Evaluating the Validity of Computerized Content Analysis Programs for Identification of Emotional Expression in Cancer Narratives.

Psychological interventions provide linguistic data that are particularly useful for testing mechanisms of action and improving intervention methodologies. For this study, emotional expression in an Internet-based intervention for women with breast cancer (n = 63) was analyzed via rater coding and 2...

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Publicado en:Psychological Assessment Vol. 21; no. 1; pp. 79 - 89
Autores principales: Bantum, Erin O'Carroll, Owen, Jason E.
Formato: Artículo
Publicado: American Psychological Association March 2009
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Acceso en línea:Ver este registro en EBSCOhost
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      pub: American Psychological Association
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        10.1037/a0014643
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        atl: Evaluating the Validity of Computerized Content Analysis Programs for Identification of Emotional Expression in Cancer Narratives.
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          Bantum, Erin O'Carroll
          Owen, Jason E.
      su:
        Inter-observer reliability
        Emotions
        Computer software
        Content analysis
        Cancer patient psychology
        Cancer in women
        Psychology
      sug:
        subj:
          Inter-observer reliability
          Emotions
          Computer software
          Content analysis
          Cancer patient psychology
          Cancer in women
          Psychology
      ab: Psychological interventions provide linguistic data that are particularly useful for testing mechanisms of action and improving intervention methodologies. For this study, emotional expression in an Internet-based intervention for women with breast cancer (n = 63) was analyzed via rater coding and 2 computerized coding methods (Linguistic Inquiry and Word Count [LIWC] and Psychiatric Content Analysis and Diagnosis IPCAD]). Although the computerized coding methods captured most of the emotion identified by raters (LIWC sensitivity = .88; PCAD sensitivity = .83), both over-identified emotional expression (LIWC positive predictive value = .31; PCAD positive predictive value = .19). Correlational analyses suggested better convergent and discriminant validity for LIWC. The results highlight previously unrecognized deficiencies in commonly used computerized content-analysis programs and suggest potential modifications to both programs that could impmve overall accuracy of automated identification of emotional expression. Although the authors recognize these limitations, they conclude that LIWC is superior to PCAD for rapid identification of emotional expression in text. Reprinted by permission of the publisher.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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