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Use of the Theory of Planned Behaviour to assess factors influencing the identification of students at clinical high-risk for psychosis in 16+ Education

Overview of attention for article published in BMC Health Services Research, September 2015
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Title
Use of the Theory of Planned Behaviour to assess factors influencing the identification of students at clinical high-risk for psychosis in 16+ Education
Published in
BMC Health Services Research, September 2015
DOI 10.1186/s12913-015-1074-y
Pubmed ID
Authors

Debra A. Russo, Jan Stochl, Michelle Painter, Gillian F. Shelley, Peter B. Jones, Jesus Perez

Abstract

The longer psychotic disorders are untreated the worse their prognosis. Increasing the awareness of early psychosis by professionals who come into regular contact with young people is one strategy that could reduce treatment delay. As teachers engage with students on a daily basis, their role could be exploited to increase awareness of the early signs of psychosis. This study employed the Theory of Planned Behaviour (TPB) to identify and measure factors that influence identification of students at high-risk (HR) of developing psychosis in 16+ educational institutions. An elicitation phase revealed beliefs underlying teachers' motivations to detect HR students and informed the construction of a preliminary 114-item questionnaire incorporating all constructs outlined in the TPB. To define the determinants of teachers' intention to identify HR students, 75 teachers from secondary and further education institutions in 12 counties surrounding Cambridgeshire completed the questionnaire. A psychometric model of item response theory was used to identify redundant items and produce a reduced questionnaire that would be acceptable to teachers. The final instrument comprised 73 items and showed acceptable reliability (α  = 0.69-0.81) for all direct measures. Teacher's confidence and control over identification of HR students was low. Although identification of HR students was considered worthwhile, teachers believed that their peers, students and particularly their managers might not approve. Path analysis revealed that direct measures of attitude and PBC significantly predicted intention, but subjective norm did not. PBC was the strongest predictor of intention. Collectively, the direct measures explained 37 % of the variance of intention to identify HR for psychosis. This research demonstrated how the TPB can be used to identify and measure factors that influence identification of students at HR of developing psychosis in 16+ educational institutions and confirmed the feasibility, reliability and acceptability of a TPB-based questionnaire for teachers. Consideration of the key determinants of identification in schools will facilitate the design of successful educational intervention strategies with the potential to reduce treatment delays for HR students.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 144 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Malaysia 1 <1%
Canada 1 <1%
Unknown 141 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 31 22%
Student > Ph. D. Student 27 19%
Student > Doctoral Student 15 10%
Researcher 10 7%
Student > Bachelor 7 5%
Other 19 13%
Unknown 35 24%
Readers by discipline Count As %
Psychology 21 15%
Business, Management and Accounting 20 14%
Social Sciences 17 12%
Nursing and Health Professions 11 8%
Medicine and Dentistry 11 8%
Other 21 15%
Unknown 43 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 October 2015.
All research outputs
#17,194,664
of 25,260,058 outputs
Outputs from BMC Health Services Research
#6,286
of 8,574 outputs
Outputs of similar age
#168,365
of 281,498 outputs
Outputs of similar age from BMC Health Services Research
#109
of 142 outputs
Altmetric has tracked 25,260,058 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,574 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 281,498 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.