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

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Area of Science:

  • Oral Health
  • Psychometrics
  • Health Outcomes Research

Background:

  • Dentine hypersensitivity (DH) significantly impacts patient quality of life (QoL).
  • Longitudinal QoL assessments can be confounded by Response shift (RS), where the internal meaning of QoL changes over time.
  • Understanding RS is crucial for accurately measuring treatment effects in conditions like DH.

Purpose of the Study:

  • To describe patterns of RS in individuals with DH using Classification and Regression Trees (CRT).
  • To explore the convergent validity of CRT with established then-test and ideals approaches for detecting RS.
  • To analyze how DH affects QoL and identify shifts in patient perceptions.

Main Methods:

  • Analysis of data from a 75-participant, 8-week clinical trial of mouthwashes for DH.
  • Utilized the Dentine Hypersensitivity Experience Questionnaire (DHEQ) as the primary outcome measure.
  • Employed CRT to examine changes in DHEQ scores, inferring recalibration and reprioritization based on clinical status and subscale importance over time.

Main Results:

  • Over half of participants (50.7%) showed clinical improvement in DH; 22.7% reported meaningful QoL improvement.
  • Significant proportions experienced recalibration: 36% shifted standards downward, 14.7% upward.
  • Reprioritization of QoL impacts was observed over the 8-week study period, particularly concerning social and emotional aspects.

Conclusions:

  • Classification and Regression Trees (CRT) proved effective in identifying the types and nature of RS in individuals with DH.
  • CRT demonstrated convergent validity with other design-based approaches for RS detection.
  • The study highlights the utility of CRT in understanding subjective changes in health perception for mild conditions.