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While echocardiographic parameters are used to quantify ventricular function in infants with single ventricle physiology, there are few data comparing these to invasive measurements. This study correlates echocardiographic measures of diastolic function with ventricular end-diastolic pressure in infants with single ventricle physiology prior to superior cavopulmonary anastomosis.
Data from 173 patients enrolled in the Pediatric Heart Network Infant Single Ventricle enalapril trial were analysed. Those with mixed ventricular types (n = 17) and one outlier (end-diastolic pressure = 32 mmHg) were excluded from the analysis, leaving a total sample size of 155 patients. Echocardiographic measurements were correlated to end-diastolic pressure using Spearman’s test.
Median age at echocardiogram was 4.6 (range 2.5–7.4) months. Median ventricular end-diastolic pressure was 7 (range 3–19) mmHg. Median time difference between the echocardiogram and catheterisation was 0 days (range −35 to 59 days). Examining the entire cohort of 155 patients, no echocardiographic diastolic function variable correlated with ventricular end-diastolic pressure. When the analysis was limited to the 86 patients who had similar sedation for both studies, the systolic:diastolic duration ratio had a significant but weak negative correlation with end-diastolic pressure (r = −0.3, p = 0.004). The remaining echocardiographic variables did not correlate with ventricular end-diastolic pressure.
In this cohort of infants with single ventricle physiology prior to superior cavopulmonary anastomosis, most conventional echocardiographic measures of diastolic function did not correlate with ventricular end-diastolic pressure at cardiac catheterisation. These limitations should be factored into the interpretation of quantitative echo data in this patient population.
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.
This book reports the findings of a cross-cultural study to update and extend the groundbreaking Boston Couples Study and other research on intimate relationships. It develops comprehensive models of relationship dynamics and makes explicit comparisons across relationship types and cultural regions, which are missing in the research literature. It is written in a style appropriate for college students, researchers, therapists, and others.
In 1972, Zick Rubin, Anne Peplau, and I began a pioneering longitudinal study of college-age dating couples, known as the Boston Couples Study. This research has been cited in numerous textbooks and journal articles. Our first of many articles (Hill, Rubin, & Peplau, 1976) has been cited more 750 times (Google Scholar, 2018).
Blau (1964) viewed social interaction as a process of social exchange, in which one person gives rewards to another, and the other is obligated to reciprocate by giving something appropriate back. We are taught a norm that we are supposed to reciprocate (such as Christmas gifts and birthday presents), but even more important is the need to reciprocate to obtain future rewards. What is exchanged includes not only tangible things like goods and assistance but also intangible things like advice and love. For example, mothers who unselfishly do things for their children want love in return.
Maslow argued that the set of needs listed on the bottom must be met first; then when each set is met, the next higher set emerges. While it is true that the bottom level is necessary for survival, the answers to the cognitive and aesthetic needs teach us how to meet all of the other needs. And meeting social needs provides social support to cope with the stresses involved in meeting needs. Hence, the hierarchical nature of the needs can be questioned.
Social and other needs provide reasons and goals for seeking intimate relationships. Baumeister and Leary (1995) argued that humans have a fundamental need for belonging, and this is included as relatedness along with autonomy and competence as three primary motivations in Self-Determination Theory (Ryan & Deci, 2017). A lack of interpersonal relationships can lead to loneliness (Peplau & Perlman, 1982). Weiss (1974) distinguished between two types of loneliness: emotional (due to lack of intimate relationships) and social (due to lack of a social network). DiTommaso and Spinner (1997) further distinguished between romantic emotional loneliness and family emotional loneliness. Hence, avoiding loneliness is a major reason for seeking an intimate relationship. In the Boston Couples Study, those who broke up reported feeling lonely and depressed (Hill, Rubin, & Peplau, 1976). In addition, loneliness is a major risk factor for mortality, as important as physical factors (Holt-Lunstad et al., 2015).
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.
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.
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.
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.
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).
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.
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.
To understand the present study, it is important to have certain tools for thinking. These include conceptual tools, which consist of the concepts used to categorize study participants for comparisons, as well as theoretical concepts for explaining which factors were measured and why they matter. They also include statistical tools for making comparisons and determining how much the factors matter. Statistical tools are used to reveal the results throughout this book. This chapter reviews these conceptual and statistical tools to facilitate the reader’s understanding of this study, as well as other research on intimate relationships.
There are various ways of being intimate, including physical (touching, hugging, kissing, sexual), emotional (sharing feelings), cognitive (sharing thoughts), and experiential (sharing activities), as noted by Kakabadse and Kakabadse (2004). There are also many kinds of intimate relationships, including friendships, dating, marriage, and other relationships among family members or non-relatives. This book focuses primarily on dating, marriage, and other romantic or sexual relationships.