Evidence map›Paper›PMID 38689830›Full record

ArticlePEC innovation2024

A family-centered approach to social needs awareness in the pediatric emergency department.

Raymen Rammy Assaf, Ryan David Assaf, Patricia Sencer Padlipsky, Kelly Dee Ann Young

Abstract read
In one paragraph

Article in PEC innovation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Raymen Rammy AssafEmergency Medicine Specialists of Orange County, Children's Hospital Orange County, Orange, USA.
Ryan David AssafBenioff Homelessness and Housing Initiative, Center for Vulnerable Populations, Department of Medicine, University of California, San Francisco (UCSF), San Francisco, USA.
Patricia Sencer PadlipskyDepartment of Emergency Medicine, Harbor-University of California, Los Angeles (UCLA) Medical Center, Torrance, USA.
Kelly Dee Ann YoungDepartment of Emergency Medicine, Harbor-University of California, Los Angeles (UCLA) Medical Center, Torrance, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We aimed to understand family preferences around reporting and receiving health-related social needs (HRSN) information by assessment modality during pediatric emergency department (PED) visits. Methods: Families were randomized into paper (control), cell phone, or tablet modality groups by their child's exam room. Nurses alerted families to complete a single HRSN assessment during routine workflow. We used logistic regression and McNemar's test to assess discordance in modality preference. Results: Forty-seven percent of families disclosed at least one HRSN across a total 611 assessments. Disclosure of HRSN was similar by modality. Twenty-three percent of those assigned tablet preferred cell phone ( Conclusions: Assessment modality did not appear to influence family HRSN disclosure. Families were generally satisfied with all HRSN assessment modalities but demonstrated a particular preference in using personal cell phones over tablets. Digitally formatted community referrals also pose numerous advantages over conventional paper handouts. Innovation: Use of personal cell phones is a novel, streamlined method of HRSN interventions in the clinical setting, performing similar to more conventional modalities, with a preference among families when compared to tablets.

Indexed as

Health-related social needPediatric emergency department

Identifiers

PMID38689830
PMCPMC11059452

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.