Title |
Motivation and treatment engagement intervention trial (MotivaTe-IT): the effects of motivation feedback to clinicians on treatment engagement in patients with severe mental illness
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Published in |
BMC Psychiatry, November 2012
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DOI | 10.1186/1471-244x-12-209 |
Pubmed ID | |
Authors |
Eline C Jochems, Cornelis L Mulder, Arno van Dam, Hugo J Duivenvoorden, Sylvia CM Scheffer, Willem van der Spek, Christina M van der Feltz-Cornelis |
Abstract |
Treatment disengagement and non-completion poses a major problem for the successful treatment of patients with severe mental illness. Motivation for treatment has long been proposed as a major determinant of treatment engagement, but exact mechanisms remain unclear. This current study serves three purposes: 1) to determine whether a feedback intervention based on the patients' motivation for treatment is effective at improving treatment engagement (TE) of severe mentally ill patients in outpatient psychiatric treatment, 2) to gather insight into motivational processes and possible mechanisms regarding treatment motivation (TM) and TE in this patient population and 3) to determine which of three theories of motivation is most plausible for the dynamics of TM and TE in this population. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Egypt | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Germany | 1 | <1% |
Unknown | 190 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 34 | 18% |
Student > Master | 27 | 14% |
Student > Ph. D. Student | 25 | 13% |
Student > Bachelor | 23 | 12% |
Student > Doctoral Student | 16 | 8% |
Other | 25 | 13% |
Unknown | 41 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 62 | 32% |
Medicine and Dentistry | 30 | 16% |
Social Sciences | 14 | 7% |
Nursing and Health Professions | 8 | 4% |
Computer Science | 4 | 2% |
Other | 22 | 12% |
Unknown | 51 | 27% |