RESUMO
Many of us "see red," "feel blue," or "turn green with envy." Are such color-emotion associations fundamental to our shared cognitive architecture, or are they cultural creations learned through our languages and traditions? To answer these questions, we tested emotional associations of colors in 4,598 participants from 30 nations speaking 22 native languages. Participants associated 20 emotion concepts with 12 color terms. Pattern-similarity analyses revealed universal color-emotion associations (average similarity coefficient r = .88). However, local differences were also apparent. A machine-learning algorithm revealed that nation predicted color-emotion associations above and beyond those observed universally. Similarity was greater when nations were linguistically or geographically close. This study highlights robust universal color-emotion associations, further modulated by linguistic and geographic factors. These results pose further theoretical and empirical questions about the affective properties of color and may inform practice in applied domains, such as well-being and design.
Assuntos
Emoções , Idioma , Cor , Percepção de Cores , Humanos , Ciúme , Linguística , Aprendizado de MáquinaRESUMO
AIM: To explore what thoughts, feelings, and learning processes were involved in obese participants' lifestyle change during an acceptance and commitment therapy (ACT) lifestyle intervention delivered in primary health care. BACKGROUND: Previous studies have revealed that lifestyle interventions are effective at promoting initial weight loss, but reduced weight is often difficult to sustain because of the failure to maintain healthy lifestyle changes. Achieving and maintaining lifestyle changes requires to learn self-regulation skills. ACT-based lifestyle interventions combine many self-regulatory skill factors, and the results from previous studies are promising. Research on the individual learning processes of lifestyle change is still needed. METHODS: This study investigated a subset of data from a larger web-based lifestyle intervention. This subset consisted of online logbooks written by 17 obese participants (n = 17, body mass index mean 41.26 kg/m2) during the six-week online module. The logbooks were analyzed via data-driven content analysis. FINDINGS: Four groups were identified based on the participants being at different phases in their lifestyle changes: stuck with barriers, slowly forward, reflective and hardworking, and convincingly forward with the help of concrete goals. Differences between the groups were manifested in personal barriers, goal setting, training of mindfulness and acceptance, and achieving healthy actions. The ACT-based lifestyle intervention offered participants an opportunity to reflect on how their thoughts and feelings may hinder healthy lifestyle changes and provided tools for learning psychological flexibility.