PART1-What is meant by the utility of a test? What are factors that affect a test’s utility?

What stood out to you or surprised you?

PART2- PLEASE SEE JOURNALS ATTACHED BELOW TO COMPLETE THIS ASSIGNMENT!!!Write a 155-word analysis of how you developed your instrument.

  • Describe how you would norm this instrument and which reliability measures you would use.
  • Discuss how many people you would give it to.
  • Describe the characteristics that your respondents would have.
  • Explain to whom the instrument would be generalized.
  • Describe how you would establish validity.
  • Describe the methods you used for item selection.
  • Discuss whether or not cut-off scores would be established.
  • Explain how item selection will be evaluated.

Format your paper according to APA guidelines.

ONLY 155 WORDS FOR MY PART!!!THIS IS THE ONLY PART YOU WILL ANSWER Describe the characteristics that your respondents would have.

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HYPOTHESIS AND THEORY published: 01 May 2017

doi: 10.3389/fpsyg.2017.00635

Edited by: Andrew Kemp,

Swansea University, UK

Reviewed by: Justine Megan Gatt,

University of New South Wales, Australia

Wataru Sato, Kyoto University, Japan

*Correspondence: Hans IJzerman

Specialty section: This article was submitted to

Emotion Science, a section of the journal Frontiers in Psychology

Received: 11 July 2016 Accepted: 10 April 2017 Published: 01 May 2017

Citation: IJzerman H, Heine ECE, Nagel SK and Pronk TM (2017) Modernizing

Relationship Therapy through Social Thermoregulation Theory: Evidence,

Hypotheses, and Explorations. Front. Psychol. 8:635.

doi: 10.3389/fpsyg.2017.00635

Modernizing Relationship Therapy through Social Thermoregulation Theory: Evidence, Hypotheses, and Explorations Hans IJzerman1*, Emma C. E. Heine

2, Saskia K. Nagel3 and Tila M. Pronk4

1 Department of Psychology, University of Virginia, Charlottesville, VA, USA, 2 Department of Clinical Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands, 3 Department of Philosophy, University of Twente, Enschede, Netherlands, 4 Department of Social and Organisational Psychology, Tilburg University, Tilburg, Netherlands

In the present article the authors propose to modernize relationship therapy by

integrating novel sensor and actuator technologies that can help optimize people’s

thermoregulation, especially as they pertain to social contexts. Specifically, they propose

to integrate Social Thermoregulation Theory (IJzerman et al., 2015a; IJzerman and Hogerzeil, 2017) into Emotionally Focused Therapy by first doing exploratory research

during couples’ therapy, followed by Randomized Clinical Trials (RCTs). The authors

thus suggest crafting a Social Thermoregulation Therapy (STT) as enhancement to existing relationship therapies. The authors outline what is known and not known

in terms of social thermoregulatory mechanisms, what kind of data collection and

analyses are necessary to better understand social thermoregulatory mechanisms to

craft interventions, and stress the need to conduct RCTs prior to implementation. They

further warn against too hastily applying these theoretical perspectives. The article

concludes by outlining why STT is the way forward in improving relationship functioning.

Keywords: social thermoregulation, attachment, relationship therapy, emotion regulation, wearables, sensor technology, actuators


One of the strongest predictors of one’s physical health, mental health, and happiness is the quality of one’s close relationships. Having high quality relationships predicts factors that we understand as life chances, including a longer life, greater creativity, and higher self-esteem (House et al., 1988; Argyle, 1992; Holt-Lunstad et al., 2010). However, to date, our understanding of why high quality social relationships lead to a more fulfilled and healthy life is relatively limited. The present paper serves to provide further direction to understanding some prominent underlying mechanisms through social thermoregulation theory. In addition, we will outline how near-future interventions can be crafted by doing research with novel technologies during relationship therapy.

