the others. These findings have significant implications for the design of diabetes care models, which should adopt a more holistic, patient-centered approach that factors in the individual’s demographic background, such as age, education, and socio-economic status. Moreover, the study underscores the socio-economic obstacles many patients confront, with nearly half of the sample unemployed, indicating that economic factors may impact an individual’s capacity to manage chronic conditions such as diabetes effectively. It also suggests that public health interventions must be multifaceted, addressing medical needs and the social determinants of health. Developing self-management abilities and empowerment within healthcare systems can better equip patients to assume proactive roles in managing their conditions, ultimately reducing long-term healthcare costs and improving quality of life.
Conclusion
In conclusion, structured, patient-centered interventions are crucial in improving self-management behaviors, empowerment, and patient activation among patients with diabetes. Improvements found to be statistically significant on all assessed components of the intervention, namely DSMQ, DES, and PAM, may indicate the capability of educational programs to adequately support patients with the necessary skills and confidence in managing diabetes. However, the study has limitations, for instance, the possibility of being biased through a selection of samples and measures relied on self-reporting. It will be essential to consider all these considerations when interpreting its results since those are limiting factors to the valid result of the findings.
Also, the positive associations between the constructs show that enhanced self-management behaviors lead to increased empowerment and activation, thus enhancing the overall health and well-being of patients with diabetes. More studies are needed to understand the complete mechanism. Besides, the generalization of the results is limited by the small sample size of the present study, thus larger-scale studies are needed to confirm the results in more diverse populations.
The intervention probably combined education, behavioral support, and goal-setting, thus effectively achieving durable behavioral change. Thus, these findings add to the accumulating body of evidence to inform the implementation of comprehensive models of diabetes care that go beyond clinical management to include educational components aimed at increasing patient autonomy and engagement in their care. While these findings reinforce adopting a more patient-centered approach to managing chronic diseases, it is important to interpret these results cautiously and recognize the necessity for ongoing evaluation and refinement of such interventions. It would be valuable for future studies to aim to replicate these findings in larger, more diverse populations to strengthen the evidence supporting their efficacy.
Recommendations
Based on the findings of this study, a few key recommendations have been brought to light about healthcare practice and policy. These include tailored educational and behavioral interventions framed toward the specific needs and demographics considered in diabetes management programs. For instance, the study also showed high socio-economic disparities among the subjects; approximately half of them were unemployed, and many had a family history of diabetes. Consequently, future interventions should target the medical and social causes of health, incorporating, if possible, economic support services or community resources to support those with financial problems in managing health.
Secondly, given the strong correlation between patient empowerment and enhanced self-management outcomes, healthcare systems should prioritize interventions that foster patient confidence and capability in managing their condition. It would be beneficial for future research to investigate the potential of digital health technologies, such as mobile apps or telemedicine, to extend the scope of such educational interventions, particularly to underserved communities. Furthermore, studies should examine the efficacy of diverse intervention modalities, such as group versus individual sessions or integrating peer support structures.
Furthermore, healthcare policies should facilitate the broader implementation of these programmes by integrating them into the standard care pathway for patients with diabetes, guaranteeing that every patient has access to these essential resources. It is further recommended that future studies incorporate more extended follow-up periods, ideally six to twelve months post-intervention, to assess the long-term impact of these interventions on self-management behaviors, empowerment, and patient activity. Future studies should consider exploring factors that influence the sustainability of these interventions, such as the provision of ongoing support and the availability of resources, to determine the optimal means of maintaining the benefits achieved through the initial interventions.
Study limitations
Although the study gives an excellent overview of how well diabetes self-management interventions work, several limitations were identified. First, all the self-reported measures adopted the Diabetes Self-Management Questionnaire (DSMQ), Diabetes Empowerment Scale (DES), and Patient Activation Measure (PAM)-invariably have a degree of subjectivity and are prone to response bias. There may be subconscious tendencies whereby respondents provide answers that do not reflect their real-life practices and perceptions. Ideally, follow-up research should include objective measures such as HbA1c levels or clinical examination for a more valid outcome assessment regarding diabetes management. Secondly, the relatively short follow-up period limits the ability to assess the sustainability of the observed improvements in self-management, empowerment, and patient activation over time. Longitudinal studies with extended follow-up periods would be necessary to ascertain whether the benefits of the intervention are maintained and to explore the need for additional booster sessions.
Thirdly, the study’s sample did not fully represent the general population, as it included a disproportionate number of female participants and individuals from middle-class backgrounds. Finally, while the study underscores the significance of empowerment interventions, it is imperative to recognize the potential challenges associated with their implementation in diverse socio-economic contexts. The effectiveness and acceptance of such interventions can be significantly impacted by variations in healthcare access, cultural beliefs, and patient circumstances. It would be beneficial for future studies to reflect on these challenges to enhance the relevance and applicability of empowerment strategies in real-world settings.
Acknowledgements
The authors would like to thank all those who participated in the study for their invaluable contribution and collaboration.
Declarations
Ethics approval and consent to participate
Ethical considerations were paramount throughout this study to ensure that the rights and welfare of the participants were protected. Prior to the commencement of the research, approval was obtained from the Research Ethics Committee (REC) at the Faculty of Nursing, Zagazig University, Egypt, under the code ID/Zu. Nur. REC#:00212. Before participating, all subjects provided informed consent, attesting to their comprehension of the study’s purpose, procedures, potential risks, and anticipated benefits. The confidentiality of the data was strictly maintained, with the information anonymized and securely stored to protect the participants’ identities. Furthermore, participants were informed of their right to withdraw from the study at any time without any adverse consequences. The study was conducted per the ethical guidelines set forth by relevant national and international standards, ensuring the ethical integrity and respect for all individuals involved.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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