Adherence to Glycemic Monitoring in Diabetes

Patton, Susana R.

doi:10.1177/1932296814567709

Cited by 60 publications

(54 citation statements)

References 47 publications

(112 reference statements)

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“…The burden of adhering to these various behaviors is carried by adolescents and their families and affects nearly every aspect of daily life. Barriers to optimal treatment adherence are common and include competing demands for time and attention, miscommunication or misunderstandings about what to do (among family members and between families and healthcare providers), financial or insurance-related barriers to obtaining needed care/supplies, insufficient adult involvement or monitoring of adolescent self-management and emotional or behavioral difficulties, among others [7,13]. …”

Section: Conceptual Issues In Adherencementioning

confidence: 99%

“…A meta-analysis of 21 studies and 2429 adolescents showed that higher adherence predicts better glycemic control independent of various indices of sociodemographic status (e.g., socioeconomic, minority race/ethnicity, single parent caregiver) [6]. Adolescents who demonstrate better adherence – for instance, more frequent BGM and premeal insulin administration – have better glycemic control and fewer acute complications than youth who engage in these behaviors less frequently [7,8]. Thus, accurate measurement of adherence behaviors is critical for research and clinical care that aims to promote optimal health outcomes.…”

mentioning

confidence: 99%

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Adherence in adolescents with Type 1 diabetes: strategies and considerations for assessment in research and practice

Gandhi

Eshtehardi

et al. 2015

Diabetes Management

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Suboptimal adherence remains a significant concern for adolescents with Type 1 diabetes, the treatment regimen for which is complex and includes numerous behaviors. Accurate assessment of adherence is critical for effective healthcare and to measure trial outcomes. Without a valid biomarker of adherence, assessment strategies must rely on measuring management behaviors. This paper provides an overview of approaches to measure adherence, with an emphasis on contemporary, validated measures that are appropriate for current diabetes care. Objective measures include electronic data from diabetes management devices. Subjective measures include self/parent-report questionnaires, structured interviews and diaries/logbooks. Practical strategies for selecting measurement approaches for clinical and research purposes are reviewed, and implications of adherence assessment for clinical care delivery and adherence-promotion are discussed.

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Section: Conceptual Issues In Adherencementioning

confidence: 99%

mentioning

confidence: 99%

Adherence in adolescents with Type 1 diabetes: strategies and considerations for assessment in research and practice

Gandhi

Eshtehardi

et al. 2015

Diabetes Management

View full text Add to dashboard Cite

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“…• Behavioral: ○ Barriers to adherence ( [2]; ○ Demands of the technology, which may affect especially motivation to undertake regular self-management tasks ( [1,14]; ○ Time spent on diabetes therapy tasks ( [11].…”

Section: Human Factors and T1dmmentioning

confidence: 99%

“…This puts emphasis on adherence and patient behaviors. It has been suggested that large numbers of people with T1DM are non-adherent [1], however Patton [2] highlights multiple social, emotional and cognitive barriers. The prevalence of new and emergent technologies to support selfmanagement of T1DM through personal data logging processes and support for decision-making may have potential in addressing these issues.…”

Section: Introductionmentioning

confidence: 99%

Human Factors and Data Logging Processes With the Use of Advanced Technology for Adults With Type 1 Diabetes: Systematic Integrative Review (Preprint)

