Introduction
Despite substantial efforts to prevent and control diabetes mellitus (DM), this non-communicable disease remains a global crisis, with increasing prevalence in all regions worldwide [
1,
2]. In 2021, approximately 537 million adults aged 20 to 75 years lived with DM, representing 10.5% of all adults in this age group, according to the International Diabetes Federation [
3]. This number is projected to reach around 783 million by 2045, with a global prevalence of 12.2% [
3]. Of this increase, 94% is expected to occur in low- to middle-income countries [
3]. Additionally, approximately 6.7 million deaths globally were attributed to DM in 2021 [
3].
Type 2 diabetes mellitus (T2DM) is the most common form of DM, accounting for over 90% of global cases [
3]. The rise in T2DM prevalence and incidence has been driven by rapid economic and social developments that have promoted dietary changes and reduced physical activity [
1,
2]. Effective T2DM management is complex, extending beyond pharmacological treatments, and includes self-care practices such as healthy eating, regular physical activity, weight control, and smoking cessation [
3].
In Morocco, approximately 12.4% of adults had T2DM in 2023, according to World Health Organization data [
2]. T2DM is responsible for over 12,000 deaths annually, with an additional 32,000 deaths attributed to complications of high blood glucose levels [
4]. This disease imposes a significant socioeconomic burden on Morocco, increasing medical expenses primarily due to chronic complications such as neuropathy, retinopathy, kidney failure, heart attacks, and strokes [
5]. These complications require costly treatments and often impair patients’ ability to work and perform daily activities, additionally affecting their families and society [
6].
In light of this considerable socioeconomic impact, medication adherence for T2DM management is essential. Poor adherence can worsen health outcomes, increase the risk of therapeutic failure and hospitalizations, and impose financial burdens on patients and healthcare systems [
7]. Numerous studies have explored medication adherence in patients with T2DM, identifying various socioeconomic, clinical, and behavioral determinants [
8–
11].
Medication adherence is typically relatively low in developing countries due to resource constraints [
2]. Non-adherence rates to antidiabetic treatments vary widely, ranging from 36% to 93% [
12,
13], and can adversely impact blood glucose control, contributing to complications and reduced quality of life [
14]. Additionally, more than half of individuals with T2DM experience poor glycemic control [
15], which worsens health outcomes; this issue is particularly common in East African countries such as Ethiopia, Tanzania, Uganda, and Kenya [
14,
16,
17].
Factors associated with poor adherence include the high cost of medications, prolonged treatment duration, adverse drug effects (such as fatigue, nausea, vomiting, psychological distress, and itching), sociocultural influences, substance use, limited health literacy, personal beliefs, and the availability and affordability of insulin. Non-persistence with treatment is also a major concern [
18–
20]. Studies conducted in middle-income countries like Egypt [
21] and Tunisia [
22], using the adherence to refills and medications scale (ARMS), have reported low adherence rates due in part to medication costs and sociocultural constraints. These findings underscore similar challenges to those expected in Morocco. However, the general medication adherence scale (GMAS) offers a more tailored assessment by incorporating socioeconomic and behavioral factors specific to the Moroccan context.
Globally, medication adherence in diabetes is influenced by various factors, including gender [
23], education level [
24,
25], knowledge about diabetes [
24,
25], disease duration [
25,
26], and perceived severity of the disease [
23], among others. Medication adherence refers to the extent to which a patient’s behavior aligns with agreed-upon recommendations from the prescriber [
27]. It is an active commitment that requires collaboration with the healthcare provider, as well as a personal and motivated decision aimed at maintaining effective management of one’s health condition [
27]. Non-adherence manifests as missed doses, irregular medication intake, or discontinuation of the treatment regimen [
27]. According to extensive research, approximately half of patients with chronic diseases do not adhere to their medication regimens, and around half of these individuals discontinue treatment within 1 year [
28]. Non-adherence remains a major challenge among patients with chronic diseases, particularly those with T2DM. This lack of adherence contributes to disease progression and increased healthcare costs, underscoring the urgent need for improved management strategies.
