Evidence map›Paper›PMID 25092966›Full record

ArticlePatient preference and adherence2014

Interaction between functional health literacy, patient activation, and glycemic control.

LeChauncy D Woodard, Cassie R Landrum, Amber B Amspoker, David Ramsey, Aanand D Naik

Abstract read
In one paragraph

Article in Patient preference and adherence, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. 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

5 authors.

LeChauncy D WoodardVeterans Affairs Health Services Research and Development Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, and Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Cassie R LandrumVeterans Affairs Health Services Research and Development Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, and Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Amber B AmspokerVeterans Affairs Health Services Research and Development Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, and Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
David RamseyVeterans Affairs Health Services Research and Development Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, and Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Aanand D NaikVeterans Affairs Health Services Research and Development Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, and Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFunctional health literacy (FHL) and patient activation can impact diabetes control through enhanced diabetes self-management. Less is known about the combined effect of these characteristics on diabetes outcomes. Using brief, validated measures, we examined the interaction between FHL and patient activation in predicting glycosylated hemoglobin (HbA1c) control among a cohort of multimorbid diabetic patients.

methodsWe administered a survey via mail to 387 diabetic patients with coexisting hypertension and ischemic heart disease who received outpatient care at one regional VA medical center between November 2010 and December 2010. We identified patients with the study conditions using the International Classification of Diseases-Ninth Revision-Clinical Modification (ICD-9-CM) diagnoses codes and Current Procedure Terminology (CPT) procedures codes. Surveys were returned by 195 (50.4%) patients. We determined patient activation levels based on participant responses to the 13-item Patient Activation Measure and FHL levels using the single-item screening question, "How confident are you filling out medical forms by yourself?" We reviewed patient medical records to assess glycemic control. We used multiple logistic regression to examine whether activation and FHL were individually or jointly related to HbA1c control.

resultsNeither patient activation nor FHL was independently related to glycemic control in the unadjusted main effects model; however, the interaction between the two was significantly associated with glycemic control (odds ratio 1.05 [95% confidence interval 1.01-1.09], P=0.02). Controlling for age, illness burden, and number of primary care visits, the combined effect of these measures on glycemic control remained significant (odds ratio 1.05 [95% confidence interval 1.01-1.09], P=0.02).

conclusionThe interaction between FHL and patient activation is associated with HbA1c control beyond the independent effects of these parameters alone. A personalized approach to diabetes management incorporating these characteristics may increase patient-centered care and improve outcomes for patients with diabetes.

Indexed as

diabetes mellitushealth literacyself-careveterans

Identifiers

PMID25092966
PMCPMC4114908

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.