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Attitude Similarity and Familiarity and Their Links to Mental Health: An Examination of Potential Interpersonal Mediators

Ms. shannon moore.

University of Utah, Psychology, 380 S., 1530 E., Room 502, Salt Lake City, 84112-0251 United States

Dr. Bert Uchino

University of Utah, Psychology, Salt Lake City, United States

Dr. Brian Baucom

Arwen behrends, dr. david sanbonmatsu.

Similarity and familiarity with partner's attitudes ( Byrne, Clore, & Smeaton, 1986 ; Sanbonmatsu, Uchino, & Birmingham, 2011 ) are linked to positive relationship outcomes, while interpersonal variables have been linked to mental health (e.g., Lakey & Cronin, 2008 ). Using multilevel models (MLMs), we modeled the associations between these attitudinal variables and mental health outcomes in 74 married couples. We found that higher levels of attitude similarity in couples were linked to lower depression, while higher levels of attitude familiarity in couples were associated with greater satisfaction with life. Mediational analyses indicated marital satisfaction and interpersonal stress mediated the link between attitude similarity and depression. Marital satisfaction also mediated the link between familiarity and satisfaction with life. This study is the first linking attitude familiarity to mental health and provides evidence that familiarity and similarity have mental health effects partly due to their interpersonal consequences.

Attitudes have long been recognized to play a central role in guiding individual behavior and decisions (e.g., Ajzen & Fishbein, 1977 ; Blascovich, Ernst, Tomaka, Kelsey, Salomon, & Fazio, 1993 ). Attitudes are evaluations of and feelings toward objects, persons, situations, issues, events, and behaviors that are stored in memory (e.g., Petty & Cacioppo, 1981 ; Sanbonmatsu, Posavac, Vanous, Ho, & Fazio, 2007 ). Increasingly, attitudes are also being shown to play an important role in interpersonal behavior and relationships. Several studies have found that similarity in attitudes is related to partners' liking of one another ( Byrne, Clore, & Smeaton, 1986 ; Gaunt, 2006 ; Luo & Kohnen, 2005 ). More recently, research has shown that familiarity with partners' attitudes may be vital to providing support, avoiding conflict, and maintaining close relationships ( Sanbonmatsu, Uchino, Wong, & Seo, 2012 ). The interpersonal benefits of attitude similarity and attitude familiarity are important because they have been linked to physical health outcomes ( Sanbonmatsu, Uchino, & Birmingham, 2011 ). Our research investigated the possibility that these benefits extend to mental health as well. More specifically, we examined whether attitude similarity and familiarity have important mental health consequences through their effects on interpersonal functioning.

Prior work has established that similar people are attracted to one another and have closer and more lasting relationships ( Byrne et al., 1986 ; Gaunt, 2006 ; Luo & Klohnen, 2005 ). One specific measure of similarity in couples is attitude similarity. Attitude similarity refers to the extent to which individuals' attitudes are similar to one another. Luo and Kohnen (2005) measured similarity in terms of couples' personality traits, as well as values, political attitudes, and religiosity and concluded that while similar personalities are linked to marital satisfaction, similar values, attitudes (in this case, political attitudes), and religiosity were not related to marital satisfaction. A related study found that while similarity in personality traits and value domains showed a strong and consistent association with relationship satisfaction, similarity of attitudes (i.e., attitudes toward family roles) and religiosity showed weaker, less consistent patterns ( Gaunt, 2006 ). Previous studies may have failed to find an association between attitude similarity and relationship quality because the measurement of attitudes was limited to narrow domains (i.e., political attitudes and attitudes toward family roles). We anticipated that a broader measure of the similarity of partners' likes and dislikes would be more predictive of interpersonal processes.

Attitude Familiarity and Interpersonal Functioning

A more recently developed construct is attitude familiarity, which refers specifically to knowledge of another person's attitudes. Couples in general tend to have more accurate impressions of one another than those not in interdependent relationships ( Fiske & Neuberg, 1990 ). Greater knowledge of one's partner has been linked to successful relationship outcomes, such as greater feelings of partner intimacy ( Swann, De La Ronde, & Hixon, 1994 ) and greater relationship satisfaction ( Gottman, 1994 ). Furthermore, Swann, Hixon, and De La Ronde (1992) found that when people have negative self-views, they “displayed more commitment to spouses who evaluated them unfavorably than to spouses who evaluated them favorably” (p. 120). Thus, there are even positive consequences for relationships when a partner verifies a spouse's negative identity. Neff and Karney (2005) found that the extent to which wives' perceptions of their husbands' traits matched their husbands' self-reports predicted higher feelings of control in the relationship, more support behaviors, and a decreased likelihood of divorce.

Prior research indicates that our own attitudes guide information processing ( Lord, Ross, & Lepper, 1979 ), appraisals of situations and response alternatives ( Sanbonmatsu & Fazio, 1990 ), and behavior ( Ajzen & Fishbein, 1977 ). Familiarity with the attitudes of others may be similarly functional, enabling an individual to more easily avoid conflict and better fulfill partners' support needs. Sanbonmatsu et al. (2011) found that partners more familiar with each other's attitudes reported more positive interactions and higher state self-esteem during daily life. A follow-up study ( Sanbonmatsu et al., 2012 ) found that familiarity with partners' attitudes was associated with reports of lower fighting and upsetting one another, more helpful behavior, and higher levels of affiliation.

Attitude similarity is positively correlated with attitude familiarity ( Sanbonmatsu et al., 2012 ). However, prior research indicates that attitude similarity and familiarity, while overlapping, are distinct from one another. Sanbonmatsu et al. (2012) found that attitude familiarity continued to predict less fighting, conflict and upset, somewhat greater affiliation, and global relationship importance after statistically controlling for the effects of attitude similarity. Thus, it does not appear that attitude familiarity is simply capturing the effects of attitude similarity. Research supports the idea that the two constructs are differentially related to interpersonal variables like conflict and support.

Based on prior research, we expected both attitude similarity and familiarity would be linked to interpersonal outcomes. Might these links have consequences for mental health? At a broad level, the break-up of a romantic relationship has been associated with increases in psychological distress and declines in life satisfaction (e.g., Rhoades, Kamp Dush, Atkins, Stanley, & Markman, 2011 ). Additionally, important interpersonal variables such as social support are linked to lower rates of depression ( Lakey & Cronin, 2008 ), lower levels of psychological distress ( Barrera, 1986 ; Cohen & Wills, 1985 ), and negative affect ( Finch, Okun, Pool, & Ruehlman, 1999 ).

Prior research on trait similarity in couples suggests that attitude similarity would also have mental health consequences. Trait similarity in couples is linked to happiness. For instance, when both partners rated high on femininity, they reported being happier than couples where one partner was low on femininity ( Antill, 1983 ). Arrindell and Luteijn (2000) studied married or cohabiting couples and measured several personality dimensions, finding that higher satisfaction with life was linked to greater similarity in partners' personalities.

We have proposed previously that one benefit of attitude familiarity is its influence on interpersonal processes, such as the provision of social support. Greater knowledge of a partner's preferences should allow a person to provide his or her partner with better support. While attitude familiarity has not been directly tied to social support, various findings support this link. Greater levels of attitude familiarity are associated with reporting more positive interactions ( Sanbonmatsu et al., 2011 ), less fighting and upset, and more helpful behavior ( Sanbonmatsu et al., 2012 ). All of these findings point to the likelihood that attitude familiarity would be associated with greater social support within couples, and this influence may be one way in which attitude familiarity's influence on interpersonal processes would also influence mental health.

Previous research strongly suggests that attitude familiarity and similarity would be related to interpersonal constructs, such as marital satisfaction and interpersonal stress. Additionally, research has linked certain aspects of relationships to mental health outcomes. We hypothesized that attitude familiarity and similarity are linked to mental health through their effects on interpersonal processes. That is, couples that are more familiar with one another's attitudes are also likely more satisfied and experience less conflict. Because of this, we would expect to see mental health benefits also. Couples that have similar attitudes may also be happier because they experience less conflict and higher marital satisfaction. It is important to determine whether attitude familiarity and similarity are related to mental health because it could provide another avenue through which to target improvements in treating people for depression or increasing one's subjective well-being.

The current study sought to establish the links between attitude similarity and familiarity, and mental health, and the potential interpersonal mediators. We thus first examined whether attitude similarity in couples was associated with the mental health outcomes of depression and satisfaction with life, and the relational outcomes of marital satisfaction and interpersonal stress. We then examined those outcomes and their associations with attitude familiarity. Finally, we entered these variables into the model simultaneously to test if attitude similarity and familiarity were unique associations. Following past work, it was hypothesized that attitude similarity and attitude familiarity would be associated with marital satisfaction and interpersonal stress. Additionally, we predicted that attitude similarity and familiarity would be linked to mental health and that their effects on relationship functioning would mediate these associations.

Participants

Seventy-four couples were included in the study. The participants were largely middle-aged (mean age = 56.06), college educated, and White (95.9%), with an average yearly income of $30,000 – $40,000. Because this was part of a larger study of spousal relationship quality and inflammation ( Uchino et al., 2013 ), participants were excluded if they were currently on strong immunosuppressive treatment, or had HIV or cancer. Participants received monetary compensation for serving in the study.

Participants were recruited through advertisements placed in local newspapers, workplace newsletters, and flyers distributed around the community. Potential participants were screened for eligibility and informed consent was obtained. Eligible couples filled out questionnaires, presented in a fixed order. They first filled out demographic and health questionnaires, followed by relationship assessments, and then finished by completing the attitude scales (see below). Spouses completed the questionnaires in the same room. One partner sat in a chair and the other partner sat on a couch on the opposite side of the room. They were unable to see each other's questionnaires and were instructed not to share their answers. They were also guaranteed that their responses would not be shared with their spouse.

Attitude familiarity and similarity

Participants indicated their evaluations of 25 different attitude objects on 7 point scales anchored by -3 very negative and +3 very positive . The items were selected to broadly sample different attitudinal objects (e.g., money, Wal-Mart, guns, recycling) and have been used in our prior work on attitudinal processes (e.g., Fazio, Sanbonmatsu, Powell, & Kardes, 1986 ; Sanbonmatsu et al., 2011 ). Spouses also indicated their perceptions of their partners' evaluations of the same targets on the same scale.

Separate attitude familiarity scores were calculated for each spouse by determining the correlation between each spouse's ratings of his/her partner's attitudes toward the 25 attitude objects and his/her partner's actual reported attitudes. The average level of attitude familiarity in the sample was r = .66 (range .15 to .92). These correlations were transformed into z scores using Fisher's r to z transformation and averaged across spouses to create a couple score of attitude familiarity that was used in all analyses.

Attitude similarity scores for each couple were calculated by determining the correlation between each spouse's attitudes toward the 25 attitude objects. The average level of attitude similarity in the sample was r = .47 (range -.05 to .87). These correlations were transformed into z scores using Fisher's r to z transformation for subsequent analyses.

