Can psychological models bridge the gap between clinical guidelines and clinicians' behaviour? A randomised controlled trial of an intervention to influence dentists' intention to implement evidence-based practice

Abstract

Objective: The lag between publication of evidence for clinical practice and implementation by clinicians may be decades. Research using psychological models demonstrates that changing intention is very important in changing behaviour. This study examined an intervention (rehearsing alternative actions) to change dentists' intention to implement evidence-based practice (EBP) for third molar (TM) management. Design: Randomised controlled trial/postal. Setting: Primary care. Subjects and methods: Dentists were randomly selected from the Scottish Dental Practice Board Register, then randomly allocated to intervention or control groups, and sent a questionnaire. The intervention group listed management alternatives to TM extraction prior to their TM extraction intention, and the control group did not. Based on psychological models for reducing a behaviour's frequency (EBP is weighted against TM extraction), prior listing of alternatives should decrease extraction intention. Main outcome measure: Intention to extract TMs. Results: A total of 99 dentists - 70 Males, 29 Females; mean age = 41.42 years (SD = 8.62) participated in the study. The intervention significantly influenced intention to extract TMs, as desired. Despite similar background and knowledge of management alternatives, participants in the intervention group had significantly lower intention to extract: control group mean (SD) = 0.39 (1.99); intervention group mean (SD) = -0.78 (1.89); mean difference (SE) = 1.17 (0.42); 95% confidence interval for the difference = 0.34 to 1.99. Conclusion: Results suggest this intervention, which successfully influenced a proximal predictor of behaviour pertinent to dental EBP, may result in improved EBP in a service-level trial. Basing implementation interventions and trial methodology on psychological models may effectively bridge the gap between clinical guidelines and practice.