Impactul monitorizării continue a glicemiei asupra echilibrului psihoemoțional al pacienților cu diabet de tip 1

1. Introduction

Background of the study

The management of type 1 diabetes (T1D) presents an ongoing challenge, not only from a medical standpoint but also from a psycho-emotional perspective. In recent years, research has increasingly focused on the psychological effects associated with daily glucose monitoring, dietary self-regulation, and the uncertainty surrounding hypoglycemic episodes^(1-4). Within this context, continuous glucose monitoring (CGM) technology represents a fundamental shift, providing patients with constant access to essential glycemic data and thereby contributing to reduced anxiety and enhanced perceived control^(5,6).

The scientific literature highlights a strong association between chronic stress and disruptions in psychobiological balance, particularly among individuals living with chronic illnesses such as diabetes^(3,7,8). Emotional imbalances, including anxiety and sleep disturbances, are frequently observed among patients with T1D, and the complexity of the therapeutic regimen often exacerbates feelings of uncertainty and frustration^(2,9-11). A high level of treatment adherence is closely linked to psychological factors such as motivation, self-efficacy, and emotional regulation^(12-15). Neurobiological studies have explored the role of biomarkers like serotonin and cortisol in relation to depression among diabetic patients, offering a foundation for targeted psychological interventions ^(2,7,16).

CGM technology functions not only as a clinical tool, but also as a means of psychological self-regulation. By delivering real-time alerts on glycemic fluctuations, CGM reduces the unpredictability of hypoglycemia, which in turn lowers anticipatory stress and improves overall quality of life^(17-20). Recent studies have reported that the psychological benefits of CGM use extend to improved mental clarity, enhanced mood, better sleep quality, and healthier attitudes toward food^(5,13,21-26). The literature confirms the emergence of disordered eating behaviors among adolescents and young adults with T1D, particularly when glycemic control becomes a source of psychological tension^(27-36). Behaviors such as insulin omission, restrictive dieting, or binge eating have been documented as maladaptive coping mechanisms^(33,35,37). In this regard, CGM may serve an indirect preventive function by promoting a more balanced relationship with food and body image^(30,38-40). While numerous studies have examined the technical dimensions of CGM, such as sensor accuracy, calibration errors and their implications for day-to-day therapeutic decisions^(41-46), the long term psycho-emotional impact of CGM use remains underexplored in the Romanian population. The primary aim of this study is to investigate the influence of continuous glucose monitoring on emotional balance, mental clarity and self-management capacity in adult patients with type 1 diabetes. Building upon previous findings, our general hypothesis is that CGM use contributes to reduced stress and anxiety while supporting healthier eating behaviors and improved well-being^(5,21,27). This research adopts an integrative perspective, combining behavioral, emotional and technological dimensions to inform the development of effective psychological support strategies for individuals with T1D.

The study is structured around the following hypotheses:

• Hypothesis 1. The use of continuous glucose monitoring (CGM) contributes to a significant reduction in anxiety levels among patients with type 1 diabetes.
• Hypothesis 2. Patients who plan their meals based on glycemic values exhibit higher levels of mental clarity and emotional calm.
• Hypothesis 3. The duration of CGM use is significantly associated with improved overall mood and emotional well-being.
• Hypothesis 4. Patients with greater confidence in their ability to self-manage the disease demonstrate enhanced capacity for regulating negative emotions.
• Hypothesis 5. CGM reduces perceived stress levels in patients who report effective interventions during hypoglycemic episodes.

2. Materials and method

The study was conducted on a convenience sample consisting of 90 adult patients diagnosed with type 1 diabetes, recruited from various regions across Romania. A summary of the participant selection process is presented in Figure 1.

The inclusion criteria required participants to have a confirmed diagnosis of type 1 diabetes, to have been using a continuous glucose monitoring device for at least one month, and to have completed the questionnaire in full. Incomplete or incoherent responses were excluded. Out of a total of 97 collected questionnaires, seven were eliminated due to failing to meet validity requirements, resulting in a final sample of 90 respondents.

