Information and communication technology use by female residents of public housing.

Lisa M Quintiliani, Shivani Reddy, Rachel Goodman, Deborah J Bowen
Author Information
  1. Lisa M Quintiliani: Department of Medicine, Boston University, School of Medicine, Boston, MA, USA.
  2. Shivani Reddy: VA Advanced Fellow in Women's Health, Boston University, School of Medicine, Boston, MA, USA; RTI International, Center for Advanced Methods Development, Waltham, MA, USA.
  3. Rachel Goodman: Community Services Department, Center for Community Engagement & Civil Rights, Boston Housing Authority, Boston, MA, USA.
  4. Deborah J Bowen: Boston University, School of Public Health, Boston, MA, USA; University of Washington, School of Public Health, Seattle, WA, USA.

Abstract

BACKGROUND: Evidence suggests that Internet, mobile, or social media based-interventions may promote obesity-lowering behavior change, which has implications for cancer prevention and control interventions. However, the uptake of communication technologies among low socioeconomic status individuals, who need obesity management strategies most, is unclear.
METHODS: Using the baseline data from a cluster-randomized behavioral intervention trial, we examined the cross-sectional associations of frequency of information and communication technologies (ICT) use among female public housing residents, as well as the variation of ICT use across demographic and health-related variables.
RESULTS: ICT use was common among female public housing residents, with mobile use for calls and texts most prevalent (97% and 84%, respectively). Internet, social media, and health information users tended to be younger compared to non-users. Email, Internet, multimodal, and health information users were more likely to be born in the U.S. and be more highly educated than non-users. Social media and health information users were more likely to be Spanish speakers and people of Hispanic ethnicity compared to non-users, although this was not statistically significant. There were few differences according to obesity or physical activity level.
CONCLUSIONS: Our findings of differential socio-demographics between users . non-users suggests that future cancer prevention and control interventions among public housing residents should consider selecting ICT that are aligned with the usage patterns of different groups making up the intended audience.

Keywords

References

  1. J Med Internet Res. 2013 Dec 23;15(12):e287 [PMID: 24366061]
  2. Health Commun. 2007;21(2):153-63 [PMID: 17523861]
  3. J Health Care Poor Underserved. 2013 Aug;24(3):1031-41 [PMID: 23974378]
  4. J Med Internet Res. 2014 Jan 13;16(1):e9 [PMID: 24418967]
  5. Am J Health Educ. 2014 Jan 1;45(2):67-75 [PMID: 24910855]
  6. Prev Med. 2016 Aug;89:230-6 [PMID: 27283096]
  7. Am J Public Health. 2008 Jan;98(1):85-91 [PMID: 18048798]
  8. J Nutr Educ Behav. 2012 Jan-Feb;44(1):60-5 [PMID: 21924959]
  9. JMIR Mhealth Uhealth. 2015 Feb 24;3(1):e22 [PMID: 25714907]
  10. Contemp Clin Trials. 2014 Nov;39(2):201-10 [PMID: 25139728]
  11. JMIR Public Health Surveill. 2016 Jul 11;2(2):e32 [PMID: 27400979]
  12. Prog Community Health Partnersh. 2012 Fall;6(3):239-48 [PMID: 22982838]
  13. J Commun. 2013 Feb 1;63(1):201-220 [PMID: 23439871]
  14. Soc Sci Med. 2011 Jul;73(1):22-32 [PMID: 21683493]
  15. Res Q Exerc Sport. 2000 Jun;71 Suppl 2:114-20 [PMID: 25680021]
  16. Curr Obes Rep. 2015 Dec;4(4):510-9 [PMID: 26364308]
  17. J Med Internet Res. 2015 Mar 27;17(3):e77 [PMID: 25831199]
  18. Cancer Epidemiol Biomarkers Prev. 2012 Oct;21(10):1701-8 [PMID: 23045545]
  19. Prev Chronic Dis. 2004 Oct;1(4):A15 [PMID: 15670447]
  20. J Gen Intern Med. 2016 Dec;31(12 ):1417-1426 [PMID: 27418347]
  21. J Cancer Surviv. 2015 Dec;9(4):660-82 [PMID: 25757733]
  22. J Health Soc Behav. 1997 Mar;38(1):21-37 [PMID: 9097506]
  23. Prog Community Health Partnersh. 2013 Spring;7(1):39-47 [PMID: 23543020]
  24. Obes Rev. 2010 Apr;11(4):306-21 [PMID: 19754633]
  25. Transl Behav Med. 2013 Dec;3(4):392-401 [PMID: 24294327]
  26. Appetite. 2015 Dec;95:138-51 [PMID: 26165415]
  27. J Med Internet Res. 2007 Dec 13;9(4):e35 [PMID: 18093903]
  28. Prev Chronic Dis. 2011 Jan;8(1):A15 [PMID: 21159227]

Grants

  1. U48 DP001922/NCCDPHP CDC HHS

Word Cloud

Created with Highcharts 10.0.0usepublichousingamonginformationICTresidentshealthusersnon-usersInternetmediacommunicationfemalesuggestsmobilesocialcancerpreventioncontrolinterventionstechnologiesstatusobesitycomparedlikelyBACKGROUND:Evidencebased-interventionsmaypromoteobesity-loweringbehaviorchangeimplicationsHoweveruptakelowsocioeconomicindividualsneedmanagementstrategiesunclearMETHODS:Usingbaselinedatacluster-randomizedbehavioralinterventiontrialexaminedcross-sectionalassociationsfrequencywellvariationacrossdemographichealth-relatedvariablesRESULTS:commoncallstextsprevalent97%84%respectivelytendedyoungerEmailmultimodalbornUShighlyeducatedSocialSpanishspeakerspeopleHispanicethnicityalthoughstatisticallysignificantdifferencesaccordingphysicalactivitylevelCONCLUSIONS:findingsdifferentialsocio-demographicsfutureconsiderselectingalignedusagepatternsdifferentgroupsmakingintendedaudienceInformationtechnologyMedicalinformaticsdisparities

Similar Articles

Cited By