Invalidity of “Disconfirmation of the Predictive Validity of the Self-Appraisal Questionnaire in a Sample of High-Risk Drug Offenders” (2006)

2007 ◽  
Vol 22 (8) ◽  
pp. 1077-1089 ◽  
Author(s):  
Gurmeet K. Dhaliwal ◽  
Wagdy Loza ◽  
John R. Reddon
1987 ◽  
Vol 14 (1) ◽  
pp. 33-37 ◽  
Author(s):  
D. A. ANDREWS ◽  
WALTER FRIESEN

These notes place an important limitation on the conclusions drawn by Friesen and Andrews (1982) regarding the predictive validity of a measure of the inprogram self-regulation efforts of 42 young-adult probationers. In the earlier report, assessments of self-regulation were found to be reliable (interrater r(20) = .96) and they correlated with intake socialization scores ( r(42) = .38), and with reconvictions monitored from the start of probation to the end of three postprobation years ( r(42) = -.38). The present note shows that the predictive validity of the self-regulation scores was only evident among high-risk cases: The correlation was -.70 with the recidivism of 19 low-socialization cases compared with -.02 among 23 high-socialization probationers. The results are discussed in relation to the risk principle of case classification.


2001 ◽  
Vol 27 (2) ◽  
pp. 281-299 ◽  
Author(s):  
Steve Sussman ◽  
Susan L. Ames ◽  
Clyde W. Dent ◽  
Alan W. Stacy
Keyword(s):  
Drug Use ◽  

2000 ◽  
Vol 15 (11) ◽  
pp. 1183-1191 ◽  
Author(s):  
WAGDY LOZA ◽  
AMEL LOZA-FANOUS
Keyword(s):  

2011 ◽  
Vol 271-273 ◽  
pp. 1049-1052
Author(s):  
Yong Cheng Wu

Sports insurance originates in the nature of sports-high risk, and its basic position in the sports industry is determined by its particularity. However, sports insurance in China is only limited to high-risk competitive sports. School sports insurance is still in the development stage. The self-construction of sports insurance and insurance codes are imperfect with few sectors. What’s more, because of weak insurance consciousness of schools and students, unavoidable sports accidents take great pressure to the school, family and the student, which make an impact on the normal operation of schools. Thus it is necessary and urgent to build up and perfect school sports insurance.


1996 ◽  
Vol 39 ◽  
pp. 18-18
Author(s):  
M. Marie Kim ◽  
Kathleen O'Connor ◽  
Jennifer McLean ◽  
Ann Robson ◽  
Francine Macinnis ◽  
...  