The study employed a quantitative, cross-sectional design, carried out over a two-month period (May-June 2025). The questionnaire was organized into five sections: demographic data, eating behaviors, perceived control, emotional impact, and openness to nutritional support. It incorporated items adapted from internationally validated instruments, including the WHO-5 (for emotional well-being), HADS (for anxiety), DASS-21 (for psychological stress), and DERS (for emotion regulation). Attitudinal and psycho-emotional impact items were measured using a 1-5 Likert scale, while demographic and behavioral questions were categorical or ordinal in nature. Data collection was conducted online, based on voluntary participation, using patient communities, social media platforms, and specialized forums. Statistical analyses were performed using IBM SPSS Statistics, version 20. Depending on variable types, the Spearman rho correlation coefficient, Kruskal-Wallis test, and Mann-Whitney U test were applied.

Participation was both anonymous and voluntary, in alignment with the ethical standards of psychological research. The study protocol received approval from the Research Ethics Committee of the “George Emil Palade” University of Medicine, Pharmacy, Sciences and Technology, Târgu-Mureș, Romania, as confirmed by Decision No. 3785, issued on 19 May 2025, certifying compliance with ethical guidelines for scientific research. 

Results

Demographic characteristics of the sample of students

The final sample comprised 90 adult patients diagnosed with type 1 diabetes, originating from various regions of Romania. Of these participants, 66 (73.3%) were female and 24 (26.7%) were male. Regarding age distribution, 38.9% of respondents were between 18 and 30 years old, while 61.1% were aged between 31 and 50. The majority of participants (73.3%) received their diabetes diagnosis after the age of 11, whereas 16.7% were diagnosed before the age of 5, and 10% between the ages of 5 and 10 years old. The duration of CGM sensor usage varied: 65.6% reported using the sensor for more than two years, 13.3% for approximately one year, and the remainder for less than one year, accounting for smaller proportions. As for the type of CGM device, 67.8% of participants used the Dexcom G7, 31.1% used the Dexcom G6, and a small fraction (1.1%) reported using the Freestyle Libre.

Eating behaviors and nutritional adjustments

This section examines how the use of continuous glucose monitoring devices influences the eating behaviors of individuals with type 1 diabetes. The analysis focused on the frequency of main meals and snacks, changes in meal planning, the avoidance of certain foods, adjustments in nutritional composition, and the degree of attention paid to food labels. The aim was to highlight the extent to which sensor-generated data support self-regulation of dietary habits and promote more conscious, glycemic-responsive nutritional choices. The descriptive results are summarized in Table 1 and visually represented in Figure 2, which displays the average scores associated with these behaviors. The average scores indicate a high prevalence of adaptive dietary behaviors among participants. A significant proportion of participants (85.6%) reported taking effective action in response to hypoglycemic episodes, as reflected by the low mean score (M=1.04) for the item addressing hypoglycemia intervention. A substantial proportion of respondents indicated that they avoid hyperglycemic foods (M=1.31), pay close attention to nutritional labels (M=1.20), and have adjusted their meal structure based on glucose level readings. On average, participants reported consuming nearly three main meals per day (M=2.66), suggesting the presence of a stable and consistent dietary routine.

Perceptions of control and clarity in diabetes management

This section explores how the use of continuous glucose monitoring (CGM) devices influences the perceptions of individuals with type 1 diabetes regarding mental clarity, emotional self-regulation, and their sense of control over dietary choices. The findings summarized in Table 2 and illustrated in Figure 3 indicate a predominantly positive perception across these dimensions.

The mean values illustrated in the graph reflect a generally positive perception among patients regarding the impact of CGM use on their psycho-emotional state. The elevated scores for improved eating behavior (M=4.33) and emotion regulation (M=4.20) indicate effective self-regulation and the adoption of healthier behavioral patterns. At the same time, the low score for anxiety-related clarity (M=1.13) suggests a significant reduction in diabetes-related anxiety and improved psychological clarity.

