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J Am Pharm Assoc (2003) · Jul 2002
Understanding how patients form beliefs about pharmacists' trustworthiness using a model of belief processing.
- Donna S West, Noel E Wilkin, John P Bentley, Faye Gilbert, and Dewey D Garner.
- College of Pharmacy, University of Arkansas for Medical Sciences, Little Rock 72205-7199, USA. westdonnas@uams.edu
- J Am Pharm Assoc (2003). 2002 Jul 1; 42 (4): 594-601.
ObjectiveTo determine what information people use in forming beliefs about pharmacists' trustworthiness and to determine whether these pieces of information can be categorized using elements of a model of belief processing.DesignParticipants in two focus groups were asked about the trustworthiness of pharmacists in one dispensing scenario and two pharmaceutical care scenarios. Transcripts were analyzed, and each piece of information provided was coded as an evidence statement or a claim, according to a model of belief processing.SettingUniversity campus.ParticipantsUniversity staff and students.Main Outcome MeasuresInformation used to form beliefs about pharmacists' trustworthiness and classification of the information using constructs from the model of belief processing.ResultsCoders identified 92 evidence statements and 19 claims. An evaluation of the data across the scenarios using predetermined criteria showed 20 evidence statements and 11 claims to be the most salient pieces of information used to form beliefs about pharmacists' trustworthiness. In considering the pharmaceutical care scenarios, participants focused more on communication and interpersonal skills when forming a trustworthiness belief. The information could be categorized as evidence statements or claims, which are parts of arguments as described by a model of belief processing.ConclusionThe study participants used the pharmacists' credentials, communication skills, personableness, and appearance to form trustworthiness beliefs. Overall, they wanted pharmacists to be honest, knowledgeable, and caring. Variables used to form trustworthiness beliefs represent different levels of abstraction that can be detected and coded using a model of belief processing.
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