Evidence map›Paper›PMID 32130191›Full record

ArticleJMIR mHealth and uHealth2020

Leveraging Providers' Preferences to Customize Instructional Content in Information and Communications Technology-Based Training Interventions: Retrospective Analysis of a Mobile Phone-Based Intervention in India.

Hanu Tyagi, Manisha Sabharwal, Nishi Dixit, Arnab Pal, Sarang Deo

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-weighted citation impact, top 9% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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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

5 authors at 1 institution in 2 countries.

Hanu TyagiCarlson School of Management, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0002-2066-6788
Manisha SabharwalClinton Health Access Initiative, New Delhi, India.ORCID 0000-0001-8528-5866
Nishi DixitClinton Health Access Initiative, New Delhi, India.ORCID 0000-0002-6231-4617
Arnab PalClinton Health Access Initiative, New Delhi, India.ORCID 0000-0003-2161-7520
Sarang DeoMax Institute of Healthcare Management, Indian School of Business, Hyderabad, India.ORCID 0000-0002-3233-6014
Indian School of Business · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany public health programs and interventions across the world increasingly rely on using information and communications technology (ICT) tools to train and sensitize health professionals. However, the effects of such programs on provider knowledge, practice, and patient health outcomes have been inconsistent. One of the reasons for the varied effectiveness of these programs is the low and varying levels of provider engagement, which, in turn, could be because of the form and mode of content used. Tailoring instructional content could improve engagement, but it is expensive and logistically demanding to do so with traditional training.

objectiveThis study aimed to discover preferences among providers on the form (articles or videos), mode (featuring peers or experts), and length (short or long) of the instructional content; to quantify the extent to which differences in these preferences can explain variation in provider engagement with ICT-based training interventions; and to compare the power of content preferences to explain provider engagement against that of demographic variables.

methodsWe used data from a mobile phone-based intervention focused on improving tuberculosis diagnostic practices among 24,949 private providers from 5 specialties and 1734 cities over 1 year. Engagement time was used as the primary outcome to assess provider engagement. K-means clustering was used to segment providers based on the proportion of engagement time spent on content formats, modes, and lengths to discover their content preferences. The identified clusters were used to predict engagement time using a linear regression model. Subsequently, we compared the accuracy of the cluster-based prediction model with one based on demographic variables of providers (eg, specialty and geographic location).

resultsThe average engagement time across all providers was 7.5 min (median 0, IQR 0-1.58). A total of 69.75% (17,401/24,949) of providers did not consume any content. The average engagement time for providers with nonzero engagement time was 24.8 min (median 4.9, IQR 2.2-10.1). We identified 4 clusters of providers with distinct preferences for form, mode, and length of content. These clusters explained a substantially higher proportion of the variation in engagement time compared with demographic variables (32.9% vs 1.0%) and yielded a more accurate prediction for the engagement time (root mean square error: 4.29 vs 5.21 and mean absolute error: 3.30 vs 4.26).

conclusionsProviders participating in a mobile phone-based digital campaign have inherent preferences for instructional content. Targeting providers based on individual content preferences could result in higher provider engagement as compared to targeting providers based on demographic variables.

Indexed as

Cell PhoneCommunicationHumansIndiaRetrospective StudiesTechnologyhealth care providershealth care workersinfectious diseasesinformation technologyinstructional technologylearning preferencesmobile healthprovider trainingpublic health

Identifiers

PMID32130191
PMCPMC7078634
OpenAlexW3010430501

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.