Risk for psychotherapy drop-out in survival analysis: The influence of general change mechanisms and symptom severity.

2020 ◽  
Vol 67 (6) ◽  
pp. 712-722
Author(s):  
Sebastian Gmeinwieser ◽  
Kai Sebastian Schneider ◽  
Maximilian Bardo ◽  
Timo Brockmeyer ◽  
York Hagmayer
Keyword(s):  
Survival Analysis ◽  
Symptom Severity ◽  
Drop Out ◽  
General Change ◽  
Change Mechanisms

Validation predicting premature drop-out from treatment provided in training clinics

2019 ◽  
Vol 48 (1) ◽  
pp. 116-120
Author(s):  
Kristen P. Howard ◽  
Erin M. Altenburger ◽  
Jennifer S. Cheavens
Keyword(s):  
Symptom Severity ◽  
Drop Out ◽  
Self Report ◽  
Positive Outcomes ◽  
Client Perceptions ◽  
Therapist Experience ◽  
Cognitive Behavioural ◽  
Trainee Therapists ◽  
Training Clinics

AbstractBackground:Therapist validation in treatment is theorized to be related to positive outcomes (Linehan, 1993), including keeping patients in therapy longer.Aims:We sought to evaluate the role of therapist validation from both therapists’ and clients’ perspectives as a predictor of drop-out from psychotherapy in three cognitive behavioural training clinics.Method:Clients in psychotherapy (n = 50; 80% female; 82% Caucasian) and their trainee therapists (n = 22; 68% female; 86% Caucasian) rated validation by the therapist at each of four early sessions of therapy.Results:After accounting for symptom severity, clients who reported greater therapist validation were less likely to drop out of treatment. Therapist ratings of their own validating behaviours were unrelated to client drop-out. Therapist experience moderated the relation between client-rated validation and drop-out, such that validation was unrelated to drop-out for more experienced therapists.Conclusions:Assessing and attending to client perceptions of validation by the therapist early in treatment, with brief self-report inventories, can alert therapists to clients at greater risk of drop-out.

scholarly journals Effects of Different Types of Progress Indicators on Drop-Out Rates in Web Surveys

2009 ◽  
Vol 40 (1) ◽  
pp. 43-52 ◽  
Author(s):  
Uwe Matzat ◽  
Chris Snijders ◽  
Wouter van der Horst
Keyword(s):  
Survival Analysis ◽  
Completion Rate ◽  
Drop Out ◽  
Web Survey ◽  
Web Surveys ◽  
Different Types ◽  
Online Access ◽  
Drop Out Rates

The present study analyzes whether and how different types of progress indicators affect the tendency of respondents to continue filling out a web survey, focusing on whether the progress indicators’ effects depend on the position of the respondent in the questionnaire. Using a sample of 2460 respondents of a Dutch online access panel, we analyze three kinds of progress indicators (linear, fast-then-slow, slow-then-fast, and a control condition) using survival analysis. The results show that the effect of the indicators on the completion rate is either negative or nonexistent, depending on the questionnaire length. Moreover, the effect of an indicator does not depend on the position of the respondent in the answering process. We interpret our findings in terms of the implicit narrative between survey designer and respondent.

Opiate Withdrawal Symptoms in Response to 10-Day and 21-Day Methadone Withdrawal Programmes

1989 ◽  
Vol 154 (3) ◽  
pp. 360-363 ◽  
Author(s):  
Michael Gossop ◽  
Paul Griffiths ◽  
Brendan Bradley ◽  
John Strang
Keyword(s):  
Symptom Severity ◽  
Drop Out ◽  
Withdrawal Symptoms ◽  
Opiate Withdrawal ◽  
Drop Out Rate ◽  
Oral Methadone ◽  
Opiate Addicts ◽  
Withdrawal Phase

This study investigates and compares the responses of 132 opiate addicts to a 10-day or a 21-day in-patient oral methadone withdrawal regime. For both groups, symptom severity (on the Opiate Withdrawal Scale) steadily increased through the methadone withdrawal phase, and peaked near the point of completion of the prescribed drug, declining slowly thereafter. Patients on the 10-day programme reported significantly higher peak withdrawal scores than those on the 21-day programme. Although the proportions who completed detoxification were similar, there was a significantly higher drop-out rate immediately after detoxification for the 10-day group. The possible benefits and handicaps of the two withdrawal schedules are considered and recommendations are proposed for further refinement of the present widely adopted approach.

Stayin' Alive: An Introduction to Survival Analysis

1995 ◽  
Vol 40 (8) ◽  
pp. 439-444 ◽  
Author(s):  
David L Streiner
Keyword(s):  
Survival Analysis ◽  
Manic Episode ◽  
Drop Out

In some studies, the outcome of interest is the time until some event occurs: readmission to hospital, the next manic episode, or even death. Survival analysis is a techique which can be used to analyze such data. It has added usefulness because it allows us to use data from subjects who drop out of sight over the course of the follow-up period as well as from those who do not experience the event by the time the study ends. This article introduces this technique and provides some guidelines for designing follow-up trials.

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