Marital satisfaction

The Marital Adjustment Test (MAT; Locke & Wallace, 1959 ) is a 15-item scale that is widely used to measure the overall quality of marital relationships. It has good psychometric properties and is able to reliably differentiate between non-distressed and distressed married couples.

Interpersonal stress

The Test of Negative Social Exchange (TENSE; Ruehlman & Karoly, 1991 ) is an 18 item assessment of the extent of conflict in social interactions. The measure has strong psychometric properties and provides an overall assessment of interpersonal stress related to hostility/impatience, insensitivity, interference, and ridicule. This was a measure of general interpersonal stress—not specific to one's partner.

The Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977 ) is a 20 item assessment that measures depressive symptoms. Participants indicate how often they have experienced a depression-related symptom in the past week. The scale is widely used and has demonstrated good psychometric properties.

Satisfaction with life

The Satisfaction with Life scale (SWL) is widely used and measures participants' global judgments of their satisfaction with life ( Diener, Emmons, Larsen, & Griffin, 1985 ). It has strong psychometric properties including good internal consistency and test-retest reliability ( Diener et al., 1985 ).

Statistical analyses

The research questions in the current study focus on how spouses' attitude familiarity and similarity are related to depression, interpersonal stress, marital satisfaction, and satisfaction with life. A series of multilevel models (MLMs) was used to model associations between attitudinal familiarity/similarity and these mental health outcomes while controlling for age, income, education, and gender—standard demographic controls which prior research indicates would be relevant. The following equation illustrates the series of equations for the 2-level model used to examine the association between marital satisfaction and attitude familiarity:

for t = 1 to 4, π ti = β t0

where t indexes partners and i indexes couples. Separate, identical models were run with interpersonal stress, satisfaction with life, and depression as the dependent variable and with attitude similarity substituted for attitude familiarity at level-2. Finally, attitude familiarity and similarity were both included as predictors in models for each outcome. We also examined the interpersonal variables of interpersonal stress and marital satisfaction as potential mediators in predicting depression and satisfaction with life. In all models, attitudinal variables were averaged across spouses and grand mean centered, resulting in single couple scores of attitude familiarity and similarity. This was done in order to allow for examination of between couple associations between attitudinal variables and outcomes. Additionally, age, income, and education were grand mean centered at level-1 to control for within- and between-couple effects of these covariates ( Enders & Tofighi, 2007 ). All MLMS were run in HLM, version 7 ( Raudenbush, Bryk, Cheong, Congdon, & du Toit, 2011 ).

We first examined associations from separate models for attitude similarity (see Table 1 ) and attitude familiarity separately (see Table 2 ) 1 . In these analyses, higher levels of attitude similarity were significantly associated with lower interpersonal stress, higher marital satisfaction, and lower depression. In comparison, greater attitude familiarity was significantly associated with lower levels of interpersonal stress, higher levels of marital satisfaction, and higher levels of satisfaction with life.

Turning to models where attitude similarity and familiarity were simultaneously included as predictors (see Table 3 ), associations between higher levels of attitude similarity and lower levels of depression remained significant ( B = -4.25, p = .02). Similarly, associations between higher levels of attitude familiarity and higher marital satisfaction ( B = 25.58, p < .01) as well as higher levels of satisfaction with life ( B = 3.80, p = .04) remained significant. In contrast, associations between attitude similarity and marital satisfaction ( B = 3.92, p = .63) and attitude similarity and interpersonal stress ( B = -.30, p = .09), as well as associations between attitude familiarity and interpersonal stress ( B = -.22, p = .30) that were significant in the separate models were non-significant in the combined model.

Finally, interpersonal stress and marital satisfaction were examined as potential mediators of associations between attitude similarity and depression and attitude familiarity and satisfaction with life given the independence of these links. The magnitude of mediated effects were determined by calculating the difference between the estimated coefficient for the attitudinal predictor without the mediator included in the model minus the estimated coefficient for the attitudinal predictor with the mediator included in the model (i.e., C – C'; MacKinnon, 2008 ; Preacher & Hayes, 2004 ; Rucker, Preacher, Tormala, & Petty, 2011 ). The significance of these mediated effects was assessed using recommended procedures for estimating nonparametric bootstrapped confidence intervals in MLMs (i.e., empirical M tests; Preacher & Hayes, 2004 ; Tofighi & MacKinnon, 2011 ). Significant mediation is considered to occur when the bootstrapped 95% confidence interval does not include 0.

We first examined whether marital satisfaction mediated the relationship between attitude similarity and depression. Results were consistent with mediation (C – C' = -1.24, 95% CI: -2.88 to -.02). Interpersonal stress was also examined to determine whether it mediated the relationship between attitude similarity and depression. Results were again consistent with mediation (C – C' = -1.30, 95% CI: -2.92 to -.19). Analyses next aimed at examining the interpersonal mediators of the link between attitude familiarity and life satisfaction produced results consistent with mediation for marital satisfaction (C – C' = 1.11, 95% CI: .01 to 2.7) but not interpersonal stress (C – C' = .72, 95% CI: -.07 to 1.99).

The main contribution of our study was to show that knowledge of partner's attitudes and similarity in partners' attitudes are associated with mental health. Attitude familiarity was significantly associated with higher levels of satisfaction with life, an association that was mediated by marital satisfaction. In addition, attitude similarity was linked to lower depression, which was mediated by both marital satisfaction and interpersonal stress. This appears to be the first study showing these associations between these attitudinal processes in couples and mental health outcomes as well as the mechanisms responsible for such links. Importantly, these mechanisms indicate that our findings regarding attitude familiarity and similarity correspond with the many other studies that link interpersonal variables to mental health consequences ( Rhoades et al., 2011 ; Lakey & Cronin, 2008 ; Barrera, 1986 ; Cohen & Wills, 1985 ; Finch et al., 1999 ).

As we reviewed earlier, prior studies have linked trait similarity but not attitude similarity in couples to interpersonal functioning and mental health ( Antill, 1983 ; Arrindell & Luteijn, 2000 ). We examined similarity in couples on a broader range of attitudinal topics than the narrower domains of political attitudes ( Luo & Kohnen, 2005 ) or attitudes toward family roles ( Gaunt, 2006 ) used in the past. Analyses showed that attitude similarity was significantly associated with lower depression in our study, even when controlling for attitude familiarity. Moreover, as we indicated above, our study was novel in showing that the link between similarity in couples and mental health is mediated by interpersonal processes.

An unexpected pattern that emerged in the study was that similarity in partners' attitudes significantly predicted depression while familiarity with partners' attitudes significantly predicted life satisfaction. The statistical meaningfulness of this pattern may be questionable, as the relation between attitude familiarity and depression also approached significance. Additionally, although attitude similarity was not associated with happiness in our study, Arrindell and Luteijn (2000) previously found that couples that were more similar on various personality dimensions reported higher satisfaction with life in a study characterized by greater statistical power. Nevertheless, there may be at least one theoretically-based reason for attitude similarity to be strongly linked to depression. Although similarity in attitudes affects liking ( Byrne et al., 1986 ), the level of satisfaction with a relationship may be driven more heavily by the dissimilarity between partners ( Rosenbaum, 1986 ). Measures of attitude similarity may be more predictive of negative mental health outcomes such as depression than positive mental health outcomes such as life satisfaction because dissimilarity contributes to discord more than similarity contributes to harmony.

Marital satisfaction and mental health have been associated with biased perceptions of partners and relationships (e.g., Fletcher & Kerr, 2010 ). This suggests an alternative model to the one that was investigated in our study in which relationship satisfaction and mental health influence perceptions of attitude similarity and familiarity. However, it is important to recognize that we did not measure perceived similarity or perceived familiarity in our study. Rather, we measured actual similarity in attitudes and actual knowledge of partners' attitudes—interpersonal factors that are not directly influenced by subjective biases. Nevertheless, there is the possibility that relationship satisfaction and mental health may affect the time partners spend together which, in turn, may affect their familiarity. Another possibility to consider is that couples that are more satisfied become more similar over time. However, past studies suggest that convergence in couples is unlikely. For example, Luo & Klohnen (2005) examined whether relationship length was linked to similarity in couples and concluded that partner similarity was likely not due to convergence.

There are several important limitations of the current study. First, inferences are necessarily limited by the cross-sectional design. Future longitudinal or laboratory research will be needed to address this limitation. Second, the study only looked at sub-clinical levels of mental health so generalizations to clinical samples are not warranted. Nevertheless, this study is the first to show that attitude familiarity and similarity are related to mental health, and that interpersonal processes mediate such links. Our research suggests that individuals who find romantic partners with similar likes and dislikes are more apt to have satisfying relationships which contribute to better mental health.

The findings further indicate that we may be able to improve relationships and, hence, mental health by learning more about our partner's attitudes. One intervention for couples that are struggling or simply hoping to improve upon their relationships may be to make a concentrated effort to learn more about each others' likes and dislikes. By doing this, we would expect improvements not only in the relationship but also for subjective well-being. Establishing feelings or likes that one has in common with a partner or simply learning more about a partner's preferences could also have far greater influence that we would initially suspect. These fairly simple attempts to establish common ground or learn more about another person could help us decrease the amount of conflict and make us more satisfied with that relationship. In addition to improving interpersonal relations, this could then ultimately enhance our own sense of well-being.

1 Several error structures were examined, including standard MLM, homogenous compound symmetry, and heterogeneous compound symmetry. The results were found to be the same in terms of magnitude, direction, significance of effects, and resulted in identical substantive conclusions. Here, results are presented based on homogenous compound symmetry, as it is the simplest error structure.

Contributor Information

Ms. Shannon Moore, University of Utah, Psychology, 380 S., 1530 E., Room 502, Salt Lake City, 84112-0251 United States.

Dr. Bert Uchino, University of Utah, Psychology, Salt Lake City, United States.

Dr. Brian Baucom, University of Utah, Psychology, Salt Lake City, United States.

Arwen Behrends, University of Utah, Psychology, Salt Lake City, United States.

Dr. David Sanbonmatsu, University of Utah, Psychology, Salt Lake City, United States.

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9.4 Coupling and Repulsion (cis and trans) Configuration

Just by looking at an organism that is heterozygous at two loci, you cannot tell how the mutant and wild type alleles are arranged. Both mutant alleles could be on one homologous chromosome, and both wild type alleles could be on the other (e.g., a – b – / A + B + ). This is known as a coupling (or cis) configuration . When one wild type allele and one mutant allele are on one homologous chromosome, and the opposite is on the other, this is known as a repulsion (or trans) configuration (e.g., A + b – / a – B + ). The way to determine the orientation is to look at the parents (or P generation) of that cross if you know the genotypes of them. If the parents are homozygous for both genes, and one shows both dominant phenotypes and the other shows both recessive phenotypes, then you know that the individual you are looking at is in coupling configuration. If one parent has one dominant and one recessive phenotype, and the other has the opposite, then you know the individual is in repulsion configuration.

