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Using Motivational Interviewing to reduce threats in conversations about environmental behavior.
Florian E Klonek1, Amelie V Güntner2, Nale Lehmann-Willenbrock2
1Department of Industrial/Organizational and Social Psychology, Institute of Psychology, Technische Universität Braunschweig Braunschweig, Germany.
Frontiers in Psychology
|August 11, 2015
Summary
Motivational Interviewing (MI) reduces threats in environmental behavior change conversations. This approach enhances intrinsic motivation by lowering social and cognitive threats, supporting sustainable practices.
Area of Science:
- Environmental Psychology
- Behavioral Science
- Communication Studies
Background:
- Human behavior significantly impacts environmental resource waste.
- Feedback on environmental behavior can be perceived as threatening, reducing intrinsic motivation for change.
- Self-determination theory (SDT) and self-affirmation theory (SAT) explain how threats impact motivation and self-integrity.
Purpose of the Study:
- To examine recipient responses to threats in environmental behavior change interactions.
- To investigate how Motivational Interviewing (MI) mitigates social and cognitive threats.
- To understand the role of MI in fostering intrinsic motivation for pro-environmental behavior.
Main Methods:
- 68 dyadic interactions between change agents and recipients were videotaped.
- Change agents either used MI or were in a control group.
- Verbal threats, expressions of motivation, perceived confrontation, and empathy were coded and rated.
Main Results:
- MI significantly reduced threats from change agents.
- Perceived confrontation aligned with observable agent behavior.
- Threats negatively correlated with recipients' expressed motivation to change.
- No significant relationship was found between agent threats and recipient "sustain talk" (self-defenses).
Conclusions:
- MI effectively reduces threats in environmental behavior change discussions.
- MI lessens adverse social and cognitive impacts, supporting intrinsic motivation.
- Findings offer practical insights for environmental change agents using MI techniques.
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