Evidence map›Paper›PMID 39309617›Full record

ArticleMentoring & tutoring2024

Exploring Organizational Digital Readiness to Offer Youth E-Mentoring.

Michelle R Kaufman, Xiaobin Zhou, Gayane Yenokyan, Deborah K Levine, Kate Wright, Maritza Salcido, Michael Garringer, Lori-Ann Palen

Abstract read
In one paragraph

Article in Mentoring & tutoring, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Michelle R KaufmanJohns Hopkins Bloomberg School of Public Health.ORCID 0000-0003-1901-8676
Xiaobin ZhouJohns Hopkins Bloomberg School of Public Health.ORCID 0000-0003-2924-9478
Gayane YenokyanJohns Hopkins Bloomberg School of Public Health.
Deborah K LevineJohns Hopkins Bloomberg School of Public Health.ORCID 0000-0001-5355-139X
Kate WrightJohns Hopkins Bloomberg School of Public Health.ORCID 0000-0002-6203-5087
Maritza SalcidoUniversity of Erlangen-Nuremberg.
Michael GarringerMENTOR.
Lori-Ann PalenData Soapbox.ORCID 0009-0004-6577-1065

Funding

mHealth Intervention via Mentors: Preventing Substance Use, Sexual Risk and Violence among Inner City Youth through Technology-Enhanced MentoringK01DA042138 · NIDA · JOHNS HOPKINS UNIVERSITY · PI KAUFMAN, MICHELLE R. · 2017 to 2021
$896k
NIDA NIH HHS K01 DA042138
6 · The paper itself

Abstract

The COVID-19 pandemic prompted many youth mentoring programs to offer digital services (e-mentoring). The sustained success of these efforts depended, in large part, on organizations' digital readiness. Although there are established, broad measures of digital readiness, mentoring organizations have unique requirements for readiness that have not been previously measured. The current cross-sectional survey research study measured the state of digital readiness for youth mentoring organizations and tested the organizational E-Mentoring Readiness Scale. Ninety-five representatives from U.S. mentoring programs completed an online survey. Participants felt mentors, mentees, and families were moderately comfortable with e-mentoring. There was less confidence and comfort with the required technology and execution of e-mentoring. A confirmatory factor analysis of the E-Mentoring Readiness Scale showed two distinct but related factors with good model fit. An honest assessment using this tool may allow the youth mentoring field to move into the digital age more seamlessly.

Indexed as

digital mentoringdigital readinesse-mentoringmentoringtechnologyyouth development

Identifiers

PMID39309617
PMCPMC11415230

What OpenQuestion holds

Textmetadata
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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.