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Original Article

Pharmacists' Brand Recommendations of Nonprescription Analgesics for a Simple, Tension, and Migraine Headache

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Pages 27-49 | Received 17 Nov 1997, Accepted 04 Mar 1998, Published online: 04 Dec 2011
 

ABSTRACT

Pharmacists are considered to be vital in the area of nonprescription medication. The objective of this study was to determine the attributes and pharmacist characteristics that influence pharmacists' brand recommendation of a nonprescription analgesic for an adult with a simple, tension, or migraine headache. The main questionnaire was mailed to 1,500 randomly selected Australian community pharmacies and resulted in a 68.3% usable response rate. Principal components analysis with varimax rotation was employed. Factor scores were calculated and used along with some demographic details as explanatory variables in a technique called discrete choice modeling. The probability of pharmacists recommending particular analgesic brands for the three types of headaches was significantly influenced by external factors and pharmacist characteristics. External factors included economic (p < 0.05), brand and professional (p < 0.01), customer (p < 0.05), company (p < 0.05), and new product (p < 0.05) influences. Characteristics of the pharmacist included pharmacist's position in the pharmacy (p < 0.05); the number of hours per week pharmacist works in community pharmacy (p < 0.05); the percentage of the pharmacy's ordering, purchasing, and dealing of nonprescription analgesics in which a pharmacist was involved (p < 0.05); postgraduate qualifications (p < 0.1); year of registration (p < 0.01); and the percentage of the pharmacy's recommendation of nonprescription analgesics in which a pharmacist was involved (p < 0.01). The study has shown that for pharmacists' recommendations of nonprescription analgesic brands, it was the balance between certain external factors and pharmacist characteristics that was important. The technique developed allowed the researcher to ascertain the likely changes in pharmacists' recommendation behavior following increases in importance of significant attributes.

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