Thus far, the evidence linking relationships and life chances focused at “higher order” levels: marital couples that regulate each other’s emotions successfully have fewer marital problems, have better health, and are more satisfied with their relationship than couples who do not successfully co-regulate (Gottman and Levenson, 1992). But our position is broader: first, disturbances in health closely relate to dysregulated body temperature (Benzinger, 1969). Second, temperature regulation has been a major driving force for sociality in homeothermic (= warm-blooded) animals

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(Ebensperger, 2001). For humans, the aggregate evidence is similarly in favor of an evolved reliance of social warmth on physical warmth (IJzerman et al., 2015a). Finally, the literature is in favor of the idea of co-regulation, a lower level dynamic that can help down-regulate emotional states socially (Butler and Randall, 2013).

The present article brings together these three concepts and asks the question if thermoregulation is crucial for physiological co-regulation in close relationships, and, consequently, proceeds to ask whether therapists can help improve physiological co- regulation in couples. Altogether, we propose to rely on novel technologies that can aid in developing Social Thermoregulation Therapy (STT) to help optimize people’s social lives.

In this article, we first provide what we see as one of the main functions of relationships: relationships help distribute the burdens of the environment and help to co-regulate. Then, we provide the available evidence on social thermoregulation theory, integrate co-regulation with social thermoregulation theory, after which we discuss potential interventions to improve co-thermoregulation. Most prominently, we point to modern sensor and actuator technology as tools to help develop and then implement STT. We clarify what we know and don’t know, followed by some of the risks we perceive in moving forward with such novel therapies. We anticipate that this approach will dramatically reduce the gap between researchers (theory) and therapists (application). Our position paper is much needed, as advances in this field will likely be so rapid that consequential mistakes in crafting novel relationship therapies are not unimaginable and potentially disastrous.


In a seminal 1992 article, Gottman and Levenson (1992) found that co-regulation is crucial for a relationship’s success. They found that positive exchanges (e.g., responses through humor or positive problem descriptions rather than a negative, defensive response) toward a marriage partner were predictive of lower chance on divorce later, better health, and greater finger amplitude (indicative of autonomic activation). In the early days of this research, co-regulation was mostly understood through the regulation of emotions at higher, more conscious forms of attending to the other’s emotion (e.g., through humor or positive problem descriptions). With more advanced equipment, researchers have also started to pay greater attention to lower level dynamics that used to be much harder to capture. As but one example, Coan et al. (2006) found that simply holding the partner’s hand while under distress decreased stress- related activation in the brain while under threat of electric shock.

These insights on lower level dynamics led Butler and Randall (2013) to redefine co-regulation as the “bidirectional linkage of oscillating emotional channels (subjective experience, expressive behavior, and autonomic physiology) between partners (a linkage

that) contributes to emotional and physiological stability for both partners in a close relationship” (p. 203), which thus incorporates lower level (autonomic) regulation with more conscious forms. Butler and Randall’s (2013) perspective supplements the early views imparted by Gottman and Levenson (1992) with a type of social emotion regulation that is less “in the head” and more distributed and dynamic, relying on an “a�ective attunement” between close partners (e.g., romantic partners or caregiver and infant).

The general aim of such a�ective attunement is to achieve an allostatic balance in the relationship through distributing risks of environmental threats, leading to an o�oading of energetic demands created by such threats (e.g., Beckes and Coan, 2011; Fitzsimons et al., 2015). The field of behavioral ecology has illustrated this idea of load sharing with conspecifics. Ostriches, for example, increase the rate of eating when they are in the presence of other ostriches, which can look out for predators (Bertram, 1980; Krebs and Davies, 1993). Homeothermic animals, like rodents, huddle up to other animals when cold to o�oad the energetic demands of warming up (Ebensperger, 2001). Thus, beyond distributing threat, one of the constant and very demanding threats to allostatic balance is the near-constant change in environmental temperature. For most animals their ilk help downregulate the environmental challenge that fluctuations of temperature pose on them.


