An eHealth computer-based tool named ORION was constructed to assist patients in the clinic to appreciate the factors responsible for risks of drug overdose. The aim of this study was to investigate the associations between risk perception of overdose, engagement in the ORION tool and willingness to alter overdose risk factors. Methods: 194 opioid dependent patients participated from 4 countries (UK, N=39; Germany, N=99; Italy, N=40 and Denmark, N=16). A structural equation model was fitted (AMOS version 17) to summarise the predicted associations between perceived risk and willingness to change risks of opioid overdose. The degree of engagement with the tool (time spent and number of changes to overdose risk factors) was explored. Results: A variety of models were fitted and the most parsimonious model provided a non-significant difference between the raw data and the specified model: Chi Sq = 16.87, df10, p =.077 chi sq/df = 1.688. The fit indices: CFI =.991, RMSEA =.066. Pre and post self-assessments of risk towards known factors linked with overdose were highly correlated. A significant path was found between engagement in the tool and the willingness to change one or more risk factors (stand. coeff. = 0.16, p =.04). In addition, the final assessment of the risk factors was associated with engagement (stand. coeff. = 0.18, p =.02). Conclusion: The encouragement of drug users to engage in exploring changes to their overdose risk when presented on a computer screen appears to increase willingness to change risky behaviour.

Humphris, G., Carra', G., Frisher, M., Neufeind, J., Cecil, J., Scherbaum, N., et al. (2017). Engagement in an e-health tool (ORION) predicts opioid-dependent patient likelihood of behavioural change. HEROIN ADDICTION AND RELATED CLINICAL PROBLEMS, 19(5), 35-44.

Engagement in an e-health tool (ORION) predicts opioid-dependent patient likelihood of behavioural change

CARRA', GIUSEPPE
Secondo
;
2017

Abstract

An eHealth computer-based tool named ORION was constructed to assist patients in the clinic to appreciate the factors responsible for risks of drug overdose. The aim of this study was to investigate the associations between risk perception of overdose, engagement in the ORION tool and willingness to alter overdose risk factors. Methods: 194 opioid dependent patients participated from 4 countries (UK, N=39; Germany, N=99; Italy, N=40 and Denmark, N=16). A structural equation model was fitted (AMOS version 17) to summarise the predicted associations between perceived risk and willingness to change risks of opioid overdose. The degree of engagement with the tool (time spent and number of changes to overdose risk factors) was explored. Results: A variety of models were fitted and the most parsimonious model provided a non-significant difference between the raw data and the specified model: Chi Sq = 16.87, df10, p =.077 chi sq/df = 1.688. The fit indices: CFI =.991, RMSEA =.066. Pre and post self-assessments of risk towards known factors linked with overdose were highly correlated. A significant path was found between engagement in the tool and the willingness to change one or more risk factors (stand. coeff. = 0.16, p =.04). In addition, the final assessment of the risk factors was associated with engagement (stand. coeff. = 0.18, p =.02). Conclusion: The encouragement of drug users to engage in exploring changes to their overdose risk when presented on a computer screen appears to increase willingness to change risky behaviour.
Articolo in rivista - Articolo scientifico
Behaviour change; ORION tool; Overdose prevention; Structural equation modelling; Medicine (miscellaneous); Psychiatry and Mental Health
English
2017
19
5
35
44
none
Humphris, G., Carra', G., Frisher, M., Neufeind, J., Cecil, J., Scherbaum, N., et al. (2017). Engagement in an e-health tool (ORION) predicts opioid-dependent patient likelihood of behavioural change. HEROIN ADDICTION AND RELATED CLINICAL PROBLEMS, 19(5), 35-44.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/172236
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