Evidence map›Paper›PMID 28404657›Full record

Trial reportDiabetes care2017

Predicting and Reducing Driving Mishaps Among Drivers With Type 1 Diabetes.

Daniel J Cox, Linda A Gonder-Frederick, Harsimran Singh, Karen S Ingersoll, Tom Banton, Jesse H Grabman, Karen Schmidt, William Clarke

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Diabetes care, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 3 pooled it
–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

7 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2022
    Guideline
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
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

8 authors.

Daniel J CoxUniversity of Virginia School of Medicine, Charlottesville, VA djc4f@virginia.edu.
Linda A Gonder-FrederickUniversity of Virginia School of Medicine, Charlottesville, VA.
Harsimran SinghUniversity of Virginia School of Medicine, Charlottesville, VA.
Karen S IngersollUniversity of Virginia School of Medicine, Charlottesville, VA.
Tom BantonUniversity of Virginia School of Medicine, Charlottesville, VA.
Jesse H GrabmanUniversity of Virginia School of Medicine, Charlottesville, VA.
Karen SchmidtDepartment of Psychology, University of Virginia, Charlottesville, VA.
William ClarkeUniversity of Virginia School of Medicine, Charlottesville, VA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTwo aims of this study were to develop and validate A) a metric to identify drivers with type 1 diabetes at high risk of future driving mishaps and B) an online intervention to reduce mishaps among high-risk drivers. RESEARCH DESIGN AND

methodsTo achieve aim A, in study 1, 371 drivers with type 1 diabetes from three U.S. regions completed a series of established questionnaires about diabetes and driving. They recorded their driving mishaps over the next 12 months. Questionnaire items that uniquely discriminated drivers who did and did not have subsequent driving mishaps were assembled into the Risk Assessment of Diabetic Drivers (RADD) scale. In study 2, 1,737 drivers with type 1 diabetes from all 50 states completed the RADD online. Among these, 118 low-risk (LR) and 372 high-risk (HR) drivers qualified for and consented to participate in a 2-month treatment period followed by 12 monthly recordings of driving mishaps. To address aim B, HR participants were randomized to receive either routine care (RC) or the online intervention "DiabetesDriving.com" (DD.com). Half of the DD.com participants received a motivational interview (MI) at the beginning and end of the treatment period to boost participation and efficacy. All of the LR participants were assigned to RC. In both studies, the primary outcome variable was driving mishaps.

resultsRelated to aim A, in study 1, the RADD demonstrated 61% sensitivity and 75% specificity. Participants in the upper third of the RADD distribution (HR), compared with those in the lower third (LR), reported 3.03 vs. 0.87 mishaps/driver/year, respectively (

conclusionsThe RADD identified higher-risk drivers, and identification seemed relatively stable across time, samples, and procedures. This 11-item questionnaire could inform patients at higher risk, and their clinicians, that they should take preventive steps to reduce driving mishaps, which was accomplished in aim B using DD.com.

Indexed as

Automobile DrivingHealth EducationAccidents, TrafficAdultBostonDiabetes Mellitus, Type 1FemaleGlycated HemoglobinHumansHypoglycemiaInternetLogistic ModelsMaleMiddle AgedMinnesotaMotivational InterviewingGlycated Hemoglobin

Identifiers

PMID28404657
PMCPMC5439415

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.