Literature DB >> 3949541

Developing and testing a decision model for predicting influenza vaccination compliance.

W B Carter, L R Beach, T S Inui, J P Kirscht, J C Prodzinski.   

Abstract

Influenza vaccination has long been recommended for elderly high-risk patients, yet national surveys indicate that vaccination compliance rates are remarkably low (20 percent). We conducted a study to model prospectively the flu shot decisions and subsequent behavior of an elderly and/or chronically diseased (at high risk for complications of influenza) ambulatory care population at the Seattle VA Medical Center. Prior to the 1980-81 flu shot season, a random (stratified by disease) sample of 63 patients, drawn from the total population of high-risk patients in the general medicine clinic, was interviewed to identify patient-defined concerns regarding flu shots. Six potential consequences of influenza and nine of vaccination were emphasized by patients and provided the content for a weighted hierarchical utility model questionnaire. The utility model provides an operational framework for (1) obtaining subjective value and relative importance judgments from patients; (2) combining these judgments to obtain a prediction of behavioral intention and behavior for each patient; and, if the model is valid (predictive of behavior), (3) identifying those factors which are most salient to patient's decisions and subsequent behavior. Prior to the 1981-82 flu season, the decision model questionnaire was administered to 350 other high-risk patients from the same general medicine clinic population. The decision model correctly predicted behavioral intention for 87 percent and vaccination behavior for 82 percent of this population and, more importantly, differentiated shot "takers" and "nontakers" along several attitudinal dimensions that suggest specific content areas for clinical compliance intervention strategies.

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Year:  1986        PMID: 3949541      PMCID: PMC1068913     

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  10 in total

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  10 in total
  11 in total

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Journal:  J Gen Intern Med       Date:  1992 Sep-Oct       Impact factor: 5.128

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Authors:  Anjum S Kaka; Gregory A Filice; Sharon Myllenbeck; Kristin L Nichol
Journal:  Open Forum Infect Dis       Date:  2017-01-12       Impact factor: 3.835

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