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Signal Attenuation as a Rat Model of Obsessive Compulsive Disorder
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Published on: January 9, 2015

Explaining clinical behaviors using multiple theoretical models.

Martin P Eccles1, Jeremy M Grimshaw, Graeme MacLennan

  • 1College of Life Sciences and Medicine, University of Aberdeen, Health Sciences Building (2nd floor), Foresterhill, Aberdeen, United Kingdom.

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PubMed
Summary
This summary is machine-generated.

This study evaluated multiple behavior change theories in healthcare professionals, finding that while theories like the Theory of Planned Behavior (TPB) and Social Cognitive Theory (SCT) could predict intentions, they explained less variance in actual behavior. Further research is needed to improve theory application for effective behavior change interventions.

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Area of Science:

  • Implementation Science
  • Behavioral Science
  • Healthcare Research

Background:

  • Growing interest in utilizing theory for designing behavior change interventions in implementation research.
  • Initiated a series of five studies to establish a scientific rationale for interventions aimed at translating research findings into clinical practice.
  • Explored the performance of commonly used behavioral theories and models, reflecting on their strengths, weaknesses, and applicability to healthcare professional behavior change.

Purpose of the Study:

  • To evaluate the performance of multiple behavioral theories in explaining healthcare professional behavior change.
  • To establish a scientific rationale for interventions that translate research findings into clinical practice.
  • To compare the predictive value of various theories including Theory of Planned Behavior (TPB), Social Cognitive Theory (SCT), and others.

Main Methods:

  • Conducted five studies on theory-based cognitions and clinical behaviors of primary care dentists and physicians.
  • Derived measures for theoretical constructs from TPB, SCT, Common Sense Self Regulation Model (CSSRM), Learning Theory (LT), Implementation Intentions (II), and Precaution Adoption Process.
  • Collected data via postal questionnaires on cognitions, intentions, and simulated behavior, linked to objective behavioral data over 12 months.

Main Results:

  • Response rates varied (21%-48%), with target sample sizes met for three studies.
  • Predictor variables generally scored above the midpoint; median values across behaviors were above four out of seven.
  • Theories consistently explained more variance in intention (25%-42.6%) than in behavior (2.4%-6.3%). Knowledge-Attitudes-Behavior Model and CSSRM performed poorly. TPB, SCT, II, and LT showed moderate predictive value for intention and simulation, but limited for behavior.

Conclusions:

  • Operationalized and measured multiple theories across five distinct healthcare behaviors.
  • Identified ongoing challenges including better behavior specification and theory operationalization.
  • Highlighted the need for extending theory application, assessing value in different settings, exploring implications for chronic disease management, and employing experimental designs for understanding behavior change.