Evidence map›Paper›PMID 35727723›Full record

ArticleJournal of nursing studies and patient care2022

An Integrated Conceptual Framework of Behavioral Intervention Technologies to Promote Healthcare Utilization Among Socially-Marginalized Populations in the United States.

Chen Zhang, Shelby Przybylek, Amy Braksmajer, Yu Liu

Open access · greenAbstract read
In one paragraph

Article in Journal of nursing studies and patient care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Leveraging virtual reality to improve medication adherence among marginalized populations with high-risk chronic health conditions: Proof-of-concept protocol, considerations, and next steps.Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences · 2025
    Article
  4. Article
  5. Informing Acceptability and Feasibility of Digital Phenotyping for Personalized HIV Prevention among Marginalized Populations Presenting to the Emergency Department.Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences · 2024
    Article
  6. Article
  7. 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 at 1 institution in 1 country.

Chen ZhangSchool of Nursing, University of Rochester Medical Center, Rochester, NY, USA.
Shelby PrzybylekSchool of Nursing, University of Rochester Medical Center, Rochester, NY, USA.
Amy BraksmajerSociology Department, The State University of New York at Geneseo, Geneseo, NY, USA.
Yu LiuDepartment of Public Health Science, University of Rochester Medical Center, Rochester, NY, USA.
University of Rochester Medical Center · US

Funding

Virology/Immunology CoreP30AI078498 · NIAID · UNIVERSITY OF ROCHESTER · PI DEWHURST, STEPHEN · 2008 to 2018
$14.6M
NIAID NIH HHS P30 AI078498
6 · The paper itself

Abstract

In the U.S., socially marginalized groups disproportionately shoulder the burden of health outcomes. The evolving development of behavioral intervention technologies provides opportunities to support users in changing behaviors and improving health. No conceptual model is available to guide technology-based behavioral interventions among vulnerable groups in the new era of digitalization. Our conceptual framework combines the Behavioral Model of Healthcare Utilization (HCU) for Vulnerable Populations and the Integrated Model of Behavioral Prediction (IMBP). With the Socioecological Model leading the vertical direction, the overarching HCU-IBMP model is incorporated by the Behavioral Intervention Technology-Technological Instantiation Framework (BIT-Tech). The HCU model explains how vulnerable populations influence healthcare access and utilization behaviors by personal and contextual factors. Through the lens of the IMBP, healthcare utilization intention is highly predictable and maybe even causally correlated with the corresponding behavior. To assist the healthcare utilization intention translates into the corresponding behaviors, we employ a medium using the technological implementation in a system that can assist the end-users in adopting the desired behavior. With the integrated model that combines a technological framework with the behavioral components, the BIT-Tech guides the procedure intervention development. Our integrated conceptual framework indicated that theoretical and technical components should be considered during a technological tool development to support the research community. A real-world intervention design has been demonstrated using the framework to guide behavioral intervention technologies to promote PrEP care and utilization among racial/ethnic minority women in the U.S.

Indexed as

Behavioral intervention technologiesHealth disparitiesTheoretical frameworkVulnerable populations

Identifiers

PMID35727723
PMCPMC9201512
OpenAlexW4285744439

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.