The following video, Genetics! coupling (cis) vs Repulsion (trans) , by Medaphysics Repository (2015) on YouTube, discusses the difference between cis and trans genes.

The video, Coupling vs Repulsion, by Genetics Rocks (2019) on YouTube, looks at a worked example involving observed frequencies in a text cross and genes in coupling/repulsion.

Media Attributions

• Figure 9.4.1 Original by Deyholos (2017), CC BY-NC 3.0 , Open Genetics Lectures

Deyholos, M. (2017). Figure 5. Alleles in coupling configuration…[digital image]. In Locke, J., Harrington, M., Canham, L. and Min Ku Kang (Eds.),  Open Genetics Lectures, Fall 2017 (Chapter 18, p. 4). Dataverse/ BCcampus. http://solr.bccampus.ca:8001/bcc/file/7a7b00f9-fb56-4c49-81a9-cfa3ad80e6d8/1/OpenGeneticsLectures_Fall2017.pdf

Genetics Rocks. (2019, September 14). Coupling vs repulsion (video file). YouTube. https://www.youtube.com/watch?v=llNZP1Wmgok

Medaphysics Repository. (2015, February 24). Genetics! coupling (cis) vs Repulsion (trans) (video file). YouTube. https://www.youtube.com/watch?v=4y5vjhMq6iY

Long Description

• Figure 9.4.1 Two cells showing alleles in either the coupling or cis configuration (whereby both mutant alleles are present on one homologous chromosome, and both wild type alleles are present on the other) or the repulsion or the trans configuration (whereby one wild type allele and one mutant allele are on one homologous chromosome, and the opposite is on the other). [Back to Figure 9.4.1 ]

Introduction to Genetics Copyright © 2023 by Natasha Ramroop Singh, Thompson Rivers University is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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The sun, along with all other stars, is powered by a reaction called nuclear fusion. If this can be replicated on earth, it could provide virtually limitless clean, safe and affordable energy to meet the world’s energy demand. (Image: NASA/SDO/AIA)

What is Fusion

Five hundred years ago, the Aztec civilization in today’s Mexico believed that the sun and all its power was sustained by blood from human sacrifice. Today, we know that the sun, along with all other stars, is powered by a reaction called nuclear fusion. If nuclear fusion can be replicated on earth, it could provide virtually limitless clean, safe and affordable energy to meet the world’s energy demand.

From 10-15 May, fusion project leaders, plasma physicists and experts in the various multidisciplinary fields of fusion science and technology are gathering for the ‘ 28th IAEA Fusion Energy Conference ’ (FEC 2020). Exploring key physics and technology issues as well as innovative concepts of direct relevance to the use of nuclear fusion as a future source of energy, FEC 2020 is completely virtual and open for anyone to attend. Register to attend .

So how exactly does nuclear fusion work? Simply put, nuclear fusion is the process by which two light atomic nuclei combine to form a single heavier one while releasing massive amounts of energy. Fusion reactions take place in a state of matter called plasma — a hot, charged gas made of positive ions and free-moving electrons that has unique properties distinct from solids, liquids and gases.

To fuse on our sun, nuclei need to collide with each other at very high temperatures, exceeding ten million degrees Celsius, to enable them to overcome their mutual electrical repulsion. Once the nuclei overcome this repulsion and come within a very close range of each other, the attractive nuclear force between them will outweigh the electrical repulsion and allow them to fuse. For this to happen, the nuclei must be confined within a small space to increase the chances of collision. In the sun, the extreme pressure produced by its immense gravity create the conditions for fusion to happen.

The amount of energy produced from fusion is very large — four times as much as nuclear fission reactions — and fusion reactions can be the basis of future fusion power reactors. Plans call for first-generation fusion reactors to use a mixture of deuterium and tritium — heavy types of hydrogen. In theory, with just a few grams of these reactants, it is possible to produce a terajoule of energy, which is approximately the energy one person in a developed country needs over sixty years.

A mixture of deuterium and tritium — two hydrogen isotopes — will be used to fuel future fusion power plants. Inside the reactor, deuterium and tritium nuclei collide and fuse, releasing helium and neutrons. (Image: IAEA/M. Barbarino)

Reaching for the stars

While the sun’s massive gravitational force naturally induces fusion, without that force a higher temperature is needed for the reaction to take place. On earth, we need temperatures exceeding 100 million degrees Celsius and intense pressure to make deuterium and tritium fuse, and sufficient confinement to hold the plasma and maintain the fusion reaction long enough for a net power gain, i.e. the ratio of the fusion power produced to the power used to heat the plasma.

While conditions that are very close to those required in a fusion reactor are now routinely achieved in experiments, improved confinement properties and stability of the plasma are needed. Scientists and engineers from all over the world continue to test new materials and design new technologies to achieve fusion energy.

Nuclear fusion and plasma physics research are carried out in more than 50 countries, and fusion reactions have been successfully achieved in many experiments, albeit without demonstrating a net fusion power gain. How long it will take to recreate the process of the stars will depend on mobilizing resources through global partnerships and collaboration.

A history of collaboration

Ever since nuclear fusion was understood in the 1930s, scientists have been on a quest to recreate and harness it. Initially, these attempts were kept secret. However, it soon became clear that this complex and costly research could only be achieved through collaboration. At the second United Nations International Conference on the Peaceful Uses of Atomic Energy, held in 1958 in Geneva, Switzerland, scientists unveiled nuclear fusion research to the world.

The IAEA has been at the core of international fusion research. The IAEA launched the Nuclear Fusion journal in 1960 to exchange information about advances in nuclear fusion, and it is now considered the leading periodical in the field. The first international IAEA Fusion Energy Conference was held in 1961 and, since 1974, the IAEA convenes a conference every two years to foster discussion on developments and achievements in the field.

After two decades of negotiations on the design and location of the world’s largest international fusion facility, ITER was established in 2007 in France, with the aim of demonstrating the scientific and technological feasibility of fusion energy production. The ITER Agreement is deposited with the IAEA Director General. After ITER, demonstration fusion power plants , or DEMOs are being planned to show that controlled nuclear fusion can generate net electrical power. The IAEA hosts workshops on DEMOs to facilitate collaboration in defining and coordinating regular DEMO programme activities around the world.

It is expected that fusion could meet humanity’s energy needs for millions of years. Fusion fuel is plentiful and easily accessible: deuterium can be extracted inexpensively from seawater, and tritium can be produced from naturally abundant lithium. Future fusion reactors will not produce high activity, long lived nuclear waste, and a meltdown at a fusion reactor is practically impossible.

Importantly, nuclear fusion does not emit carbon dioxide or other greenhouse gases into the atmosphere, and so along with nuclear fission could play a future climate change mitigating role as a low carbon energy source.

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Empirical studies of the “similarity leads to attraction” hypothesis in workplace interactions: a systematic review

• Open access
• Published: 16 January 2023
• Volume 74 , pages 661–709, ( 2024 )

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• Zoleikha Abbasi   ORCID: orcid.org/0000-0002-8803-2239 1 ,
• Jon Billsberry   ORCID: orcid.org/0000-0002-3015-4196 1 &
• Mathew Todres   ORCID: orcid.org/0000-0001-6496-7809 1  

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Although the similarity-attraction hypothesis (SAH) is one of the main theoretical foundations of management and industrial/organizational (I/O) psychology research, systematic reviews of the hypothesis have not been published. An overall review of the existing body of knowledge is therefore warranted as a means of identifying what is known about the hypothesis and also identifying what future studies should investigate. The current study focuses on empirical workplace SAH studies. This systematic review surfaced and analyzed 49 studies located in 45 papers. The results demonstrate that SAH is valid in organizational settings and it is a fundamental force driving employees’ behavior. However, the force is not so strong that it cannot be overridden or moderated by other forces, which includes forces from psychological, organizational, and legal domains. This systematic review highlights a number of methodological issues in tests of SAH relating to the low number of longitudinal studies, which is important given the predictive nature of the hypotheses, and the varying conceptualizations of attraction measurement.

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1 Introduction

Individuals are positively inclined towards people who are similar to themselves. This simple but striking assertion underpins the similarity-attraction hypothesis (SAH), which frames much relationship and interpersonal attraction research (e.g., Byrne 1971 ; Montoya and Horton 2013 ). According to Byrne ( 1971 ), when people perceive themselves to be similar to other people, they experience positive feelings of attraction towards them. These similarities cover a large number of factors typically separated into demographic (e.g., race, gender, ethnicity, socio-economic background, and age) and psychological (e.g., personality, values, interests, religion, education, and occupation) divisions. Many studies have shown that similarities in these various forms lead to friendships and other close relationships (e.g., Graziano and Bruce 2008 ; Kleinbaum et al. 2013 ; McPherson et al. 2001 ; Riordan 2000 ).

In work settings, SAH is a double-edged sword. On the one hand, it is a fundamental human drive that underpins effective social interaction in workplaces (e.g., McPherson et al. 2001 ; Montoya and Horton 2012 ), but on the other hand, it can lead to affinity or similarity bias and exclude those unlike the people making decisions (e.g., Björklund et al. 2012 ; Coates and Carr 2005 ; Hambrick 2007 ; O’Reilly et al. 2014 ; Sacco et al. 2003 ). To combat such ‘natural’ biases, most countries have passed laws to protect employees and potential employees who are dissimilar to those currently employed by organizations and who wield considerable power to decide who can enter organizations, who gets promoted, and how people are treated at work. Hence, within organizational settings, there is an eternal conflict at the heart of this field study; a conflict between natural human processes and natural justice.

In the mid 1990s, two reviews of work-related SAH appeared. An unpublished paper by Alliger et al. ( 1993 ) reviewed SAH in the context of personnel selection decision and work relations. Pierce et al. ( 1996 ) reviewed the hypothesis through the lens of romance in the workplace. There do not appear to be any more recent reviews and no broad-sweep reviews of SAH in the workplace. This paper makes a contribution by conducting such a study with the goal of reviewing extant knowledge on SAH in the workplace. Prior to a detailed account of the methods used for our systematic review, we first contextualize the current study by discussing relevant concepts and their evolution over time, namely the SAH and attraction, respectively. In our findings section, we review the cluster of studies providing empirical support for SAH, draw attention to measurement-design issues, and look at the study of SAH during the distinct organizational phases of recruitment and selection, employment, and organizational exit. In the discussion, we further the contribution of the paper with an examination of the paradox of similarity effects in an age when diversity and inclusion are prime considerations for organizations. We also draw out methodological challenges in the extant SAH in the workplace literature.

