{"id":{"repo_id":"emich","oai_identifier":"oai:commons.emich.edu:theses-2386"},"canonical_url":"https://search.dev.ndltd.org/etd/emich/oai:commons.emich.edu:theses-2386","repository":{"repo_id":"emich","name":"Eastern Michigan University","base_url":"https://commons.emich.edu/do/oai/"},"display":{"title":"Recognizing addictive disorders through transdiagnostic assessment","abstract":"<p>Some evidence suggests high rates of comorbidity between substance and other related addictive disorders. However, few self-report instruments adopt a transdiagnostic approach, which would be best positioned to answer questions about comorbidity as well as other related phenomenon, such as discontinuation of one type of behavior and initiation of another. The current work aimed to develop a measure that screened for seven types of potentially addictive behavior: alcohol use, drug use, tobacco use, gambling, binge eating, hypersexual behavior, and excessive video game playing. Data were collected at three time-points to develop a large pool of possible items, establish the initial factor structure and reduce the total item pool to 35 items, and confirm the factor structure as well as examine support for reliability and validity. Initial results provided some support for the purported factor structure, though some problems with fit were evident. Subsequent validation with an independent sample, provided strong support for the measure, including evidence of excellent fit for the factor structure and excellent internal consistency reliability. The measure was also positively correlated with several associated constructs, including depression, anxiety, trauma, and emotion dysregulation. Differences in the magnitude of the correlation between subscales and associated constructs were also evident. Overall, the evidence supports use of the instrument as a continuous measure of addictive behaviors. Future research is warranted to understand the validity of the measure in clinical samples and examine the accuracy for detecting with sensitivity and specificity those who do and do not meet criteria for a substance or other related addictive disorder.</p>","abstract_html":"&lt;p&gt;Some evidence suggests high rates of comorbidity between substance and other related addictive disorders. However, few self-report instruments adopt a transdiagnostic approach, which would be best positioned to answer questions about comorbidity as well as other related phenomenon, such as discontinuation of one type of behavior and initiation of another. The current work aimed to develop a measure that screened for seven types of potentially addictive behavior: alcohol use, drug use, tobacco use, gambling, binge eating, hypersexual behavior, and excessive video game playing. Data were collected at three time-points to develop a large pool of possible items, establish the initial factor structure and reduce the total item pool to 35 items, and confirm the factor structure as well as examine support for reliability and validity. Initial results provided some support for the purported factor structure, though some problems with fit were evident. Subsequent validation with an independent sample, provided strong support for the measure, including evidence of excellent fit for the factor structure and excellent internal consistency reliability. The measure was also positively correlated with several associated constructs, including depression, anxiety, trauma, and emotion dysregulation. Differences in the magnitude of the correlation between subscales and associated constructs were also evident. Overall, the evidence supports use of the instrument as a continuous measure of addictive behaviors. Future research is warranted to understand the validity of the measure in clinical samples and examine the accuracy for detecting with sensitivity and specificity those who do and do not meet criteria for a substance or other related addictive disorder.&lt;/p&gt;","abstract_has_math":false,"creators":["Carr, Meagan M."],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Open Access Dissertation","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":["Karen Saules, Ph.D.","David Ledgerwood, Ph.D.","Tamara Loverich, Ph.D."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-01-01T08:00:00Z","date_published":"2018-01-01T08:00:00Z","updated_at":"2026-07-24T02:17:33Z","subjects":["Assessment","Behavioral Addictions","Measurement development","Substance use disorders","Transdiagnostic","Clinical Psychology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/991","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Karen Saules, Ph.D.","David Ledgerwood, Ph.D.","Tamara Loverich, Ph.D."]},{"key":"dc:creator","label":"Author","values":["Carr, Meagan M."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2020-02-26T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Assessment","Behavioral Addictions","Measurement development","Substance use disorders","Transdiagnostic","Clinical Psychology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/991"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>Some evidence suggests high rates of comorbidity between substance and other related addictive disorders. However, few self-report instruments adopt a transdiagnostic approach, which would be best positioned to answer questions about comorbidity as well as other related phenomenon, such as discontinuation of one type of behavior and initiation of another. The current work aimed to develop a measure that screened for seven types of potentially addictive behavior: alcohol use, drug use, tobacco use, gambling, binge eating, hypersexual behavior, and excessive video game playing. Data were collected at three time-points to develop a large pool of possible items, establish the initial factor structure and reduce the total item pool to 35 items, and confirm the factor structure as well as examine support for reliability and validity. Initial results provided some support for the purported factor structure, though some problems with fit were evident. Subsequent validation with an independent sample, provided strong support for the measure, including evidence of excellent fit for the factor structure and excellent internal consistency reliability. The measure was also positively correlated with several associated constructs, including depression, anxiety, trauma, and emotion dysregulation. Differences in the magnitude of the correlation between subscales and associated constructs were also evident. Overall, the evidence supports use of the instrument as a continuous measure of addictive behaviors. Future research is warranted to understand the validity of the measure in clinical samples and examine the accuracy for detecting with sensitivity and specificity those who do and do not meet criteria for a substance or other related addictive disorder.</p>"]},{"key":"dc:title","label":"Title","values":["Recognizing addictive disorders through transdiagnostic assessment"]}]}],"canonical_facts":{"dc:contributor":["Karen Saules, Ph.D.","David Ledgerwood, Ph.D.","Tamara Loverich, Ph.D."],"dc:creator":["Carr, Meagan M."],"dc:date.available":["2020-02-26T08:00:00Z"],"dc:description.abstract":["<p>Some evidence suggests high rates of comorbidity between substance and other related addictive disorders. However, few self-report instruments adopt a transdiagnostic approach, which would be best positioned to answer questions about comorbidity as well as other related phenomenon, such as discontinuation of one type of behavior and initiation of another. The current work aimed to develop a measure that screened for seven types of potentially addictive behavior: alcohol use, drug use, tobacco use, gambling, binge eating, hypersexual behavior, and excessive video game playing. Data were collected at three time-points to develop a large pool of possible items, establish the initial factor structure and reduce the total item pool to 35 items, and confirm the factor structure as well as examine support for reliability and validity. Initial results provided some support for the purported factor structure, though some problems with fit were evident. Subsequent validation with an independent sample, provided strong support for the measure, including evidence of excellent fit for the factor structure and excellent internal consistency reliability. The measure was also positively correlated with several associated constructs, including depression, anxiety, trauma, and emotion dysregulation. Differences in the magnitude of the correlation between subscales and associated constructs were also evident. Overall, the evidence supports use of the instrument as a continuous measure of addictive behaviors. Future research is warranted to understand the validity of the measure in clinical samples and examine the accuracy for detecting with sensitivity and specificity those who do and do not meet criteria for a substance or other related addictive disorder.</p>"],"dc:identifier":["https://commons.emich.edu/theses/991"],"dc:subject":["Assessment","Behavioral Addictions","Measurement development","Substance use disorders","Transdiagnostic","Clinical Psychology"],"dc:title":["Recognizing addictive disorders through transdiagnostic assessment"],"thesis:degree_discipline":["Psychology"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T02:17:33Z"}