Treatment dropout among veterans and their families: Quantitative and qualitative findings.


Journal

Psychological trauma : theory, research, practice and policy
ISSN: 1942-969X
Titre abrégé: Psychol Trauma
Pays: United States
ID NLM: 101495376

Informations de publication

Date de publication:
May 2022
Historique:
pubmed: 29 9 2021
medline: 28 4 2022
entrez: 28 9 2021
Statut: ppublish

Résumé

Psychotherapy noncompletion rates for veterans and their families are high. This study sought to (a) measure noncompletion rates of such patients at a university-based treatment center, (b) compare veteran and family member attrition rates, (c) identify dropout predictors, and (d) explore clinicians' perspectives on treatment noncompletion. Using quantitative and qualitative approaches, we analyzed demographic and clinical characteristics of 141 patients (90 military veterans; 51 family members) in a university treatment center. We defined dropout as not completing the time-limited therapy contract. Reviewing semistructured interview data assessing clinicians' perspectives on their patients' dropout, three independent raters agreed on key themes, with interrater coefficient kappa range .74 to 1. Patient attrition was 24%, not differing significantly between veterans and family members. Diagnosis of major depression (MDD) and exposure-based therapies predicted noncompletion, as did higher baseline Hamilton Depression Rating Scale (HDRS) total scores, severe depression (HDRS > 20), lack of Beck Depression Inventory weekly improvement, and history of military sexual trauma. Clinicians mostly attributed noncompletion to patient difficulties coping with intense emotions, especially in exposure-based therapies. Noncompletion rate at this study appeared relatively low compared to other veteran-based treatment centers, if still unfortunately substantial. Patients with comorbid MDD/PTSD and exposure-based therapies carried greater noncompletion risk due to the MDD component, and this should be considered in treatment planning. Ongoing discussion of dissatisfaction and patient discontinuation, in the context of a strong therapeutic alliance, might reduce noncompletion in this at-risk population. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Sections du résumé

BACKGROUND BACKGROUND
Psychotherapy noncompletion rates for veterans and their families are high. This study sought to (a) measure noncompletion rates of such patients at a university-based treatment center, (b) compare veteran and family member attrition rates, (c) identify dropout predictors, and (d) explore clinicians' perspectives on treatment noncompletion.
METHOD METHODS
Using quantitative and qualitative approaches, we analyzed demographic and clinical characteristics of 141 patients (90 military veterans; 51 family members) in a university treatment center. We defined dropout as not completing the time-limited therapy contract. Reviewing semistructured interview data assessing clinicians' perspectives on their patients' dropout, three independent raters agreed on key themes, with interrater coefficient kappa range .74 to 1.
RESULTS RESULTS
Patient attrition was 24%, not differing significantly between veterans and family members. Diagnosis of major depression (MDD) and exposure-based therapies predicted noncompletion, as did higher baseline Hamilton Depression Rating Scale (HDRS) total scores, severe depression (HDRS > 20), lack of Beck Depression Inventory weekly improvement, and history of military sexual trauma. Clinicians mostly attributed noncompletion to patient difficulties coping with intense emotions, especially in exposure-based therapies.
CONCLUSION CONCLUSIONS
Noncompletion rate at this study appeared relatively low compared to other veteran-based treatment centers, if still unfortunately substantial. Patients with comorbid MDD/PTSD and exposure-based therapies carried greater noncompletion risk due to the MDD component, and this should be considered in treatment planning. Ongoing discussion of dissatisfaction and patient discontinuation, in the context of a strong therapeutic alliance, might reduce noncompletion in this at-risk population. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Identifiants

pubmed: 34582228
pii: 2021-86112-001
doi: 10.1037/tra0001109
pmc: PMC8924016
mid: NIHMS1738442
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

578-586

Subventions

Organisme : NIMH NIH HHS
ID : R01 MH131532
Pays : United States
Organisme : NIMH NIH HHS
ID : K01 MH118428
Pays : United States
Organisme : NIMH NIH HHS
ID : K01 MH122774
Pays : United States

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Auteurs

Doron Amsalem (D)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Andrea Lopez-Yianilos (A)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Ari Lowell (A)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Alison M Pickover (AM)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Shay Arnon (S)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Xi Zhu (X)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Benjamin Suarez-Jimenez (B)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Matt Ryba (M)

Department of Psychiatry, Columbia University Irving Medical Center.

Maja Bergman (M)

Department of Psychiatry, Columbia University Irving Medical Center.

Sara Such (S)

Department of Psychiatry, Columbia University Irving Medical Center.

Hemrie Zalman (H)

Department of Psychiatry, Columbia University Irving Medical Center.

Arturo Sanchez-Lacay (A)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Amit Lazarov (A)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

John C Markowitz (JC)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

Yuval Neria (Y)

New York State Psychiatric Institute, Columbia University Irving Medical Center.

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Classifications MeSH