Aaron A Lee1, Rebecca K Sripada2, Andrew C Hale3, Dara Ganoczy2, Ranak B Trivedi4, Bruce Arnow4, Paul N Pfeiffer2. 1. Department of Psychology, University of Mississippi. 2. Veterans Affairs Center for Clinical Management Research, Veterans Affairs Ann Arbor Health Care System. 3. Department of Psychiatry, University of Michigan. 4. VA Center for Innovation to Implementation, VA Palo Alto Health Care System.
Abstract
Objective: Psychotherapy for depression is effective for many veterans, but the relationship between number of treatment sessions and symptom outcomes is not well established. The Dose-Effect model predicts that greater psychotherapeutic dose (total sessions) yields greater symptom improvement with each additional session resulting in smaller session-to-session improvement. In contrast, the Good-Enough Level (GEL) model predicts that rate of symptom improvement varies by total psychotherapeutic dose with faster improvement associated with earlier termination. This study compared the dose-effect and GEL model among veterans receiving psychotherapy for depression within the Veterans Health Administration. Method: The sample included 13,647 veterans with ≥2 sessions of psychotherapy for depression with associated Patient Health Questionnaire-9 (PHQ-9) scores in primary care (n = 7,502) and specialty mental health clinics (n = 6,145) between October 2014 and September 2018. Multilevel longitudinal modeling was used to compare the Dose-Effect and GEL models within each clinic type. Results: The GEL model demonstrated greater fit for both clinic types relative to dose-effect models. In both treatment settings, veterans with fewer sessions improved faster than those with more sessions. In primary care clinics, veterans who received 4-8 total sessions achieved similar levels of symptom response. In specialty mental health clinics, increased psychotherapeutic dose was associated with greater treatment response up to 16 sessions. Veterans receiving 20 sessions demonstrated minimal treatment response. Conclusions: These findings support the GEL model and suggest a flexible approach to determining length of psychotherapy for depression may be useful for optimizing treatment response and allocation of clinical resources. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Objective: Psychotherapy for depression is effective for many veterans, but the relationship between number of treatment sessions and symptom outcomes is not well established. The Dose-Effect model predicts that greater psychotherapeutic dose (total sessions) yields greater symptom improvement with each additional session resulting in smaller session-to-session improvement. In contrast, the Good-Enough Level (GEL) model predicts that rate of symptom improvement varies by total psychotherapeutic dose with faster improvement associated with earlier termination. This study compared the dose-effect and GEL model among veterans receiving psychotherapy for depression within the Veterans Health Administration. Method: The sample included 13,647 veterans with ≥2 sessions of psychotherapy for depression with associated Patient Health Questionnaire-9 (PHQ-9) scores in primary care (n = 7,502) and specialty mental health clinics (n = 6,145) between October 2014 and September 2018. Multilevel longitudinal modeling was used to compare the Dose-Effect and GEL models within each clinic type. Results: The GEL model demonstrated greater fit for both clinic types relative to dose-effect models. In both treatment settings, veterans with fewer sessions improved faster than those with more sessions. In primary care clinics, veterans who received 4-8 total sessions achieved similar levels of symptom response. In specialty mental health clinics, increased psychotherapeutic dose was associated with greater treatment response up to 16 sessions. Veterans receiving 20 sessions demonstrated minimal treatment response. Conclusions: These findings support the GEL model and suggest a flexible approach to determining length of psychotherapy for depression may be useful for optimizing treatment response and allocation of clinical resources. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Authors: Jason A Nieuwsma; Ranak B Trivedi; Jennifer McDuffie; Ian Kronish; Dinesh Benjamin; John W Williams Journal: Int J Psychiatry Med Date: 2012 Impact factor: 1.210
Authors: Ranak B Trivedi; Edward P Post; Haili Sun; Andrew Pomerantz; Andrew J Saxon; John D Piette; Charles Maynard; Bruce Arnow; Idamay Curtis; Stephan D Fihn; Karin Nelson Journal: Am J Public Health Date: 2015-10-16 Impact factor: 9.308
Authors: Frederic M Quitkin; Eva Petkova; Patrick J McGrath; Bonnie Taylor; Charles Beasley; Jonathan Stewart; Jay Amsterdam; Maurizio Fava; Jerrold Rosenbaum; Frederick Reimherr; Jan Fawcett; Ying Chen; Donald Klein Journal: Am J Psychiatry Date: 2003-04 Impact factor: 18.112
Authors: Rebecca K Sripada; Paul N Pfeiffer; Jessica Rampton; Dara Ganoczy; Sheila A M Rauch; Melissa A Polusny; Kipling M Bohnert Journal: J Trauma Stress Date: 2017-01-19
Authors: Paul N Pfeiffer; Kara Zivin; Avinash Hosanagar; Vanessa Panaite; Dara Ganoczy; H Myra Kim; Timothy Hofer; John D Piette Journal: J Behav Health Serv Res Date: 2022-10-07 Impact factor: 1.475