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    Is it possible to evaluate addiction from clinical records? Testing a retrospective addiction severity evaluation measure.

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    AIM: To compare an addiction severity score estimated from clinical records to addiction severity index (ASI) scores. METHODS: During April-May 2004, 31 patients treated in a therapeutic community in the Piedmont region (Italy) were interviewed using the ASI questionnaire and their clinical records were used to obtain severity scores in seven areas: physical health, occupational functioning, alcohol use, drug use, legal problems, family/social relationships, psychological health. Correlation, agreement, and discriminatory capacity of the clinical records score in correctly classifying persons with low or high severity were investigated using Spearman, Kappa coefficient, and receiver operating characteristics curves. CONCLUSIONS: Clinical records score showed good correlation, agreement, and discriminatory accuracy with respect to ASI scores, especially in the drug use and legal problems areas. Further research is suggested to study the use of the score in other settings

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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