Evidence map›Paper›PMID 29781750›Full record

ReviewHuman vaccines & immunotherapeutics2018

The use of technology to promote vaccination: A social ecological model based framework.

Chelsea A Kolff, Vanessa P Scott, Melissa S Stockwell

Registry-linked trialAbstract readReview
In one paragraph

Review in Human vaccines & immunotherapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06935084 (Conducting a Randomized Controlled Trial for A Novel Patient-Facing Mobile Platform to Collect and Implement Patient-Reported Outcomes and Voice Biomarkers in Underserved Adult Patients With Asthma), which is not on this map. Cited by 38 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing 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.

NCT06935084 narecruitingnot on this mapstarted 2025, after this paper: background citation

Conducting a Randomized Controlled Trial for A Novel Patient-Facing Mobile Platform to Collect and Implement Patient-Reported Outcomes and Voice Biomarkers in Underserved Adult Patients With Asthma

TypeinterventionalSponsorMontefiore Medical CenterRan2025 to 2028Enrolled200ConditionsAsthmaArmsASTHMAXcel Voice platform
3 · Its place in the literature

Who cites it

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

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  12. The Experience of Discrimination Impacts Technology Readiness and Psychosocial States of Minoritized Families Living With Type 1 Diabetes: Findings From the BEAD-T1D Pilot Study.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2025
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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

3 authors.

Chelsea A Kolffa Department of Pediatrics , Columbia University , New York , NY , USA.
Vanessa P Scotta Department of Pediatrics , Columbia University , New York , NY , USA.
Melissa S Stockwella Department of Pediatrics , Columbia University , New York , NY , USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vaccinations are an important and effective cornerstone of preventive medical care. Growing technologic capabilities and use by both patients and providers present critical opportunities to leverage these tools to improve vaccination rates and public health. We propose the Social Ecological Model as a useful theoretical framework to identify areas in which technology has been or may be leveraged to target undervaccination across the individual, interpersonal, organizational, community, and society levels and the ways in which these levels interact.

Indexed as

Models, TheoreticalCell PhoneEducational TechnologyHumansPublic HealthText MessagingVaccinationdigitalimmunizationsinfluenzaSMSsocial ecological modeltechnologyvaccinations

Identifiers

PMID29781750
PMCPMC6067841

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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.