Source Paper
Source Paper
Susan Michie, Caroline E Wood, Marie Johnston, Charles Abraham, Jill J Francis et al.
Health Technology Assessment • 2015
Background Meeting global health challenges requires effective behaviour change interventions (BCIs). This depends on advancing the science of behaviour change which, in turn, depends on accurate intervention reporting. Current reporting often lacks detail, preventing accurate replication and implementation. Recent developments have specified intervention content into behaviour change techniques (BCTs) – the ‘active ingredients’, for example goal-setting, self-monitoring of behaviour. BCTs are ‘the smallest components compatible with retaining the postulated active ingredients, i.e. the proposed mechanisms of change. They can be used alone or in combination with other BCTs’ (Michie S, Johnston M. Theories and techniques of behaviour change: developing a cumulative science of behaviour change. Health Psychol Rev 2012; 6:1–6). Domain-specific taxonomies of BCTs have been developed, for example healthy eating and physical activity, smoking cessation and alcohol consumption. We need to build on these to develop an internationally shared language for specifying and developing interventions. This technology can be used for synthesising evidence, implementing effective interventions and testing theory. It has enormous potential added value for science and global health. Objective (1) To develop a method of specifying content of BCIs in terms of component BCTs; (2) to lay a foundation for a comprehensive methodology applicable to different types of complex interventions; (3) to develop resources to support application of the taxonomy; and (4) to achieve multidisciplinary and international acceptance for future development. Design and participants Four hundred participants (systematic reviewers, researchers, practitioners, policy-makers) from 12 countries engaged in investigating, designing and/or delivering BCIs. Development of the taxonomy involved a Delphi procedure, an iterative process of revisions and consultation with 41 international experts; hierarchical structure of the list was developed using inductive ‘bottom-up’ and theory-driven ‘top-down’ open-sort procedures ( n = 36); training in use of the taxonomy (1-day workshops and distance group tutorials) ( n = 161) was evaluated by changes in intercoder reliability and validity (agreement with expert consensus); evaluating the taxonomy for coding interventions was assessed by reliability (intercoder; test–retest) and validity ( n = 40 trained coders); and evaluating the taxonomy for writing descriptions was assessed by reliability (intercoder; test–retest) and by experimentally testing its value ( n = 190). Results Ninety-three distinct, non-overlapping BCTs with clear labels and definitions formed Behaviour Change Technique Taxonomy version 1 (BCTTv1). BCTs clustered into 16 groupings using a ‘bottom-up’ open-sort procedure; there was overlap between these and groupings produced by a theory-driven, ‘top-down’ procedure. Both training methods improved validity (both p < 0.05), doubled the proportion of coders achieving competence and improved confidence in identifying BCTs in workshops (both p < 0.001) but did not improve intercoder reliability. Good intercoder reliability was observed for 80 of the 93 BCTs. Good within-coder agreement was observed after 1 month ( p < 0.001). Validity was good for 14 of 15 BCTs in the descriptions. The usefulness of BCTTv1 to report descriptions of observed interventions had mixed results. Conclusions The developed taxonomy (BCTTv1) provides a methodology for identifying content of complex BCIs and a foundation for international cross-disciplinary collaboration for developing more effective interventions to improve health. Further work is needed to examine its usefulness for reporting interventions. Funding This project was funded by the Medical Research Council Ref: G0901474/1. Funding also came from the Peninsula Collaboration for Leadership in Applied Health Research and Care.
Objective: To develop and evaluate a taxonomic method for reporting behaviour change interventions by training participants in taxonomy use and assessing changes in intercoder reliability and validity against expert consensus
This is a Taxonomy Training and Competency Evaluation protocol using human as the model organism. The procedure involves 6 procedural steps. Extracted from a 2015 paper published in Health Technology Assessment.
Model and subjects
human • 161
Study window
~1 day study window
Core workflow
Participant Recruitment and Selection • 1-Day Workshop Training • Distance Group Tutorial Training
Primary readouts
Key equipment and reagents
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Recruit 161 participants consisting of systematic reviewers, researchers, practitioners, and policy-makers from 12 countries who are engaged in investigating, designing and/or delivering behaviour change interventions
Note: Participants were selected from a larger pool of 400 participants involved in the broader taxonomy development project
“training in use of the taxonomy (1-day workshops and distance group tutorials) (n = 161) was evaluated by changes in intercoder reliability and validity”
Conduct 1-day workshops to train participants in the use of the Behaviour Change Technique Taxonomy version 1 (BCTTv1) for identifying and coding behaviour change techniques in interventions
Note: This is one of two training delivery methods evaluated in the study
“training in use of the taxonomy (1-day workshops and distance group tutorials) (n = 161)”
Conduct distance group tutorials to train participants in the use of the Behaviour Change Technique Taxonomy version 1 (BCTTv1) for identifying and coding behaviour change techniques in interventions
Note: This is the second training delivery method evaluated in the study, conducted remotely
“training in use of the taxonomy (1-day workshops and distance group tutorials) (n = 161)”
Evaluate changes in intercoder reliability by having trained coders independently code the same behaviour change interventions and comparing their coding agreement
Note: Intercoder reliability was assessed as one of the primary outcome measures for training effectiveness
“was evaluated by changes in intercoder reliability and validity (agreement with expert consensus)”
Evaluate validity by comparing trained coders' identification of behaviour change techniques against expert consensus coding to determine agreement with expert standards
Note: Validity was measured as agreement with expert consensus coding
“was evaluated by changes in intercoder reliability and validity (agreement with expert consensus)”
Assess participant confidence in identifying behaviour change techniques in workshop settings using appropriate measurement tools
Note: Confidence was measured as an outcome of training effectiveness
“improved confidence in identifying BCTs in workshops (both p < 0.001)”
This section explains what the experiment is doing, which readouts matter, what the data artifacts usually look like, and how the analysis should flow from raw capture to reported result.
