Evidence map›Paper›PMID 35381026›Full record

ArticlePloS one2022

Mass email risk communication: Lessons learned from COVID-19-triggered campus-wide evictions in Canada and the United States.

Haorui Wu

Abstract read
In one paragraph

Article in PloS one, 2022. 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

1 author.

Haorui WuSchool of Social Work, Dalhousie University, Halifax, Nova Scotia, Canada.ORCID 0000-0002-6314-0452

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

From an out-of-province/state and international post-secondary student perspective, this article (a) explores mass email risk communication facilitation during the COVID-19-triggered campus-wide evictions in Canada and the United States; and (b) develops relative recommendations to improve mass email risk communication strategies for future emergency response. Investigating mass email risk communication-related impacts on students in a tertiary educational context has revealed a significant deficit in emergency response research, practice, and policymaking. Mandatory temporary university and college closures during the COVID-19 first wave provided an opportunity to address this research and practice deficit, as most Canadian and American universities/colleges administered their eviction communication via daily mass email chains. Through a phenomenological lens, this study interviewed twenty out-of-province/state and international students, ten from each country respectively, to examine student eviction experiences associated with intensive mass email risk communication. This research identified four factors linked to mass email risk communication: email chain characteristics, student interpretation, interdepartmental cooperation, and frontline voices. Synthesizing these findings, four evidence-based recommendations were developed: to efficiently convey risk information to students, to understand student perceptions and to inform their behaviors, to enhance interdepartmental cooperation, and to enable mutual dialogue in decision making. These recommendations could assist post-secondary institutions, and other organizations, in strengthening their mass email risk communication strategies and advancing organizational emergency response plans for future extreme events.

Indexed as

COVID-19CanadaCommunicationElectronic MailHumansUnited StatesUniversities

Identifiers

PMID35381026
PMCPMC8982839

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.