characterizing persistent disturbing behavior using longitudinal and multivariate techniques jan...
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Characterizing Persistent Disturbing Behavior Using Longitudinal and
Multivariate Techniques Jan Serroyen, UHasselt
Liesbeth Bruckers, UHasselt
Geert Rogiers, PZ Sancta Maria
Geert Molenberghs, UHasselt
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Outline
Persistent Disturbing Behavior (PDB)
Research questions
Pilot study
Longitudinal analysis
Cluster analysis
Concluding remarks
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Persistent Disturbing Behavior
Observation by mental health care professionals
Problematic group of patients:Disturbing behavior
Therapy resistant
Living together is extremely difficult
Intensive supervision over 24h
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Where do they belong?
Psychiatric hospital (PH): Definition: non-residential institution for intensive
specialist care Problem: need for a prolonged stay
Psychiatric nursing home (PNH): Royal Decree: chronic and stabilized psychiatric
conditions Problem: instable disease status
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Research Questions
Distinguish PDB from non-PDB
Size of PDB group
Homogeneous group or subgroups
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Minimal Psychiatric Data (MPD)
Imposed by the Ministry of Public Health
Started in 1996
Goal : Transparency in care Diversity of patients Variability in care
Items Socio demographic Diagnostic items (DSM IV) Psycho-social problems Received treatment
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Pilot study
Cross-sectional study in 1998 (N = 611)
Discriminant analysis: PDB screening by expert opinion
Discriminant function: based on MPD data
Sensitivity & Specificity: 72% - 85%
80% correctly classified
Conclusion: PDB is a substantial group
Focus on disturbance aspect
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Longitudinal analysis
Aim: study persistence dimension
Discriminant analysis -> PDB-score
Calculate score at other registration occasions
-> PDB-score over time
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Linear mixed-effects model
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Linear mixed-effects model
Separate models for both types of institutions
Starting model:Mean structure: PDB group, time, time² and pairwise
interactions
Variance model: 3 group-specific random effects: intercept, time, time²
PH: group specific power-of-mean structure
PNH: group specific Gaussian serial correlation structure
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Linear mixed-effects model
Final model:Mean structure:
Random-effects covariance matrix:
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Cluster analysis
Identify subgroups within PDB group
Gower’s distance:
can handle all outcome types
Ward’s minimum variance method
Result: 2 clusters
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Concluding remarks
Differences PDB & non-PDB:Mean profilesVarianceCorrelation structure
Numerous PDB patients
Need for specialized treatment facilities