The current study examined the diverse ways individuals with co-occurring Posttraumatic Stress Disorder and Substance Use Disorders (PTSD-SUD) attend treatment. The study was a secondary analysis of a randomized controlled trial for PTSD-SUD (Ruglass et al., 2017), in which participants meeting criteria for both PTSD and SUD (N=82) were randomized to either Concurrent Treatment of PTSD and SUD using Prolonged Exposure (COPE: n=39) or Relapse Prevention Therapy (RPT: n=43). Latent class growth analysis (Muthén & Muthén, 2000) revealed three distinct classes of attendance as the model of best fit. Diagnostic, but not demographic, variables were significantly associated with treatment attendance patterns. Namely, the number of trauma exposures and the presence of co-occurring Major Depressive Disorder (MDD) were associated with attendance patterns. Titrators (n=26) were more likely to have multiple traumas compared to those subjects who were droppers (n=26), the participants who attended the fewest overall sessions. Titrators (n=26) were more likely to have current MDD than completers (n=30). In the initial treatment phase (baseline – session 4), self-report of PTSD symptom severity decreased more quickly for titrators (n=26) than for completers (n=30). There were no significant differences within the initial treatment phase in terms of substance use among completers and titrators; frequency or type of substance use was not predictive of attendance class in this sample of those with PTSD-SUD. Finally, the distribution of attendance class patterns did not vary across treatment types, COPE or RPT. Understanding the heterogeneity of those with PTSD-SUD including the relationship between variables that describe this diversity and attendance irregularities may improve treatment engagement and effectiveness on an individual and programmatic level, as well as facilitate appropriate resource allocation. Future efforts to clarify the relationship between baseline patient characteristics, treatment attendance patterns, rates of improvement and psychotherapy outcomes may offer support for treatment delivery models of increased flexibility and individualization.
","abstract_html":"<p>The current study examined the diverse ways individuals with co-occurring Posttraumatic Stress Disorder and Substance Use Disorders (PTSD-SUD) attend treatment. The study was a secondary analysis of a randomized controlled trial for PTSD-SUD (Ruglass et al., 2017), in which participants meeting criteria for both PTSD and SUD (N=82) were randomized to either Concurrent Treatment of PTSD and SUD using Prolonged Exposure (COPE: n=39) or Relapse Prevention Therapy (RPT: n=43). Latent class growth analysis (Muthén & Muthén, 2000) revealed three distinct classes of attendance as the model of best fit. Diagnostic, but not demographic, variables were significantly associated with treatment attendance patterns. Namely, the number of trauma exposures and the presence of co-occurring Major Depressive Disorder (MDD) were associated with attendance patterns. <em>Titrators</em> (n=26) were more likely to have multiple traumas compared to those subjects who were <em>droppers (n=26)</em>, the participants who attended the fewest overall sessions. T<em>itrators</em> (n=26) were more likely to have current MDD than <em>completers (n=30)</em>. In the initial treatment phase (baseline – session 4), self-report of PTSD symptom severity decreased more quickly for <em>titrators (n=26) </em>than for <em>completers (n=30)</em>. There were no significant differences within the initial treatment phase in terms of substance use among <em>completers </em>and <em>titrators</em>; frequency or type of substance use was not predictive of attendance class in this sample of those with PTSD-SUD. Finally, the distribution of attendance class patterns did not vary across treatment types, COPE or RPT. Understanding the heterogeneity of those with PTSD-SUD including the relationship between variables that describe this diversity and attendance irregularities may improve treatment engagement and effectiveness on an individual and programmatic level, as well as facilitate appropriate resource allocation. Future efforts to clarify the relationship between baseline patient characteristics, treatment attendance patterns, rates of improvement and psychotherapy outcomes may offer support for treatment delivery models of increased flexibility and individualization.</p>","abstract_has_math":false,"creators":["Rauen, Margaret"],"institution":"The Graduate School and University Center of The City University of New York","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":[],"advisors":["Denise Hien"],"committee_chairs":[],"committee_members":["Deidre Anglin (chair)","Lesia Ruglass","Teresa Lopez-Castro","Diana Punales Morejon"],"year":2017,"date_issued":"2017-09-01T07:00:00Z","date_published":"2017-09-01T07:00:00Z","updated_at":"2026-07-24T01:59:14Z","subjects":["Clinical Psychology","posttraumatic stress disorder","substance use disorder","dropout","attrition","psychotherapy","prolonged exposure"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/gc_etds/2388","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Denise Hien"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Deidre Anglin (chair)","Lesia Ruglass","Teresa Lopez-Castro","Diana Punales Morejon"]},{"key":"dc:creator","label":"Author","values":["Rauen, Margaret"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-03-30T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The Graduate School and University Center of The City University of New York"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Clinical