Several tools are available to assess medication adherence, including the Shea scale [
29], ARMS [
30], brief medication questionnaire [
31], and Morisky medication adherence scale [
32]. Although widely used, these tools are not always suitable for specific contexts, such as Morocco. Addressing this gap, the GMAS was developed in Urdu in 2017 [
33] and was subsequently validated in Moroccan Arabic in 2023 [
6]. This scale represented a major advancement in assessing medication adherence by focusing on 3 fundamental aspects: behavioral non-adherence, non-adherence associated with the additional burden of disease and medications, and cost-related non-adherence (CRNA).
Despite the scale’s potential utility and relevance, few studies have explored medication adherence in Morocco along these dimensions [
7,
34]. To date, no systematic research has evaluated the impact of socioeconomic and clinical factors on treatment adherence using this locally validated tool, highlighting a clear need for such investigation. Therefore, this study aims to assess medication adherence levels and identify associated factors among Moroccan patients with T2DM, using the GMAS within the framework of a multicenter study.
Materials and Methods
Study Design and Setting
This multicenter cross-sectional study was conducted from February to June 2024 and included 584 patients with T2DM. Participants were randomly selected from the patient registers of primary healthcare facilities in the Casablanca-Settat and Rabat-Sale regions of Morocco.
Participants
Inclusion criteria
Participants were required to: (1) be diagnosed with T2DM, (2) have received antidiabetic treatment for at least 3 months prior to the study, and (3) be at least 18 years old. T2DM diagnosis was confirmed using patients’ medical histories, antidiabetic treatments, and records from the primary healthcare facilities.
Exclusion criteria
Individuals were excluded if they: (1) had type 1 DM, (2) had gestational diabetes, (3) were severely ill and required urgent medical care, or (4) refused to participate or failed to complete the survey. Participation was voluntary, with informed consent obtained through a signed consent form.
Data Collection
Data were collected using a self-administered questionnaire comprising 2 main sections: (1) sociodemographic and disease-related data, and (2) the 11-item GMAS tool for assessing medication adherence.
Sample Size
The necessary sample size was determined based on a diabetes prevalence rate of 12.4%, as reported in previous research [
4]. The initial calculation estimated a minimum of 167 patients, assuming a 95% confidence interval (CI) and 5% precision. However, 584 patients were included, significantly exceeding the initial target. This larger sample size increases statistical robustness, improves representativeness of the diabetic population studied, and facilitates detailed analyses and the identification of significant associations. Furthermore, a larger sample yields a study with greater statistical power, aiding the detection of meaningful differences concerning medication adherence among patients with T2DM.
General Medication Adherence Scale
The GMAS, developed in 2017 [
33] to assess medication adherence through self-reporting, was translated and validated in Moroccan patients with T2DM in 2023 [
6]. This scale is divided into 3 sections: patient behavior-related non-adherence, assessed by 5 items (questions 1–5); non-adherence related to additional disease and pill burden (ADPB), covered by 4 items (questions 6–9); and CRNA, assessed by 2 items (questions 10 and 11). These sections thoroughly evaluate various factors impacting medication adherence among patients with T2DM. Participants respond to these 11 items on a 4-point Likert scale, ranging from 0 (always) to 3 (never). The total score ranges from 0 to 33, with higher scores indicating better adherence.
Adherence levels are categorized based on GMAS total score: scores of 10 or less indicate poor adherence, 11 to 16 indicate low adherence, 17 to 26 reflect partial adherence, 27 to 29 represent good adherence, and 30 to 33 indicate high adherence. These categories provide a clear framework for assessing the degree of medication adherence among patients with T2DM. A total score of 27 or higher classifies patients as adherent, while a score of 26 or lower classifies them as non-adherent. The GMAS has been transculturally validated in multiple countries, including Saudi Arabia [
28,
35], Jordan [
36], Sudan [
37], Nepal [
38], China [
39], and the United Arab Emirates [
40].