Despite modern conveniences like heaters or cloths, temperature regulation remains a considerable challenge for humans. From that perspective, Social Thermoregulation Theory complements basic approaches to co-regulation, detailing how “social warmth” (i.e., trustworthiness and social predictability) relies on more ancient needs of physical warmth. Strong evidence for the relationship between social interaction and thermoregulation can be found in studies across homoeothermic animals. In rodents, social thermoregulation has been shown to be one of the most important motivating forces behind group living, especially when temperatures drop (Ebensperger, 2001). As but one example, the Octodon Degus (a Chilean rodent) used 40% less energy and achieved a higher surface temperature when housed with three or five others (versus alone; Nuñez-Villegas et al., 2014). Studies of vervet monkeys show somewhat more complex mechanisms, with larger social networks bu�ering their core temperatures from the cold (McFarland et al., 2015), while even grooming a dead vervet monkey’s pelt insulates against temperature variations (McFarland et al., 2015).

For humans, the aggregate evidence is similarly in favor of the evolved reliance of social on physical warmth. Psychological research has consistently shown that temperature fluctuations (either outside or lab temperature) is causally tied to social behaviors ranging from renting romance movies (Hong and

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Sun, 2012) to house-purchasing decisions (Van Acker et al., 2016) to basic e�ects on perception, language use, and memory (IJzerman and Semin, 2009; Schilder et al., 2014; Messer et al., 2017). The e�ect also works the other way around: if people feel the environment to be socially unpredictable, they perceive temperatures as lower, whereas the reverse is true if people feel psychologically safe (Zhong and Leonardelli, 2008; IJzerman and Semin, 2010; IJzerman et al., 2015b, 2016; Ebersole et al., 2016). The link between psychological safety and thermoregulation extends to consumer behavior: brands that are regarded as more trustworthy induce perceptions of higher temperature, while the degree to which one is a�ected by temperature determines what one would pay for the brand (IJzerman et al., 2015b). This led IJzerman et al. (2015b) to conclude that temperature perceptions are a sort of social “weather report,” or a temperature prediction system on the basis of which people know whether to rely on their social context (or not)1.

Although it seems unlikely that social thermoregulation is still heavily involved in adult social interactions, one has to note that the evolutionary window of availability of modern conveniences (like heaters and clothes) to regulate temperature has likely been too brief to make a noticeable di�erence in the reliance of social on physical warmth. As a result, the need for physical warmth likely has formed as a model, or template, through which humans come to understand and interpret their social interactions.

Accordingly, interaction with others outside people’s direct relationships should similarly rely on “temperature estimates.” And indeed, in humans (unlike penguins) social thermoregulation is not just about huddling, but instead about attaching to di�erent people in di�erent contexts. Perhaps the most compelling evidence on attaching in a variety of contexts from recent work on social integration and climatic variation. IJzerman et al. (2017b) found in a relatively large sample in 12 di�erent countries that the lower people’s core temperatures, the more they engage in complex social integration (i.e., engage in contact with di�erent people in di�erent social contexts); they also found that this integration bu�ers their core against distance from the equator (as a proxy for colder climates). In short, the available evidence is strongly in favor of the idea that people’s social networks – even the more complex ones – protect them from the cold, and that humans adapt their social behaviors and cognitions to temperature changes.2

1The field of social thermoregulation in humans is its infancy. Nevertheless, a considerable amount of evidence has been gathered on the relationship between temperature regulation and social behavior. This does not mean that this field is without its criticism (and rightfully so). Given the discussion on power in psychological science, it may then also not come as a surprise that also in the field of thermoregulation some e�ects failed to replicate (Vess, 2012; LeBel and Campbell, 2013). Yet, other e�ects did replicate (IJzerman and Semin, 2009; Schilder et al., 2014; Inagaki et al., 2015; Ebersole et al., 2016; IJzerman et al., 2016). Further, original studies with larger Ns do exist, with some studies with participant samples between 100 and 500 (e.g., IJzerman et al., 2015b; Van Acker et al., 2016), and some outliers even with samples around 30,000 (Hong and Sun, 2012) and above 6 million (Zwebner et al., 2013). We think that the criticisms should likely be directed at better specifying the models relevant for social thermoregulation theory, for which we see this paper as an important step in the right direction. 2Note that the more dynamic view of social thermoregulation diverges substantially from what one may understand as conceptual embodiment, a view


We have reviewed evidence that temperature a�ects our social behavior and cognitions in myriad ways, while we have also reviewed evidence that shows that complex social networks still protect us against the cold. But at present, it is still unclear exactly how humans help regulate each other’s temperature through more complex dynamics, if at all. Although there is now considerable evidence that social thermoregulation is (causally) tied to social cognitions and behaviors, the literature regarding co-thermoregulatory patterns is scarce. At best, we can extract some elementary e�ects and speculate about further mechanisms. Despite the limited evidence, we feel comfortable providing some first direction given the current state of diverse, but converging literatures.