Psychology","posttraumatic stress disorder","substance use disorder","dropout","attrition","psychotherapy","prolonged exposure"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/gc_etds/2388"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The current study examined the diverse ways individuals with co-occurring Posttraumatic Stress Disorder and Substance Use Disorders (PTSD-SUD) attend treatment. The study was a secondary analysis of a randomized controlled trial for PTSD-SUD (Ruglass et al., 2017), in which participants meeting criteria for both PTSD and SUD (N=82) were randomized to either Concurrent Treatment of PTSD and SUD using Prolonged Exposure (COPE: n=39) or Relapse Prevention Therapy (RPT: n=43). Latent class growth analysis (Muthén & Muthén, 2000) revealed three distinct classes of attendance as the model of best fit. Diagnostic, but not demographic, variables were significantly associated with treatment attendance patterns. Namely, the number of trauma exposures and the presence of co-occurring Major Depressive Disorder (MDD) were associated with attendance patterns. Titrators (n=26) were more likely to have multiple traumas compared to those subjects who were droppers (n=26), the participants who attended the fewest overall sessions. Titrators (n=26) were more likely to have current MDD than completers (n=30). In the initial treatment phase (baseline – session 4), self-report of PTSD symptom severity decreased more quickly for titrators (n=26) than for completers (n=30). There were no significant differences within the initial treatment phase in terms of substance use among completers and titrators; frequency or type of substance use was not predictive of attendance class in this sample of those with PTSD-SUD. Finally, the distribution of attendance class patterns did not vary across treatment types, COPE or RPT. Understanding the heterogeneity of those with PTSD-SUD including the relationship between variables that describe this diversity and attendance irregularities may improve treatment engagement and effectiveness on an individual and programmatic level, as well as facilitate appropriate resource allocation. Future efforts to clarify the relationship between baseline patient characteristics, treatment attendance patterns, rates of improvement and psychotherapy outcomes may offer support for treatment delivery models of increased flexibility and individualization.
"]},{"key":"dc:title","label":"Title","values":["Making Sense of Missing Sessions: Attendance Patterns in Posttraumatic Stress Disorder and Substance Use Disorder Treatments"]}]}],"canonical_facts":{"dc:contributor.advisor":["Denise Hien"],"dc:contributor.committeemember":["Deidre Anglin (chair)","Lesia Ruglass","Teresa Lopez-Castro","Diana Punales Morejon"],"dc:creator":["Rauen, Margaret"],"dc:date.available":["2018-03-30T07:00:00Z"],"dc:description.abstract":["The current study examined the diverse ways individuals with co-occurring Posttraumatic Stress Disorder and Substance Use Disorders (PTSD-SUD) attend treatment. The study was a secondary analysis of a randomized controlled trial for PTSD-SUD (Ruglass et al., 2017), in which participants meeting criteria for both PTSD and SUD (N=82) were randomized to either Concurrent Treatment of PTSD and SUD using Prolonged Exposure (COPE: n=39) or Relapse Prevention Therapy (RPT: n=43). Latent class growth analysis (Muthén & Muthén, 2000) revealed three distinct classes of attendance as the model of best fit. Diagnostic, but not demographic, variables were significantly associated with treatment attendance patterns. Namely, the number of trauma exposures and the presence of co-occurring Major Depressive Disorder (MDD) were associated with attendance patterns. Titrators (n=26) were more likely to have multiple traumas compared to those subjects who were droppers (n=26), the participants who attended the fewest overall sessions. Titrators (n=26) were more likely to have current MDD than completers (n=30). In the initial treatment phase (baseline – session 4), self-report of PTSD symptom severity decreased more quickly for titrators (n=26) than for completers (n=30). There were no significant differences within the initial treatment phase in terms of substance use among completers and titrators; frequency or type of substance use was not predictive of attendance class in this sample of those with PTSD-SUD. Finally, the distribution of attendance class patterns did not vary across treatment types, COPE or RPT. Understanding the heterogeneity of those with PTSD-SUD including the relationship between variables that describe this diversity and attendance irregularities may improve treatment engagement and effectiveness on an individual and programmatic level, as well as facilitate appropriate resource allocation. Future efforts to clarify the relationship between baseline patient characteristics, treatment attendance patterns, rates of improvement and psychotherapy outcomes may offer support for treatment delivery models of increased flexibility and individualization.
"],"dc:identifier":["https://academicworks.cuny.edu/gc_etds/2388"],"dc:subject":["Clinical Psychology","posttraumatic stress disorder","substance use disorder","dropout","attrition","psychotherapy","prolonged exposure"],"dc:title":["Making Sense of Missing Sessions: Attendance Patterns in Posttraumatic Stress Disorder and Substance Use Disorder Treatments"],"thesis:degree_discipline":["Psychology"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["The Graduate School and University Center of The City University of New York"]},"updated_at":"2026-07-24T01:59:14Z"}