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Similarity can occur in terms of social characteristics, personal characteristics, and attitudes and values. Similarity is important because there needs to be something in common that brings individuals together and serves as a basis for interaction. How strong the similarity needs to be depends on the kind of social relationship, from strangers with little in common, to friends with some things in common, to lovers ideally with much in common. However, perceived similarity is often more important than actual similarity (Montoya, Horton, & Kirchner, 2008).
To capture the complex predictions from the previous chapters, these predictions are summarized in this chapter and combined to create a Comprehensive Partner Model and a Comprehensive Commitment Model. The chapter discusses how well these models predict, what is surprising about the findings, and why the same factors make similar predictions across relationship types and cultural regions.
Chapter 1 noted that when predictor factors are correlated with each other, what they predict in common may be accounted for by the factor with the strongest effect, leaving little additional variance to be accounted for by other factors correlated with it. This may be reflected in low standardized regression coefficients for the other factors, even if they have sizable correlations with the dependent variable. The strongest predictor factors that are correlated with other predictor factors and capture what they predict in common, or have additional effects beyond what they have in common, are called Central Factors in this book.
Variations in the levels of factors that predict Having a Current Partner, and variations in the levels of factors that predict Relationship Satisfaction and Relationship Commitment, are explored in this chapter. These variations are discussed in terms of overall means and standard deviations, and variations in means across relationship types and across cultural regions.
The means (averages) and standard deviations (s.d.) of Having a Current Partner and of the Comprehensive Factors predicting Having a Current Partner are listed in Table 11.1. The standard deviations indicate the amount of individual variation in responses across all participants in the study. The possible responses for Having a Current Partner and for having had a previous partner are 0=NO to 1=YES, hence those means indicate percentages expressed as decimals. Age varied from 18 to 84. The other factors have possible responses from 0=NOT AT ALL to 8=EXTREMELY.
This chapter discusses the limitations of the study, how the findings compare with the Boston Couples Study, and the implications of the study for self-reflection, couples’ counseling, and well-being.
Since the study is online (except in Pakistan), participants are limited to those who have access to the internet and to those willing to answer an extensive online questionnaire. They are likely to be younger, since older persons may be less familiar with computers. And they are likely to be better educated than the general public. Issues in using the internet for research are discussed by Gosling et al. (2004), Van Selm and Jankowski (2006), and Fraley (2007). Additional sampling issues in relationship research are discussed by Hill et al. (1979), de Jong Gieveld (1995), and Karney et al. (1995).
William James and Carl Lange proposed in the 1880s that every emotion has a unique pattern of physiological responses (Cannon, 1927), but when researchers studied emotional responses, they found overlapping responses, such as increased heart rate for anger, fear, and surprise. So Schachter and Singer (1962) proposed that all emotions have the same physiological arousal, and what differentiates them is labeling based on cognitive cues. For example, my heart is racing and I look around and see that I am in a street and a car is approaching me; therefore, I must be afraid.
But while physiological responses often overlap among emotions, they are not always the same. For example, blood rushes to the face when angry but away from the face when frightened, and heart rate slows when sad. And in most cases, the cue comes before the arousal and indeed causes the arousal, e.g., my heart is racing because I saw the approaching car. Hence, researchers thought it was impossible to measure emotions, including love.
In the Boston Couples Study, whether or not the couple had sexual intercourse did not predict whether the couple stayed together during the two years of the original study (Hill, Rubin, & Peplau, 1976), nor did it predict eventual marriage and staying married on the fifteen-year follow-up (Hill & Peplau, 1998).
Interviews revealed that there were three attitudes about love and sex (Peplau, Rubin, & Hill, 1977). Those who were called sexual traditionalists believed that premarital sex was wrong. One man said in an interview that he wanted to have sex with his girlfriend, but she believed it was wrong, so out of love and respect for her he did not pressure her to have sex. Those who were called sexual moderates believed that casual sex was wrong, but that sex was okay when a relationship reached a certain level of love and commitment. And those who were called sexual liberals believed that sex was okay even if you were not in love, and they often found that physical intimacy increased emotional intimacy. It is now understood why that occurs: orgasm releases oxytocin, which promotes emotional bonding (Crenshaw, 1996).
In the present study, conflict is measured by asking, “To what extent has each of the following been a source of conflict with CP?” Nine of the topics, marked with an asterisk (*), are similar to ones from Rivera Aragón, Díaz- Loving, and Cruz del Castillo (2005). The others are written especially for this study and include topics recently cited as top issues in marital conflict (Whitton et al., 2018).
The possible responses are from 0=NOT AT ALL to 8=EXTREMELY. The overall means and standard deviations are listed Table 7.1 in order from highest to lowest.
Previous research has indicated that social relationships are important predictors of well-being, but that the quality of the relationships is more important than merely having the relationships (Saphire-Bernstein & Taylor, 2013).
Happiness is viewed by psychologists as an emotional response, while life satisfaction is viewed as a cognitive evaluation (Diener, Oishi, & Lucas, 2002). Across a sample of 123 countries, Tay and Diener (2011) found that positive feelings were most associated with fulfilling social and esteem needs, while life evaluation was most associated with fulfilling basic needs such as food and shelter.
As noted in the Introduction to this book, there has been a great deal of research on relationships, but very little of it has been cross-cultural. Even less has involved relationships other than marriage. A notable exception is a recent anthology about grandparents in various cultures (Schwalb & Hossain, 2017). Also of interest is a one-year longitudinal study that found that Rusbult’s Investment Theory predicted staying best friends among adolescents in the Netherlands (Branje et al., 2007). Another study explored social support among siblings (brothers or sisters) in the Netherlands (Voorpostel & Blieszner, 2008).
Chapter 1 introduced the statistical tools and conceptual tools used in this book. Future research is needed using these tools in the following ways.
Research on mate selection has taken two approaches. One approach is to study mate selection criteria, asking people how important various characteristics are in selecting a mate. The other approach is to study matching between spouses in married couples.
From an evolutionary psychology perspective, it has been argued that men are seeking women who are physically attractive, as an indicator of fertility, while women are seeking men of high status, to support themselves and their offspring (Buss, 1989). Yet the mean ratings in Buss’s data indicate that both physical attractiveness and social status were rated only moderately important for both men and women across thirty-seven countries, even though there were gender differences.
Historically, parents often arranged marriages (Hunt, 1959). People married at a young age, and it was believed that marriage was too important to be left to the whims of adolescents. Marriages were often used to consolidate land holdings and political alliances, ensure the passing on of cultural traditions and religious beliefs, and preserve or move upward in social status. Marriages based on love became more widespread about the time of the Industrial Revolution, when land holding became less critical as many moved from farms to cities. It was especially common in the United States, where young immigrants were often freer from the influence of parents back in the old country.
Intimate relationships exist in social domains, in which there are cultural rules regarding appropriate behaviors. But they also inhabit psychological domains of thoughts, feelings, and desires. How are intimate relationships experienced by people living in various types of romantic or sexual relationships and in various cultural regions around the world? In what ways are they similar, and in what ways are they different? This book presents a cross-cultural extension of the findings originating from the classic Boston Couples Study. Amassing a wealth of new data from almost 9,000 participants worldwide, Hill explores the factors that predict having a current partner, relationship satisfaction, and relationship commitment. These predictions are compared across eight relationship types and nine cultural regions, then uniquely combined in a Comprehensive Partner Model and a Comprehensive Commitment Model. The findings test the generalizability of previous theories about intimate relationships, with implications for self-reflection, couples counseling, and well-being.