This page contains a Flash digital edition of a book.
Handbook of Forensic Psychiatric Practice in Capital Cases


Different types of assessment approach/data gathering


Te history of risk assessment can be divided into stages, in terms of ‘generations’ of risk prediction, in that the discipline has moved though several periods of development, as follows:


• First generation: unstructured clinicians’ judgements, exhibiting low accuracy due to problems with a lack of consistency and agreement of method, resulting in a low inter-rater reliability, difficulty with the replication of the process by which any single judgment was reached, and a lack of empirical evidence concerning immediate or long-term validity


• Second generation: actuarial methods, with assessors reaching judgements based upon statistical information according to set rules, with criticisms including focusing the


assessment on a limited number of factors which are capable of measurement in populations; the exclusion of factors with face predictive validity; the minimising of the importance of case specific, idiosyncratic factors; and the exclusion of the role and input of clinical judgement and expertise, thereby paralysing/undermining clinicians


• Tird generation: a move directly to risk management and prevention, in conjunction with identifying conditions under which risk will increase or decrease, this being criticised in


terms that it does not allow the identification of specific probability or absolute likelihood estimates of individual future risk with any reasonable degree of scientific or professional certainty


• Fourth generation: structured clinical judgment, which includes evidence-based practice (taking the best evidence from the research, as already achieved in the case of the


development of actuarial tools) and practice based evidence (using clinical judgment plus the appropriate use of actuarial information, so as to present a clear and globally informed opinion)


Actuarial assessment


Although risk assessment resides ultimately in the individual, it is still important to identify factors that are known to both increase and decrease the violence occurring in populations of individuals.


Statistical research has sought to identify, through statistical mapping, the factors that are related to the risk of violence. In general, such an approach appears to offer greater reliability and validity than unstructured clinical assessment of risk in the individual. However, the number and type of variables that are measurable in populations are very limited, and are also limited almost entirely to variables which are ‘historical’; actuarial techniques are of very little use in terms of reducing risk in the individual.


Also, most studies conducted in order to gain data are not ‘community’ studies but studies of skewed populations, such as prisoners (within which the rate of mental disorder is measured) or mental hospital patients (within which the rate of violence is measured).


Any clinician utilising such data in the form of actuarial risk assessments must make themselves aware of the base rates for offending behaviours upon which the scales are based, whether samples are from specific groups or from more general populations, and whether the scale is used for only one type of behaviour. Te following risk assessments are examples of actuarial tools:


52


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140  |  Page 141  |  Page 142  |  Page 143  |  Page 144  |  Page 145  |  Page 146  |  Page 147  |  Page 148  |  Page 149  |  Page 150  |  Page 151  |  Page 152  |  Page 153  |  Page 154  |  Page 155  |  Page 156