Decisions in the Psychology of Glucose Monitoring

How is Patient Adherence Possible? A Novel Mechanistic Model of Adherence Based on Humanities

Patient non-adherence is a major contemporary medical issue because of its consequences in terms of frequency, morbidity and mortality, and health care costs. This article aims to propose a mechanistic model of adherence based on the tenet that non-adherence is the default option, as long-term adherence in chronic diseases requires sustained effort. The real question becomes, how is patient adherence possible? By focusing on adherent patients, the paper explains the mental mechanisms of adherence using concepts largely drawn from humanities, philosophy of mind, and behavioral economics and presents the findings of empirical studies supporting these hypotheses. The analysis first demonstrates the relationship between patient adherence and temporality and the influence of character traits. Further, it points out the importance of habit, which allows adherence to become non-intentional, thereby sparing patients' cognitive efforts. Finally, it points out the importance of the quality of the interaction between the person with a chronic disease and the health professional. These features explain why adherence is a syndrome (the healthy adherer phenotype), separating people into those who are safe and those who are at risk of non-adherence, non-control of diabetes, and complications. The concepts presented in this article summarize 20 years of personal clinical and philosophical reflection on patient adherence. They are mainly illustrated by examples from diabetes care but can be applied to all chronic diseases. This novel model of adherence has major practical and ethical implications, explaining the importance of patient education and shared medical decision-making in chronic disease management.

An Unsafe/Safe Typology in People with Type 2 Diabetes: Bridging Patients' Expectations, Personality Traits, Medication Adherence, and Clinical Outcomes

BACKGROUND

Support programs are provided to people with diabetes to help them manage their disease. However, adherence to and persistence in support programs are often low, making it difficult to demonstrate their effectiveness.

AIM

To identify the determinants of patients' perceived interest in diabetes support programs because it may be a powerful determinant of effective participation in such programs.

PATIENTS AND METHODS

An online study conducted in April 2021 in metropolitan France on 600 people with diabetes recruited from a consumer panel. A 64-item psychosocial questionnaire including a question asking to evaluate the helpfulness of a support program was used. Univariate, multivariate, and multiple correspondence analyses were performed.

RESULTS

The existence of a typology, known as Unsafe/Safe, was discovered, in which patients with type 2 diabetes respond in two distinct ways. Type U (unsafe) patients, who believe that a support program would be helpful, are more likely to be nonadherent to their treatment, have high hemoglobin A1c levels, have at least one diabetic complication, lack information regarding their disease and treatment, rate the burden of their disease and impairment of their quality of life as high, worry about their future, and are pessimistic. Type S (safe) patients have the opposite characteristics. Type U patients can be dichotomized into two broad classes: one in which they lack information regarding disease and treatment and the other in which alterations in the quality of life and burden of the disease predominate. Insulin-treated patients give more importance to the lack of information, whereas noninsulin-treated patients complain primarily about the burden of the disease and impairment of quality of life.

CONCLUSION

This study describes this new U/S typology, proposes a simple method based on a nine-item questionnaire to identify type U patients by calculating a Program Helpfulness Score described herein, and clarifies the nature of the intervention to be provided to them. This novel approach could be applied to other chronic diseases.

Pharmacoadherence: An Opportunity for Digital Health to Inform the Third Dimension of Pharmacotherapy for Diabetes

The basis of pharmacotherapy requires knowledge of two properties of a drug: pharmacokinetics (PK) and pharmacodynamics (PD). In the era of precision medicine, there is growing interest in determining between-individual variations in PK and PD. While these two dimensions of pharmacotherapy are key foci of investigation, a third property is also emerging as a critical factor in understanding how a drug affects an individual. This third property of a drug is known as phamacoadherence (PA). There can be wide variation in PA among people with diabetes, whether they are using oral or injectable medications. The use of new digital health interventions and telehealth communication tools, such as smart insulin pens, is now creating opportunities for health care professionals to have a more complete understanding of the PA of drugs, which allows for more personalized prescribing practices.

Intentionality in adherence to long-term therapies. Results from an online survey of 3,001 patients with cardio-metabolic pathologies in France

PURPOSE

Some patients make a rational choice not to follow medical prescriptions; others fail to take their medications for reasons beyond their control, such as mere forgetfulness or a weak medication routine. The aim of this study was to elucidate the functioning of patient intentionality in medication adherence.

