Examining the Cultural Consensus on Beliefs about Mindfulness among US Early Adults

Objectives: Mindfulness programs are increasingly popular, yet little is known about how individuals perceive mindfulness: its origins, how it is learned, its functions, and practitioners. Using methods from Cultural Consensus Theory (CCT), the present study sought to examine whether a cultural consensus on mindfulness exists among early adults in the US, and what the content of that consensus might be.Methods: College-attending early adults aged 18-25 (Study 1 N = 275 – convenience sample; Study 2 N = 210 – nationally representative sample) completed questionnaires on beliefs about mindfulness, exposure to mindfulness, and demographics. Data were analyzed using a CCT-derived Bayesian cognitive psychometric model.Results: Early adults converged on a cultural consensus about mindfulness in both studies, and the content of this consensus was also replicated. Participants consensually agreed that mindfulness has Buddhist origins, is both spiritual (but not religious) and secular; takes patience to learn and a lifetime to master; is an antidote to suffering, but also gives one a competitive edge in the business world; is practiced more by women, and less by Conservatives. Prior exposure to mindfulness was related to greater knowledge of this cultural consensus.Conclusions: Early adults view mindfulness as a universal practice that people their age can learn, that serves both spiritual and instrumental functions, and that is not limited to wealthy or White people. Results provide useful information that can inform debates about mindfulness in the US, and guide practical efforts to increase inclusivity and participation in such programs for early adults in future.

Cultural Consensus Theory as a Method for Evaluating Culturally Shared Beliefs

A central endeavor in the study of culture and psychology is to understand how substantively meaningful cultural variables impact human behavior (e.g., cultural belief systems). Yet, the majority of studies within the field of cultural psychology neglect to do so, instead focusing primarily on group comparisons. One reason for this over-reliance on group comparisons may be the paucity of methods with which to adequately measure cultural variables. In the present paper, I describe a method for evaluating culturally shared phenomena, such as beliefs, based on Cultural Consensus Theory (CCT), and consider the utility of this approach as applied to the study of culture and psychology. Examples as to how this methodology can and has been applied are provided, as are comparisons it to other methods. In doing so, I demonstrate the potential for CCT methods to advance our understanding of cultural beliefs, while acknowledging the limitations inherent in the paradigm.

Cultural Consensus Theory for the Evaluation of Patients’ Mental Health Scores in Psychiatric Detention Centers

In many forensic psychiatric hospitals, patients’ mental health is monitored at regular intervals. Typically, clinicians score patients using a Likert scale on multiple criteria including hostility. Having an overview of patients’ scores benefits staff members in at least three ways. First, the scores may help adjust treatment to the individual patient; second, the change in scores over time allows an assessment of treatment effectiveness; third, the scores may warn staff that particular patients are at high risk of turning violent, either before or after release. Practical importance notwithstanding, current practices for the analysis of mental health scores are suboptimal: evaluations from different clinicians are averaged (as if the Likert scale were linear and the clinicians identical), and patients are analyzed in isolation (as if they were independent). Uncertainty estimates of the resulting score are often ignored. Here we outline a quantitative program for the analysis of mental health scores using cultural consensus theory (CCT; Anders & Batchelder, 2015). CCT models take into account the ordinal nature of the Likert scale, the individual differences among clinicians, and the possible commonalities between patients. In a simulation, we compare the predictive performance of the CCT model to the current practice of aggregating raw observations and, as an alternative, against often-used machine learning toolboxes. In addition, we outline the substantive conclusions afforded by the application of the CCT model. We end with recommendations for clinical practitioners who wish to apply CCT in their own work.

Hierarchical Paired Comparison Modeling, A Cultural Consensus Theory Approach

We introduce a set of models designed to analyze datasets involving responses from multiple subjects on pairwise comparisons from a fixed discrete set of alternatives.These models are part of a greater body of work known as Cultural Consensus Theory (CCT). Like other CCT models, these simultaneously infer each individual's tendency toward aligning with the group consensus, level of agreement on each item, and also a latent consensus value of each alternative. Two primary models are discussed, referred to as the Strong and Weak Consensus Paired-Comparison Models (SCPCM and WCPCM respectively). The SCPCM works under the assumption that all individuals are answering in accordance to the latent consensus values but with varying degrees of accuracy, while the WCPCM relaxes this assumption and assumes minor deviations from latent consensus values in people's average valuation of alternatives. The WCPCM also includes inferences on participants' individual tendencies toward self-consistency (related to their tendencies toward committing violations of transitivity) as well as inferences on the tendency of each item to be evaluated consistently by individuals. The Case III Thurstonian model is used as the backbone for both CPCMs, and inference is conducted under a hierarchical Bayesian framework. Model checks along with applications to both simulated and real data are overviewed.

A Formal Method for Detecting and Describing Cultural Complexity

The most widely used formal approach to culture, the cultural consensus theory (CCT) of Romney, Weller, and Batchelder, originally relied on a priori definitions of cultural groups to map their unity and diversity. Retaining key features of classical CCT, we provide techniques to identify two or more cultural subgroups in a sample, whether those groups are known in advance or not. Our method helps CCT practitioners connect to contemporary approaches to culture in anthropology and related disciplines, which emphasize complexity. We suggest that our method provides reasonable and easily implementable approximations of cultural unity and diversity within a sample. In pursuing these matters, we contribute to other ongoing efforts to bring CCT closer to contemporary theorizing on cultural multiplicity, thus rendering CCT potentially more useful to a wider range of practicing social scientists.

What does it mean to feel loved: Cultural consensus and individual differences in felt love

Cultural consensus theory is a statistical framework (CCT) for the study of individual differences in the knowledge of culturally shared opinions. In this article, we demonstrate how a CCT analysis can be used to study individual differences and cultural consensus on what makes people feel loved, or more generally any social behaviors that are governed by cognitive schemata. To highlight the advantages of the method, we describe a study in which people reported on their everyday experiences of feeling loved. Our unique approach to understanding this topic is to focus on people’s cognitive evaluations on what feeling loved (both romantically and nonromantically) entails by exploring the shared agreement regarding when one is most likely to feel loved and the individual differences that influence knowledge of these shared agreements. Our results reveal that people converge on a consensus about indicators of expressed love and that these scenarios are both romantic and nonromantic. Moreover, people show individual differences in (1) the amount of knowledge they have about this consensus and (2) their guessing biases in responding to items on love scenarios, depending on personality and demographics—all conclusions made possible by the CCT method.