The Experts below are selected from a list of 36 Experts worldwide ranked by ideXlab platform
International Food Policy Research Institute - One of the best experts on this subject based on the ideXlab platform.
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Pakistan Rural Household Panel Survey (PRHPS) 2013, Round 2
Washington DC, 2020Co-Authors: International Food Policy Research InstituteAbstract:The Pakistan Rural Household Panel Survey (PRHPS) 2013, Round 2 is the second round of the PRHPS; Round 1 was conducted in 2012. This survey aims to provide a quantitative basis to identify and address urgent economic development and policy priorities in Pakistan. Many modules and questions are consistent with the prior round. PRHPS Round 2 covers 2002 of the 2090 households surveyed during Round 1 in 76 primary sampling units in the rural areas of three provinces namely: (i) Punjab; (ii) Sindh; and (iii) Khyber Pakhtunkhwa (KPK). Information on 88 households could not be collected because they refused to respond, migrated or were not available. The sample is representative of the rural areas of Punjab and Sindh provinces, and of the rural areas in 11 of the districts in KPK province. The survey collected information on a large number of topics including sources of income, nature of employment, consumption patterns, time use, assets and savings, loans and credit, education, migration, economic shocks, governance, and participation in social safety nets. Four survey instruments were developed to collect this information. These included two household questionnaires (designed to collect individual- and household-level information from a main male and a main Female Respondent who were interviewed separately), a community questionnaire, and a price questionnaire.IFPRI2; PACEEPTD; DSG
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Pakistan Rural Household Panel Survey (PRHPS) 2014, Round 3
Washington DC, 2020Co-Authors: International Food Policy Research InstituteAbstract:The Pakistan Rural Household Panel Survey (PRHPS) 2014, Round 3 is the third round of the PRHPS; Round 1 and 2 were conducted in 2012 and 2013 respectively. This survey aims to provide a quantitative basis to identify and address urgent economic development and policy priorities in Pakistan. Many modules and questions in Round 3 are consistent with the prior rounds. PRHPS Round 3 was able to collect complete data from 1,876 households in the rural areas of three provinces namely: (i) Punjab; (ii) Sindh; and (iii) Khyber Pakhtunkhwa (KPK).The sample is representative of the rural areas of Punjab and Sindh provinces, and of the rural areas in 11 of the districts in KPK province. The survey collected information on a large number of topics including sources of income, nature of employment, consumption patterns, time use, assets and savings, loans and credit, education, migration, women decision making, economic shocks, transfers in and out, health and nutrition, and participation in social safety nets. Four survey instruments were developed to collect this information. These included two household questionnaires (designed to collect individual- and household-level information from a main male and a main Female Respondent who were interviewed separately), a community questionnaire, and a price questionnaire.IFPRI1; PACEDSG
Jennifer L. Brenner - One of the best experts on this subject based on the ideXlab platform.
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Female Respondent acceptance of computer-assisted personal interviewing (CAPI) for maternal, newborn and child health coverage surveys in rural Uganda
International journal of medical informatics, 2016Co-Authors: Hannah Faye G. Mercader, Jerome Kabakyenga, David Tumusiime Katuruba, Amy J. Hobbs, Jennifer L. BrennerAbstract:Abstract Introduction High maternal and child mortality continues in low- and middle-income countries (LMIC). Measurement of maternal, newborn and child health (MNCH) coverage indicators often involves an expensive, complex, and lengthy household data collection process that is especially difficult in less-resourced settings. Computer-assisted personal interviewing (CAPI) has been proposed as a cost-effective and efficient alternative to traditional paper-and-pencil interviewing (PAPI). However, the literature on Respondent-level acceptance of CAPI in LMIC has reported mixed outcomes. This is the first study to prospectively examine Female Respondent acceptance of CAPI and its influencing factors for MNCH data collection in rural Southwest Uganda. Methods Eighteen women aged 15–49 years were randomly selected from 3 rural villages to participate. Each Respondent was administered a Women’s Questionnaire with half of the survey questions asked using PAPI techniques and the other half using CAPI. Following this PAPI/CAPI exposure, semi-structured focus group discussions (FGDs) assessed Respondent attitudes towards PAPI versus CAPI. FGD data analysis involved an immersion/crystallization method (thematic narrative analysis). Results The sixteen FGD Respondents had a median age of 27 (interquartile range: 24.8, 32.3) years old. The majority (62.5%) had only primary level education. Most Respondents (68.8%) owned or regularly used a mobile phone or computer. Few Respondents (31.3%) had previously seen but not used a tablet computer. Overall, FGDs revealed CAPI acceptance and the factors influencing CAPI acceptability were ‘familiarity’, ‘data confidentiality and security’, ‘data accuracy’, and ‘modernization and development’. Discussion Female survey Respondents in our rural Southwest Ugandan setting found CAPI to be acceptable. Global health planners and implementers considering CAPI for health coverage survey data collection should accommodate influencing factors during survey planning in order to maximize and facilitate acceptance and support by local stakeholders and community participants. Further research is needed to generate best practices for CAPI implementation and LMIC; higher quality, timely, streamlined and budget-friendly collection of MNCH indicators could help direct and improve programming to save lives of mothers and children.