Statistical Analysis
We performed statistical analysis using IBM SPSS ver. 23.0 (IBM Corp.). Data were anonymized to ensure participant confidentiality. The sociodemographic characteristics of participants are presented as frequencies, percentages, means, and standard deviations.
To evaluate statistically significant associations between variables, cross-tabulations with the Pearson chi-square test were used. For counts less than 5, the Fisher exact test was applied. A multivariate binary logistic regression model was employed to explore significant associations between explanatory and outcome variables. The independent variables included in the model were gender, age group, area of residence, marital status, employment status, education level, health insurance status, type of health insurance, prescribed treatment, prevalence of combination therapy, diabetes-related comorbidities, duration of the disease, and patient education regarding their condition. A p-value less than 0.05 was considered to indicate statistical significance.
Ethics Approval
Data collection for the study was approved by IRB00012973 of the Moroccan Association for Research and Ethics, IRB #1 [09/REC/22], in accordance with the ethical principles outlined in the Declaration of Helsinki and relevant local ethical regulations. Written informed consent was obtained from all participants prior to their inclusion in the study. Participants were fully informed about the purpose of the study, the procedures involved, and their right to withdraw at any time without consequences to their medical care. This informed consent process was also approved by IRB #1 [09/REC/22].
Results
Figure 1 illustrates the steps of participant recruitment from the 4 healthcare facilities involved in the study, outlining the selection process based on the inclusion and exclusion criteria.
Association between Sociodemographic Characteristics and Medication Adherence
Medication adherence was observed in 96.2% of participants (
n=562/584), as shown in
Figure 2.
Table 1 presents the associations between various sociodemographic characteristics and medication adherence, assessed using the GMAS. The mean age of participants was 60.53±12.47 years (range, 29–91 years). Most participants lived in rural areas (
n=343, 58.7%), and adherence rates were similar between rural (96.5%,
n=331) and urban residents (96.7%,
n=233;
χ2=0.14,
p=0.90). Women comprised 59.4% of the sample (
n=347) and exhibited an adherence rate comparable to men (96.3% vs. 97.1%), again without any significant difference (
χ2=0.60,
p=0.60). Participants aged 29 to 49 years (
n=110) had the highest adherence rate (98.2%,
n=108), while those aged 80 to 91 years (
n=36) had the highest non-adherence rate (8.3%,
n=3); however, this difference was not statistically significant (
χ2=3.48,
p=0.17). Marital status was not significantly associated with adherence (
χ2=1.48,
p=0.68). Single participants (
n=67) exhibited a non-adherence rate of 4.5% (
n=3), while divorced individuals (
n=35) displayed full adherence (100%). Regarding education level, illiterate patients (
n=401, 68.7%) had a slightly higher non-adherence rate of 4.2% (
n=17) compared to those with primary (1.4%,
n=1/74) or middle school education (2.1%,
n=1/48). Patients with high school education (
n=39) reported 100% adherence, while university-educated participants (
n=22) had an adherence rate of 95.5% (
n=21). These differences were not statistically significant (
χ2=3.49,
p=0.47). Similarly, employment status was not significantly associated with adherence (
χ2=3.16,
p=0.20). Unemployed individuals (
n=469, 80.3%) had a 95.9% adherence rate (
n=450), retired participants (
n=65) showed full adherence (100%), and employed patients (
n=50) had slightly higher adherence than unemployed patients (98.0%,
n=49). Notably, health insurance status exhibited a significant association (
χ2=5.40,
p=0.02); uninsured patients (
n=200) had higher adherence (99.0%,
n=198) than insured patients (95.3%,
n=366). Although type of insurance did not reach statistical significance (
χ2=7.13,
p=0.06), participants covered by Mandatory Health Insurance (AMO;
n=274) displayed a higher non-adherence rate (5.5%,
n=15) than those insured through the National Fund of Social Welfare Organizations (1.9%,
n=1/53) or the National Social Security Fund (3.0%,
n=2/67). Overall, while most sociodemographic factors were not significantly associated with medication adherence, being uninsured was significantly linked to better adherence in this population.