2021 ◽  
Author(s):  
◽  
Morgan K.A. Sissons

<p>Personality disorders are common among high-risk offenders. These disorders may have relevance for their risk of offending, and they are likely to present barriers to their engagement in rehabilitation programmes. Co-morbidity between personality disorders - and the high frequency of clinical disorders in general - in offender samples complicate research on personality disorder in offender rehabilitation. One approach to understanding this heterogeneity is to use cluster analysis (CA). CA is an empirical strategy which is used to identify subgroups (clusters) of individuals who have similar scores on the variables used in the analysis. It has been used to empirically identify different patterns of personality and clinical psychopathology among incarcerated offenders. Two profiles frequently emerge in cluster analytic research on offender psychopathology profiles: an antisocial/narcissistic profile and a high-psychopathology profile. However, previous research has not empirically examined whether the identification of these profiles has clinical relevance for offender rehabilitation; that is, whether the profiles are simply descriptive, or whether they can provide useful information for the management and rehabilitation of offenders.  In the current research, I used data collected from high risk offenders entering prison-based rehabilitation programmes to investigate the clinical utility of psychopathology clusters. Using a self-report measure of personality and clinical psychopathology - the Millon Clinical Multiaxial Inventory III - I identified three clusters: a low-psychopathology cluster (26% of the sample), a high-psychopathology cluster (35% of the sample), and an antisocial/narcissistic cluster (39% of the sample). The high-psychopathology and antisocial/narcissistic clusters in particular resembled high risk clusters found in previous research.  To determine whether the three clusters had clinical relevance, I investigated cluster differences in criminal risk, treatment responsivity, and self-report predictive validity. I found evidence for cluster differences in criminal risk: men in the high-psychopathology and antisocial/narcissistic clusters had higher rates of criminal recidivism after release compared to men in the low-psychopathology cluster. However, I found that regardless of psychopathology, men in all three clusters made progress in treatment, and there was little evidence that clusters that reported more psychopathology were less engaged, or made less progress. In the final study I examined cluster differences in self-presentation style and the predictive validity of self-report. Results indicated that offenders who reported high levels of psychopathology had a more general tendency for negative self-presentation, and their self-report on risk-related measures was highly predictive of criminal recidivism.  Combined, the results of this research show that cluster analysis of self-reported psychopathology can generate a parsimonious model of heterogeneity in offender samples. Importantly, the resulting clusters can also provide information for some of the most important tasks in offender management: assessment and treatment. The results suggest the highest risk offenders tend to report higher levels of psychopathology, and that offenders who report extensive psychopathology also have highly predictive risk-related self-report. Perhaps one of the most reassuring findings of the current research is that even offenders who report high levels of psychopathology appear to benefit from rehabilitation.</p>


2013 ◽  
Vol 5 (1) ◽  
pp. 14-20 ◽  
Author(s):  
Grace Milad ◽  
Saria Izzeldin ◽  
Fahmida Tofail ◽  
Tahmeed Ahmed ◽  
Maliha Hakim ◽  
...  

CORRECTION: The following authors were added to this paper on 11/10/2013: Grace Milad; Saria Izzeldin; Tahmeed Ahmed; William A. Petri.The author Mohammad Ibrahim Khalil was changed to Ibrahim KhalilBackground: Maternal depression has been found to be associated with increased diarrheal incidence and childhood malnutrition. Objective: The purpose of the present study was to observe whether the Self- Reporting Qustinative (SRQ-20) questionnaire was sensitive enough to pick-up the depressive symptoms of mothers in the urban slum community. Methodology: This was a pilot study in a Dhaka Shantytown and women were interviewed to examine the relationship between maternal depression and their children's diarrheal morbidity. In addition to other socio-demographic information, the Self-Reporting Questionnaire (SRQ-20) was used to screen for maternal depression. Result: A total number of 55 women were interviewed to examine fifty-one percent of mothers scored within the high-risk psycho-morbidity group, suggesting depression. High SRQ scores significantly correlated with poor marital relationships (Regression coefficient ± standard error =-0.624+0.225, p=0.008; 95%CI:-1.076, -0.172). High-risk mothers breastfed for a shorter duration than low-risk mothers (3.4 vs. 4.4 months, p=0.35) and their children had more diarrheal episodes (2 episodes vs. 1, p=0.18), although these differences did not show statistical significance. Conclusion: Depression is common among mothers in urban slums and that a well-designed large study is required to further explore the provocative relationship between maternal depression and child diarrhea with subsequent malnutrition to improve the quality of life of those at risk. DOI: http://dx.doi.org/10.3329/jssmc.v5i1.16199 J Shaheed Suhrawardy Med Coll, 2013;5(1):14-20


1997 ◽  
Vol 34 (2) ◽  
pp. 286-291 ◽  
Author(s):  
V. Srinivasan ◽  
Chan Su Park

The authors introduce customized conjoint analysis, which combines self-explicated preference structure measurement with full-profile conjoint analysis. The more important attributes for each respondent are identified first using the self-explicated approach. Full-profile conjoint analysis customized to the respondent's most important attributes then is administered. The conjoint utility function on the limited set of attributes then is combined with the self-explicated utility function on the full set of attributes. Surprisingly, the authors find that the self-explicated approach by itself yields a slightly (but not statistically significantly) higher predictive validity than does the combined approach.


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