2 Similarity-attraction hypothesis

Although scientific focus on SAH gathered steam in the 1950s and 1960s (e.g., Byrne 1961 ; Festinger et al. 1950 ; Newcomb 1961 ; Walster et al. 1966 ), it has been studied for much longer. The relation between similarity and interpersonal attraction was mentioned as early as 1870 by Sir Francis Galton, who observed that illustrious men married illustrious women. Terman ( 1938 ) demonstrated that the greater the similarity between husband and wife, the more successful the marriage.

In the 1950s and 1960s, SAH studies focused on the interpersonal space and the role of attribution in attraction. In one of the first examples, Newcomb ( 1961 ) analyzed the establishment of friendships between new students at a college residence. He recorded students’ demographic information, attitudes, values, and beliefs and then measured their interpersonal attraction to each other. He showed that similarity between the students was the main predictor of attraction amongst them. Taking an experimental approach, Byrne and his colleagues used a “bogus stranger” methodology, in which they varied the similarity of a perceiver’s attitudes to those of a stranger, and then quantified the liking of that stranger. In a series of studies (e.g., Byrne 1971 , 1997 ; Byrne and Blaylock 1963 ; Byrne and Clore 1967 ; Byrne and Nelson 1965 ), they demonstrated that attitude similarity delivered more liking of the target.

Byrne and Clore ( 1967 ) presented a reinforcement model to explain the positive relationship between similarity and attraction, in which similarity presents social validation of one’s views of the self and the world, thus helping to satisfy an individual’s needs. The positive influence that is caused by this need fulfillment becomes correlated with its source, namely the similar individual, and leads to their liking. As an alternative, dissimilarity jeopardizes epistemic needs (i.e., the desire for establishing understanding) as it challenges one’s views about the self and the world, and therefore stimulates negative affect that, in turn, becomes linked with the dissimilar person. Consequently, according to Byrne and Clore ( 1967 ), personal attraction is a conditioned reaction to the positive or negative effect that is created by an unconditioned similarity motivation.

While cognition was recognized as an essential aspect of shaping a judgment of another, the data indicated that the more attitudes individuals held in common with each other, the more attracted they were to the other person (Byrne 1971 , 1997 ). This explains why people are attracted to like-minded individuals. Motivation to find others who are similar may have something to do with keeping a person’s perspective coherent with what they already know; people struggle for guaranteed certainty in dealing with the world around them (Byrne et al. 1966 ). Drawing on Newcomb ( 1956 ), Byrne ( 1997 ) argues that a key reason explaining the repeated support for SAH is due to the interpersonal rewards that follow from attraction: “At its simplest level, […] people like feeling good and dislike feeling bad” (Byrne 1997 : 425). Further, assessments of similarity increase the validation of individuals’ values, which leads to attraction, harmony, and cooperation between individuals (Edwards and Cable 2009 ). Thus, the more similar people perceive themselves to be to each other, the more attractive they will be to each other.

Although most SAH studies have researched similarities in peoples’ attitudes, concluding that individuals are more attracted to people with whom they have many shared attitudes (Byrne 1961 ; Byrne et al. 1970 ; Kaptein et al. 2014 ), studies have found that actual similarity in external characteristics (e.g., age, hairstyle) is more predictive of attraction than similarity in psychological characteristics such as cleverness and confidence (Condon and Crano 1988 ; Duck and Craig 1975 ; Montoya et al. 2008 ). Amongst the demographic attributes most commonly studied are age, education, ethnic background, religious affiliation (Gardiner 2022 ; Grigoryan 2020 ), and occupation (Bond et al. 1968 ; Heine et al. 2009 ; Singh et al. 2008 ). A possible explanation for this is that external abilities can be more easily identified and measured. Nevertheless, there is also support for the SAH from studies of psychological similarity. These studies demonstrate that people are attracted to others on the perceived basis of shared attitudes (Newcomb 1961 ; Tidwell et al. 2013 ), personality traits (Griffitt 1966 ; Klohnen and Luo 2003 ), and values (Cable and DeRue 2002 ).

In addition to studies measuring the impact of actual similarity, scholars have also looked at the impact of perceived similarity. Many of these studies show that perceived similarities are better predictors of attraction than real similarities (Condon and Crano 1988 ; Montoya et al. 2008 ), but the impact of actual similarity–attraction is mainly restricted to interactions with associates or impressions of “bogus strangers” in laboratory settings (Sunnafrank 1992 ). Montoya et al. ( 2008 ) found a significant impact of actual similarity on attraction, while the strength of the attraction is highly connected to the interaction of the participants and targets (e.g., romantic partner, confederate, bogus stranger); these findings are typically interpreted to mean that demographic similarity information is a single source of information and that over time other information becomes more important than similarity-derived information.

The positive association of similarity to attraction can be explained by social cognition theory (Bandura 1991 ). According to this theory, people make sense of the world around them by gathering information in suitable cognitive classes or conceptual memory bins. This theory highlights how the role played by the categories of schemas, prototypes, and stereotypes biases decision-making reducing the accuracy and objectiveness of judgments (Fiske and Taylor 2008 ). For example, when people perceive someone who has grown up in the same neighborhood as themselves (same sport and school), it results in approval of them as they match a well-formed and well-understood stereotype in the person’s mind. The same person might be much less comfortable with someone from a different racial group or who comes from a completely different area since the appropriate cognitive ‘bin’ is still very immature and might even be distorted due to a few random encounters with similar stimuli. According to social cognition theory, people judge others not based on individual qualities, but rather on the stereotype held regarding that individual’s group membership (Kulik and Bainbridge 2006 ). Self-categorization theory builds on social cognition theory. It says that people assign people to ingroup and outgroup membership of prototypes. People are not thought of as unique individuals but rather as expressions of the relevant prototype, which is a process of depersonalization. Self-categorization theory suggests people classify their membership internally for themselves and others based on socially defined qualities (Turner and Chelladurai 2005 ). Individuals identify themselves and others into in-group and out-group (Hogg and Terry 2000 ) according to their preconceived notions of fit based on the following amongst other things: gender, age, race, organizational membership, and status (Turner and Chelladurai 2005 ).

3 Attraction

One of the vaguer elements in SAH is the definition of the word “attraction’. In the 1500s, the word ‘attraction’ was a medical phrase referring to the body’s tendency to absorb fluids or nourishment (Oxford English Dictionary 2013). Over time, the meaning of this word changed to the ability for an object to draw an object to itself, and then to the capability of a person to draw another person to him or her (Montoya and Horton 2014 ). Although there are a few studies that explore different definitions of the word, there is considerable variation in how it is conceptualized in SAH studies. Some studies emphasize the behavioral dimension (i.e., “drawing one to another,” Schachter 1959 ), other scholars highlight the emotion and affection (i.e., feeling positive towards another; e.g., Zajonc 1968 ), while others stress cognitive aspects (i.e., inferring positive attributes; e.g., Singh et al. 2007 ). Despite the variety, these all have positive connotations (Berscheid 1985 ; Huston and Levinger 1978 ). More recently, the literature has focused on the definition of attraction as an attitude, but limited the definition to an individual’s direct and positive emotional and/or behavioral response to a specific person (Montoya and Horton 2014 ). In this approach, the definition of attraction concentrates on the quality of someone’s emotional reaction to another person and a behavioral element that shows an individual’s tendency to act in a specific way to another (i.e., choosing to move closer to them). According to Montoya and Horton ( 2014 : 60), “attraction is a person’s immediate and positive affective and/or behavioral response to a specific individual, a response that is influenced by the person’s cognitive assessments”. According to this point of view, the cognitive component is not considered part of attraction, but rather a process of forecasting an attraction reaction (Montoya et al. 2018 ).

Hence, the attraction literature has evolved different terms to describe the various attraction elements: affective attraction, behavioral attraction, and interpersonal attraction (or liking), Footnote 1 among other terms (Montoya and Horton 2020 ). Montoya et al. ( 2018 ) applied behavioral attraction to refer entirely to a self-reported preference for a certain behavioral reaction by using liking and interpersonal attraction to refer to an undifferentiated positive evaluation that comprises both affective and behavioral attraction. Reinforcing variation in definition of the word ‘attraction’, Montoya and Horton ( 2020 ) define attraction as an emotion that ranges from the professional, to the romantic, to the familial, meaning that attraction can be operationalized as an emotion in a wide range of settings (Montoya and Horton 2020 ).

4 Methodology

The goal of this study (Kuckertz and Block 2021 ) is to provide an overview of research findings on SAH as they relate to the workplace and, in particular, how they relate to interactions between people at work. To do this, we conducted a systematic review of SAH adopting the PRISMA (i.e., Preferred Reporting Items for Systematic reviews and Meta-Analyses) approach (Caulley et al. 2020 ; O’Dea et al. 2021 ). We conducted a systematic review that looked for both empirical and theoretical papers published in refereed journals with JCR impact factors that investigate SAH. We only included papers written in English. As there had been no previous systematic reviews of SAH, no date limits were set.

4.1 Search methodology

4.1.1 inclusion criteria.

The following search terms were used to identify studies on SAH: ‘similarity-attraction’, ‘similarity attraction’, ‘similarity leads to attraction’, ‘similarity predicts attraction’, ‘similarity-interpersonal attraction’, ‘similarity to attraction’, ‘similarity/attraction’, ‘dissimilarity-repulsion’, ‘dissimilarity leads to repulsion’, ‘dissimilarity/repulsion’, ‘dissimilarity repulsion’, ‘Rosenbaum’s repulsion hypothesis’. Given the specific nature of these search terms, logical operators were used to find at least one of these terms in the titles, subjects, or abstracts of papers. For thoroughness, we included the reverse hypothesis, dissimilarity leads to repulsion (Rosenbaum 1986 ), in our search.

4.1.2 Exclusion criteria

As we employed relatively complex search strings such as ‘similarity-attraction’, exclusion criteria were not needed at the subject level.

4.1.3 Databases searched

The following databases were searched for articles on SAH: PsycInfo and PsycArticles, Web of Science, and Business Search Complete.

4.2 Search results

Table 1 presents the results of the initial trawl of the databases and shows how these 880 articles were filtered. Since the search yielded articles published before the onset of journal rankings and some journals have subsequently merged or ceased publishing, there were papers in the database that would have been excluded because of the evolution of the journal rather than due to their own inherent qualities. To avoid this, we decided to include any paper in a journal without a JCR impact factor that had been published before 2000 and had received 100 or more citations on Google Scholar. This resulted in five additional papers that otherwise would have been excluded from the dataset.

The final stage of filtering was to eliminate papers not located in organizational, business, or management settings in which similarity comparisons were based on staff-staff, staff-team members, staff-leaders, staff-managers, or staff-supervisors. This led to the removal of a further 275 studies and 8 more which were not empirical. 45 studies emerged containing four papers that featured two separate studies. The final database for this systematic review is therefore 45 papers containing 49 separate studies. Figure  1 shows the chronological distribution of the 45 workplace SAH articles in the dataset.

