Sunday, April 3, 2016

Do People Agree on What Makes One Feel Loved? A Cognitive Psychometric Approach to the Consensus on Felt Love

This pragmatic study examines love as a mode of communication. Our focus is on the receiver side: what makes an individual feel loved and how felt love is defined through daily interactions. 

Our aim is to explore everyday life scenarios in which people might experience love, and to consider people’s converging and diverging judgments about which scenarios indicate felt love. We apply a cognitive psychometric approach to quantify a receiver’s ability to detect, understand, and know that they are loved. 

Through crowd-sourcing, we surveyed lay participants about whether various scenarios were indicators of felt love. We thus quantify these responses to make inference about consensus judgments of felt love, measure individual levels of agreement with consensus, and assess individual response styles. More specifically, we 
  1. derive consensus judgments on felt love; 
  2. describe its characteristics in qualitative and quantitative terms, 
  3. explore individual differences in both 
    1. participant agreement with consensus, and
    2. participant judgment when uncertain about shared knowledge, and 
  4. test whether individual differences can be meaningfully linked to explanatory variables. 
Results indicate that people converge towards a shared cognitive model of felt love. Conversely, respondents showed heterogeneity in knowledge of consensus, and in dealing with uncertainty. We found that, when facing uncertainty, female respondents and people in relationships more frequently judge scenarios as indicators of felt love. Moreover, respondents from smaller households tend to know more about consensus judgments of felt love, while respondents from larger households are more willing to guess when unsure of consensus.

Below:  Raw data means and model based estimates on selected felt love items.
The second columns shows the mean of the answers for the item with ‘True’ coded as 1 and ‘False’ as 0. The posterior distribution on the consensus parameters for each item is summarized in columns 3 and 4, in terms of posterior median estimate, labeled as ‘True’ for 1 and ‘False’ for 0 and posterior standard deviation (abbreviated as ‘psd’). It quantifies standard error around the point estimate. The last column shows the item difficulty rank of the item in ascending order. 

Full article at:

Zita Oravecz, Chelsea Muth 
Human Development and Family Studies, The Pennsylvania State University, State College, PA, United States of America

Joachim Vandekerckhove 
Cognitive Sciences, University of California Irvine, Irvine, CA, United States of America

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