Evidence map›Paper›PMID 24823953›Full record

SynthesisCirculation. Cardiovascular quality and outcomes2014

Impact of sociodemographic patient characteristics on the efficacy of decision AIDS: a patient-level meta-analysis of 7 randomized trials.

Megan Coylewright, Megan Branda, Jonathan W Inselman, Nilay Shah, Erik Hess, Annie LeBlanc, Victor M Montori, Henry H Ting

Abstract readEvaluation StudyMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Circulation. Cardiovascular quality and outcomes, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 4 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

24 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Quality and effectiveness of osteoporosis treatment decision aids: a systematic review and environmental scan.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2020
    Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. What is the effect of a decision aid in potentially vulnerable parents? Insights from the head CT choice randomized trial.Health expectations : an international journal of public participation in health care and health policy · 2020
    Trial
  6. Shared decision-making following disclosure of coronary heart disease genetic risk: results from a randomized clinical trial.Journal of investigative medicine : the official publication of the American Federation for Clinical Research · 2017
    Trial
  7. Trial
  8. Trial
  9. Article
  10. JACC. Advances · 2024
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Explaining professionalism in moral reasoning: a qualitative study.Advances in medical education and practice · 2019
    Article
  17. Article
  18. Decisional conflict in mental health care: a cross-sectional study.Social psychiatry and psychiatric epidemiology · 2018
    Article
  19. Article
  20. Shared Decision Making With Vulnerable Populations in the Emergency Department.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2016
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Megan CoylewrightFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN.
Megan BrandaFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN.
Jonathan W InselmanFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN.
Nilay ShahFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN.
Erik HessFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN.
Annie LeBlancFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN.
Victor M MontoriFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN.
Henry H TingFrom the Division of Cardiovascular Diseases, Department of Medicine (M.C., H.H.T.), Knowledge and Evaluation Research Unit (M.C., M.B., J.W.I., N.S., E.H., A.L., V.M.M., H.H.T.), and Divisions of Health Care Policy and Research, Department of Health Sciences Research (N.S.), Emergency Medicine Research, Department of Emergency Medicine (E.H.), and Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Medicine (V.M.M.), Mayo Clinic, Rochester, MN. ting.henry@mayo.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDecision aids (DAs) increase patient knowledge, reduce decisional conflict, and promote shared decision making (SDM). The extent to which they do so across diverse sociodemographic patient groups is unknown. METHODS AND

resultsWe conducted a patient-level meta-analysis of 7 randomized trials of DA versus usual care comprising 771 encounters between patients and clinicians discussing treatment options for chest pain, myocardial infarction, diabetes mellitus, and osteoporosis. Using a random effects model, we examined the impact of sociodemographic patient characteristics (age, sex, education, income, and insurance status) on the outcomes of knowledge transfer, decisional conflict, and patient involvement in SDM. Because of small numbers of people of color in the study population, we were not powered to investigate the role of race. Most patients were aged ≥65 years (61%), white (94%), and women (59%); two thirds had greater than a high school education. Compared with usual care, DA patients gained knowledge, were more likely to know their risk, and had less decisional conflict along with greater involvement in SDM. These gains were largely consistent across sociodemographic patient groups, with DAs demonstrating similar efficacy when used with vulnerable patients such as the elderly and those with less income and less formal education. Differences in efficacy were found only in knowledge of risk in 1 subgroup, with greater efficacy among those with higher education (35% versus 18%; P=0.02).

conclusionsIn this patient-level meta-analysis of 7 randomized trials, DAs were efficacious across diverse sociodemographic groups as measured by knowledge transfer, decisional conflict, and patient involvement in SDM. To the extent that DAs increase patient knowledge and participation in SDM, they have potential to impact health disparities related to these factors.

Indexed as

Decision Support TechniquesSocioeconomic FactorsAgedAged, 80 and overDecision MakingFemaleHumansMalePatient Acceptance of Health CarePatient ParticipationRandomized Controlled Trials as TopicUnited Statesdecision makingdecision support techniques

Identifiers

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.