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Using classification and regression tree modelling to investigate response shift patterns in dentine hypersensitivity

Overview of attention for article published in BMC Medical Research Methodology, August 2017
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Title
Using classification and regression tree modelling to investigate response shift patterns in dentine hypersensitivity
Published in
BMC Medical Research Methodology, August 2017
DOI 10.1186/s12874-017-0396-3
Pubmed ID
Authors

Carolina Machuca, Mario V. Vettore, Marta Krasuska, Sarah R. Baker, Peter G. Robinson

Abstract

Dentine hypersensitivity (DH) affects people's quality of life (QoL). However changes in the internal meaning of QoL, known as Response shift (RS) may undermine longitudinal assessment of QoL. This study aimed to describe patterns of RS in people with DH using Classification and Regression Trees (CRT) and to explore the convergent validity of CRT with the then-test and ideals approaches. Data from an 8-week clinical trial of mouthwashes for dentine hypersensitivity (n = 75) using the Dentine Hypersensitivity Experience Questionnaire (DHEQ) as the outcome measure, were analysed. CRT was used to examine 8-week changes in DHEQ total score as a dependent variable with clinical status for DH and each DHEQ subscale score (restrictions, coping, social, emotional and identity) as independent variables. Recalibration was inferred when the clinical change was not consistent with the DHEQ change score using a minimally important difference for DHEQ of 22 points. Reprioritization was inferred by changes in the relative importance of each subscale to the model over time. Overall, 50.7% of participants experienced a clinical improvement in their DH after treatment and 22.7% experienced an important improvement in their quality of life. Thirty-six per cent shifted their internal standards downward and 14.7% upwards, suggesting recalibration. Reprioritization occurred over time among the social and emotional impacts of DH. CRT was a useful method to reveal both, the types and nature of RS in people with a mild health condition and demonstrated convergent validity with design based approaches to detect RS.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 12%
Student > Ph. D. Student 6 9%
Professor 5 7%
Student > Bachelor 5 7%
Student > Doctoral Student 4 6%
Other 14 21%
Unknown 25 37%
Readers by discipline Count As %
Medicine and Dentistry 15 22%
Nursing and Health Professions 8 12%
Agricultural and Biological Sciences 3 4%
Biochemistry, Genetics and Molecular Biology 2 3%
Psychology 2 3%
Other 11 16%
Unknown 26 39%
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 15 August 2017.
All research outputs
#20,442,790
of 22,997,544 outputs
Outputs from BMC Medical Research Methodology
#1,891
of 2,027 outputs
Outputs of similar age
#277,277
of 317,683 outputs
Outputs of similar age from BMC Medical Research Methodology
#42
of 51 outputs
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