Scholarlink

<p>Simultaneous alcohol and cannabis use (SAC) poses greater health risks than using each substance separately or concurrently. This two-wave prospective study examined (1) the Theory of Planned Behavior (TPB) capacity to explain the frequency of avoiding SAC use; (2) whether adding past behavior and habit strength—non-deliberative processes—improved prediction; and (3) model invariance across sex and college status. A community sample of 378 young adults (60.3% men, <i>M</i><sub>age</sub> = 21.02, <i>SD</i> = 2.12) completed baseline and 3-month follow-up questionnaires. The TPB explained 55.9% of the variance in intention and 31.4% in behavior. Adding habit strength and past behavior raised explained variance to 73.6% and 49.9%. These non-deliberative factors were the strongest predictors, reducing the effect of traditional TPB components. The model’s predictive capacity was invariant across gender and educational status. While the TPB provides a strong framework for understanding health-promoting behaviors, our results highlight the importance of considering both automatic and reasoned processes.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Explaining Avoidance of Simultaneous Alcohol and Cannabis Use: An Extended Theory of Planned Behavior Model Including Non-deliberative Processes

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月11日

查看全文
  • Belén Valle del Vera,
  • Alberto Parrado-González,
  • José Carmona-Márquez,
  • Fermín Fernández-Calderón

摘要

Simultaneous alcohol and cannabis use (SAC) poses greater health risks than using each substance separately or concurrently. This two-wave prospective study examined (1) the Theory of Planned Behavior (TPB) capacity to explain the frequency of avoiding SAC use; (2) whether adding past behavior and habit strength—non-deliberative processes—improved prediction; and (3) model invariance across sex and college status. A community sample of 378 young adults (60.3% men, Mage = 21.02, SD = 2.12) completed baseline and 3-month follow-up questionnaires. The TPB explained 55.9% of the variance in intention and 31.4% in behavior. Adding habit strength and past behavior raised explained variance to 73.6% and 49.9%. These non-deliberative factors were the strongest predictors, reducing the effect of traditional TPB components. The model’s predictive capacity was invariant across gender and educational status. While the TPB provides a strong framework for understanding health-promoting behaviors, our results highlight the importance of considering both automatic and reasoned processes.