Speaker
Description
The concept of meaning in life (MIL) is inherently complex, subjective, and thus challenging to measure, despite its core relevance in the promotion of individual well-being and flourishing. Self-measure tools based on verbal items (e.g., SMILE, Zambelli & Tagliabue, 2024) are traditionally used to measure self-perception of life meaningfulness, however, they face well-documented limitations, including social desirability bias and inaccessibility for individuals with limited linguistic competence (King & Hicks, 2021). The SMILE Visual is a self-report measure which operationalizes the basic components of meaning in life (presence and search for meaning) through images. The development of the SMILE Visual followed a rigorous process. Twelve professional artists with different background (painters, designers, architects) were involved in three workshops with the aim of identifying key technical characteristics (e.g., composition, color, lighting) required for images to operationalize the MIL construct as defined by well-known theoretical definitions. Based on these insights, a set of images was created using AI tools (MidJourney and DALL·E) to represent each MIL dimension. The adequacy of images as valid operationalizations of both theoretical and technical definitions of the MIL dimensions was evaluated by expert researchers and professionals. Construct validity was further explored by conducting cognitive interviews with a gender-balanced convenience sample of adults who evaluated the comprehensibility and applicability of the SMILE Visual. This project marks a first step toward the adoption of visual stimuli to develop psychological measures with fair and inclusive methods. Opportunities and challenges of the development and validation of visual measures are discussed.