Assessing the impact of CGM use on emotional self-regulation, confidence and overall psychological well-being in individuals with type 1 diabetes

This section explores how continuous glucose monitoring technology influences the emotional dimension of diabetes management in individuals diagnosed with type 1 diabetes. The analysis focuses on key aspects such as confidence in disease self-management, anxiety reduction, mental clarity, overall emotional state, and perceived stress levels. The data, summarized in Table 3, provide a comprehensive overview of the psychological and emotional benefits that patients associate with the integration of CGM into their daily self-care routines.

Table 3 highlights that the use of continuous glucose monitoring is significantly associated with improved emotional self-regulation among patients with type 1 diabetes. The highest mean scores were observed for self-management confidence (M=4.5556), anxiety reduction (M=4.4556), and decreased stress levels (M=4.4222). These findings suggest a favorable perception of the emotional and functional impact of CGM technology in the daily lives of individuals managing type 1 diabetes.

Patients’ openness to nutrition counselling based on CGM data

This section examines the willingness of individuals with type 1 diabetes to engage in personalized nutritional counselling tailored to the data provided by continuous glucose monitoring (CGM) systems. This approach explores the receptiveness to psychonutritional support aimed at promoting better glycemic control and a more balanced diet. Table 4 and Figure 4 present the distribution of responses regarding interest in this type of counselling, reflecting the perceived need for specialized guidance in disease management.

The findings presented in Table 4 and Figure 4 indicate a substantial level of interest among patients with type 1 diabetes in receiving personalized nutritional counselling informed by CGM data. Nearly 69% of participants demonstrated a clear openness to this type of targeted intervention, suggesting a growing awareness of the benefits of data-driven support in managing daily glycemic control. These results underscore the potential for integrating CGM-based insights into psychonutritional strategies, thereby enhancing adherence, autonomy, and patient-centered care in diabetes management.

Discussions on confirming the hypotheses through variable correlation

To test the hypotheses formulated in this study, Spearman correlation analyses were performed using SPSS software. The choice of the Spearman coefficient was justified by the ordinal nature of the data collected through the Likert scale, as well as the nonparametric distribution observed for most of the analyzed variables. The primary objective was to explore the relationships between dietary behavior changes influenced by CGM use and key psychological indicators such as emotional self-regulation, mental clarity, anxiety reduction and confidence in disease self-management. The study investigated whether the duration of CGM use correlated with the perceived level of disease control, as well as the participants’ interest in personalized nutritional counselling. The results provided relevant insights into the perceived effectiveness of CGM technology in promoting more mindful eating behaviors and enhancing psychological well-being among individuals with type 1 diabetes.

Hypothesis 1. The use of continuous glucose monitoring (CGM) contributes to a significant reduction in anxiety levels among patients with type 1 diabetes.

To examine this hypothesis, a correlation analysis was conducted between the variable “Anxiety_Reduction” and other relevant indicators, such as “Sensor_Use_Duration”, “Anxiety_Clarity”, and “Self-Management_Confidence”, using the Spearman coefficient in SPSS. These variables reflect patients’ perceptions of their emotional state in relation to CGM use. The hypothesis aimed to identify a negative association between the duration of sensor use and the perceived level of anxiety, as well as a positive correlation between the clarity provided by CGM data and the reduction of disease-related anxiety.

To verify the validity of Hypothesis 1 stating that the use of continuous glucose monitoring (CGM) contributes to anxiety reduction in patients with type 1 diabetes, a Spearman correlation analysis was conducted between the variable “Anxiety_Reduction” and several relevant indicators: “Sensor_Use_Duration”, “Anxiety_Clarity”, and “Self-Management_Confidence”. The results revealed a significant negative correlation between the duration of sensor use and perceived anxiety levels (r = -0.443; p<0.01), suggesting that prolonged use of CGM is associated with reduced anxiety. The perceived clarity regarding one’s health status, as provided by the sensor, was also negatively correlated with anxiety (r = -0.649; p<0.01), indicating that individuals who feel more informed and in control tend to experience fewer anxiety symptoms. Confidence in one’s ability to self-manage diabetes showed a strong positive correlation with anxiety reduction (r = 0.751; p<0.01). These findings support the proposed hypothesis and emphasize the beneficial role of CGM technology in enhancing emotional self-regulation among patients.

