ArticleDrug and alcohol review2022
Postpartum heavy episodic drinking: A survey to inform development of a text messaging intervention.
Article in Drug and alcohol review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Text Messaging Intervention for Postpartum Alcohol Use: Micro-Randomized Trial Supports Feasibility, Acceptability, and Maternal Message Preference.Journal of studies on alcohol and drugs · 2026Trial
- Development of Survey Measures of Uncontrolled Vaping and Vaping Restraint.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2025Article
- Alcohol Use in the Early Postpartum Period: An Ecological Momentary Assessment Study to Understand the Role of Self-Efficacy.Drug and alcohol review · 2025Article
- Terms tobacco users employ to describe e-cigarette aerosol.Tobacco control · 2023Article
- Adaptive Text Messaging for Postpartum Risky Drinking: Conceptual Model and Protocol for an Ecological Momentary Assessment Study.JMIR research protocols · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
Abstract
introductionText messaging interventions (TMI) are promising for addressing heavy episodic drinking (HED) in non-treatment-seeking postpartum women. Their anonymous delivery can overcome fear of consequences that often prevents postpartum women from seeking treatment for HED. We assessed feasibility and acceptability of text messaging to inform the development of a tailored TMI for postpartum HED.
methodsWe surveyed 165 postpartum women recruited via a national Qualtrics panel on their drinking behaviours, mobile technology use and TMI preferences.
resultsTwenty-five percent of the sample (N = 41) were classified as heavy episodic drinkers, with significant drinking reported before, during and after pregnancy, supporting the need for intervention. Feasibility of text messaging was supported by nearly universal mobile phone ownership and text messaging. Attitudes and intervention preferences varied, with 30% of HEDs likely to participate in an intervention asking them to receive automated messages, and 46% likely to participate in an intervention that included live texting with a counsellor. Respondents were more likely to participate in a study that asked them to respond to messages about mood and stress (63%) than daily drinking behaviours (35%), and were most interested in a TMI that included live texting with a counsellor. Nearly half the sample endorsed fear of child removal as a significant barrier to participation. DISCUSSION AND
conclusionsFindings support the feasibility of text messaging as an intervention approach for postpartum HEDs. Postpartum women may have unique concerns and preferences that differ from other groups of HEDs, making a user-centred design approach critical.
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Registered trials
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.