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Predictors of treatment failure in a...

Lindahl, Virginia H.

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Predictors of treatment failure in an alternative community treatment program.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predictors of treatment failure in an alternative community treatment program./
Author:	Lindahl, Virginia H.
Description:	73 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-11, Section: B, page: 5790.
Contained By:	Dissertation Abstracts International64-11B.
Subject:	Psychology, Clinical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3111597
ISBN:	0496591274

Predictors of treatment failure in an alternative community treatment program.
Lindahl, Virginia H.

Predictors of treatment failure in an alternative community treatment program. - 73 p.

Source: Dissertation Abstracts International, Volume: 64-11, Section: B, page: 5790.

Thesis (Ph.D.)--The Catholic University of America, 2004.

In recent years, the tendency to hospitalize all severely mentally ill patients in acute crisis has been reconsidered in favor of more cost-effective, community-based programs. One type of program, referred to crisis residential treatment, offers effective short-term, acute care to patients who would otherwise be voluntarily admitted to an inpatient psychiatric unit. In triage settings, clinicians regularly consider whether traditional inpatient care or crisis residential treatment is more appropriate, but without the benefit of empirical research as to which patients are most likely to fail in these programs. The present study used exploratory research methods to develop a profile of these patients and then tested the predictive power of that profile on a validation subsample. Both models used five potential predictor variables: current age, age at onset, current employment status, number of hospitalizations over the lifetime, and presence of thought disorder. Of the two models developed during the exploratory phase of the study, discriminant function analysis resulted in a non-statistically significant equation that was nonetheless able to account for 19% of the variance between the "success" group and the "failure" group. The second analysis used logistic regression and resulted in a statistically significant equation predicting group membership. The model correctly classified 100% of participants in the failure group and 86.4% of participants in the success group, for an overall correct classification rate of 91.7%. When the logistic regression model was tested on the validation subsample, it was able to correctly classify 80% of the participants in the failure group and 93.3% of the participants in the success group, for an overall correct classification rate of 90.0%. Individual predictors were not significant in any of the three models. This investigation suggests that highly predictive multivariate models of failure in crisis residential treatment programs can be developed using variables already routinely assessed by clinicians. The theoretical and clinical implications of these findings are discussed and areas for future research are highlighted.

ISBN: 0496591274Subjects--Topical Terms:

524864
Psychology, Clinical.

Predictors of treatment failure in an alternative community treatment program.
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245 1 0 $a Predictors of treatment failure in an alternative community treatment program.
300 $a 73 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-11, Section: B, page: 5790.
500 $a Director: David A. Jobes.
502 $a Thesis (Ph.D.)--The Catholic University of America, 2004.
520 $a In recent years, the tendency to hospitalize all severely mentally ill patients in acute crisis has been reconsidered in favor of more cost-effective, community-based programs. One type of program, referred to crisis residential treatment, offers effective short-term, acute care to patients who would otherwise be voluntarily admitted to an inpatient psychiatric unit. In triage settings, clinicians regularly consider whether traditional inpatient care or crisis residential treatment is more appropriate, but without the benefit of empirical research as to which patients are most likely to fail in these programs. The present study used exploratory research methods to develop a profile of these patients and then tested the predictive power of that profile on a validation subsample. Both models used five potential predictor variables: current age, age at onset, current employment status, number of hospitalizations over the lifetime, and presence of thought disorder. Of the two models developed during the exploratory phase of the study, discriminant function analysis resulted in a non-statistically significant equation that was nonetheless able to account for 19% of the variance between the "success" group and the "failure" group. The second analysis used logistic regression and resulted in a statistically significant equation predicting group membership. The model correctly classified 100% of participants in the failure group and 86.4% of participants in the success group, for an overall correct classification rate of 91.7%. When the logistic regression model was tested on the validation subsample, it was able to correctly classify 80% of the participants in the failure group and 93.3% of the participants in the success group, for an overall correct classification rate of 90.0%. Individual predictors were not significant in any of the three models. This investigation suggests that highly predictive multivariate models of failure in crisis residential treatment programs can be developed using variables already routinely assessed by clinicians. The theoretical and clinical implications of these findings are discussed and areas for future research are highlighted.
590 $a School code: 0043.
650 4 $a Psychology, Clinical. $3 524864
650 4 $a Health Sciences, Mental Health. $3 1017693
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710 2 0 $a The Catholic University of America. $3 1019220
773 0 $t Dissertation Abstracts International $g 64-11B.
790 1 0 $a Jobes, David A., $e advisor
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791 $a Ph.D.
792 $a 2004
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3111597