Hypothesis 2. Patients who plan their meals based on glycemic values exhibit higher levels of mental clarity and emotional calm.

To assess the validity of Hypothesis 2, which posits that patients who plan their meals according to CGM-indicated glucose values experience greater mental clarity and emotional stability, a Spearman correlation analysis was conducted, using the SPSS software. This hypothesis is grounded in the assumption that self-regulation of dietary behavior, guided by real-time objective data, may help reduce uncertainty and enhance the sense of personal control, thereby positively influencing emotional well-being.

Two relevant variables were selected: Meal_Planning_Self-Regulation (assessing the extent to which participants plan meals based on CGM readings) and Mental_Clarity_Emotional_Calm (reflecting the perceived level of cognitive clarity and emotional steadiness in managing diabetes).

The analysis was performed on a sample of 90 participants, and Spearman correlation coefficients were used to examine the direction and strength of the relationship between the two variables, to determine whether the proposed hypothesis is confirmed or refuted.

The results indicate a statistically significant negative correlation between the two variables (ρ = -0.699; p<0.01). This suggests that as the frequency of meal planning increases (lower scores on the ordinal variable reflect more frequent planning), the perceived level of mental clarity and emotional calm also rises.

Hypothesis 2 is confirmed. Meal planning informed by CGM data is associated with a more balanced psychological state, underscoring the beneficial role of technology-assisted nutritional self-regulation in alleviating emotional distress related to type 1 diabetes.

Hypothesis 3. The duration of CGM use is significantly associated with improved overall mood and emotional well-being.

To evaluate Hypothesis 3, which posits that the duration of continuous glucose monitoring (CGM) use is associated with enhanced overall mood, a Kruskal-Wallis test was applied (Table 7). This nonparametric method is appropriate for comparing multiple independent groups when the dependent variable is ordinal and the assumption of normality is not met. For this analysis, the variable Sensor_Use_Duration was categorized into three distinct groups: less than six months, between six and 12 months, and more than one year. This variable served as the grouping factor. Scores on the Overall_Mood variable, assessed using a 1-5 Likert scale, were compared across these groups to determine whether statistically significant differences existed in reported emotional well-being based on length of CGM exposure. The choice of the Kruskal-Wallis test was informed by the ordinal nature of the data and the independent structure of the compared groups.

To test Hypothesis 3, which posits that the duration of continuous glucose monitoring (CGM) use is associated with a significant improvement in overall mood, the Kruskal-Wallis test was applied. This nonparametric method is suitable when the dependent variable is ordinal and the groups being compared are independent, particularly when normality assumptions are not met. The variable Sensor_Use_Duration was divided into six distinct categories, ranging from less than one month to more than two years. Scores on the Overall_Mood variable, measured on a 1-5 Likert scale, were compared across these groups to assess the presence of statistically significant differences in emotional well-being.

The test yielded a statistically significant result (Chi-Square=43.609; df=5; p<0.001), indicating that CGM use duration has a meaningful impact on patients’ reported mood. Participants who had used the sensor for less than two years reported higher well-being scores, while those with over two years of usage tended to report lower scores. These findings support the hypothesis but also suggest that the emotional benefits of CGM use may be more pronounced in the earlier stages of adoption. Over time, adaptive processes or external influences may attenuate the perceived psychological advantages.

Hypothesis 4. Patients with greater confidence in their ability to self-manage the disease demonstrate enhanced capacity for regulating negative emotions.

To test Hypothesis 4, which proposes that patients with higher confidence in their ability to self-manage diabetes also demonstrate a greater capacity for regulating negative emotions, the Spearman correlation coefficient was used. This nonparametric method is appropriate for examining the relationship between two ordinal variables measured on a 1-5 Likert scale, particularly when the assumption of normality is not met.

