Evidence map›Paper›PMID 39150678›Full record

SynthesisJournal of general internal medicine2024

Relationship Between Delay Discounting and Clinical Diabetes Outcomes: A Systematic Review.

Jennifer A Campbell, Sebastian Linde, Rebekah J Walker, Leonard E Egede

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  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.

Jennifer A CampbellDivision of Population Health, Department of Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.
Sebastian LindeDepartment of Health Policy and Management, School of Public Health at, Texas A&M University, College Station, TX, USA.
Rebekah J WalkerDivision of Population Health, Department of Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.
Leonard E EgedeDivision of Population Health, Department of Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA. legede@buffalo.edu.ORCID 0000-0003-1546-1515

Funding

HOME DM-BAT: Home-based Diabetes-Modified Behavioral Activation Treatment for Low Income Seniors with T2DM Diversity SupplementR01DK118038 · NIDDK · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI EGEDE, LEONARD E. · 2019 to 2023
$3.5M
Financial Incentives And Nurse Coaching to Enhance Diabetes Outcomes (FINANCE-DM) - Diversity SupplementR01DK120861 · NIDDK · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI EGEDE, LEONARD E. · 2019 to 2023
$3.4M
Lowering the Impact of Food insecurity in African American Adults with Type 2 Diabetes Mellitus (LIFT-DM) - Diversity SupplementR01MD013826 · NIMHD · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI EGEDE, LEONARD E., WALKER, REBEKAH J · 2019 to 2023
$3.4M
Structural Racism and Disparities in Social Risk, Human Capital, Health Care Resources, and Health Outcomes: A Multi-level Analysis of Pathways and Policy Levers for ChangeR01MD017574 · NIMHD · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI Leonard E. Egede, Sebastian Linde · 2023 to 2026
$2.5M
Impact of structural racism on hospital/clinic closures, community assets, and health outcomes in urban communitiesR01MD018012 · NIMHD · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI Leonard E. Egede, Sebastian Linde · 2023 to 2026
$2.4M
Conditional Cash Transfer Intervention to Improve Health Outcomes among Inner-City African Americans with T2DMK01DK131319 · NIDDK · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI Jennifer Annette Campbell · 2022 to 2026
$682k
NIDDK NIH HHS K01 DK131319NIDDK NIH HHS R01 DK118038NIDDK NIH HHS R01 DK120861NIMHD NIH HHS R01 MD013826NIMHD NIH HHS R01 MD017574NIMHD NIH HHS R01 MD018012
6 · The paper itself

Abstract

objectiveTo evaluate the evidence on the relationship between delay discounting and clinical diabetes outcomes, identify current measures, and recommend areas for future work.

methodsA reproducible search using OVID Medline, PsycINFO, PubMed, Science Direct, and Scopus was conducted. Articles published from database creation up to March 2024 were searched. Medical Subject Heading (MeSH) terms and keywords representing delay discounting and diabetes were used. Outcomes included hemoglobin A1c (HbA1c), LDL, body mass index (BMI), blood pressure, quality of life (QOL), psychosocial factors, self-care behaviors, and diabetes complications.

resultsA total of 15 articles met the inclusion criteria and were included for final synthesis. Overall, 14 studies included in this review found a significant relationship between delay discounting and diabetes-related outcomes, such that higher delay discounting is significantly related to worse diabetes outcomes for HbA1c, self-care behaviors, BMI, stress, and quality of life across self-reported measures of delay discounting and delay discounting tasks.

conclusionsEvidence supports the relationship between delay discounting and diabetes-related outcomes and self-care behaviors across measures of delay discounting and type of diabetes. To understand delay discounting as a mechanism driving diabetes outcomes and to develop targeted interventions, additional work using a multidisciplinary approach is needed to validate the construct, identify pathways, and refine intervention approaches that can be tested to improve population health.

Indexed as

Delay DiscountingDiabetes MellitusQuality of LifeGlycated HemoglobinHumansSelf CareGlycated Hemoglobin

Identifiers

PMID39150678
PMCPMC11576688

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.