PATIENTS AND METHODS

This online study was conducted in metropolitan France in 2019. A cross-sectional survey of 50 questions was conducted with 3001 respondents diagnosed with diabetes, hypertension, and/or hypercholesterolemia identified from a panel of 54,000 people. These questions included a validated six-item questionnaire to detect nonadherence, two questions to detect intentional nonadherence by patients, and three questions on the effects of habit. Our questionnaire also included questions on the feelings of respondents regarding their doctor's attitude to their problems and needs, their trust in general practitioners (GP) and specialists, their sense of being involved in treatment decisions, and the influence of side effects and habits on patients' adherence. This study used the strategy of focusing on strictly adherent patients in the hope of finding ways to improve adherence. For this reason, we defined adherence as the absence of a positive response to the 6-item nonadherence screening questionnaire.

RESULTS

Of 3001 respondents, 1804 were diagnosed with hypertension, 1458 with hypercholesterolemia, and 774 with diabetes. Of the total number of patients, 72% were afflicted with one disease, 21% with two ailments, and 7% with three simultaneous illnesses. One-third (33%) of the patients did not tender a positive answer to the adherence questionnaire and were deemed adherent. 1) Thirty-two percent of the patients reported occasionally omitting their medication deliberately, and 84% said they had a reason for missing doses. These statements suggesting intentional nonadherence were negatively associated with adherence as identified via multivariate analysis (P = 0.0012 and P < 0.0001, for the first and second statement, respectively). 2) Univariate analyses revealed strong associations (P < 0.0001) between strict adherence on one hand and lack of intentional nonadherence, patient age, absence of drug side effects, taking drugs by habit, feeling involved in treatment decisions, getting information about treatment, and disease, and trust in doctors, on the other hand. 3) Specifically, univariate analysis of the absence of reported side effects revealed strong associations (P < 0.0001) with adequate information about medicines and diseases and trust in GP. These original data were consistent with the concept of the nocebo effect. 4) We observed a strong association between the absence of intentional nonadherence (statement of never deliberately missing medication) and respondent statements about generally sticking to the routine (P < 0.0001), ie, "I take my medication because I am used to taking it." This important result suggests that patients are strictly adherent in two ways: the absence of intentional nonadherence and reliance on habit, which we term as "unintentional adherence." 5) Finally, a multiple correspondence analysis illustrated all statistically significant relationships found in this study.

CONCLUSION

We present a new global model of adherence in which patient adherence was improved both by reducing intentional nonadherence and by promoting the abovementioned unintentional adherence by habit. This model highlights the role of shared decision-making and the trust felt by patients in their doctors. These results could exert a major impact on medical practice and education by demonstrating the importance of physicians' attitudes, involving the patient in decisions (shared decision-making), offering information about medicines and diseases (patient education), understanding the problems of patients, and taking their needs into account (empathy). The development of these attitudes should be an important aspect of the medical curricula.

Patient Satisfaction and Clinical Efficacy of Flash Glucose Monitoring in Patients with Type 1 Diabetes: A Prospective, Single-Center, Single-Arm Study

INTRODUCTION

Frequent self-monitoring of blood glucose (SMBG) is usually required in patients with type 1 diabetes (T1D). However, the fear of self-testing, hygiene, and social obstacles may deter some patients from SMBG. Flash glucose monitoring (FGM), a less-invasive glucose monitoring method, was launched in Japan in September 2017. The aim of this study was to evaluate patient satisfaction and the clinical efficacy of FGM in Japanese patients with T1D.

METHODS

Patient satisfaction with FGM was assessed using the Diabetes Treatment Satisfaction Questionnaire (DTSQ) and Diabetes Therapy-Related Quality of Life (DTR-QOL) questionnaire before (baseline) and 4 and 12 weeks after initiating FGM use in 20 Japanese patients with T1D. Clinical parameters related to glucose metabolism, such as glycated hemoglobin (HbA1c) levels, were assessed, and glucose fluctuations were evaluated using the FGM data. Values at 4 and 12 weeks after initiating FGM were compared with baseline data using the Wilcoxon signed-rank test. The mean absolute relative difference (MARD) between glucose values detected using the FGM device and by SMBG was also calculated.

RESULTS

The DTSQ scores significantly improved 12 weeks after initiating FGM (P < 0.001). The DTR-QOL scores related to "burden in social activities" and "treatment satisfaction" also significantly improved 12 weeks after initiating FGM (P = 0.024 and 0.007, respectively). The HbA1c values and the percentage of time within the target glucose range (3.9-7.8 mmol/L) at the 12-week time point also improved, from 58 ± 5 (baseline) to 54 ± 4 mmol/mol (P = 0.002) and from 36% (interquartile range [IQR] 25-44.5%) (baseline) to 43% (IQR 39-50%) (P = 0.016), respectively. The MARD between glucose values detected using FGM and those detected using SMBG was 12.2% throughout the study period.

CONCLUSIONS

Flash glucose monitoring contributed to improved patient satisfaction and the adjustment of blood glucose levels in patients with T1D.

TRIAL REGISTRATION

University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR): UMIN000029673.