The variables included in the analysis were Self-Management_Confidence, reflecting the respondent’s perceived control over managing the disease and its associated lifestyle, and Emotion_Regulation, which assessed the ability to cope with negative emotional states (such as frustration, irritability or anxiety) in the context of living with diabetes. The objective of this analysis was to identify a significant positive association between the two constructs, supporting the notion that confidence in one’s self-management abilities contributes to more effective emotional regulation when facing the challenges of the illness.

The analysis results (Table 8) reveal a very strong and statistically significant positive correlation between the two variables, with a Spearman coefficient of ρ=0.833 (p<0.001). This association suggests that patients who report higher confidence in their ability to manage diabetes also demonstrate greater emotional self-regulation. The hypothesis is confirmed, and the findings emphasize the importance of fostering a sense of self-efficacy within psychological interventions targeting individuals with type 1 diabetes.

Hypothesis 5. CGM reduces perceived stress levels in patients who report effective interventions during hypoglycemic episodes.

To evaluate the hypothesis that continuous glucose monitoring (CGM) use contributes to a reduction in perceived stress levels particularly among patients who have effectively intervened during hypoglycemic episodes, the Spearman correlation coefficient was used. The selection of this nonparametric test was justified by the ordinal nature of the variables and the non-normal distribution of the data. The variable Stress_Reduction captures patients’ subjective perception of reduced stress following CGM use, while Hypoglycemia_Intervention reflects the frequency and effectiveness of actions taken during critical episodes. The analysis aimed to determine whether a significant relationship exists between self-regulatory capacity during hypoglycemic events and the reduction of stress associated with day-to-day diabetes management.

The Spearman correlation analysis revealed a statistically significant negative association between Hypoglycaemia_Intervention (the perceived effectiveness of responses during hypoglycaemic episodes) and Stress_Reduction (the perceived reduction in stress attributed to the use of continuous glucose monitoring CGM), with a rho coefficient of -0.400 and a significance level of p

Practical implications and recommendations

The findings of this study underscore the positive impact of continuous glucose monitoring (CGM) technology on the psychological and emotional well-being of individuals with type 1 diabetes. In addition to its well-documented clinical benefits, CGM offers several psychological advantages, including reduced anxiety related to hypoglycemia, enhanced mental clarity, and increased confidence in self-management. These factors contribute to improved quality of life and more effective daily disease management.

Based on these findings, several strategic recommendations can be advanced. These include broadening access to continuous glucose monitoring (CGM) for eligible individuals through targeted institutional support and well-defined reimbursement frameworks, embedding CGM-related education within national diabetes care and support initiatives, facilitating individualized psychological and nutritional counselling informed by sensor-derived data and ensuring that healthcare professionals receive ongoing practice-oriented training to incorporate CGM effectively into a comprehensive, patient-centered approach to diabetes management.

It is also essential for clinical psychologists involved in chronic illness care to consider CGM-generated data in tailoring interventions to the patient’s emotional landscape. Equitable access to this technology, coupled with support for the development of self-management skills, has the potential to significantly reduce emotional vulnerability and promote a more stable and health-oriented lifestyle among individuals living with type 1 diabetes.

Discussion

The results of this study confirm that continuous glucose monitoring (CGM) has a significant positive effect on the psychological and emotional balance of patients with type 1 diabetes, supporting the proposed hypotheses. Individuals using CGM reported lower levels of anxiety and stress, along with increased perceptions of mental clarity and personal control findings that are consistent with previous research highlighting the link between glycemic variability and affective states^(47,48). CGM facilitates meal planning and emotional self-regulation by reducing uncertainty related to glucose fluctuations, a finding also supported by international literature emphasizing the mental health implications of glycemic variability^(49,50). The increased confidence in self-management, correlated with CGM use, reinforces the idea that real-time access to critical glycemic information helps diminish avoidance behaviors and negative emotional reactions.

