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Introduction to Clinical Psychology Science, Practice and Ethics Chapter 5 General Issues in Psychological Assessment This multimedia product and its contents.

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Presentation on theme: "Introduction to Clinical Psychology Science, Practice and Ethics Chapter 5 General Issues in Psychological Assessment This multimedia product and its contents."— Presentation transcript:

1 Introduction to Clinical Psychology Science, Practice and Ethics Chapter 5 General Issues in Psychological Assessment This multimedia product and its contents are protected under copyright law. The following are prohibited by law: Any public performance or display, including transmission of any image over a network; Preparation of any derivative work, including the extraction, in whole or in part, of any images; Any rental, lease, or lending of the program Copyright ©Allyn & Bacon 2005

2 Stages of Psychological Assessment  Stage I: Planning the Assessment  Stage II: Data Collection  Stage III: Processing Assessment Data  Stage IV: Communicating Assessment Findings Copyright ©Allyn & Bacon 2005

3 Goals of Psychological Assessment  Classification  Description  Prediction

4 Copyright ©Allyn & Bacon 2005 Classification  Diagnoses DSM-IV  Criticisms of Diagnoses Implies understanding Association with medical model Variable reliability Negative social stigma

5 Copyright ©Allyn & Bacon 2005 Diagnoses: Responses to Criticisms  Categorization facilitates research  Diagnostic labels can facilitate treatment  Diagnostic labels can facilitate communication

6 Copyright ©Allyn & Bacon 2005 Description  Dimensional (as opposed to categorical)  Person by situation  Generates research hypotheses  Facilitate treatment planning  Evaluate treatment outcome

7 Copyright ©Allyn & Bacon 2005 Prediction  Prediction terms: True positive False positive True negative False negative Sensitivity Specificity

8 Copyright ©Allyn & Bacon 2005 Prediction  The Base Rate Problem Low base rate problems are difficult to predict Low base rate problems tend to be overpredicted (many false positives)  Clinical versus Statistical prediction

9 Copyright ©Allyn & Bacon 2005 Clinical versus Statistical Approaches  Clinical (or subjective) method – clinician constructs a model to explain client’s behavior and predict future behavior  Statistical (or quantitative or actuarial) – people are classified based upon the characteristics they share with others. They are expected to behave the way similarly classified people behave

10 Copyright ©Allyn & Bacon 2005 Clinical versus Statistical Approaches  Paul Meehl (1954) Clinical versus Statistical Prediction: A Theoretical Analysis and Review of the Literature “in all but one…the predictions made actuarially were either equal to or superior to those made by the clinician”  Jack Sawyer (1966) Statistical superior to clinical approach to prediction Clinicians could not improve upon actuarial prediction

11 Copyright ©Allyn & Bacon 2005 Responses to Statistical Superiority  Methodologically weak studies  Not Expert Judges  Findings not cross-validated  Poor Ecological Validity

12 Copyright ©Allyn & Bacon 2005 Counter-arguments  Methodologically weak studies Methodologically weak and strong studies yield consistent findings (actuarial > clinical  Not Expert Judges But those that did yield use expert judges yielded the same findings (actuarial > clinical)  Findings not cross-validated But those that did cross-validate yielded the same findings (actuarial > clinical)  Poor Ecological Validity But the tasks are not meaningless

13 Copyright ©Allyn & Bacon 2005 Recent Review  Meehl (1957, 1965, 1986)  Dawes, Faust, & Meehl (1989) – reviewed close to 100 studies – actuarial equal to or superior to clinical in every one.  Dawes (1994) House of Cards: Psychology and Psychotherapy Built on Myth  Milner & Campbell (1995) – “ The consensus of opinion is that statistical prediction is more accurate than clinical prediction”

14 Copyright ©Allyn & Bacon 2005 Clinical Approach: Current Status  Clinical approach is necessary in situations for which no statistical equations have been developed.  Unforeseen circumstances impair the efficiency of the formula.  Rare, unusual events of highly individualized nature are to be predicted.  Clinician as data-gatherer

15 Copyright ©Allyn & Bacon 2005 Stage II: Data Collection  Interviews  Norm-referenced tests  Observations  Informal assessment methods  Life records

16 Copyright ©Allyn & Bacon 2005 Stage III: Processing  Clinical Judgment  Computer assisted assessment

17 Copyright ©Allyn & Bacon 2005 Clinical Judgment: Threats to Accuracy  Preconceived Notions  Confirmation Bias  Hindsight Bias  Overconfidence Recall successes Only examining certain types of cases Self-fulfilling prophecy

18 Copyright ©Allyn & Bacon 2005 Reducing Impact of Biases  Search for alternative explanations  Understand the impact of base rates  Decrease reliance on memory

19 Copyright ©Allyn & Bacon 2005 Computer-assisted assessment  Professional time savings  Test administration consistency  Rapid turnaround time  Scoring accuracy  Data analysis  Special populations

20 Copyright ©Allyn & Bacon 2005 Communicating Assessment Findings  Goals Address the referral question Improve understanding Impact client Provide a written record A legal document

21 Copyright ©Allyn & Bacon 2005 Communicating Assessment Findings  Include all relevant information  Delete irrelevant or damaging information  Avoid undue generalizations  Use behavioural referents  Communicate clearly  Eliminate biased terms

22 Copyright ©Allyn & Bacon 2005 Communicating Assessment Findings  Identifying Information  Reason for Referral  Background Information  Behavioural Observations  Assessment Results and Interpretation  Summary  Recommendations


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