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dc.contributor.authorMuhoro, Christine
dc.date.accessioned2018-10-19T06:55:28Z
dc.date.available2018-10-19T06:55:28Z
dc.date.issued2018
dc.identifier.citationMaster of Science in Applied Computingen_US
dc.identifier.urihttp://hdl.handle.net/11295/104237
dc.description.abstractBackground: The use of mobile texting has grown dramatically in the world including in Kenya. It has been suggested that the technology influences people‘s behaviors including alcoholic addiction. Many studies have been done in developed world to investigate the effects of using mobile texting in supporting alcoholic addicts from relapse and it has proved to be effective. The same technology if used here in Kenya would also help in reducing the cases of relapse among the alcoholics. Method/design: This was a cross sectional descriptive study of recovering alcoholic addicts and their caregivers in a rehabilitation center of ages above between 18 and 50 years. Quantitative data was obtained from 39 addicts and their caregivers using a self-administered semi structured questionnaire. One Focus Group Discussion (FGDs) with 12 caregiver and addicts which discussion was conducted to obtain qualitative data. Quantitative data was analyzed using Statistical Package for Social Sciences (SPSS) software version 20, while qualitative data was analyzed using content analysis. Secondly design of an android based application individually tailored with automated text message-based for alcohol relapse self-care support application intervention in addition to usual care. Discussion: This study will provide information on the effectiveness of a text message-based self-management support tool for people with alcoholics. If found to be effective it has the potential to provide individualized support to people with alcoholism across other counties in Kenya, thus extending care outside the clinic environment.en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.titleUsing mobile messaging to support aftercare for recovering alcohol addictsen_US
dc.typeThesisen_US


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