Association between Clinical Variables and Medication Adherence
Table 2 presents the associations between clinical variables and medication adherence among the 584 participants. Patients with diabetes for less than 1 year (
n=47, 8.0%) exhibited a high adherence rate of 97.9% (
n=46/47), compared to 95.2% for 1 to 5 years (
n=158/166), 96.6% for 6 to 10 years (
n=172/178), and 98.8% for 11 to 15 years (
n=80/81). However, the association between disease duration and adherence was not statistically significant (
χ2=2.4,
p=0.79). Regarding body mass index, adherence rates were 100% among underweight patients (
n=18/18), 96.7% for those with normal weight (
n=377/390), 97.9% for the overweight group (
n=94/96), and 93.8% for those with obesity (
n=75/80). These differences were not statistically significant (
χ2=3.10,
p=0.37). Self-monitoring of blood glucose was reported by 71.7% of participants (
n=419/584), with significantly higher adherence (97.9%,
n=410/419) compared to patients who did not self-monitor (93.3%,
n=154/165;
χ2=7.30,
p=0.007); this finding suggests a positive impact of self-monitoring on adherence. Patients considered to be informed regarding their condition (
n=333, 57.0%) exhibited a slightly higher adherence rate (97.3%,
n=324/333) than uninformed patients (95.6%,
n=240/251), although this difference was statistically insignificant (
χ2=1.22,
p=0.26). We also examined the type of pharmacological treatment. Patients taking 2 or more oral antidiabetic drugs (OADs;
n=195) exhibited the highest adherence (99.0%,
n=193/195), followed by those receiving an OAD plus insulin (95.6%,
n=65/68), an OAD alone (95.7%,
n=156/163), and insulin alone (94.9%,
n=150/158). These differences were not statistically significant (
χ2=5.24,
p=0.15). However, analysis of specific OADs did reveal a significant difference in adherence rates (
χ2=18.32,
p=0.01). Patients treated with combined gliclazide and acarbose (
n=155), glipizide (
n=18), or combined metformin and glimepiride (
n=5) showed perfect adherence (100%). Lower adherence occurred with metformin alone (83.3%,
n=5/6) and combined gliclazide, acarbose, and glipizide (90.9%,
n=30/33). Combination therapy was prevalent, with adherence rates of 97.6% for dual therapy (
n=206/211), 96.7% for triple therapy or more (
n=117/121), and 95.6% for monotherapy (
n=241/252). However, number of medications was not significantly associated with adherence (
χ2=1.38,
p=0.49). Regarding comorbidities, high adherence rates were noted among patients with hypertension (97.2%,
n=205/211), dyslipidemia (100%,
n=22/22), and other conditions (91.4%,
n=53/58), as well as those without comorbidities (97.4%,
n=187/192). The overall association between comorbidities and adherence was not statistically significant (
χ2=8.99,
p=0.17). Overall, while most clinical variables were not significantly associated with adherence, self-monitoring of blood glucose emerged as a significant determinant, highlighting its potential as an intervention target.
Medication Adherence Patterns Based on GMAS Items
Table 3 presents data on treatment adherence based on participant responses to the Moroccan Arabic version of the GMAS. The results, representing self-reported answers, indicate that 86.8% of patients (
n=507) never had difficulty remembering to take their medications (GMAS1), while 87.3% (
n=510) never missed doses due to busy schedules or unexpected events (GMAS2). Regarding intentional non-adherence, 94.7% (
n=553) reported continuing their treatment even when feeling well (GMAS3), while 95.7% (
n=559) did not stop medication despite experiencing side effects (GMAS4). Additionally, 94.3% (
n=551) reported never discontinuing treatment without informing their doctor (GMAS5). In the ADPB domain, 97.1% of respondents (
n=567) did not discontinue medication due to concurrent treatments (GMAS6). Moreover, 90.2% (
n=527) did not find their treatment regimen complex or difficult to manage (GMAS7), and 90.6% (
n=529) did not miss medications due to the addition of new drugs (GMAS8). A large majority (93.5%,
n=546) indicated that they never modified their dosage or treatment schedule without medical advice (GMAS9).
