Evidence map›Paper›PMID 33635280›Full record

ArticleJMIR mental health2021

Improving Mood Through Community Connection and Resources Using an Interactive Digital Platform: Development and Usability Study.

Robin Ortiz, Lauren Southwick, Rachelle Schneider, Elissa V Klinger, Arthur Pelullo, Sharath Chandra Guntuku, Raina M Merchant, Anish K Agarwal

Open access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  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

8 authors at 2 institutions in 1 country.

Robin Ortiz *Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-0957-5850
Lauren Southwick *Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0001-5290-9759
Rachelle Schneider *Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0003-4467-3875
Elissa V KlingerDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0003-1311-0826
Arthur PelulloDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-3667-4301
Sharath Chandra GuntukuDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-2929-0035
Raina M MerchantPenn Medicine Center for Digital Health, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-9801-6881
Anish K AgarwalDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0003-2175-0196
University of Pennsylvania · USUniversity of Pennsylvania Health System · US

Funding

Learning Health Systems Mentored Career Development ProgramK12HS026372 · AHRQ · UNIVERSITY OF PENNSYLVANIA · PI ASCH, DAVID A, LANE-FALL, MEGHAN BROOKS · 2018 to 2022
$3.2M
6 · The paper itself

Abstract

backgroundCOVID-19 continues to disrupt global health and well-being. In April-May 2020, we generated a digital, remote interactive tool to provide health and well-being resources and foster connectivity among community members through a text messaging platform.

objectiveThis study aimed to prospectively investigate the ability of a health system-based digital, remote, interactive tool to provide health and well-being resources to local community participants and to foster connectivity among them during the early phases of COVID-19.

methodsWe performed descriptive and nonparametric longitudinal statistical analyses to describe and compare the participants' mood ratings over time and thematic analysis of their responses to text messages to further assess mood.

resultsFrom among 393 individuals seeking care in an urban emergency department in an academic setting, engaged in a two-way text messaging platform, we recorded 287 mood ratings and 368 qualitative responses. We observed no difference in the initial mood rating by week of enrollment [Kruskal-Wallis chi-square H(5)=1.34; P=.93], and the average mood rating did not change for participants taken together [Friedman chi-square Q(3)=0.32; P=.96]. However, of participants providing mood ratings at baseline, mood improved significantly among participants who reported a low mood rating at baseline [n=25, 14.97%; Q(3)=20.68; P<.001] but remained stable among those who reported a high mood rating at baseline [n=142, 85.03%; Q(3)=2.84; P=.42]. Positive mood elaborations most frequently included words related to sentiments of thankfulness and gratitude, mostly for a sense of connection and communication; in contrast, negative mood elaborations most frequently included words related to anxiety.

conclusionsOur findings suggest the feasibility of engaging individuals in a digital community with an emergency department facilitation. Specifically, for those who opt to engage in a text messaging platform during COVID-19, it is feasible to assess and respond to mood-related queries with vetted health and well-being resources.

Indexed as

communityCOVID-19digital healthdigital toolmental healthmoodprospectivethematic analysisvirtual supportwell-being

Identifiers

PMID33635280
PMCPMC7919843
OpenAlexW3128772464

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.