Hannah Faye G. Mercader - One of the best experts on this subject based on the ideXlab platform.
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Female Respondent acceptance of computer-assisted personal interviewing (CAPI) for maternal, newborn and child health coverage surveys in rural Uganda
International journal of medical informatics, 2016Co-Authors: Hannah Faye G. Mercader, Jerome Kabakyenga, David Tumusiime Katuruba, Amy J. Hobbs, Jennifer L. BrennerAbstract:Abstract Introduction High maternal and child mortality continues in low- and middle-income countries (LMIC). Measurement of maternal, newborn and child health (MNCH) coverage indicators often involves an expensive, complex, and lengthy household data collection process that is especially difficult in less-resourced settings. Computer-assisted personal interviewing (CAPI) has been proposed as a cost-effective and efficient alternative to traditional paper-and-pencil interviewing (PAPI). However, the literature on Respondent-level acceptance of CAPI in LMIC has reported mixed outcomes. This is the first study to prospectively examine Female Respondent acceptance of CAPI and its influencing factors for MNCH data collection in rural Southwest Uganda. Methods Eighteen women aged 15–49 years were randomly selected from 3 rural villages to participate. Each Respondent was administered a Women’s Questionnaire with half of the survey questions asked using PAPI techniques and the other half using CAPI. Following this PAPI/CAPI exposure, semi-structured focus group discussions (FGDs) assessed Respondent attitudes towards PAPI versus CAPI. FGD data analysis involved an immersion/crystallization method (thematic narrative analysis). Results The sixteen FGD Respondents had a median age of 27 (interquartile range: 24.8, 32.3) years old. The majority (62.5%) had only primary level education. Most Respondents (68.8%) owned or regularly used a mobile phone or computer. Few Respondents (31.3%) had previously seen but not used a tablet computer. Overall, FGDs revealed CAPI acceptance and the factors influencing CAPI acceptability were ‘familiarity’, ‘data confidentiality and security’, ‘data accuracy’, and ‘modernization and development’. Discussion Female survey Respondents in our rural Southwest Ugandan setting found CAPI to be acceptable. Global health planners and implementers considering CAPI for health coverage survey data collection should accommodate influencing factors during survey planning in order to maximize and facilitate acceptance and support by local stakeholders and community participants. Further research is needed to generate best practices for CAPI implementation and LMIC; higher quality, timely, streamlined and budget-friendly collection of MNCH indicators could help direct and improve programming to save lives of mothers and children.
Jerome Kabakyenga - One of the best experts on this subject based on the ideXlab platform.
