Evidence map›Paper›PMID 38866839›Full record

ArticleScientific reports2024

Integration of passive sensing technology to enhance delivery of psychological interventions for mothers with depression: the StandStrong study.

Alastair van Heerden, Anubhuti Poudyal, Ashley Hagaman, Sujen Man Maharjan, Prabin Byanjankar, Dörte Bemme, Ada Thapa, Brandon A Kohrt

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Observational
  4. Review
  5. Article
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

8 authors.

Alastair van HeerdenCenter for Community Based Research, Human Sciences Research Council, Pietermaritzburg, South Africa. avanheerden@hsrc.ac.za.ORCID http://orcid.org/0000-0003-2530-6885
Anubhuti PoudyalDepartment of Sociomedical Sciences, Columbia Mailman School of Public Health, New York, NY, USA.
Ashley HagamanDepartment of Social and Behavioral Sciences, Yale School of Public Health, Yale University, New Haven, CT, USA.
Sujen Man MaharjanTranscultural Psychosocial Organization Nepal, Kathmandu, Nepal.
Prabin ByanjankarTranscultural Psychosocial Organization Nepal, Kathmandu, Nepal.
Dörte BemmeDepartment for Global Health and Social Medicine, Kings College London, London, UK.
Ada ThapaDivision of Global Health Equity, Brigham and Women's Hospital Boston, Boston, MA, USA.
Brandon A KohrtDepartment of Psychiatry and Behavioral Sciences, Center for Global Mental Health Equity, George Washington School of Medicine and Health Sciences, Washington, DC, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Sensing Technologies for Maternal Depression Treatment (StandStrong)R33MH126877 · NIMH · GEORGE WASHINGTON UNIVERSITY · PI KOHRT, BRANDON ALAN · 2023 to 2025
$868k
NCATS NIH HHS UL1 TR001863NIMH NIH HHS R33 MH126877
6 · The paper itself

Abstract

Psychological interventions delivered by non-specialist providers have shown mixed results for treating maternal depression. mHealth solutions hold the possibility for unobtrusive behavioural data collection to identify challenges and reinforce change in psychological interventions. We conducted a proof-of-concept study using passive sensing integrated into a depression intervention delivered by non-specialists to twenty-four adolescents and young mothers (30% 15-17 years old; 70% 18-25 years old) with infants (< 12 months old) in rural Nepal. All mothers showed a reduction in depression symptoms as measured with the Beck Depression Inventory. There were trends toward increased movement away from the house (greater distance measured through GPS data) and more time spent away from the infant (less time in proximity measured with the Bluetooth beacon) as the depression symptoms improved. There was considerable heterogeneity in these changes and other passively collected data (speech, physical activity) throughout the intervention. This proof-of-concept demonstrated that passive sensing can be feasibly used in low-resource settings and can personalize psychological interventions. Care must be taken when implementing such an approach to ensure confidentiality, data protection, and meaningful interpretation of data to enhance psychological interventions.

Indexed as

DepressionMothersAdolescentAdultFemaleHumansInfantNepalProof of Concept StudyPsychosocial InterventionTelemedicineYoung Adult

Identifiers

PMID38866839
PMCPMC11169515

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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.