Reliability and validity of the dynamic risk outcome scales-short version for clients with mild intellectual disabilities or borderline intellectual functioning.

INTRODUCTION: This study investigated the reliability and validity of the dynamic risk outcome scales-short version (DROS-SV). This instrument is developed to monitor treatment progress using dynamic risk factors in clients with mild intellectual disabilities or borderline intellectual functioning and behavioural and/or mental health problems. METHOD: Data were collected from 264 clients who received Flexible Assertive Community Treatment (FACT), a form of intensive outpatient treatment. RESULTS: A principal component analysis showed that there were six components explaining 73.9% of the variance. Furthermore, the DROS-SV showed good internal consistency of its subscales and total score (α > 0.78). Correlating the DROS-SV with the Historical and Clinical subscales of the Historical, Clinical and Future-30 indicated convergent and divergent validity. DISCUSSION: The DROS-SV has good psychometric properties for measuring dynamic risk factors in clients with mild intellectual disabilities or borderline intellectual functioning in FACT teams.

The predictive value of the dynamic risk outcome scales (DROS) for recidivism in (forensic) clients with mild intellectual disabilities or borderline intellectual functioning.

BACKGROUND: The dynamic risk outcome scales (DROS) was developed to assess treatment progress of clients with mild intellectual disability or borderline intellectual functioning using dynamic risk factors. We studied the predictive value of the DROS on various classifications and severity levels of recidivism. METHOD: Data of 250 forensic clients with intellectual disabilities were linked to recidivism data from the Judicial Information Service in the Netherlands. Receiver operating characteristics (ROC) analyses were used to determine the predictive values. RESULTS: The DROS total score could not significantly predict recidivism. A DROS recidivism subscale predicted general, violent and other recidivism. These predictive values were comparable to those of a Dutch tool validated for risk assessment in the general forensic population. CONCLUSIONS: The DROS recidivism subscale predicted various classifications of recidivism better than chance. At present, the DROS appears to have no added value beyond the HKT-30 for the purpose of risk assessment.

[The predictive value of the Dynamic Risk Outcome Scales (DROS) for predicting recidivism in (forensic) patients with mild intellectual disabilities or borderline intellectual functioning]. / De voorspellende waarde van de Dynamic Risk Outcome Scales (DROS) voor recidive bij (forensische) patiënten met een lichte verstandelijke beperking.

BACKGROUND: The Dynamic Risk Outcome Scales (DROS) was developed to assess treatment progress of patients with mild intellectual disability (MID) or borderline intellectual functioning (BIF) and severe behavioral and/or psychiatric problems. Because of the focus on dynamic risk factors, practitioners also see this instrument as a tool for risk assessment.
AIM: To investigate the predictive value of the DROS on different classifications and severities of recidivism.
METHOD: DROS data from the routine outcome monitoring (ROM) of 250 forensic patients with MID-BIF who were discharged between 2007 and end of 2014 were linked to recidivism data from the Judicial Information Service.
RESULTS: The DROS total score predicted general, violence and sexual recidivism better than chance (AUCs > 0.58), although the effect was small. A DROS-recidivism subscale predicted general, violence and other recidivism with a medium to large effect (AUCs > 0.67). The predictive values of the DROS total score and DROS-recidivism subscale were comparable to those of the Historic, Clinical, Future (in Dutch: HKT)-30.
CONCLUSION: The DROS total score and DROS-recidivism subscale predict different classifications of recidivism better than chance. However, for risk assessment the DROS appears to have no added value to the HKT-30.

Evolution of the primary and secondary structures of the E1a mRNAs of the adenovirus.

In this paper we investigate and compare (evolutionary) patterns in the primary and secondary structure of four homologous E1a mRNAs of the adenovirus. Our main results are as follows: (1) The similarity of the coding regions of the mRNA sequences reflects both similarity in function (i.e., oncogenicity) and evolutionary divergence. (2) The similarity of the leader and the trailer regions reflects host specificity (i.e., human or simian) and must therefore arise from convergence. (3) Minimal energy foldings of the mRNAs show similar secondary structures (in particular around the splice sites). The conservation of pre-mRNA secondary structure shows that mRNAs are subject to selection constraints in addition to those associated with proteins. (4) The conserved secondary (helical) structures consist of nonhomologous subsequences, i.e., shifts have occurred. The observed shifts near the splice sites seem to be the simplest way of dealing with the dual constraints.

Energy directed folding of RNA sequences.

A modification of Nussinov's algorithm (1) for (planar) secondary structure generation is described. Our algorithm postpones decisions on matches involving destabiling loops until they prove to be energetically more favourable than more local matches. We present, moreover, an alternative way of representing secondary structures which avoids unwarranted suggestions on higher order neighbourhood, can be automated easily, allows for any amount of annotation of the sequences, makes comparison of alternate foldings easy and is pleasing to the eye. 5S RNA sequences are used to illustrate the methods.

The alignment of sets of sequences and the construction of phyletic trees: an integrated method.

In this paper we argue that the alignment of sets of sequences and the construction of phyletic trees cannot be treated separately. The concept of 'good alignment' is meaningless without reference to a phyletic tree, and the construction of phyletic trees presupposes alignment of the sequences. We propose an integrated method that generates both an alignment of a set of sequences and a phyletic tree. In this method a putative tree is used to align the sequences and the alignment obtained is used to adjust the tree; this process is iterated. As a demonstration we apply the method to the analysis of the evolution of 5S rRNA sequences in prokaryotes.

Comparison of the nucleotide sequences of early region E1b DNA of human adenovirus types 12, 7 and 5 (subgroups A, B and C).

The nucleotide sequences of human adenovirus serotypes 12 (Ad12, oncogenic subgroups A), 7 (Ad7, weakly oncogenic subgroup B) and 5 (Ad5, non-oncogenic subgroup C) DNAs have been compared. The region studied stretches from the termination codon of region E1a (m.p. 4.2) and comprises the entire region of the three viral DNAs, ending at the polyadenylation signal of the gene for viral polypeptide IVa2 (m.p. 11.2). The homology in the sequences encoding the E1b proteins of Mr 20 000 and Mr 55 000 is 55-60%, when two serotypes are compared, and about 45% in a three-strain comparison. However, a short internal segment encoding the C terminus of the Mr 20 000 protein, and at the same time amino acids 23-120 of the Mr 55 000 protein show a much higher degree of divergence in the three strains, as do the noncoding areas. The present study does not reveal how the three serotypes are phylogenetically related.

Interactive instruction on population interactions.

PIP: A tool for teaching and investigating population simulation models, entitled TRICLE (Program for tridimensional representation of trajectories and isoclines) is presented. It can handle deterministic models in terms of differential and difference equations and stochastic models in terms of difference equations. TRICLE works with up to 10 coupled equations, illustrates the structure of the interactions, and incorporates default parameter values and a representation to show dissimilarity of the parameters. Population models are used to demonstrate use of the system; they are not the only use of the TRICLE system. This system provides a graphic presentation of models as static and dynamic states. It relies on the complex pattern recognition of human beings to sense errors in the model of the data.^ieng