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Full-Text Articles in Arts and Humanities
Collaborative Recovery: An Integrative Model For Working With Individuals Who Experience Chronic And Recurring Mental Illness, Lindsay G. Oades, Frank P. Deane, Trevor P. Crowe, Gordon Lambert, David Kavanagh, Christopher Lloyd
Collaborative Recovery: An Integrative Model For Working With Individuals Who Experience Chronic And Recurring Mental Illness, Lindsay G. Oades, Frank P. Deane, Trevor P. Crowe, Gordon Lambert, David Kavanagh, Christopher Lloyd
Faculty of Health and Behavioural Sciences - Papers (Archive)
Objectives: Recovery is an emerging movement in mental health. Evidence for recovery-based approaches is not well developed and approaches to implement recovery-oriented services are not well articulated. The collaborative recovery model (CRM) is presented as a model that assists clinicians to use evidencebased skills with consumers, in a manner consistent with the recovery movement. A current 5 year multisite Australian study to evaluate the effectiveness of CRM is briefly described. Conclusion: The collaborative recovery model puts into practice several aspects of policy regarding recovery-oriented services, using evidence-based practices to assist individuals who have chronic or recurring mental disorders (CRMD). It …
Individual Difference & Computer User-Training Behaviour: Examination Of An Empirical Model, Anura R. Jayasuriya, Peter Caputi, Leonie M. Miller, Jocelyn R. Harper, Shae-Leigh C. Vella, Joseph A. Meloche
Individual Difference & Computer User-Training Behaviour: Examination Of An Empirical Model, Anura R. Jayasuriya, Peter Caputi, Leonie M. Miller, Jocelyn R. Harper, Shae-Leigh C. Vella, Joseph A. Meloche
Faculty of Health and Behavioural Sciences - Papers (Archive)
A model that incorporates both stable and dynamic individual differences to the nomological net of the Technology Acceptance Model (TAM) in the context of computer user training is proposed. A study using 348 completed surveys from University students engaged in computer training found that stable traits (Negative Affects, Trait Anxiety and Personal Innovativeness in IT (PIIT)) explained 35% of variance in Computer Anxiety (CA). Significant support to the model provides evidence that stable individual differences are antecedents to and predict both Computer Self Efficacy and CA. In addition, the model demonstrates the relationship of these determinants to the TAM.