Evidence map›Paper›PMID 37844088›Full record

ArticlePLOS digital health2023

Effects of digital chatbot on gender attitudes and exposure to intimate partner violence among young women in South Africa.

Alexandra De Filippo, Paloma Bellatin, Neville Tietz, Eli Grant, Alexander Whitefield, Puseletso Nkopane, Camilla Devereux, Kaitlyn Crawford, Benjamin Vermeulen, Abigail M Hatcher

Abstract read
In one paragraph

Article in PLOS digital health, 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
–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

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

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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

10 authors.

Alexandra De FilippoBehavioral Insights Team, New York, New York, United States of America.
Paloma BellatinBehavioral Insights Team, New York, New York, United States of America.
Neville TietzPraekelt.org, Johannesburg, South Africa.
Eli GrantIndependent consultant, Connecticut, United States of America.
Alexander WhitefieldBehavioural Insights Team, London, United Kingdom.
Puseletso NkopanePraekelt.org, Johannesburg, South Africa.
Camilla DevereuxBehavioural Insights Team, London, United Kingdom.
Kaitlyn CrawfordPraekelt.org, Johannesburg, South Africa.
Benjamin VermeulenPraekelt.org, Johannesburg, South Africa.
Abigail M HatcherDepartment of Health Behavior, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, United States of America.ORCID https://orcid.org/0000-0002-4150-1405

Funding

Mechanisms and pilot intervention for addressing intimate partner violence and HIV in antenatal careK01MH121185 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HATCHER, ABIGAIL MAE · 2019 to 2023
$820k
NIMH NIH HHS K01 MH121185
6 · The paper itself

Abstract

backgroundSouth Africa has among the highest rates of intimate partner violence (IPV) globally, with young women at heightened risk due to inequitable gender roles, limited relationship skills, and inadequate social support. Despite an urgent need for violence prevention in low- and middle-income settings, most efficacious approaches are time-intensive and costly to deliver. Digital, interactive chatbots may help young women navigate safer relationships and develop healthier gender beliefs and skills.

methodsYoung women (18-24 years old) across South Africa were recruited via Facebook for participation in an individually randomised controlled trial (n = 19,643) during the period of June 2021-September 2021. Users were randomly allocated, using a pipeline algorithm, to one of four trial arms: Pure Control (PC) had no user engagement outside of study measures; Attention Treatment (T0) provided didactic information about sexual health through a text-based chatbot; Gamified Treatment (T1) was a behaviourally-informed gamified text-based chatbot; Narrative Treatment (T2) was a behaviourally-informed drama delivered through pre-recorded voice notes. All chatbots were delivered in WhatsApp, through which users were invited to complete brief "quizzes" comprising adapted versions of validated scales. Primary outcomes were short-form adaptations of scales for gender attitudes (Gender Relations Scale) and past-month IPV (WHO Multi-country Study Instrument). Secondary outcomes were identification of unhealthy relationship behaviours (Intimate Partner Violence Attitudes Scale) and brief screener for depressive symptoms (Patient Health Questionnaire). A direct chat link to a trained counsellor was a safety measure (accessed by 4.5% of the sample). We estimated treatment effects using ordinary least squares and heteroskedasticity robust standard errors.

findingsThe trial retained 11,630 (59.2%) to the primary endpoint of gender attitudes. Compared to control, all treatments led to moderate and significant changes in attitudes towards greater gender equity (Cohen's D = 0.10, 0.29, 0.20 for T0, T1, and T2, respectively). The gamified chatbot (T1) had modest but significant effects on IPV: 56% of young women reported past-month IPV, compared to 62% among those without treatment (marginal effects = -0.07, 95%CI = -0.09to-0.05). The narrative treatment (T2) had no effect on IPV exposure. T1 increased identification of unhealthy relationship behaviours at a moderate and significant level (Cohen's D = 0.25). Neither T1 nor T2 had a measurable effect on depressive symptoms as measured by the brief screener. Interpretation: A behaviourally-informed, gamified chatbot increased gender equitable attitudes and was protective for IPV exposure among young women in South Africa. These effects, while modest in magnitude, could represent a meaningful impact given potential to scale the low-cost intervention.

Identifiers

PMID37844088
PMCPMC10578594

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.