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Female Respondent acceptance of computer-assisted personal interviewing (CAPI) for maternal, newborn and child health coverage surveys in rural Uganda
International journal of medical informatics, 2016Co-Authors: Hannah Faye G. Mercader, Jerome Kabakyenga, David Tumusiime Katuruba, Amy J. Hobbs, Jennifer L. BrennerAbstract:Abstract Introduction High maternal and child mortality continues in low- and middle-income countries (LMIC). Measurement of maternal, newborn and child health (MNCH) coverage indicators often involves an expensive, complex, and lengthy household data collection process that is especially difficult in less-resourced settings. Computer-assisted personal interviewing (CAPI) has been proposed as a cost-effective and efficient alternative to traditional paper-and-pencil interviewing (PAPI). However, the literature on Respondent-level acceptance of CAPI in LMIC has reported mixed outcomes. This is the first study to prospectively examine Female Respondent acceptance of CAPI and its influencing factors for MNCH data collection in rural Southwest Uganda. Methods Eighteen women aged 15–49 years were randomly selected from 3 rural villages to participate. Each Respondent was administered a Women’s Questionnaire with half of the survey questions asked using PAPI techniques and the other half using CAPI. Following this PAPI/CAPI exposure, semi-structured focus group discussions (FGDs) assessed Respondent attitudes towards PAPI versus CAPI. FGD data analysis involved an immersion/crystallization method (thematic narrative analysis). Results The sixteen FGD Respondents had a median age of 27 (interquartile range: 24.8, 32.3) years old. The majority (62.5%) had only primary level education. Most Respondents (68.8%) owned or regularly used a mobile phone or computer. Few Respondents (31.3%) had previously seen but not used a tablet computer. Overall, FGDs revealed CAPI acceptance and the factors influencing CAPI acceptability were ‘familiarity’, ‘data confidentiality and security’, ‘data accuracy’, and ‘modernization and development’. Discussion Female survey Respondents in our rural Southwest Ugandan setting found CAPI to be acceptable. Global health planners and implementers considering CAPI for health coverage survey data collection should accommodate influencing factors during survey planning in order to maximize and facilitate acceptance and support by local stakeholders and community participants. Further research is needed to generate best practices for CAPI implementation and LMIC; higher quality, timely, streamlined and budget-friendly collection of MNCH indicators could help direct and improve programming to save lives of mothers and children.
David Tumusiime Katuruba - One of the best experts on this subject based on the ideXlab platform.
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Female Respondent acceptance of computer-assisted personal interviewing (CAPI) for maternal, newborn and child health coverage surveys in rural Uganda
International journal of medical informatics, 2016Co-Authors: Hannah Faye G. Mercader, Jerome Kabakyenga, David Tumusiime Katuruba, Amy J. Hobbs, Jennifer L. BrennerAbstract:Abstract Introduction High maternal and child mortality continues in low- and middle-income countries (LMIC). Measurement of maternal, newborn and child health (MNCH) coverage indicators often involves an expensive, complex, and lengthy household data collection process that is especially difficult in less-resourced settings. Computer-assisted personal interviewing (CAPI) has been proposed as a cost-effective and efficient alternative to traditional paper-and-pencil interviewing (PAPI). However, the literature on Respondent-level acceptance of CAPI in LMIC has reported mixed outcomes. This is the first study to prospectively examine Female Respondent acceptance of CAPI and its influencing factors for MNCH data collection in rural Southwest Uganda. Methods Eighteen women aged 15–49 years were randomly selected from 3 rural villages to participate. Each Respondent was administered a Women’s Questionnaire with half of the survey questions asked using PAPI techniques and the other half using CAPI. Following this PAPI/CAPI exposure, semi-structured focus group discussions (FGDs) assessed Respondent attitudes towards PAPI versus CAPI. FGD data analysis involved an immersion/crystallization method (thematic narrative analysis). Results The sixteen FGD Respondents had a median age of 27 (interquartile range: 24.8, 32.3) years old. The majority (62.5%) had only primary level education. Most Respondents (68.8%) owned or regularly used a mobile phone or computer. Few Respondents (31.3%) had previously seen but not used a tablet computer. Overall, FGDs revealed CAPI acceptance and the factors influencing CAPI acceptability were ‘familiarity’, ‘data confidentiality and security’, ‘data accuracy’, and ‘modernization and development’. Discussion Female survey Respondents in our rural Southwest Ugandan setting found CAPI to be acceptable. Global health planners and implementers considering CAPI for health coverage survey data collection should accommodate influencing factors during survey planning in order to maximize and facilitate acceptance and support by local stakeholders and community participants. Further research is needed to generate best practices for CAPI implementation and LMIC; higher quality, timely, streamlined and budget-friendly collection of MNCH indicators could help direct and improve programming to save lives of mothers and children.