Chronology of workplace SAH papers

Descriptive details and brief summaries of the 49 employee SAH studies surfaced in this systematic review are presented in Tables 3 , 4 , 5 , 6 , 7 and 8 . They are placed in one of three categories. A total of 22 articles explore demographic similarity (Tables 2 and 3 ), 20 studies in 17 papers study psychological similarity (Tables 4 and 5 ), and seven studies in six papers investigate both psychological and demographic similarity (Tables 6 and 7 ). Demographic similarity involves the comparison of surface-level characteristics, such as gender, age, and race. They are permanent, usually observable, and easily measured (Harrison et al. 1998 ; Jackson et al. 1991 ). Psychological similarity involves deep-level attributes such as values, personality, attitudes, and beliefs (e.g., Engle and Lord 1997 ) and tend to be measured through direct assessment of self-reported perceptions.

5.1 Support for SAH

Just over half of the studies in the dataset yield empirical findings broadly in line with SAH predictions. These breakdown as follows: 11 demographic, 11 psychological, and 4 combined studies. In the demographic studies, similarity in gender, race, age, educational level, political affiliation have all been shown repeatedly to (1) positively associate with trust, job satisfaction, affective commitment, and in-role and extra-role performance, and selection decisions, and (2) negatively associate with staff turnover and related exit outcomes. In the psychological similarity studies, a matching pattern of results can be observed when similarity involves personality, emotional intelligence, and leadership and cognitive style. Such studies demonstrate that the SAH applies as much in organizational settings as it does in other settings. Rather, it is the studies that produce contradictory and asymmetric results that provide a more nuanced understanding of how SAH applies in these settings, particularly in studies of demographic similarity.

For example, Geddes and Konrad ( 2003 ) demonstrated a complex set of results in terms of race and performance feedback. They showed that both white and black employees responded more favorably to performance feedback from white managers demonstrating that SAH interacts with effects from other theories; in this case, status characteristics theory (Ridgeway 1991 ; Ridgeway and Balkwell 1997 ; Webster and Hysom 1998 ). Goldberg ( 2005 ) demonstrated a contrarian finding. Both male and female interviewers favored applicants on the opposite sex, which is better explained by social identity theory (Gaertner and Dovidio 2000 ) than SAH. Chatman and O’Reilly ( 2004 ) demonstrated that women reported a greater likelihood of leaving homogenous groups (i.e., groups comprising members of the same gender) than men, suggesting that other factors are in-play such as status conflict (Carli and Eagly 1999 ; Pugh and Wahrman 1983 ). It seems that SAH may be an underlying and natural driver of human behavior, but it is not such a dominant force in organizational settings that it cannot be moderated or eliminated by alternative forces. Although studies have shown that competing forces can influence the emergence of SAH effects, research is needed to understand the causes, circumstances, and conditions that give rise to this submergence. When and why does the SAH not appear in organizational settings?

5.2 What is attraction?

In these studies, there is considerable variation in the ways that attraction has been defined and conceptualized. Examples of the three different definitions of attraction – affective attraction, behavioral attraction, and interpersonal attraction – could be found in the dataset. Very few of the ways in which attraction has been measured might be regarded as direct measurement of attraction. They may be influenced by attractiveness, but most constructs used as interpretations of attraction in these studies are implicit and (at least) one step away from direct and isolated measures of attractiveness. For example, constructs like affective and normative commitment, perceived trustworthiness of managers, reaction to performance feedback, and organizational citizenship behaviors (OCBs) may all be associated with feeling closer (affective attraction), moving closer (behavior attraction), or liking, but many other factors are simultaneously in play and at the very least require some explanation as to the reasons why and how they relate to attraction. Even the more direct conceptualizations like organizational attractiveness or selection outcomes are confounded by other factors such as the scant and managed information typically available during recruitment and selection processes (Billsberry 2007a ; Herriot 1989 ) and other factors influencing attractiveness choices, such as the need to find a job (Billsberry 2007b ). Overall, one of the biggest weaknesses in tests of SAH in organizational settings is the way that attractiveness has been conceived. An analysis of attraction conceptualizations can be found in Table 8 .

Another noteworthy feature of the constructs used to capture attraction is the infrequency of repetition. Other than selection outcomes (of various sorts), perceptions of leadership, and OCBs (which have quite a tenuous association with attraction as there are many and varied reasons why people might engage in extra-role activities), most of the other constructs feature in just one study, occasionally two. This creates a sense that the field is still in an exploratory mode scoping out relevant relationships. Replication studies would provide confidence in these original findings and bring robustness. Further, there is a danger that the inclusiveness of constructs to represent attraction risks reifying the term. A challenge with such reification is that “scholars unknowingly integrate findings from studies with inconsistent construct definitions, which can create serious threats to validity” (Lane et al. 2006 : 835). To avoid this, construct clarity is essential and an important precondition of theory testing (Fisher et al. 2021 ).

5.3 Measurement and design issues

Most work on SAH has been conducted outside of organizations. Our initial searches of these databases generated 880 journal articles of which only 45 were empirical studies in which the participants were workers and data was collected from them or about them. At the fringes of eligibility, we included analyses of the gender composition of top management teams (TMTs) and members of unions. We also included policy capturing studies that involve employees undertaking some type of experiment to find out what they would do in circumstances relevant to their jobs. But we excluded student samples even when they were performing a work-related task as students are too far detached from the reality of work. Our sample was also limited to studies that set out to examine the SAH rather than studies that adopted a SAH to test other relationships, such as value congruence studies (e.g., Cable and DeRue 2002 ). As such, the studies in the present paper typically employed a design in which a similarity independent variable (IV) predicted (or, more commonly, as a result of the dominance of cross-sectional designs, was associated with) an attractiveness dependent variable (DV). This IV → DV relationship was predicted and used to design the empirical study, which was tested with a variation of it (i.e., different types of similarity or attraction variable), typically with moderators or mediators. As such, similarity is viewed as the fundamental driver of effects and there is an absence of studies exploring why similarity is important to people in workplaces.

This dataset is dominated by cross-sectional (13 demographic (59%), 11 psychological (55%), and 4 combined (57%)) studies, which is counter-intuitive given the inherently predictive nature of the SAH (i.e., similarity leads to attraction). Testing the IV and DV at the same time makes the predictive element of the hypothesis unproven. Cross-sectional designs can, at best, show an association of the two constructs and only imply a predictive relationship (Kraemer et al. 2000 ). To get around the confounds in cross-sectional designs, researchers have adopted (1) experimental designs (2 demographic (9%) and 6 psychological (30%)) that capture policy intentions of organizational members, (2) archival studies (6 demographic (27%), 1 psychological (5%), and 1 combined (14%)), which can capture the historical effects on staff turnover and recruitment of similarity, and (3) longitudinal designs (1 demographic similarity, 2 psychological similarity, and 1 combined study). The low number of longitudinal studies in this field clearly presents an opportunity for future research. Such studies could validate the findings of cross-sectional studies, test the predictive nature of the similarity → attraction relationship, and explore the influence of other factors upon it. In addition, longitudinal studies adopting repeated measure methodologies could test for bidirectional effects and look at the strength and duration of the effect; this latter point is important given that Rosenfeld and Jackson ( 1965 ) reported that personality similarity only influenced friendship in the 1st year of acquaintance suggesting that SAH influences the initiation of attraction, but not its long-term survival.

Almost all of the demographic similarity studies in this review operationalize their similarity variables in very stark categorical terms. Gender is male or female; race is skin color and/or ethnographic background. Similarity or difference is calculated as being on one of the predetermined categories. These singular categorizations present a simple view of gender, race, and other demographic similarities. An alternative approach is intersectionality (Crenshaw 1990 ), which argues that different aspects of a person’s identity intersect to influence behavior towards them. For example, to treat Black women like White women ignores many socio-cultural factors disadvantaging them (Wilkins 2012 ). Intersectional analysis could take demographic similarity into a cultural and political space where the purpose of studying demographic SAH is to highlight privilege, disadvantage, and discrimination (Tatli and Özbilgin 2012 ).

5.4 Recruitment and selection

Perhaps the greatest influence of SAH in organizational settings is in explaining recruitment and selection decisions. Various scholars (e.g., Riordan 2000 ; Schneider 1987 ) have argued that applicants are more attracted to, and more expected to choose to work for, an organization whose workforce has features similar to their own. For example, people may be more attracted to a company that recruits a group of employees who are racially like them, predicting that these workers share their values and attitudes (Avery et al. 2004 ). These predictions have been demonstrated to be accurate in several studies in this review. Roth et al. ( 2020 ) showed that candidates’ perceived similarity of their political affiliation influences employment decision-makers, which eventually resulted in liking and organizational citizenship behavior performance (i.e., an employee’s voluntary commitment to the organization beyond his/her contractually obligated tasks). Kacmarek et al. ( 2012 ) found that greater female presence on nominating committees subsequently led to increased female representation on company boards. Chen and Lin ( 2014 ) showed that recruiters’ perceptions of applicants’ similarity to them influenced selection decisions. However, some asymmetric findings have emerged. For example, while Goldberg ( 2005 ) demonstrated race similarity effects, she also noted that male recruiters have a preference for female applicants. But, by and large, these studies align with findings in the general recruitment and selection literature reporting that organizational recruiters favor applicants resembling themselves and this reinforces opportunity in organizations to groups of people who already enjoy employment positions there (Bye et al. 2014 ; Kennedy and Power 2010 ; Noon 2010 ; Persell and Cookson 1985 ; Rivera 2012 ). As a consequence, many countries have passed legislation to protect those disadvantaged by these processes, although such legislation mainly confines itself to surface-level demographic factors such as gender, race, and disability. Hence, the application of SAH to recruitment situations is challenging as it separates demographic and psychological similarity and is located behind a legal mask that probably suppresses its appearance.

5.5 Post-hire

During employment, SAH presents a paradox for organizations. On the one hand, employees like working with people like themselves and are more productive (Bakar and McCann 2014 ; Chatman and O’Reilly 2004 ). But, on the other hand, it creates employee homogeneity, which Schneider ( 1987 ) argues causes organizations to occupy a self-defeating and increasingly narrow ecological niche, and crystalizes disadvantage and discrimination (Dali 2018 ). Empirical studies included in this review demonstrate both sides of this paradox. Interestingly though, looking across the demographic and psychological similarity studies separately, we gained a sense that demographic similarity worked in the initial phases of relationships to bring people together (e.g., Rosenfeld and Jackson 1965 ) and during short engagements (e.g., during recruitment and selection and loan decisions) when demographic similarity aids decision-making when there is impoverished information. Psychological similarity works over more prolonged periods and therefore comes more to the fore in during long-term employment (e.g., Marchiondo et al. 2018 ; Sears and Holmvall, 2010 ).

