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PubMed · 15573337

Using PDAs for data collection.

Lisa Guadagno·Carla VandeWeerd·Dirk Stevens·Ivo Abraham·Gregory J Paveza·Terry Fulmer
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Abstract

Advances in handheld computer technology are making data collection faster, easier, and more accurate. In this article, the use of personal digital assistants (PDAs) to collect data for a study on elder neglect is described and evaluated. Methods for integrating this technology into a research study are discussed as are suggestions for increasing the performance of data collectors using these devices. The authors offer some practical solutions for researchers and clinicians planning to use PDAs in their research.

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Attitude of Health PersonnelAttitude to ComputersComputer User TrainingComputers, HandheldData CollectionElder AbuseEquipment FailureFloridaGeriatric AssessmentHumansMass ScreeningNeeds AssessmentNew York CityNursing AssessmentNursing Evaluation ResearchNursing InformaticsNursing RecordsObserver VariationPoint-of-Care SystemsRisk AssessmentUser-Computer InterfaceEvaluation StudyJournal ArticleResearch Support, U.S. Gov't, P.H.S.

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Lisa Guadagno, Carla VandeWeerd, Dirk Stevens, Ivo Abraham, Gregory J Paveza, Terry Fulmer. 2004. Using PDAs for data collection.. https://pubmed.ncbi.nlm.nih.gov/15573337/

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Getting physicians to accept new information technology: insights from case studies.

BACKGROUND: The success or failure of a computer information system (CIS) depends on whether physicians accept or resist its implementation. Using case studies, we analyzed the implementation of such systems in 3 hospitals to understand better the dynamics of physicians' resistance to CIS implementation. METHODS: We selected cases to maximize variation while allowing comparison of CIS implementations. Data were collected from observations, documentation and interviews, the last being the main source of data. Interviewees comprised 15 physicians, 14 nurses and 14 system implementers. Transcripts were produced; 45 segments of the transcripts were coded by several judges, with an appropriate level of intercoder reliability. We conducted within-case and cross-case analyses of the data. RESULTS: Initially, most staff were neutral or enthusiastic about the CIS implementations. During implementation, the level of resistance varied and in 2 instances became great enough to lead to major disruptions and system withdrawal. Implementers' responses to physicians' resistance behaviours played a critical role. In one case, the responses were supportive and addressed the issues related to the real object of resistance; the severity of resistance decreased, and the CIS implementation was ultimately successful. In the other 2 cases, the implementers' responses reinforced the resistance behaviours. Three types of responses had such an effect in these cases: implementers' lack of response to resistance behaviours, antagonistic responses, and supportive responses aimed at the wrong object of resistance. INTERPRETATION: The 3 cases we analyzed showed the importance of the roles played by implementers and users in determining the outcomes of a CIS implementation.

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