Evidence map›Paper›PMID 34095055›Full record

ArticleFrontiers in public health2021

The Development of an Electronic Clinical Decision and Support System to Improve the Quality of Antenatal Care in Rural Tanzania: Lessons Learned Using Intervention Mapping.

Sandra van Pelt, Karlijn Massar, Laura Shields-Zeeman, John B F de Wit, Lisette van der Eem, Athanas S Lughata, Robert A C Ruiter

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. The FemTech revolution: Unlocking the potential of new technology for optimizing pregnancy outcomes in low- and middle-income countries and remote areas.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026
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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

7 authors at 4 institutions in 3 countries.

Sandra van PeltDepartment of Work and Social Psychology, Maastricht University, Maastricht, Netherlands.
Karlijn MassarDepartment of Work and Social Psychology, Maastricht University, Maastricht, Netherlands.
Laura Shields-ZeemanDepartment of Mental Health and Prevention, Netherlands Institute for Mental Health and Addiction, Utrecht, Netherlands.
John B F de WitDepartment of Interdisciplinary Social Science, International Public Health, Utrecht University, Utrecht, Netherlands.
Lisette van der EemWoman Centered Care Project, A Project of the African Woman Foundation, Magu, Tanzania.
Athanas S LughataWoman Centered Care Project, A Project of the African Woman Foundation, Magu, Tanzania.
Robert A C RuiterDepartment of Work and Social Psychology, Maastricht University, Maastricht, Netherlands.
Maastricht University · NLAmref Health Africa · TZInstitute of Mental Health · GBUtrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is widely recognised that high quality antenatal care is a key element in maternal healthcare. Tanzania has a very high maternal mortality ratio of 524 maternal deaths per 100,000 live births. Most maternal deaths are due to preventable causes that can be detected during pregnancy, and antenatal care therefore plays an important role in reducing maternal morbidity and mortality. Unfortunately, quality of antenatal care in Tanzania is low: Research has shown that healthcare workers show poor adherence to antenatal care guidelines, and the majority of pregnant women miss essential services. Digital health tools might improve the performance of healthcare workers and contribute to improving the quality of antenatal care. To this end, an electronic clinical decision and support system (the Nurse Assistant App) was developed and implemented in Tanzania in 2016 to provide digital assistance during antenatal care consultations to healthcare workers. The current study systematically evaluated the development and implementation process of the Nurse Assistant App in Magu District, Tanzania, with the aim of informing future programme planners about relevant steps in the development of a digital health intervention. Desk research was combined with semi-structured interviews to appraise the development process of the digital health tool. We employed the criteria stipulated by Godin et al., which are based on the six steps of Intervention Mapping [IM; Bartholomew Eldredge et al.]. Findings indicated that five of the six steps of IM were completed during the development and implementation of the Nurse Assistant App. Tasks related to community engagement, adjustment to local context, implementation in the practical context in collaboration with local partners, and rigorous evaluation were accomplished. However, tasks related to identifying theory-based behaviour change methods were not accomplished. Based on the lessons learned during the process of developing and implementing the Nurse Assistant App, we conclude that programme developers are recommended to (1) engage the community and listen to their insights, (2), focus on clear programme goals and the desired change, (3), consult or involve a behaviour change specialist, and (4), anticipate potential problems in unexpected circumstances.

Indexed as

Prenatal CareRural PopulationElectronicsFemaleHumansPregnancyPregnant PeopleTanzaniaantenatal caredigital healthelectronic clinical decision and support systemhealthcare worker performanceimplementationintervention mappingmaternal health

Identifiers

PMID34095055
PMCPMC8172617
OpenAlexW3160491925

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.