To develop and evaluate a taxonomic method for reporting behaviour change interventions by training participants in taxonomy use and assessing changes in intercoder reliability and validity against expert consensus
Objective
To develop and evaluate a taxonomic method for reporting behaviour change interventions by training participants in taxonomy use and assessing changes in intercoder reliability and validity against expert consensus
Subjects
From paperhuman
Sample count
From paper161
Cohort notes
From paperParticipants were systematic reviewers, researchers, practitioners, and policy-makers from 12 countries engaged in investigating, designing and/or delivering behaviour change interventions
Participant Recruitment and Selection
1-Day Workshop Training (1 day)
Distance Group Tutorial Training
Assess Intercoder Reliability
Intercoder reliability (agreement between coders)
From paperStatistical analysis was conducted with p-values reported (p < 0.05 and p < 0.001 thresholds used); reliability and validity were assessed qualitatively as 'good' for specific numbers of BCTs
Artifact type
Endpoint measurements summarized by group or timepoint
Comparison focus
Compare endpoint magnitude between groups, timepoints, or both
Validity (agreement with expert consensus)
From paperStatistical analysis was conducted with p-values reported (p < 0.05 and p < 0.001 thresholds used); reliability and validity were assessed qualitatively as 'good' for specific numbers of BCTs
Artifact type
Endpoint measurements summarized by group or timepoint
Comparison focus
Compare endpoint magnitude between groups, timepoints, or both
Proportion of coders achieving competence
From paperStatistical analysis was conducted with p-values reported (p < 0.05 and p < 0.001 thresholds used); reliability and validity were assessed qualitatively as 'good' for specific numbers of BCTs
Artifact type
Endpoint measurements summarized by group or timepoint
Comparison focus
Compare endpoint magnitude between groups, timepoints, or both
Confidence in identifying BCTs in workshops
From paperStatistical analysis was conducted with p-values reported (p < 0.05 and p < 0.001 thresholds used); reliability and validity were assessed qualitatively as 'good' for specific numbers of BCTs
Artifact type
Endpoint measurements summarized by group or timepoint
Comparison focus
Compare endpoint magnitude between groups, timepoints, or both
Intercoder reliability (agreement between coders)
From paperRaw artifact
Per-sample or per-animal endpoint measurements collected during the experiment
Processed artifact
Structured table with cleaned measurements ready for comparison
Final reported form
Summary statistics and between-group or across-timepoint comparisons
Validity (agreement with expert consensus)
From paperRaw artifact
Per-sample or per-animal endpoint measurements collected during the experiment
Processed artifact
Structured table with cleaned measurements ready for comparison
Final reported form
Summary statistics and between-group or across-timepoint comparisons
Proportion of coders achieving competence
From paperRaw artifact
Per-sample or per-animal endpoint measurements collected during the experiment
Processed artifact
Structured table with cleaned measurements ready for comparison
Final reported form
Summary statistics and between-group or across-timepoint comparisons
Confidence in identifying BCTs in workshops
From paperRaw artifact
Per-sample or per-animal endpoint measurements collected during the experiment
Processed artifact
Structured table with cleaned measurements ready for comparison
Final reported form
Summary statistics and between-group or across-timepoint comparisons
Acquisition
Collect raw experimental outputs with enough metadata to preserve sample identity, condition, and timing.
Preprocessing / cleaning
Statistical analysis was conducted with p-values reported (p < 0.05 and p < 0.001 thresholds used); reliability and validity were assessed qualitatively as 'good' for specific numbers of BCTs
Scoring or quantification
Quantify the primary readouts for this experiment: Intercoder reliability (agreement between coders); Validity (agreement with expert consensus); Proportion of coders achieving competence; Confidence in identifying BCTs in workshops.
Statistical comparison
Statistical method not yet structured for this page.
Reporting output
Report representative outputs alongside summary comparisons for Intercoder reliability (agreement between coders), Validity (agreement with expert consensus), Proportion of coders achieving competence, Confidence in identifying BCTs in workshops.
Source links and direct wording from the methods section for validation and deeper review.
Citation
Susan Michie et al. (2015). Behaviour change techniques: the development and evaluation of a taxonomic method for reporting and describing behaviour change interventions (a suite of five studies involving consensus methods, randomised controlled trials and analysis of qualitative data). Health Technology Assessment
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