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

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

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

2020-12-06T17:05:45-05:00June 22nd, 2020|
Journal Name J Med Internet Res
Publication Year 2020
Volume Jun; 22(6) e14714
Authors Ashish Joshi, Bhavya Malhotra, Chioma Amadi, Menka Loomba, Archa Misra, Shruti Sharma, Arushi Arora, Jaya Amatya

Abstract

Background: Disparities 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.

Objective: This 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.

Methods: A 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.

Results: Our 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.

Conclusions: Our 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.

Keywords: gender, digital divide, mobile phone, internet access, text messaging, slums