Evidence map›Paper›PMID 31968384›Full record

ArticleApplied clinical informatics2020

Self-Management Behaviors of Patients with Type 1 Diabetes: Comparing Two Sources of Patient-Generated Data.

George Karway, Maria Adela Grando, Kevin Grimm, Danielle Groat, Curtiss Cook, Bithika Thompson

Abstract readComparative Study
In one paragraph

Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

George KarwayCollege of Health Solutions, Arizona State University, Scottsdale, Arizona, United States.
Maria Adela GrandoCollege of Health Solutions, Arizona State University, Scottsdale, Arizona, United States.
Kevin GrimmDepartment of Psychology, Arizona State University, Scottsdale, Arizona, United States.
Danielle GroatCollege of Health Solutions, Arizona State University, Scottsdale, Arizona, United States.
Curtiss CookDepartment of Endocrinology, Mayo Clinic, Scottsdale, Arizona, United States.
Bithika ThompsonDepartment of Endocrinology, Mayo Clinic, Scottsdale, Arizona, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis article aims to evaluate adult type 1 diabetes mellitus (T1DM) self-management behaviors (SMBs) related to exercise and alcohol on a survey versus a smartphone app to compare self-reported and self-tracked SMBs, and examine inter- and intrapatient variability.

methodsAdults with T1DM on insulin pump therapy were surveyed about their alcohol, meal, and exercise SMBs. For 4 weeks, participants self-tracked their alcohol, meal, and exercise events, and their SMBs corresponding with these events via an investigator-developed app. Descriptive statistics and generalized linear mixed-effect models were used to analyze the data

resultsThirty-five participants self-tracked over 5,000 interactions using the app. Variability in how participants perceived the effects of exercise and alcohol on their blood glucose was observed. The congruity between SMBs self-reported on the survey and those self-tracked with the app was measured as mean (SD). The lowest congruity was for alcohol and exercise with 61.9% (22.7) and 66.4% (20.2), respectively. Congruity was higher for meals with 80.9% (21.0). There was significant daily intra- and interpatient variability in SMBs related to preprandial bolusing: recommended bolus,

conclusionThis study highlights the variability in intra- and interpatient SMBs obtained through the use of a survey and app. The outcomes of this study indicate that clinicians could use both one-time and every-day assessment tools to assess SMBs related to meals. For alcohol and exercise, further research is needed to understand the best assessment method for SMBs. Given this degree of patient variability, there is a need for an educational intervention that goes beyond the traditional "one-size-fits-all" approach of diabetes management to target individualized treatment barriers.

Indexed as

BehaviorSelf-ManagementAlcohol DrinkingBlood GlucoseDiabetes Mellitus, Type 1ExerciseFemaleHumansMaleMealsMiddle AgedMobile ApplicationsSelf ReportSmartphoneSurveys and QuestionnairesBlood Glucose

Identifiers

PMID31968384
PMCPMC6976334

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.