Evidence map›Paper›PMID 38805444›Full record

Trial reportPloS one2024

Effectiveness of a chatbot in improving the mental wellbeing of health workers in Malawi during the COVID-19 pandemic: A randomized, controlled trial.

Eckhard Kleinau, Tilinao Lamba, Wanda Jaskiewicz, Katy Gorentz, Ines Hungerbuehler, Donya Rahimi, Demoubly Kokota, Limbika Maliwichi, Edister Jamu, Alex Zumazuma and 4 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 3 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, 3 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

14 authors.

Eckhard KleinauUniversity Research Co. (URC), Chevy Chase, Maryland, United States of America.ORCID 0000-0003-0304-1644
Tilinao LambaDept. of Psychology, University of Malawi-Chancellor College, Zomba, Malawi.
Wanda JaskiewiczGlobal Health Division, Chemonics International, Washington, District of Columbia, United States of America.ORCID 0000-0001-7904-0432
Katy GorentzGlobal Health Division, Chemonics International, Washington, District of Columbia, United States of America.
Ines HungerbuehlerClinical Division, Vitalk, São Paulo, Brazil.
Donya RahimiGlobal Health Division, Chemonics International, Washington, District of Columbia, United States of America.
Demoubly KokotaDept. of Psychology, University of Malawi-Chancellor College, Zomba, Malawi.
Limbika MaliwichiDept. of Psychology, University of Malawi-Chancellor College, Zomba, Malawi.ORCID 0000-0002-9026-4282
Edister JamuDept. of Psychology, University of Malawi-Chancellor College, Zomba, Malawi.ORCID 0000-0002-3532-7535
Alex ZumazumaDepartment of Mental Health, Kamuzu University of Health Sciences (KUHES), Blantyre, Malawi.ORCID 0000-0001-6065-8160
Mariana NegrãoClinical Division, Vitalk, São Paulo, Brazil.
Raphael MotaClinical Division, Vitalk, São Paulo, Brazil.
Yasmine KhouriClinical Division, Vitalk, São Paulo, Brazil.
Michael KappsClinical Division, Vitalk, São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We conducted a randomized, controlled trial (RCT) to investigate our hypothesis that the interactive chatbot, Vitalk, is more effective in improving mental wellbeing and resilience outcomes of health workers in Malawi than the passive use of Internet resources. For our 2-arm, 8-week, parallel RCT (ISRCTN Registry: trial ID ISRCTN16378480), we recruited participants from 8 professional cadres from public and private healthcare facilities. The treatment arm used Vitalk; the control arm received links to Internet resources. The research team was blinded to the assignment. Of 1,584 participants randomly assigned to the treatment and control arms, 215 participants in the treatment and 296 in the control group completed baseline and endline anxiety assessments. Six assessments provided outcome measures for: anxiety (GAD-7); depression (PHQ-9); burnout (OLBI); loneliness (ULCA); resilience (RS-14); and resilience-building activities. We analyzed effectiveness using mixed-effects linear models, effect size estimates, and reliable change in risk levels. Results support our hypothesis. Difference-in-differences estimators showed that Vitalk reduced: depression (-0.68 [95% CI -1.15 to -0.21]); anxiety (-0.44 [95% CI -0.88 to 0.01]); and burnout (-0.58 [95% CI -1.32 to 0.15]). Changes in resilience (1.47 [95% CI 0.05 to 2.88]) and resilience-building activities (1.22 [95% CI 0.56 to 1.87]) were significantly greater in the treatment group. Our RCT produced a medium effect size for the treatment and a small effect size for the control group. This is the first RCT of a mental health app for healthcare workers during the COVID-19 pandemic in Southern Africa combining multiple mental wellbeing outcomes and measuring resilience and resilience-building activities. A substantial number of participants could have benefited from mental health support (1 in 8 reported anxiety and depression; 3 in 4 suffered burnout; and 1 in 4 had low resilience). Such help is not readily available in Malawi. Vitalk has the potential to fill this gap.

Indexed as

AnxietyCOVID-19DepressionHealth PersonnelMental HealthResilience, PsychologicalAdultBurnout, ProfessionalFemaleHumansLonelinessMalawiMaleMiddle AgedPandemicsSARS-CoV-2

Identifiers

PMID38805444
PMCPMC11132445

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.