Concerning CRNA, 92.0% of patients (n=537) stated that they do not stop treatment due to the perceived value of the medication (GMAS10). However, 10.4% (n=61) reported difficulty purchasing medications due to their cost (GMAS11), although 84.6% (n=494) indicated an absence of financial barriers. These findings reflect a high overall adherence rate among the study population, although minor challenges remain regarding treatment complexity and medication affordability.
Probabilities of Medication Adherence
Table 4 summarizes the results of the multivariate logistic regression examining associations of sociodemographic and clinical factors with medication adherence among patients with T2DM in Morocco. The outcome variable is binary, distinguishing between adherence and non-adherence. Patients in rural areas exhibited a lower probability of adherence compared to urban residents (adjusted odds ratio [aOR], 0.245; 95% CI, 0.053–1.123;
p=0.070), although this finding was not statistically significant (
p>0.05). Men displayed a slightly lower probability of adherence compared to women, while the marital status categories of “single,” “married,” and “widowed”—relative to the reference category of “divorced”—displayed high odds ratios with wide CIs and high
p-values (0.997 for all), suggesting a lack of statistical power or limited variability within these groups. Education level did not exhibit a significant association with adherence; for instance, illiterate participants had a high odds ratio without statistical significance (aOR, 1.429; 95% CI, 0.033–62.133;
p=0.853). Similarly, professional status did not significantly affect adherence, as exemplified by the finding regarding retirees (aOR, 0.000;
p=0.996). The chi-square test revealed significantly lower non-adherence among uninsured patients (1%) compared to insured patients (4.7%;
p=0.02). However, logistic regression adjusting for age, sex, residence, and other variables showed that insured patients had a higher probability of adherence (aOR, 2.585), although this difference was statistically insignificant (
p=0.827). Patients covered by AMO showed a slightly elevated, although not significant, probability of adherence (aOR, 1.248; 95% CI, 0.114–13.66;
p=0.856) compared to those without insurance. Patients receiving combined treatment with 2 or more OADs displayed significantly better adherence compared to those on a single treatment (aOR, 0.026; 95% CI, 0.001–0.642;
p=0.026). Patients with a diabetes duration of 11 to 15 years had significantly lower odds of adherence (aOR, 0.037; 95% CI, 0.001–0.956;
p=0.047), possibly reflecting disease duration-related burnout or a decline in motivation to follow treatment guidelines. Lastly, being informed about their illness had no significant impact on adherence in our study population (aOR, 0.552; 95% CI, 0.121–2.527;
p=0.444).
Figure 3 illustrates the distribution of medication adherence levels among patients with T2DM, showing that 89.4% of participants exhibited high adherence, while 7.2% had good adherence. Notably, no patients demonstrated low or moderate adherence (0.0%). These results highlight positive adherence to treatment overall, possibly reflecting effective awareness and diabetes management strategies in primary healthcare facilities in Morocco.
Figure 4 details medication adherence levels across dimensions of the GMAS, including patient behavior (intentional and non-intentional), comorbidities, polypharmacy, and financial constraints. The results indicate that 93.0% of patients exhibited high behavior-related adherence. Additionally, 91.5% of patients demonstrated good adherence despite comorbidities and a significant medication burden, with no cases of low or poor adherence. Finally, 81.5% of patients maintained good adherence despite financial constraints, with only 0.3% showing poor adherence for this reason.
Discussion
The assessment of medication adherence is complex, as adherence depends on both intentional and unintentional patient behaviors [
41]. Adherence to antidiabetic regimens is essential for optimal blood glucose control, while non-adherence can lead to serious complications. Our study found high adherence levels among patients with T2DM, aligning with findings from Naqvi et al. [
35] and Khardali et al. [
42], who also reported satisfactory adherence rates. Notably, however, our observed rate of 96.2% is significantly higher than those reported by Naqvi et al. [
35] and Khardali et al. [
42] (61.7% and 66%, respectively). These differences might reflect regional variations, despite the use of the same GMAS-based definition of adherence (with scores of ≥27 categorized as adherence and ≤26 as non-adherence).
