Evidence map›Paper›PMID 37746640›Full record

ArticleInternet interventions2023

A chatbot-delivered intervention for optimizing social media use and reducing perceived isolation among rural-living LGBTQ+ youth: Development, acceptability, usability, satisfaction, and utility.

César G Escobar-Viera, Giovanna Porta, Robert W S Coulter, Jamie Martina, Jeremy Goldbach, Bruce L Rollman

Open access · goldAbstract read
In one paragraph

Article in Internet interventions, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 5 pooled it
15.6field-weighted citation impact, top 1% 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

14 citing papers in PubMed, 5 syntheses or guidelines pooled it, 27 citations in OpenAlex.

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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

6 authors at 3 institutions in 1 country.

César G Escobar-VieraDepartment of Psychiatry, School of Medicine, University of Pittsburgh, United States.
Giovanna PortaThe Enhancing Triage and Utilization for Depression and Emergent Suicidality (ETUDES) Center, School of Medicine, University of Pittsburgh, United States.
Robert W S CoulterDepartment of Behavioral and Community Health Sciences, School of Public Health, University of Pittsburgh, United States.
Jamie MartinaWestern Psychiatric Hospital, University of Pittsburgh Medical Center, United States.
Jeremy GoldbachBrown School of Social Work, Washington University in St. Louis, United States.
Bruce L RollmanThe Enhancing Triage and Utilization for Depression and Emergent Suicidality (ETUDES) Center, School of Medicine, University of Pittsburgh, United States.
University of Pittsburgh · USUniversity of Pittsburgh Medical Center · USWashington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ+) youth are at higher risk of isolation and depression than their heterosexual peers. Having access to tailored mental health resources is a documented concern for rural living LGBTQ+ youth. Social media provides access to connections to a broader and like-minded community of peers, but it also is a vehicle for negative interactions. We developed REALbot, an automated, social media-based educational intervention to improve social media efficacy, reduce perceived isolation, and bolster connections for rural living LGBTQ+ youth. This report presents data on the acceptability, feasibility, and utility of REALbot among its target audience of rural living LGBTQ+ youth. Methods: We conducted a week-long exploratory study with a single non-comparison group of 20 rural-living LGBTQ+ youth aged 14-19 recruited from social media to test our Facebook- and Instagram-delivered chatbot. We assessed pre- and post-test scores of social media self-efficacy, social isolation (4-item Patient-Reported Outcomes Measurement System - PROMIS), and depressive symptoms (Patient Health Questionnaire, Adolescent Version - PHQ-A). At post-test, we assessed acceptability (User Experience Questionnaire - UEQ-S), usability (Chatbot Usability Questionnaire -CUQ and Post-Study Satisfaction and Usability Questionnaire -PSSUQ), and satisfaction with the chatbot (Client Satisfaction Questionnaire - CSQ), along with two open-ended questions on 'likes' and 'dislikes' about the intervention. We compared pre- and post-test scores with standard univariate statistics. Means and standard deviations were calculated for usability, acceptability, and satisfaction. To analyze the responses to post-test open-end questions, we used a content analysis approach. Results: Acceptability of REALbot was high with UEQ-S 5.3 out of 7 (SD = 1.1) and received high usability scores with CUQ and PSSUQ (mean score (M) = 78.0, SD = 14.5 and M = 86.9, SD = 25.2, respectively), as well as high user satisfaction with CSQ (M = 24.9, SD = 5.4). Themes related to user 'likes' and 'dislikes' were organized in two main categories: usability and content provided. Participants were engaged with the chatbot, sending an average of 49.3 messages (SD = 43.6, median = 30). Pre-/post- changes in scores of perceived isolation, depressive symptoms and social media self-efficacy were not significant (p's > 0.08). Conclusion: REALbot deployment was found to be feasible and acceptable, with good usability and user satisfaction scores. Participants reported changes from pre- to post-test in most outcomes of interest and effect sizes were small to medium. Additional development and a formal evaluation of feasibility and engagement with behavioral targets is warranted.

Indexed as

LGBT youthRuralSocial isolationSocial media, chatbot

Identifiers

PMID37746640
PMCPMC10511780
OpenAlexW4386566618

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.