JMIR Publications

ABSTRACT

Background:

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

Objective:

The objective of this study was to examine gender differences in cell phone ownership, internet access and knowledge of SMS among males and females living in urban slum settings.

Methods:

A convenience sampling approach was utilized in sample selection from 675 un-notified slums. Thirty-eight slum sites were then selected across 4 geographic zones. Ten percent of the households in each slum site were selected from each zone, and one household member was interviewed, based on their availability and fulfilment of the eligibility criteria. Eligible individuals included those aged 18 years and above, resident in these slums and provided voluntary consent to participate in the study. Individuals with mental or physical challenges were excluded from the study.

Results:

Results showed that more than half of the study participants owned a cell phone (67%, n=602 of 907), 49% were capable of sending text messages (n=446 of 907), and 24% (n=220 of 907) had internet service on their cell phones. Females were half as likely to own cell phones compared with males (OR=0.532, 95% CI: 0.371, 0.763), less likely to have internet access (OR=0.785, 95% CI: 0.556, 1.107), or send text messages (OR=0.93, 95% CI: 0.661, 1,308). The predictors of cell 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 (p<0.05). Among males, the number of earning members was a predictor of both cell phone ownership and text messaging, while household education was a predictor both internet access and text messaging. Age and individual education only predicted internet access, while 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 cell phone ownership; housing type only predicted internet access; while TV 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 utilization of cell phones, internet and text messaging among women in slum settings, owing 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.