Previous studies conducted in Saudi Arabia have reported high rates of non-adherence, reaching 67.9% in the Al Hasa district [
43]. Additionally, high rates of non-adherence have been observed in various Middle Eastern countries, including Jordan (58%) [
44,
45], Palestine (52.7%) [
46], the United Arab Emirates (61.7%) [
47], and Qatar (73%) [
48]. These findings contrast with ours, underscoring the importance of regional context.
The data from our study corroborate the results of a previous investigation we conducted with 284 patients [
7]. However, expanding the sample size to 584 patients, distributed across 2 major regions, and examining factors associated with adherence provide a more comprehensive perspective. A complementary qualitative study is planned to better understand the reasons for the high adherence rate in Morocco and to identify additional influencing factors.
Public health policies in Morocco, such as initiatives from the Ministry of Health and Social Protection, could play a key role in improving medication adherence. These initiatives aim to promote economic and health prosperity by reducing health disparities among patients with chronic diseases [
49]. Strategies include improving access to treatments and preventive care services and providing free basic medical care to all Moroccan citizens, including those with non-communicable diseases. Other noteworthy measures include increasing the budget for antidiabetic medications, raising awareness about diabetes, and collaborating with the private sector and civil society regarding therapeutic education [
49]. Expanding health coverage may also improve adherence.
We identified a significant association between treatment adherence and the absence of health insurance, suggesting that uninsured patients might be more mindful of medical costs and more diligent in adhering to treatment. This observation contrasts with findings from Naqvi et al. [
35], Khardali et al. [
42], Allaham et al. [
40], and Shakya et al. [
9], who reported no significant association between health insurance and adherence. However, our results may be compared with an Ethiopian study [
50] that indicated lower adherence among uninsured patients paying out-of-pocket for medications. Our unexpected finding may stem from Morocco’s cultural and economic context. Uninsured Moroccan patients might view healthcare costs as a substantial financial burden, prompting stricter treatment management to avoid costly medical consultations or hospitalizations.
Furthermore, individuals from lower socioeconomic backgrounds may adopt stricter health behaviors, driven by the need to maximize the effectiveness of self-funded treatments. Psychological factors, such as fear of diabetes-related complications or cultural emphasis on individual responsibility in managing illness, might also influence this behavior. Additionally, strong community support systems in rural areas of Morocco could reinforce adherence among uninsured patients through informal advice and social solidarity. A lack of health coverage may also foster a heightened sense of personal accountability, motivating patients to avoid expenses related to complications from poor adherence. Nonetheless, we must acknowledge that unmeasured variables, including cultural beliefs about illness or psychological factors such as anxiety over future medical costs, might also influence this association. Future research should explore these hypotheses to clarify the mechanisms driving this unanticipated finding.
A significant association was observed between treatment adherence and self-monitoring of blood glucose. Self-monitoring enables patients to regularly track glucose levels, detect variations, and adjust their treatment accordingly, thereby fostering a better understanding of diabetes and improving disease management. Thus, this practice might be expected to increase adherence to medical recommendations, aligning with Sendekie et al. [
50]. However, some studies have not found a significant relationship between adherence and self-monitoring [
51,
52].
Combinations of specific antidiabetic medications, such as gliclazide and acarbose, were associated with relatively high adherence levels. This significant association suggests that medication choice might influence treatment compliance. Conversely, our study found no significant links between adherence and factors such as sex, marital status, education level, employment status, or comorbidities, although other studies have identified such associations [
9,
35,
42,
51].
Logistic regression analysis revealed that patients on 2 or more OADs had significantly lower adherence, consistent with studies from the United Arab Emirates and Ethiopia [
40,
50]. This reduced adherence may result from the complexity and higher risk of errors associated with managing multiple medications.
Finally, longer disease duration, specifically 11 to 15 years, was associated with lower medication adherence, a finding consistent with a study conducted in Nepal [
51]. Despite developing a better understanding of their condition, patients may experience fatigue or apathy towards treatment, undermining rigorous adherence.