One noticeable absence in the studies captured in this review are those that explore value congruence (e.g., Adkins et al. 1994 ; Billsberry 2007b ; Chatman 1989 , 1991 ; Meglino et al. 1992 ; Yu and Verma 2019 ). These studies compare the similarity of aspects of people at work, most typically work values, and explore the consequences. Work value congruence has been shown to lead to positive organizational outcomes such as job satisfaction, organizational commitment, decrease employee conflict and negatively related to intentions to leave and organizational exit (Hoffman and Woehr 2006 ; Jehn 1994 ; Jehn et al. 1997 , 1999 ; Kristof-Brown and Guay 2011 ; Subramanian et al. 2022 ; Verquer et al. 2003 ), thereby supporting SAH. Conversely, value incongruence is associated with distancing outcomes such as feelings of not belonging or being unfulfilled, and organizational exit (Edwards and Cable 2009 ; Edwards and Shipp 2007 ; Follmer et al. 2018 ; Kristof-Brown et al. 2005 ; Vogel et al. 2016 ) thereby supporting DRH leading Abbasi et al. ( 2021 ) to suggest that value congruence and value incongruence, and therefore SAH and DRH, are two different forces. The non-appearance of these studies in the current review appears to stem from the way these value congruence studies are theoretically justified. Rather than being direct tests of SAH, they are one step removed and based on ideas of person-environment (PE) fit and person-organization (PO) fit. These theories are themselves grounded in SAH (e.g., Chatman 1989 ; Schneider 1987 ), but the field is sufficiently well developed as a branch of PE and PO fit that it is not necessary to refer back to the conceptual roots of the SAH. This is likely to be the case for many others forms of congruence and incongruence such as political ideology incongruence (e.g., Bermiss and MacDonald 2018 ) or personality congruence (Schneider et al. 1998 ).

5.6 Organizational exit

Perhaps the biggest surprise in this dataset is the almost complete absence of any SAH studies exploring the organizational exit phase of work as voluntary decisions to leave organizations is one of the clearest examples of employees’ behavioral distancing (i.e., moving apart). Furthermore, there is theory arguing (e.g., Schneider 1987 ) that when employees feel dissimilar to others, they leave organizations. As mentioned above, there are many studies in the value congruence, PE fit, and PO fit literatures that explore the effect of dissimilarity on organizational exit, but these are not positioned as direct tests of SAH and so did not appear in this review.

6 Discussion

This systematic review has shown that, by and large, SAH holds true in organizational settings; similarity leads to attraction. There are some contrarian and asymmetrical findings, but these typically occur when other theories interact with SAH. An example comes from Gaertner and Dovidio ( 2000 ) who showed that both male and female interviewers favored applicants of the opposite sex, which is better explained by social identity theory. Further, legal sanctions can influence the appearance of SAH during recruitment, selection, and other episodes. Consequently, SAH can be viewed as a strong underlying force driving employees’ natural behavior, but it is not so strong that it cannot be overcome by other forces.

In organizational settings, paradox surrounds the application of SAH. People have a natural tendency to want to be with people like themselves and, without other influence, will choose to recruit people like themselves. Moreover, they prefer working with people like themselves and are more productive doing so. But such behavior can be exclusionary, discriminatory, and inequitable. Most countries have laws protecting many different categories of people from disadvantageous behavior for this reason. Further, many, perhaps most, organizations have espoused values and adopt policies of equal opportunity and these policies police formal selection processes, performance appraisals, and promotion practices, and informal behavior between employees. Neo-normative organizations go further and espouse values celebrating diversity and inclusivity (Husted 2021 ). In such organizations, employees are encouraged to “just be yourself” (Fleming and Sturdy 2011 : 178), although this does not extend to their natural tendency to want to associate with people like themselves and strict rules exist to ensure compliance (Fleming and Sturdy 2009 ). So, there are many rules and regulations in organizations protecting those who might be disadvantaged from people’s natural tendency to be attracted to people similar to themselves.

Organization-level analysis is missing from the studies included in this systematic review. Instead, all the studies are designed as individual-level studies where data for both IVs and DVs are gathered from or about individuals and the impact of similarity or dissimilarity for them. This aligns with traditions in industrial/organizational psychology (Schneider and Pulakos 2022 ), but although it sheds light on individual differences, it fails to explore the ramifications of similarity and dissimilarity for organizations. This is not an insignificant omission as theoretical work by Schneider ( 1987 ) argues that the similarity-attraction hypothesis is a powerful force creating and reinforcing the cultures of organizations that explains why organizations are different to each other even when in the same industry and location. Further, exploring the impact of individual-level processes at the level of the organization can test assumptions about the importance of individual-level effects for the organization. As Schneider and Pulakos ( 2022 : 386) state, “[t]he problem lies in our tendency to assume that the characteristics that produce high-performing individuals and teams also yield high-performing organizations, without testing this as often as we could or should.” In short, the assumption that effects at the individual-level lead to effects at the organization-level is an ecological fallacy and there is a need to test the organizational impact, if any, of individual-level findings.

Similarly, this systematic review did not include any empirical studies of the dissimilarity-repulsion hypothesis (DRH; Rosenbaum 1986 ). Relevant search terms were included, but no empirical studies of DRH in workplaces were found. One possible explanation accounting for this gap is that researchers may have presumed that since this theory is the polar opposite of similarity-attraction theory, low similarly-attraction means high dissimilarity repulsion, so the testing of both hypotheses may have been viewed as unnecessary. Alternatively, the low number of studies of organizational exit, particularly voluntary turnover, the most natural and powerful repulsion outcome in organizational settings, in this dataset constrains the appearance of the DRH. Organizational exit is a large literature and dissimilarity and misfit are known to be drivers of these actions (e.g., Doblhofer et al. 2019 ; Jackson et al. 1991 ; Kristof-Brown et al. 2005 ), so the suggestion is, like with value congruence, that these studies are grounded on theories other than DRH. Another interesting problem with DRH is the use of the term repulsion, which hints at “abhorrence, loathing, disgust and hatred” (Abbasi et al. 2021 : 9). In times when there is a strong skew towards positive psychology (Kanfer 2005 ), examining the darker side of organizational life is much less common. Nevertheless, these are the moments that have the most impact on people and deserve much greater scholarly attention.

In addition to the above, this systematic review has surfaced several key avenues for future research related to methodological advancement. The first notable weakness in the empirical papers reviewed on this topic is the absence of studies adopting a longitudinal design. This is particularly noteworthy because the similarity leads to attraction hypothesis is inherently predictive in nature. Cross-sectional studies can give a sense of associations between similarity and attraction constructs, but do not convince when applied to predictive hypotheses. Some authors (e.g., Bruns et al. 2008 ; Eagleson et al. 2000 ; Young et al. 1997 ) have circumvented this issue by adopting policy-gathering designs in which respondents give an opinion about what they would do in a particular situation, but the findings of such studies would carry more weight if they were followed up with empirical studies of what people actually do or did in such circumstances. In this literature, there is a tendency for each study to stand separate from the other studies almost as if each study was exploring the hypothesis in a particular aspect of workplaces for the first time. Such exploratory work is commendable, but there is a need for studies to replicate and integrate findings.

The second noticeable methodological weakness in these studies is the manner in which attraction outcomes have been defined. Decisions to join or leave organizations are the most obvious examples of behavioral attraction and repulsion (i.e., ‘moving to’ and ‘moving away’). However, even attraction and repulsion outcomes like these are rarely the exclusive consequence of similarity or dissimilarity, but they have the advantage of being clear movements into or out of organizations. Other behavioral outcomes used in these studies as measures of attraction include absenteeism, TMT homogeneity, diversity levels, advice-seeking, and small business loan decisions, which appear to show decreasing alignment to the notions of attraction or repulsion. The psychological interpretations of attraction are perhaps even further removed from direct definitions of the word. Many constructs have been used as the dependent variables ranging from job satisfaction, perceived PO fit, perceptions of the quality of LMX relationships, commitment to a trade union, reactions to incivility, and employee well-being. These are all important outcomes, but they are not necessarily capturing a sense of feeling closer to others. Only five studies in this sample collected attraction data based on interpersonal liking, relations, or friendship, which might be thought to be the most direct capture of attraction. As a result, the workplace SAH literature gives the impression of actually being a literature that has rigorously explored the impact of many different types of demographic and psychological similarity in organizations, but not necessarily in terms of how it predicts attraction and repulsion outcomes. Hence, there is a strong need for SAH studies that capture more direct measures of attraction and this could prove to be a fruitful avenue for future research.

Another methodological consideration centers on causation. All the studies reviewed in this review employed an IV predicts DV design where the IVs were a form of similarity or dissimilarity and the DVs were a form of attraction or repulsion. As the SAH was being tested, the natural assumption in these studies is that similarity itself is the driver of outcomes. This, of course, triggers questions about why similarity (or dissimilarity) might be driving outcomes. What is it about similarity that drives attraction outcomes? An unkind hypothesis might be that people are inherently racist, sexist, ageist, linguicist, and so forth, in which case management control strategies appear a natural response. A kinder hypothesis is that people feel less threat from people similar to themselves and have a greater sense of belonging amongst people similar to themselves, in which case strategies focused on improving integration appear appropriate. A more neutral hypothesis might be the similarity makes it easier to predict others’ behavior and brings expectations of reciprocity (Newcomb 1956 ), which would raise distributive justice concerns. At present, the SAH in the workplace literature talks little about why similarity drives attraction outcomes and instead tends to focus on whether it does lead to attraction. But as different organizational responses might be expected to follow different causations, it is important to explore the reasons why similarity (and dissimilarity) are having attraction (and repulsion) effects in workplaces.

6.1 Limitations

This systematic review was strictly limited to empirical studies that set out to test SAH (and DRH) in organizational settings. To be included in this systematic review, this intention needed to be stated in the title, abstract, or keywords through the mention of various words and phrases suggesting SAH. This approach means that there are likely to be many studies not included in this systematic review that might measure some form of human similarity and use it to predict some form of attraction. The most obvious examples are the various organizational fit literatures, the value congruence and incongruence literatures, the recruitment, selection, induction, and socialization literatures, and the organizational exit literature. In all these cases, there are theoretical foundations based on SAH or DRH, but these literatures take the SAH and DRH roots ‘as a given’ and have placed their own theoretical frameworks on them (Evertz and Süß 2017 ). For example, an empirical PO fit study, which has similarity assessments at its core, might refer to PE interactions as its theoretical base and not deconstruct this further to the underlying SAH. It seems a common theme in these fields; there is no longer feel the need to justify the study in terms of testing SAH or DRH and therefore these underpinning hypotheses are not mentioned in titles, abstracts, or keywords. Although considerable scholarly advantage would accrue from including these literatures in a systematic review of SAH and DRH, it would be a truly Herculean task as it would require reading literally thousands of papers without any search terms to guide the hunt for similarity IVs and attraction DVs.

