Theory-based promotion of diet and transportation behavior change to reduce carbon footprint among students: Randomized parallel trial of the GROW app.
学生のカーボンフットプリント削減に向けた理論に基づく食習慣と交通行動の変容促進：GROWアプリのランダム化並行試験 (AI 翻訳)
Dario Baretta, Carole Lynn Rüttimann, Jennifer Inauen
🤖 gxceed AI 要約
日本語
本研究は、健康行動プロセスアプローチに基づくデジタル介入（GROWアプリ）が、学生の食事および交通由来のカーボンフットプリント削減に有効か検証した二重盲検ランダム化比較試験である。動機付けのみのバージョンと、行動計画・問題解決を含む動機付け+意図的バージョンを比較した結果、食事由来のCFPは全体的に減少したが、群間差はなく、交通由来のCFPに変化は見られなかった。行動計画と行動コントロールが食事由来CFPの低下と最も強く関連した。
English
This double-blind randomized trial tested a digital intervention (GROW app) based on the Health Action Process Approach to reduce diet- and transportation-related carbon footprints in students (N=226). Participants used either a motivational-only or motivational+volitional version for 5 weeks. Diet-related carbon footprint decreased overall but no difference between groups; no change in transportation footprint. Action planning and control were key correlates of diet footprint reduction.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、GHG排出削減目標達成に向けて個人の行動変容が注目されている。本研究成果は、食事分野ではデジタル介入が一定の効果を持つ可能性を示す一方、交通分野では物理的環境の整備等、構造的対策の必要性を示唆しており、日本のGX政策における行動科学アプローチの位置づけに示唆を与える。
In the global GX context
The study provides evidence on digital behavior change interventions for carbon footprint reduction, relevant to global climate mitigation efforts. It highlights that while dietary emissions can be reduced through app-based interventions, transportation emissions require structural changes, informing the design of comprehensive climate policies worldwide.
👥 読者別の含意
🔬研究者:Provides empirical evidence on the efficacy of HAPA-based digital interventions for carbon footprint reduction, with implications for behavior change theory.
🏢実務担当者:Limited direct applicability; the app design and techniques (goal setting, action planning) could inspire corporate wellness or sustainability programs.
🏛政策担当者:Informs the need for combining behavioral interventions with structural measures (e.g., cycling infrastructure) to reduce transportation emissions.
📄 Abstract（原文）
Adopting a low-emission diet and choosing low-emission transportation modes are among the most effective strategies for mitigating one's individual impact on climate. However, interventions targeting these behaviors often fall short because they focus primarily on motivation, neglecting volitional processes. Guided by the Health Action Process Approach, this double-blind randomized parallel trial tested whether a digital intervention addressing both motivational and volitional determinants of behavior was more effective in reducing diet- and transportation-related carbon footprints than an intervention addressing motivation only. The intervention was delivered via the GROW app, which included two versions: a motivational version (goal setting and feedback) and a motivational + volitional version (additional techniques such as action planning and problem solving). Participants (N = 226; 97% students) used either version of the app for 5 weeks, reporting daily animal-based food consumption (e.g., red meat and poultry) and transportation behaviors (e.g., bike and car). Psychological determinants (e.g., action planning and action control) were measured weekly. Multilevel models showed an overall reduction in diet-related carbon footprint (B = -0.1, 95% CI [-0.02, -0.01]); however, this decrease did not differ between intervention groups. No changes emerged for transportation-related or total carbon footprints. Action planning and action control emerged as the strongest correlates of lower diet-related carbon footprint. The findings show preliminary indication of the efficacy of digital behavior change interventions for reducing diet-related carbon footprint. Structural measures addressing opportunities and barriers in the physical environment may be needed to reduce transportation-related emissions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.48620/98644first seen 2026-06-23 05:57:14
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