Although our study primarily analyzed socioeconomic and clinical factors associated with medication adherence, cultural beliefs, lifestyle, and patient education can also play critical roles. In Morocco, traditional practices involving medicinal plants and cultural perceptions of diabetes might influence patient attitudes toward medication adherence. Additionally, lifestyle factors, such as dietary habits and physical activity, affect diabetes management and treatment motivation. Furthermore, a low level of health education could limit patient understanding of medical recommendations and compromise adherence, as observed in other studies of chronic diseases in low-resource settings.
In this context, our findings also highlight the positive impact of Moroccan public health policies, such as free access to care and increased resources for treatment. However, certain limitations of the study should be acknowledged. Its focus on 2 regions of the country may limit the generalizability of the results. Additionally, certain key variables were not captured by the GMAS tool used. Psychological factors such as depression and anxiety, as well as cultural beliefs, may also influence adherence but were not explored in this study. These dimensions warrant consideration in future research to gain a more comprehensive understanding of determinants of adherence and to enhance therapeutic strategies. A broader and more diverse approach, incorporating these factors, will help strengthen the effectiveness of interventions for patients with T2DM.
This study has several notable strengths. First, it includes a large, multicenter sample of 584 patients from 2 major regions of Morocco, thus providing nationally representative results. Additionally, its use of the GMAS, specifically validated for the Moroccan context, facilitates an accurate assessment of adherence by considering local socioeconomic and cultural factors. Furthermore, the study adopts a multidimensional approach, exploring a variety of socioeconomic and clinical factors associated with medication adherence; as such, it offers an in-depth understanding of the underlying determinants. Finally, the results of this study complement existing research while providing new and relevant insights to improve public health policies and psychosocial support programs in Morocco.
In conclusion, while our study reveals good medication adherence among patients with T2DM, implementing personalized strategies to strengthen this adherence is essential, especially for groups identified as at-risk. To address the lower adherence rates observed among these patients, several public health interventions can be considered. Education and awareness programs are necessary to inform patients about diabetes management and emphasize the importance of adherence to treatment. Furthermore, personalized follow-up combined with the use of mobile applications could facilitate treatment monitoring. Additionally, psychosocial support through support groups and counselors with lived experience can increase patient motivation. Involving family members in the care process and proposing cost-reduction strategies for medications could also contribute to improving therapeutic adherence.
Finally, additional limitations of our study should be acknowledged. The cross-sectional design limits the ability to establish causal relationships between sociodemographic factors and medication adherence. Furthermore, the inclusion criteria may have influenced the sample by excluding certain vulnerable groups, such as newly diagnosed patients or those with acute conditions. Although reasonably large, the sample was limited to 2 regions of Morocco, which may not fully represent the diverse socioeconomic and cultural realities across the country. Furthermore, the GMAS, while reliable, does not account for psychosocial and cultural factors potentially influencing adherence, such as personal beliefs or family support systems.
Future research should aim for a broader and more diverse analysis to better identify the factors influencing treatment adherence and to optimize T2DM management strategies.
Implications and Directions for Future Research
In Morocco, public health reforms are needed to optimize healthcare spending and improve outcomes for citizens and residents. Increasing medication adherence for T2DM could significantly impact health economics, patient clinical outcomes, and medical practices. Strategies such as simplifying treatment regimens, actively involving healthcare professionals in medication management, and educating patients are often recommended. Healthcare professionals must also be encouraged to proactively foster treatment adherence.
The results of this study suggest the need for further research to better understand the factors contributing to the high levels of adherence observed. Qualitative surveys could provide valuable insights by exploring the experiences and perceptions of patients in detail. Additionally, future efforts should examine the barriers to adherence among patients in rural areas and identify facilitating factors for adherence among patients with long disease duration. These approaches will help develop more effective strategies to improve health outcomes and reduce the economic burden associated with medication non-adherence in the Moroccan healthcare system.
, Nadia Al Wachami