Waite¹,

Martin²,

Franklin³

et al. 2017

Preprint

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Background: People with T1DM are confronted with self-management tasks and strategies to reduce risks of long-term complications against the risk of hypoglycemic events. The potential of advanced and evolving technology to address these issues involves consideration of psychological and behavioral constructs alongside the usability of devices. Access and uptake of advanced technology is further influenced by economic factors and health care provider capacity to support such interventions. Previous reviews have focused upon either clinical outcomes or descriptively scoped the literature and sometimes synthesize studies on adults with children and young people where human factors are different. Objective:The objective of this review was to describe the relationship between human factors and adherence with technology for data logging processes in adults with T1DM and to explore the factors which influence this association. Methods: A systematic literature review.Results: 18 studies were included in the review following a literature search using the PRISMA guidelines and the quality appraisal process. Six constructs emerged from the data analysis:. The relationship between adherence to data logging and measurable outcomes; Satisfaction with the transition to advanced technology for self-management; Use of advanced technology and time spent on diabetes related activities; Strategies to mediate the complexities of diabetes and the use of advanced technology; Cognition in the wild and Meanings, views and perspectives from the users of technology.There was evidence of increased treatment satisfaction on transition to advanced technology (insulin pump and CGM), the most significant contributing factor was when BG levels were consistently < 7.00mmol/l (P =.009). However, participants spent considerable time on their diabetes self-care. There was evidence that 1 logging of data was positively correlated with increasing age with the use of an app that provided meaningful feedback (regression coefficient = 55.8 recordings/ year; P = 0.009). Furthermore, there were benefits of CGM for older people in mediating complexities and their fears of hypoglycemia with reported significant differences in well-being (P= .009).Qualitative studies within the review aimed to explore the use and uptake of technology within the context of everyday lives. There were 'frustrations' with CGM, CSII, calibration of devices and alarms. In addition, the implications of 'body image' and the way in which 'significant' others impacted on the behavior and attitude of the individual towards technology use. There were wide variations in the normal use of and interaction with technology across a continuum of sociocultural contexts. This has implications for the way in which future technologies are designed. Conclusions:Many of the quantitative studies in the review were limited by small sample sizes. This may make it difficult to generalize findings to other contexts. This is further limited by a sample that was predominantly Caucasian, well-contr...

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“…13 In REPLACE, individuals with T2D utilizing flash CGM had a significantly improved mean DTSQ total treatment satisfaction score of Adherence to SMBG has been reported to be as low as 44% in T1D and 24% in T2D. 16 Given that flash CGM provides continuous, unobtrusive, and convenient glucose monitoring without the need for routine blood glucose tests, it may improve patient adherence versus SMBG. High rates of adherence to flash CGM were seen in both studies: the percentage of available data collected was 92.8% in IMPACT and 88.7% in REPLACE.…”

Section: Clinical Implications Of Flash Continuous Glucose Monitoringmentioning

confidence: 99%

Flash Continuous Glucose Monitoring and its IMPACT to REPLACE Blood Glucose Monitoring in the Management of Type 1 and Type 2 Diabetes

Twigg¹,

Kazemi²,

Craig³

2017

US Endocrinology

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O bjective: Established methods of self-monitoring of glucose levels include capillary self-monitoring of blood glucose (SMBG) and interstitial continuous glucose monitoring (CGM). Flash CGM is a novel form of self-monitoring that provides on-demand continuous interstitial glucose profiles. The purpose of this article is to critically review the recent outcome data from randomized controlled trials that assessed the efficacy and safety of flash CGM to replace routine SMBG in diabetes management. Methods: Two recent six-month, prospective, multicenter, randomized controlled trials in type 1 (IMPACT; NCT02232698) and type 2 (REPLACE; NCT02082184) diabetes compared flash CGM with SMBG under otherwise usual care conditions. The trials did not use a prescribed treatment algorithm based on self-monitoring of glucose. Results: Both trials demonstrated that the time spent in hypoglycemia over a 24-hour period, as well as overnight, was markedly reduced by flash CGM without deterioration in glycated hemoglobin (A1C) levels. In IMPACT there was a 38% reduction in time in hypoglycemia with flash CGM versus SMBG, and in REPLACE there was a 43% reduction in time in hypoglycemia with flash CGM compared with SMBG. Moreover, patient satisfaction improved with flash CGM, usage adherence rates were high, and flash CGM was well tolerated. Conclusions: The findings from these trials suggest that improved care outcomes can be achieved when flash CGM is integrated into current established clinical care paradigms. Flash CGM provides important advantages over SMBG that are likely to be applicable to real-world care of individuals with differing forms of diabetes requiring intensive insulin treatment.

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Adherence to Glycemic Monitoring in Diabetes

Cited by 60 publications

References 47 publications

Adherence in adolescents with Type 1 diabetes: strategies and considerations for assessment in research and practice

Adherence in adolescents with Type 1 diabetes: strategies and considerations for assessment in research and practice

Human Factors and Data Logging Processes With the Use of Advanced Technology for Adults With Type 1 Diabetes: Systematic Integrative Review (Preprint)

Flash Continuous Glucose Monitoring and its IMPACT to REPLACE Blood Glucose Monitoring in the Management of Type 1 and Type 2 Diabetes

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