Evidence map›Paper›PMID 38892623›Full record

ArticleNutrients2024

What Is the Tech Missing? Nutrition Reporting in Type 1 Diabetes.

Nicole Lubasinski, Hood Thabit, Paul W Nutter, Simon Harper

Abstract read
In one paragraph

Article in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

4 authors.

Nicole LubasinskiDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0001-5829-8258
Hood ThabitDiabetes, Endocrine & Metabolism Centre, Manchester Royal Infirmary, Manchester University NHS, Manchester M13 9WL, UK.
Paul W NutterDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0003-4075-861X
Simon HarperDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0001-9301-5049

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionType 1 Diabetes (T1D) presents self-management challenges, requiring an additional 180 daily decisions to regulate blood glucose (BG) levels. Despite the potential, T1D-focused applications have a 43% attrition rate. This work delves into the willingness of people living with T1D (PwT1D) to use technology.

methodAn online questionnaire investigated the current practices for carbohydrate estimation, nutritional tracking, and attitudes towards technology engagement, along with hypothetical scenarios and preferences regarding technology use.

resultsThirty-nine responses were collected from PwT1D (

conclusionPwT1D shows interest in using technology to reduce the diabetes burden when it leads to an improved TIR. For such technology to be ecologically valid, it needs to strike a balance between requiring minimal user input and providing significant data, such as meal tags, to ensure accurate blood glucose management without overwhelming users with reporting tasks.

Indexed as

Diabetes Mellitus, Type 1AdultBlood GlucoseBlood Glucose Self-MonitoringDietary CarbohydratesFemaleHumansInsulinMaleMealsMiddle AgedMobile ApplicationsNutritional StatusSurveys and QuestionnairesYoung AdultBlood GlucoseDietary CarbohydratesInsulinappsbolus targeting solution (BTS)mHealthnutrition reportingself-managementT1Dtechnologytype 1 diabetes

Identifiers

PMID38892623
PMCPMC11174934

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.