DOI: 10.57760/sciencedb.psych.00420
title: Rituals reduce state anxiety: The roles of ritual symbolism and belief in ritual efficacy
title: Rituals reduce state anxiety: The roles of ritual symbolism and belief in ritual efficacy

description: Rituals are known to help regulate anxiety, yet the underlying mechanisms remain unclear. Physical features of rituals, such as rigidity and repetition, are hypothesized to engage bottom-up emotion regulation, while their symbolic meanings are thought to activate top-down emotion regulation. Prior research suggests that top-down mechanisms may play a dominant role, but the relative and independent contributions of ritual symbolism and belief in ritual efficacy (BRE) are still unclear. This study investigated the role of ritual symbolism in reducing anxiety by assigning novel actions with explicit symbolic meanings. It also examined BRE as another top-down mechanism, exploring its influence on anxiety reduction and its relationship with ritual symbolism. Participants (N = 126) viewed a horror video to elicit state anxiety and were randomly assigned to one of four action conditions: ritual symbolism (RS), ritual actions (RIA), random actions (RAA), or no action (NA). Anxiety levels were assessed at baseline, induction, and post-treatment. Results showed that, after controlling for confounding factors, the RS group experienced greater anxiety reduction than other control groups, supporting the role of top-down mechanisms. Furthermore, BRE significantly moderated the anxiety-reducing effects of ritual actions in the absence of symbolic meaning, but not when symbolic meaning was provided. These findings indicate that ritual symbolism and BRE operate through distinct top-down pathways: the former via symbolic reappraisal and the latter via belief-based expectancy.The database includes the study's raw data (participant IDs, basic participant information, emotion ratings across three measurement phases, mental arithmetic scores, and efficacy belief ratings for actions and so on), as well as the R analysis code used to construct mixed-effects models, multiple regression models, and hierarchical regression models.
description: Rituals are known to help regulate anxiety, yet the underlying mechanisms remain unclear. Physical features of rituals, such as rigidity and repetition, are hypothesized to engage bottom-up emotion regulation, while their symbolic meanings are thought to activate top-down emotion regulation. Prior research suggests that top-down mechanisms may play a dominant role, but the relative and independent contributions of ritual symbolism and belief in ritual efficacy (BRE) are still unclear. This study investigated the role of ritual symbolism in reducing anxiety by assigning novel actions with explicit symbolic meanings. It also examined BRE as another top-down mechanism, exploring its influence on anxiety reduction and its relationship with ritual symbolism. Participants (N = 126) viewed a horror video to elicit state anxiety and were randomly assigned to one of four action conditions: ritual symbolism (RS), ritual actions (RIA), random actions (RAA), or no action (NA). Anxiety levels were assessed at baseline, induction, and post-treatment. Results showed that, after controlling for confounding factors, the RS group experienced greater anxiety reduction than other control groups, supporting the role of top-down mechanisms. Furthermore, BRE significantly moderated the anxiety-reducing effects of ritual actions in the absence of symbolic meaning, but not when symbolic meaning was provided. These findings indicate that ritual symbolism and BRE operate through distinct top-down pathways: the former via symbolic reappraisal and the latter via belief-based expectancy.The database includes the study's raw data (participant IDs, basic participant information, emotion ratings across three measurement phases, mental arithmetic scores, and efficacy belief ratings for actions and so on), as well as the R analysis code used to construct mixed-effects models, multiple regression models, and hierarchical regression models.