7 Conclusion

This paper systematically reviewed empirical studies of the ‘similarity leads to attraction’ (SAH) and ‘dissimilarity leads to repulsion’ (DRH) hypotheses in organizational settings. A total of 49 studies in 45 separate papers were surfaced, which split roughly 50/50 into studies of demographic similarity and psychological similarity. The results of these studies confirm that SAH remains valid in organizational settings and that it is a fundamental force driving employees’ behavior. However, although similarity and dissimilarity drive attraction and repulsion outcomes, the force is not so strong that it cannot be overridden or moderated by other forces, which includes forces from psychological, organizational, and legal domains. This systematic review highlighted a number of methodological issues in tests of SAH relating to the low number of longitudinal studies, which is important given the predictive nature of the hypotheses, and the varying conceptualizations of attraction measurement. This study also demonstrated that paradox is at the heart of SAH in organizational settings.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Code availability

The search terms used to gather data are detailed in the methodology section.

It should be noted that although Montoya and Horton ( 2020 ) categorize ‘liking’ as an element of interpersonal attraction, others have categorized it as an aspect of affective attraction. Differences relate to how ‘liking’ is conceptualized and measured in studies.

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January 31, 2012 report

Repulsive gravity as an alternative to dark energy (Part 1: In voids)

by Lisa Zyga , Phys.org

(PhysOrg.com) -- When scientists discovered in 1998 that the Universe is expanding at an accelerating rate, the possibility that dark energy could explain the observation was intriguing. But because there has been little progress in figuring out exactly what dark energy is, the idea has since become more of a problem than a solution for some scientists. One physicist, Massimo Villata of the National Institute for Astrophysics (INAF) in Pino Torinese, Italy, describes dark energy as “embarrassing,” saying that the concept is an ad hoc element to standard cosmology and is devoid of any physical meaning. Villata is one of many scientists who are looking for new explanations of the Universe’s accelerating expansion that involve some form of repulsive gravity. In this case, the repulsive gravity could stem from antimatter hiding in voids.

“Cosmic voids (and in particular the nearby Local Void) are observationally very well known and constitute the largest structures of which our Universe is composed,” Villata told PhysOrg.com . “The problem is whether they are really empty or contain the repulsive antimatter.”

In Villata’s paper, which will soon be published in Astrophysics and Space Science , he suggests that antimatter could be hiding in these large voids, separated from matter by mutual gravitational repulsion. As he explained previously , the gravitational repulsion between matter and antimatter is a prediction of general relativity. In this scenario, matter has a positive gravitational charge while antimatter has a (hypothetical) negative gravitational charge. As a result, both matter and antimatter are gravitationally self-attractive, yet mutually repulsive. The gravitational repulsion between matter and antimatter could be so powerful, in fact, that Villata has calculated that it could be responsible for the accelerated expansion of the Universe, eliminating the need for dark energy and possibly dark matter.

Repulsive gravity of this form could even theoretically explain some observations that dark energy cannot, even theoretically, explain. Recently, scientists observed an anomalous motion of the “Local Sheet,” the part of the Universe that includes the Milky Way and other nearby galaxies, which has its own peculiar velocity distinct from other parts of the Universe. Astronomers have identified three components that contribute to the velocity of the Local Sheet: one is due to the well-known attraction to the nearby dense Virgo Cluster; the second component, although its origin is less clear, is thought to be due to the attraction to the Centaurus Cluster; and the third component is what astronomers call the “local velocity anomaly” because the force is not directed toward any significant structure.

Unlike the first two components that are attractive, the third component could be repulsive, according to Villata. In support of this possibility, he notes that the Leo Spur galaxies, which would be located in between the Local Sheet and the attractive area, appear to be at rest with respect to this motion. Villata suggests that the origins of the third component may be on the opposite side, repelling the Local Sheet instead of attracting it. He calculates that a reasonable antimatter mass, located in a particular void, could account for the local velocity anomaly by the mechanism of repulsive gravity.

In this way, the antimatter would act like dark energy in our local neighborhood. On a large scale, numerous antimatter voids could drive the expansion of the Universe without the need for dark energy, and possibly even without the need for an explosive Big Bang (perhaps implying a cyclic Universe). The theory also implies that we live in a Universe with equal amounts of matter and antimatter, as expected by standard theories. To Villata, these results make repulsive gravity an alluring alternative to dark energy.

“Dark energy is thought to be uniformly permeating, so it can explain (formally, not physically) the global acceleration,” Villata said. “But it cannot explain either the strong repulsive effect on the Local Sheet nor the extreme emptiness of the Local Void and several other properties of our extragalactic neighborhood, while the proposed antimatter ‘dark repulsor’ in the Local Void can account for all these things and, at the global level, with antimatter hidden in all cosmic voids, can explain the overall accelerated expansion (and other Universe features) without dark energy and the funny initial explosion.”

Villata hopes these ideas might be tested by experiments, although such tests would be difficult.

“Some people may think that my analysis of general relativity predicting antigravity is not correct or appropriate,” he added. “In this case, a further, definitive test is mentioned in my last paper: the antigravitational lensing effect. In principle, if we had a good 3D map of galaxy clusters lying beyond the voids, it would be relatively easy to analyze whether some of them have shapes squeezed around the line of sight, which would mean that they are aligned with large concentrations of antimatter in the intervening void. But the problem is that there is another concurrent effect, which strongly distorts the distribution of galaxies in the radial direction, due to the peculiar motions affecting the redshift measurements: the finger-of-god effect, which stretches the shape of clusters along the line of sight. It is thus very difficult to distinguish whether a cluster already severely stretched by this effect is further thinned by antigravitational lensing.”

Part 2: Repulsive gravity as an alternative to dark energy (In the quantum vacuum)

Website of Massimo Villata (comments welcome): link

Journal information: Astrophysics and Space Science

© 2011 PhysOrg.com

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Is Dark Energy Really "Repulsive Gravity"?

Antimatter could be behind mysterious force, new theory says.

A powerful repulsion between normal matter and hidden pockets of antimatter could be an alternate explanation for the mysterious force known as dark energy, according to a controversial new theory.

In 1998 scientists discovered that the universe is not only expanding but that its expansion is accelerating.

This totally unexpected behavior has been called the "most profound problem" in physics , because our current understanding of gravity says that attractions between mass in the universe should be causing the expansion to slow down.

The leading theory to explain the accelerating expansion is the existence of a hypothetical repulsive force called dark energy. (Related: "New Galaxy Maps to Help Find Dark Energy Proof?" )

But in the new study, Massimo Villata , an astrophysicist at the Observatory of Turin in Italy, suggests the effects attributed to dark energy are actually due to a kind of "antigravity" created when normal matter and antimatter repel one another.

"Usually this repulsion is ascribed to a mysterious dark energy that would uniformly permeate the cosmos, but nobody knows what it is nor why it behaves this way," Villata said in an email.

"We are replacing an unknown force caused by an unknown element with the repulsive gravity of the well-known antimatter."

(Related: "Dark Matter Is an Illusion, New Antigravity Theory Says." )

Antimatter Hiding in "Holes" in the Universe?

According to Villata, the keys to accelerated expansion lie in large-scale voids that are seen scattered throughout the cosmos.

These holes in our map of the universe—which can each be millions of light-years wide—are inexplicably empty of galaxies and galaxy clusters. The nearest hole to us is called the Local Void, bordering the Virgo supercluster of galaxies.

Villata thinks these voids harbor vast quantities of antimatter, which could even be organized into antimatter galaxies, complete with antimatter stars and planets.

(Related: "Antimatter Found Orbiting Earth—A First." )

All this antimatter doesn't emit radiation that can be detected by current sensors, making it effectively invisible, Villata said.

"There can be various reasons why antimatter in voids should be invisible, but we do not know which of them is the right one," Villata said. "Moreover, antimatter in laboratories could have different behavior, since it is 'immersed' in a world of matter."

(See "Antimatter Atoms Trapped for First Time—'A Big Deal.'" )

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While we can't see antimatter superstructures, we can observe their effects on our visible universe, Villata argues, because antimatter must repel the normal matter in galaxies, pushing them farther from one another.

Villata says his theory, which will appear in an upcoming issue of the journal Astrophysics and Space Science , has the potential to solve other cosmic mysteries, such as the universe's "missing antimatter" problem .

According to standard physics, matter and antimatter particles should have been created in equal amounts during the big bang. Yet the visible universe appears to be dominated by structures made up of normal matter.

To determine how much antimatter might be contained in the Local Void, Villata calculated how much would be needed to create a repulsive force strong enough to explain the so-called Local Sheet. This collection of normal matter, which includes our Milky Way and other nearby galaxies, is all moving at the same speed.

"If each void contains a mass of antimatter similar to that calculated for our Local Void ... then our universe would host an amount of antimatter equivalent to that of matter, and [there] would finally be a matter-antimatter symmetric universe," Villata said.

But Do Matter and Antimatter Repel?

While Villata's theory doesn't require mysterious forces created from nothing, it does rely on the untested assumption that matter and antimatter are mutually repulsive.

There is as yet "no [experimental] evidence that antimatter repels matter," said physicist Frank Close of the University of Oxford in the U.K., although, he added, plans are underway at the European Organization for Nuclear Research (CERN) in Switzerland to test the idea.

In fact, Dragan Hajdukovic, a physicist at CERN, recently proposed a separate antigravity theory that also relies on repulsion between matter and antimatter to explain dark energy and dark matter.

Hajdukovic called Villata's theory "an interesting idea," be he added that he disagrees with the hypothesis of a matter-antimatter symmetric universe.

"The major problem is why [such] big quantities of antimatter in the voids are not observed," Hajdukovic said.

In Hajdukovic's theory, antimatter particles spontaneously pop in and out of existence in the quantum vacuum, which is the name physicists give to seemingly empty space.

"I use the reality of the quantum vacuum. For a physicist, it is more natural and plausible," Hajdukovic said.

"In order to explain the invisibility of antimatter, proponents of a matter-antimatter symmetric universe would be forced to invoke an additional hypothesis"—such as the emission by antimatter of so-called advanced photons, which travel backward in time and so wouldn't be detectable to current instruments.

(Related: "Time Travel Impossible, Mini 'Big Bang' Hints." )

"It is not a good sign for a theory if one hypothesis immediately demands introduction of other hypotheses."

But study author Villata argues that the assumptions in his theory—including matter-antimatter repulsion and advanced photons—are predicted by well-established theories in physics.

In that sense, he said, there is "no introduction of other hypotheses."

Related Topics

Extreme 'ghostly' particles detected in our galaxy for the first time

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Who is Oppenheimer? The controversial man behind the atomic bomb

Can the moon influence human health? Surprising new research suggests it might.

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Home » What is a Hypothesis – Types, Examples and Writing Guide

What is a Hypothesis – Types, Examples and Writing Guide

Table of Contents

Definition:

Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation.

