Characterizing Persistent Disturbing Behavior Using Longitudinal and Multivariate Techniques Jan...

Characterizing Persistent Disturbing Behavior Using Longitudinal and

Multivariate Techniques Jan Serroyen, UHasselt

Liesbeth Bruckers, UHasselt

Geert Rogiers, PZ Sancta Maria

Geert Molenberghs, UHasselt

QMSS - UHasselt - 2 -

Outline

Persistent Disturbing Behavior (PDB)

Research questions

Pilot study

Longitudinal analysis

Cluster analysis

Concluding remarks

QMSS - UHasselt - 3 -

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

QMSS - UHasselt - 4 -

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

QMSS - UHasselt - 5 -

Research Questions

Distinguish PDB from non-PDB

Size of PDB group

Homogeneous group or subgroups

QMSS - UHasselt - 6 -

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

QMSS - UHasselt - 7 -

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

QMSS - UHasselt - 8 -

QMSS - UHasselt - 9 -

Longitudinal analysis

Aim: study persistence dimension

Discriminant analysis -> PDB-score

Calculate score at other registration occasions

-> PDB-score over time

QMSS - UHasselt - 10 -

QMSS - UHasselt - 11 -

QMSS - UHasselt - 12 -

Linear mixed-effects model

QMSS - UHasselt - 13 -

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

QMSS - UHasselt - 14 -

Linear mixed-effects model

Final model:Mean structure:

Random-effects covariance matrix:

QMSS - UHasselt - 15 -

QMSS - UHasselt - 16 -

QMSS - UHasselt - 17 -

QMSS - UHasselt - 18 -

QMSS - UHasselt - 19 -

Cluster analysis

Identify subgroups within PDB group

Gower’s distance:

can handle all outcome types

Ward’s minimum variance method

Result: 2 clusters

QMSS - UHasselt - 20 -

QMSS - UHasselt - 21 -

Concluding remarks

Differences PDB & non-PDB:Mean profilesVarianceCorrelation structure

Numerous PDB patients

Need for specialized treatment facilities