Evidence map›Paper›PMID 38300760›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2024

Human technology intermediation to reduce cognitive load: understanding healthcare staff members' practices to facilitate telehealth access in a Federally Qualified Health Center patient population.

Alicia K Williamson, Marcy G Antonio, Sage Davis, Vaishnav Kameswaran, Tawanna R Dillahunt, Lorraine R Buis, Tiffany C Veinot

Open access · hybridAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Engaging knowers in the design and implementation of digital health innovations.Journal of the American Medical Informatics Association : JAMIA · 2024
    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

7 authors at 2 institutions in 1 country.

Alicia K WilliamsonSchool of Information, University of Michigan, Ann Arbor, MI, United States.
Marcy G AntonioSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-9332-8512
Sage DavisCovenant Community Care, Detroit, MI, United States.ORCID 0000-0002-7807-5235
Vaishnav KameswaranSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-1519-8956
Tawanna R DillahuntSchool of Information, University of Michigan, Ann Arbor, MI, United States.
Lorraine R BuisSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-5855-9972
Tiffany C VeinotSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-1200-9515
University of Michigan · USCommunity Care · US

Funding

National Science Foundation RAPID-COVID-19-#2031662
6 · The paper itself

Abstract

objectivesThe aim of this study was to investigate how healthcare staff intermediaries support Federally Qualified Health Center (FQHC) patients' access to telehealth, how their approaches reflect cognitive load theory (CLT) and determine which approaches FQHC patients find helpful and whether their perceptions suggest cognitive load (CL) reduction. MATERIALS AND

methodsSemistructured interviews with staff (n = 9) and patients (n = 22) at an FQHC in a Midwestern state. First-cycle coding of interview transcripts was performed inductively to identify helping processes and participants' evaluations of them. Next, these inductive codes were mapped onto deductive codes from CLT.

resultsStaff intermediaries used 4 approaches to support access to, and usage of, video visits and patient portals for FQHC patients: (1) shielding patients from cognitive overload; (2) drawing from long-term memory; (3) supporting the development of schemas; and (4) reducing the extraneous load of negative emotions. These approaches could contribute to CL reduction and each was viewed as helpful to at least some patients. For patients, there were beneficial impacts on learning, emotions, and perceptions about the self and technology. Intermediation also resulted in successful visits despite challenges. DISCUSSION: Staff intermediaries made telehealth work for FQHC patients, and emotional support was crucial. Without prior training, staff discovered approaches that aligned with CLT and helped patients access technologies. Future healthcare intermediary interventions may benefit from the application of CLT in their design. Staff providing brief explanations about technical problems and solutions might help patients learn about technologies informally over time.

conclusionCLT can help with developing intermediary approaches for facilitating telehealth access.

Indexed as

Health FacilitiesTelemedicineCognitionHumansaccess to primary carehealthcare equitylearninglow-income populationstelehealth

Identifiers

PMID38300760
PMCPMC10990534
OpenAlexW4391429760

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.