Hypothesis is often used in scientific research to guide the design of experiments and the collection and analysis of data. It is an essential element of the scientific method, as it allows researchers to make predictions about the outcome of their experiments and to test those predictions to determine their accuracy.

Types of Hypothesis

Types of Hypothesis are as follows:

Research Hypothesis

A research hypothesis is a statement that predicts a relationship between variables. It is usually formulated as a specific statement that can be tested through research, and it is often used in scientific research to guide the design of experiments.

Null Hypothesis

The null hypothesis is a statement that assumes there is no significant difference or relationship between variables. It is often used as a starting point for testing the research hypothesis, and if the results of the study reject the null hypothesis, it suggests that there is a significant difference or relationship between variables.

Alternative Hypothesis

An alternative hypothesis is a statement that assumes there is a significant difference or relationship between variables. It is often used as an alternative to the null hypothesis and is tested against the null hypothesis to determine which statement is more accurate.

Directional Hypothesis

A directional hypothesis is a statement that predicts the direction of the relationship between variables. For example, a researcher might predict that increasing the amount of exercise will result in a decrease in body weight.

Non-directional Hypothesis

A non-directional hypothesis is a statement that predicts the relationship between variables but does not specify the direction. For example, a researcher might predict that there is a relationship between the amount of exercise and body weight, but they do not specify whether increasing or decreasing exercise will affect body weight.

Statistical Hypothesis

A statistical hypothesis is a statement that assumes a particular statistical model or distribution for the data. It is often used in statistical analysis to test the significance of a particular result.

Composite Hypothesis

A composite hypothesis is a statement that assumes more than one condition or outcome. It can be divided into several sub-hypotheses, each of which represents a different possible outcome.

Empirical Hypothesis

An empirical hypothesis is a statement that is based on observed phenomena or data. It is often used in scientific research to develop theories or models that explain the observed phenomena.

Simple Hypothesis

A simple hypothesis is a statement that assumes only one outcome or condition. It is often used in scientific research to test a single variable or factor.

Complex Hypothesis

A complex hypothesis is a statement that assumes multiple outcomes or conditions. It is often used in scientific research to test the effects of multiple variables or factors on a particular outcome.

Applications of Hypothesis

Hypotheses are used in various fields to guide research and make predictions about the outcomes of experiments or observations. Here are some examples of how hypotheses are applied in different fields:

• Science : In scientific research, hypotheses are used to test the validity of theories and models that explain natural phenomena. For example, a hypothesis might be formulated to test the effects of a particular variable on a natural system, such as the effects of climate change on an ecosystem.
• Medicine : In medical research, hypotheses are used to test the effectiveness of treatments and therapies for specific conditions. For example, a hypothesis might be formulated to test the effects of a new drug on a particular disease.
• Psychology : In psychology, hypotheses are used to test theories and models of human behavior and cognition. For example, a hypothesis might be formulated to test the effects of a particular stimulus on the brain or behavior.
• Sociology : In sociology, hypotheses are used to test theories and models of social phenomena, such as the effects of social structures or institutions on human behavior. For example, a hypothesis might be formulated to test the effects of income inequality on crime rates.
• Business : In business research, hypotheses are used to test the validity of theories and models that explain business phenomena, such as consumer behavior or market trends. For example, a hypothesis might be formulated to test the effects of a new marketing campaign on consumer buying behavior.
• Engineering : In engineering, hypotheses are used to test the effectiveness of new technologies or designs. For example, a hypothesis might be formulated to test the efficiency of a new solar panel design.

How to write a Hypothesis

Here are the steps to follow when writing a hypothesis:

Identify the Research Question

The first step is to identify the research question that you want to answer through your study. This question should be clear, specific, and focused. It should be something that can be investigated empirically and that has some relevance or significance in the field.

Conduct a Literature Review

Before writing your hypothesis, it’s essential to conduct a thorough literature review to understand what is already known about the topic. This will help you to identify the research gap and formulate a hypothesis that builds on existing knowledge.

Determine the Variables

The next step is to identify the variables involved in the research question. A variable is any characteristic or factor that can vary or change. There are two types of variables: independent and dependent. The independent variable is the one that is manipulated or changed by the researcher, while the dependent variable is the one that is measured or observed as a result of the independent variable.

Formulate the Hypothesis

Based on the research question and the variables involved, you can now formulate your hypothesis. A hypothesis should be a clear and concise statement that predicts the relationship between the variables. It should be testable through empirical research and based on existing theory or evidence.

Write the Null Hypothesis

The null hypothesis is the opposite of the alternative hypothesis, which is the hypothesis that you are testing. The null hypothesis states that there is no significant difference or relationship between the variables. It is important to write the null hypothesis because it allows you to compare your results with what would be expected by chance.

Refine the Hypothesis

After formulating the hypothesis, it’s important to refine it and make it more precise. This may involve clarifying the variables, specifying the direction of the relationship, or making the hypothesis more testable.

Examples of Hypothesis

Here are a few examples of hypotheses in different fields:

• Psychology : “Increased exposure to violent video games leads to increased aggressive behavior in adolescents.”
• Biology : “Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.”
• Sociology : “Individuals who grow up in households with higher socioeconomic status will have higher levels of education and income as adults.”
• Education : “Implementing a new teaching method will result in higher student achievement scores.”
• Marketing : “Customers who receive a personalized email will be more likely to make a purchase than those who receive a generic email.”
• Physics : “An increase in temperature will cause an increase in the volume of a gas, assuming all other variables remain constant.”
• Medicine : “Consuming a diet high in saturated fats will increase the risk of developing heart disease.”

Purpose of Hypothesis

The purpose of a hypothesis is to provide a testable explanation for an observed phenomenon or a prediction of a future outcome based on existing knowledge or theories. A hypothesis is an essential part of the scientific method and helps to guide the research process by providing a clear focus for investigation. It enables scientists to design experiments or studies to gather evidence and data that can support or refute the proposed explanation or prediction.

The formulation of a hypothesis is based on existing knowledge, observations, and theories, and it should be specific, testable, and falsifiable. A specific hypothesis helps to define the research question, which is important in the research process as it guides the selection of an appropriate research design and methodology. Testability of the hypothesis means that it can be proven or disproven through empirical data collection and analysis. Falsifiability means that the hypothesis should be formulated in such a way that it can be proven wrong if it is incorrect.

In addition to guiding the research process, the testing of hypotheses can lead to new discoveries and advancements in scientific knowledge. When a hypothesis is supported by the data, it can be used to develop new theories or models to explain the observed phenomenon. When a hypothesis is not supported by the data, it can help to refine existing theories or prompt the development of new hypotheses to explain the phenomenon.

When to use Hypothesis

Here are some common situations in which hypotheses are used:

• In scientific research , hypotheses are used to guide the design of experiments and to help researchers make predictions about the outcomes of those experiments.
• In social science research , hypotheses are used to test theories about human behavior, social relationships, and other phenomena.
• I n business , hypotheses can be used to guide decisions about marketing, product development, and other areas. For example, a hypothesis might be that a new product will sell well in a particular market, and this hypothesis can be tested through market research.

Characteristics of Hypothesis

Here are some common characteristics of a hypothesis:

• Testable : A hypothesis must be able to be tested through observation or experimentation. This means that it must be possible to collect data that will either support or refute the hypothesis.
• Falsifiable : A hypothesis must be able to be proven false if it is not supported by the data. If a hypothesis cannot be falsified, then it is not a scientific hypothesis.
• Clear and concise : A hypothesis should be stated in a clear and concise manner so that it can be easily understood and tested.
• Based on existing knowledge : A hypothesis should be based on existing knowledge and research in the field. It should not be based on personal beliefs or opinions.
• Specific : A hypothesis should be specific in terms of the variables being tested and the predicted outcome. This will help to ensure that the research is focused and well-designed.
• Tentative: A hypothesis is a tentative statement or assumption that requires further testing and evidence to be confirmed or refuted. It is not a final conclusion or assertion.
• Relevant : A hypothesis should be relevant to the research question or problem being studied. It should address a gap in knowledge or provide a new perspective on the issue.

Advantages of Hypothesis

Hypotheses have several advantages in scientific research and experimentation:

• Guides research: A hypothesis provides a clear and specific direction for research. It helps to focus the research question, select appropriate methods and variables, and interpret the results.
• Predictive powe r: A hypothesis makes predictions about the outcome of research, which can be tested through experimentation. This allows researchers to evaluate the validity of the hypothesis and make new discoveries.
• Facilitates communication: A hypothesis provides a common language and framework for scientists to communicate with one another about their research. This helps to facilitate the exchange of ideas and promotes collaboration.
• Efficient use of resources: A hypothesis helps researchers to use their time, resources, and funding efficiently by directing them towards specific research questions and methods that are most likely to yield results.
• Provides a basis for further research: A hypothesis that is supported by data provides a basis for further research and exploration. It can lead to new hypotheses, theories, and discoveries.
• Increases objectivity: A hypothesis can help to increase objectivity in research by providing a clear and specific framework for testing and interpreting results. This can reduce bias and increase the reliability of research findings.

Limitations of Hypothesis

Some Limitations of the Hypothesis are as follows:

• Limited to observable phenomena: Hypotheses are limited to observable phenomena and cannot account for unobservable or intangible factors. This means that some research questions may not be amenable to hypothesis testing.
• May be inaccurate or incomplete: Hypotheses are based on existing knowledge and research, which may be incomplete or inaccurate. This can lead to flawed hypotheses and erroneous conclusions.
• May be biased: Hypotheses may be biased by the researcher’s own beliefs, values, or assumptions. This can lead to selective interpretation of data and a lack of objectivity in research.
• Cannot prove causation: A hypothesis can only show a correlation between variables, but it cannot prove causation. This requires further experimentation and analysis.
• Limited to specific contexts: Hypotheses are limited to specific contexts and may not be generalizable to other situations or populations. This means that results may not be applicable in other contexts or may require further testing.
• May be affected by chance : Hypotheses may be affected by chance or random variation, which can obscure or distort the true relationship between variables.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Definition of repulsion

Examples of repulsion in a sentence.

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'repulsion.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Middle English repulsioun, borrowed from Middle French & Medieval Latin; Middle French repulcion, repulsion, borrowed from Medieval Latin repulsiōn, repulsiō "action of driving away or expelling" (Late Latin, "refutation"), derivative, with the suffix of verbal action -tiōn-, -tiō, of Latin repellere "to push away, drive back, fend off " (with -s- from past participle and verbal noun repulsus ) — more at repel

15th century, in the meaning defined at sense 1

Dictionary Entries Near repulsion

repulsion-induction motor

Cite this Entry

“Repulsion.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/repulsion. Accessed 3 Sep. 2024.

Kids Definition

Kids definition of repulsion, medical definition, medical definition of repulsion, more from merriam-webster on repulsion.

Britannica English: Translation of repulsion for Arabic Speakers

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