Evidence map›Paper›PMID 40776060›Full record

ArticleStudies in health technology and informatics2025

Enhancing Digital Health Development Through Speech Act Theory: Application to Peripartum Depression Management.

Alexandra Zingg, Tavleen Singh, Michael Truong, Sahiti Myneni

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 2025. 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

4 authors.

Alexandra ZinggSchool of Biomedical Informatics, The University of Texas Health Science Center Houston, Houston, TX, USA.
Tavleen SinghSchool of Biomedical Informatics, The University of Texas Health Science Center Houston, Houston, TX, USA.
Michael TruongSchool of Biomedical Informatics, The University of Texas Health Science Center Houston, Houston, TX, USA.
Sahiti MyneniSchool of Biomedical Informatics, The University of Texas Health Science Center Houston, Houston, TX, USA.

Funding

Informatics-enhanced Social Networks and Affiliation Processes (ISNAP) to promote risk reduction and early diagnosis of Alzheimer's and Related Dementias.R01AG089193 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Kayo Fujimoto, SAHITI MYNENI · 2024 to 2026
$2.0M
Pragmatics to Reveal Intention in Social Media (PRISM) for Health PromotionR01LM012974 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MYNENI, SAHITI · 2019 to 2022
$1.5M
NIA NIH HHS R01 AG089193NLM NIH HHS R01 LM012974
6 · The paper itself

Abstract

The peripartum period is a time of complex transition into motherhood when women may develop peripartum depression (PPD). Digital information sources can help prevent and monitor symptoms through social support and mental health knowledge. However, few studies have characterized the content and form of peer interactions in PPD online forums to inform interventions. In this paper, we present preliminary work using a dataset of 55,301 interactions to inform our digital health development. We combine manual coding for speech acts, behavioral theory mapping, and user engagement modeling to conceptualize dynamic digital education modules for PPD. Results reveal "Expressive" speech act, where users illustrate their state of mind, was the most common (n = 364 messages), and the content theme of "Physical and Mental Health" was most discussed (n = 446). Interventions for PPD prevention and self-management should leverage naturalistic dynamics from social forums to provide just-in-time information, a sense of community, and peer support.

Indexed as

Depression, PostpartumDigital HealthSocial SupportSpeechBehavior TherapyDatabases, FactualFemaleHumansLinguisticsPatient Education as TopicPeripartum PeriodPregnancydigital healthhealth behaviorperipartum depressionsocial media

Identifiers

PMID40776060
PMCPMC13222650

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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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.