ANALYZING SELF REPORTED QUESTIONNAIRE DATA FROM AN ENVIRONMENTAL RISK REDUCTION RCT

2.50
Hdl Handle:
http://hdl.handle.net/10755/157314
Type:
Presentation
Title:
ANALYZING SELF REPORTED QUESTIONNAIRE DATA FROM AN ENVIRONMENTAL RISK REDUCTION RCT
Abstract:
ANALYZING SELF REPORTED QUESTIONNAIRE DATA FROM AN ENVIRONMENTAL RISK REDUCTION RCT
Conference Sponsor:Western Institute of Nursing
Conference Year:2010
Author:Odom-Maryon, Tamara, PhD
P.I. Institution Name:Washington State University College of Nursing
Title:Research Professor
Contact Address:PO Box 1495, Spokane, WA, 99210-1495, USA
Co-Authors:Gail Oneal
PURPOSES/AIMS: Analyzing questionnaire data from a multi-site longitudinal randomized clinical trial (RCT) can be complex. Our approach to and the challenges faced when analyzing data from a study conducted to evaluate the effectiveness of an environmental risk (ER) reduction nursing intervention and education (4 home visits by public health nurses) to rural low income families is presented.
RATIONALE/CONCEPTUAL BASIS/BACKGROUND: The pragmatic, methodological and analytical issues faced in this study are common to many longitudinal RCTs. Sharing a concrete approach to handling these challenges may help other researchers analyzing similar types of data.
METHODS: This multi-site longitudinal study utilized common Web based data entry software at two remote sites where research records were maintained until data collection was complete. A small percentage of participants were anticipated to attrit or drop out from the study as it progressed over time. Questionnaires were designed around the Precaution Adoption Process Model. Questionnaire data included multiple related questions, targeted measuring of participantsÆ intention and action towards reducing ER, as well as their confidence in their ability to do so. These data can be grouped into summary measures by ER following the health behavior model.
RESULTS: To facilitate editing data that was entered using Web based software, additional programming support (scripts) was needed and is now recommended. To handle attrition, RESULTS: from the last completed visit were carried forward to incomplete visits for these households.
METHODS: utilizing generalized estimating equations were employed to incorporate all available data in the analyses. Factor analysis, item analysis and classic test theory were approaches used to explore relationships among questionnaire items, to understand ER as impacted by the intervention, and for data reduction.
IMPLICATIONS: Longitudinal RCTs involving questionnaires as data collection tools often result in the collection of vast amounts of data. The strategy presented here demonstrates our approach to handling the pragmatic, methodological and analytical issues faced.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Western Institute of Nursing

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleANALYZING SELF REPORTED QUESTIONNAIRE DATA FROM AN ENVIRONMENTAL RISK REDUCTION RCTen_GB
dc.identifier.urihttp://hdl.handle.net/10755/157314-
dc.description.abstract<table><tr><td colspan="2" class="item-title">ANALYZING SELF REPORTED QUESTIONNAIRE DATA FROM AN ENVIRONMENTAL RISK REDUCTION RCT</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Western Institute of Nursing</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2010</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Odom-Maryon, Tamara, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Washington State University College of Nursing</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Research Professor</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">PO Box 1495, Spokane, WA, 99210-1495, USA</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">tmaryon@wsu.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Gail Oneal</td></tr><tr><td colspan="2" class="item-abstract">PURPOSES/AIMS: Analyzing questionnaire data from a multi-site longitudinal randomized clinical trial (RCT) can be complex. Our approach to and the challenges faced when analyzing data from a study conducted to evaluate the effectiveness of an environmental risk (ER) reduction nursing intervention and education (4 home visits by public health nurses) to rural low income families is presented. <br/>RATIONALE/CONCEPTUAL BASIS/BACKGROUND: The pragmatic, methodological and analytical issues faced in this study are common to many longitudinal RCTs. Sharing a concrete approach to handling these challenges may help other researchers analyzing similar types of data. <br/>METHODS: This multi-site longitudinal study utilized common Web based data entry software at two remote sites where research records were maintained until data collection was complete. A small percentage of participants were anticipated to attrit or drop out from the study as it progressed over time. Questionnaires were designed around the Precaution Adoption Process Model. Questionnaire data included multiple related questions, targeted measuring of participants&AElig; intention and action towards reducing ER, as well as their confidence in their ability to do so. These data can be grouped into summary measures by ER following the health behavior model. <br/>RESULTS: To facilitate editing data that was entered using Web based software, additional programming support (scripts) was needed and is now recommended. To handle attrition, RESULTS: from the last completed visit were carried forward to incomplete visits for these households. <br/>METHODS: utilizing generalized estimating equations were employed to incorporate all available data in the analyses. Factor analysis, item analysis and classic test theory were approaches used to explore relationships among questionnaire items, to understand ER as impacted by the intervention, and for data reduction. <br/>IMPLICATIONS: Longitudinal RCTs involving questionnaires as data collection tools often result in the collection of vast amounts of data. The strategy presented here demonstrates our approach to handling the pragmatic, methodological and analytical issues faced. <br/></td></tr></table>en_GB
dc.date.available2011-10-26T19:45:38Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T19:45:38Z-
dc.description.sponsorshipWestern Institute of Nursingen_GB
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