Evidence map›Paper›PMID 32343670›Full record

ArticleJournal of medical Internet research2020

Gender and the Digital Divide Across Urban Slums of New Delhi, India: Cross-Sectional Study.

Ashish Joshi, Bhavya Malhotra, Chioma Amadi, Menka Loomba, Archa Misra, Shruti Sharma, Arushi Arora, Jaya Amatya

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Wise investment is needed for maximising the benefits in Covid times.Journal of family medicine and primary care · 2022
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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

8 authors.

Ashish Joshi *Graduate School of Public Health and Health Policy, City University of New York, New York, NY, United States.ORCID 0000-0002-5376-9839
Bhavya MalhotraFoundation of Health care Technologies Society, Delhi, India.ORCID 0000-0001-5615-0516
Chioma AmadiGraduate School of Public Health and Health Policy, City University of New York, New York, NY, United States.ORCID 0000-0002-8016-7550
Menka LoombaFoundation of Health care Technologies Society, Delhi, India.ORCID 0000-0003-4880-6890
Archa MisraFoundation of Health care Technologies Society, Delhi, India.ORCID 0000-0002-0702-959X
Shruti SharmaFoundation of Health care Technologies Society, Delhi, India.ORCID 0000-0003-3548-0000
Arushi AroraFoundation of Health care Technologies Society, Delhi, India.ORCID 0000-0001-8913-3544
Jaya AmatyaGraduate School of Public Health and Health Policy, City University of New York, New York, NY, United States.ORCID 0000-0003-2906-7877

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisparities in access to specific technologies within gender groups have not been investigated. Slum settings provide an ideal population to investigate the contributing factors to these disparities.

objectiveThis study aimed to examine gender differences in mobile phone ownership, internet access, and knowledge of SMS text messaging among males and females living in urban slum settings.

methodsA convenience sampling approach was used in sample selection from 675 unnotified slums. A total of 38 slum sites were then selected across four geographic zones. Of these, 10% of the households in each slum site was selected from each zone. One household member was interviewed based on their availability and fulfillment of the eligibility criteria. Eligible individuals included those aged 18 years and above, residing in these slums, and who provided voluntary consent to participate in the study. Individuals with mental or physical challenges were excluded from the study.

resultsOur results showed that females were half as likely to own mobile phones compared with males (odds ratio [OR] 0.53, 95% CI 0.37-0.76), less likely to have internet access (OR 0.79, 95% CI 0.56-1.11), or know how to send text messages (OR 0.93, 95% CI 0.66-1.31). The predictors of mobile phone ownership, internet access, and text messaging between males and females included age, individual education, housing type, and the number of earning members in a household in the adjusted analysis. Among males, the number of earning members was a predictor of both mobile phone ownership and text messaging, whereas household education was a predictor of both internet access and text messaging. Age and individual education only predicted internet access, whereas housing type only predicted text messaging. Among females, household education was a predictor of all the technology outcomes. Age and type of toilet facility only predicted mobile phone ownership; housing type only predicted internet access whereas television ownership with satellite service and smoking behavior only predicted text messaging.

conclusionsOur study findings showing disparate access to technology within gender groups lend support for further research to examine the causal mechanisms promoting these differences to proffer significant solutions. Specifically, our study findings suggest that improving household education is crucial to address the disparate access and usage of mobile phones, the internet, and text messaging among women in slum settings. This suggestion is due to the consistency in household educational level as a predictor across all these technology indicators. In addition, the mechanisms by which the number of household earning members influences the disparate access to technology among men call for further exploration.

Indexed as

AdolescentAdultCross-Sectional StudiesDigital DivideFemaleGender IdentityHumansIndiaMalePoverty AreasYoung Adultdigital dividegenderinternet accessmobile phoneslumstext messaging

Identifiers

PMID32343670
PMCPMC7338923

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.