Another relevant dimension concerns the association between perceived stress, sleep disturbances, and repetitive negative thinking^(51-55). Insomnia and cognitive rumination are recognized as mediators in the relationship between chronic stress and psychological impairment, and interventions involving monitoring and feedback may help disrupt this cycle^(56-58). Recent studies suggest that nonpharmacological strategies such as mindfulness or cognitive behavioral therapy (CBT) can enhance emotional regulation and sleep quality, particularly when combined with objective feedback from sources like CGM^(59-61).

The research highlights that self-regulation processes are influenced by perseverative thinking and by the individual’s ability to interpret physiological signals realistically^(62-64). The integration of CGM may contribute to the development of this awareness and the ability to respond rapidly. The prospect of integrated interventions that combine CGM technology with personalized psychological support is taking shape, offering a patient-centered model focused on emotional self-regulation.

The conclusions of this study support the beneficial role of CGM not only in metabolic monitoring but also in supporting mental health, reinforcing the need for an interdisciplinary approach in the management of type 1 diabetes.

Limitations and future directions

Although the study offers valuable insight into the psycho-emotional impact of CGM technology on patients with type 1 diabetes, several methodological limitations should be noted. The sample was based on availability and voluntary participation, which may have introduced a selection bias. Participants more engaged with their own health or already familiar with CGM may hold more favorable views of the technology, potentially skewing the results. The cross-sectional design of the study limits the ability to establish causal relationships between CGM use and the psycho-emotional variables analyzed. Although statistically significant correlations were identified, causality cannot be inferred without longitudinal research tracking changes in psychological well-being over time. Another limitation is the absence of a direct comparison with a control group of patients not using CGM. This restricts the assessment of differential impact relative to traditional glucose monitoring methods. Most of the data were self-reported, which introduces a risk of cognitive bias or socially desirable responding. Objective measurements of variables such as sleep, stress, or mental clarity using methods like actigraphy, heart rate variability (HRV), or EEG could enhance the external validity of future research. For future directions, the study recommends expanding research to include larger, geographically and socioeconomically diverse samples, as well as implementing longitudinal designs. Exploring the impact of CGM among adolescents and other vulnerable populations may provide deeper insights into emotional adaptability across age groups and levels of family support. The integration of psychological interventions tailored to CGM data such as real-time digital counselling or biofeedback-based strategies may represent an innovative avenue for applied research in both diabetes care and mental health.

Conclusions

The findings of this study demonstrate that continuous glucose monitoring (CGM) has a significant positive impact not only on metabolic control, but also on the psycho-emotional well-being of adults living with type 1 diabetes. In the context of the daily challenges posed by this chronic condition, CGM proves to be a valuable tool in promoting emotional balance and a greater sense of security. Patients using CGM report marked reductions in perceived anxiety and stress, enhanced mental clarity and increased confidence in their ability to self-manage the disease. These effects are supported by significant correlations between variables such as CGM usage duration, meal planning frequency based on CGM data, and emotional self-regulation. Effective responses to hypoglycemia were associated with lower stress levels, emphasizing the role of continuous glucose monitoring in enabling informed, timely reactions to critical situations. Another finding is the patients’ openness to personalized nutritional counselling based on sensor data, reflecting a clear need to integrate CGM insights into psychonutritional and educational interventions. This supports the vision of an integrated, patient-centered therapeutic model that positions CGM not merely as a monitoring tool, but as an active component in behavioral and emotional self-regulation. In conclusion, CGM offers more than metabolic tracking – it becomes a psychological partner in the lives of individuals with type 1 diabetes. The results advocate for broader access to this technology and for adapting healthcare services toward personalized management, where emotional dimensions are recognized and addressed through evidence-based, practical strategies such an integrative approach that may significantly enhance the quality of life and reduce the psychological vulnerability within this patient population.  

Corresponding author: Mădălina-Gabriela Cincu E-mail: cincu.madalina@yahoo.com

Conflict of interest: none declared.

Financial support: none declared.

This work is permanently accessible online free of charge and published under the CC-BY licence.