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Media Messages and Public Health : A Decisions Approach to Content Analysis

By: (Edited by) Amy Jordan , (Edited by) Dale Kunkel , (Edited by) Jennifer Manganello , (Edited by) Martin Fishbein

Re-Printing

Ksh 8,600.00

Format: Paperback / Softback

ISBN-10: 0805860258

ISBN-13: 9780805860252

Publisher: Taylor & Francis Inc

Imprint: Routledge

Country of Manufacture: US

Country of Publication: GB

Publication Date: Nov 20th, 2008

Print length: 270 Pages

Weight: 396 grams

Dimensions (height x width x thickness): 22.80 x 15.40 x 1.50 cms

Product Classification: Media studies

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Media Messages and Public Health addresses the full range of methodological and conceptual issues involved in content analysis research, specifically focused on public health-related messages and behaviors.

Media Messages and Public Health addresses the full range of methodological and conceptual issues involved in content analysis research, specifically focused on public health-related messages and behaviors. Uniquely tailored to the challenges faced by content researchers interested in the study of public health topics, coverage includes:

    • Conceptual and methodological foundations involved in the practice of content analysis research used to examine public health issues.
    • Measurement challenges posed by the broad range of media.
    • Use of content analysis across multiple media types.
    • The potential for individual differences in audience interpretation of message content.
    • Case studies that examine public health issues in the media to illustration the decisions that are made when developing content analysis studies.

The volume concludes with a set of guidelines for optimal content analysis research, and suggests ways in which the field can accommodate new technologies and new ways of using media. Developed for researchers in communication, media, and public health, this unique resource demonstrates how the variety of decisions researchers make along the way allows the exploration of traditions, assumptions and implications for each varying alternative and ultimately advances the science of content analysis research.


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