For example, emotions like anxiety and sadness have come to be associated with lowered peripheral temperature (Ziegler and Cash, 1938; Ekman et al., 1983; McFarland, 1985; Ekman, 1993; Nummenmaa et al., 2014). Relatedly, adults’ peripheral temperatures drop when they feel socially excluded (IJzerman et al., 2012).3 Peripheral temperature changes also extend to early social interactions: when a mother leaves the room in the Strange Situation, the infant’s skin temperature drops. Skin temperature only returns to baseline once the mother returns (and not so when a stranger enters the room; Mizukami et al., 1990). Further, people respond to close others’ sadness (either partners or infants) with an increase in peripheral temperature (Vuorenkoski et al., 1969; IJzerman et al., 2015a). That these e�ects may be co-regulatory in nature could be inferred from studies that show that physical warmth downregulate the need for social contact after a lack of social warmth (IJzerman et al., 2012; Zhang and Risen, 2014).4,5

Why is the regulation of body temperature so important to our social regulation systems? Human infants – like

advocated by for example Lako� and Johnson (1999). They propose that warmth becomes paired with a�ection at an early age, and that such peripherally related constructs form a mental representation of relationships. Our view instead relies on more dynamic, and innate, co-regulation systems for which the infant searches from birth on, and that it may form an internal mental representation of its social network, sca�olded onto such early innate predispositions to search for warmth (cf. Bowlby, 1969; Mandler, 1992). 3We would like to note that when we discuss peripheral temperatures here, we mostly talk about the extremities. Little is known about temperature changes throughout the body in response to social situations, but temperature changes in the extremities are for example likely to di�er from temperature changes in the face. Indeed, social exclusion has been found to lead to decreases in the extremities (IJzerman et al., 2012) but increases in the face (Paolini et al., 2016). 4Furthermore, the evidence on physiological patterns converging with social thermoregulation (like oxytocin and serotonin) converge with these ideas on co-thermoregulation (e.g., Beckes et al., 2015; Raison et al., 2015). 5We have not discussed the di�erences between core and peripheral temperature. Core temperatures are relatively stable, although they are influenced by time of day, distance from the equator, sex, and the quality of one’s social network. Peripheral temperature is much more prone to change throughout the day. For example, peripheral temperatures drop when environmental temperatures drop and even drop about 0.7� after being socially excluded. This is so because the periphery serves as a defense mechanism from changes to the core.

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many other altricial species – are not able to regulate their temperature independently and need to rely on the caregiver to thermoregulate. Early attachment processes of the human child are thus focused on its need to keep warm, likely forming the basis for an evolved model, or, rather, template, for mental (attachment-like) models concerning the relationship between physical and social warmth. Experimental evidence supports the temperature-template-attachment view: attachment has been found to moderate people’s responses to temperature cues in a variety of reports (see, e.g., IJzerman et al., 2013). Furthermore, Vergara et al. (2017, unpublished) found that individual di�erences in need for social thermoregulation and preference for temperature predict not only individual di�erences in attachment but also stress and health, providing further support for thermoregulation as essential feature of our attachment system.6

Thermoregulation – across animals – is crucial for survival. The available evidence in humans also points to a robust link with social behavior and cognition, one that seems to be crucial for attachment. We therefore strongly suspect that thermoregulation becomes integrated into higher-order prediction systems and that this “temperature prediction system” supports us in navigating our social environment. Trustworthiness of brands for example do not only increase temperature perceptions, they also drive purchasing decisions (IJzerman et al., 2015b), while temperature fluctuations also influence people’s conformity to the majority appeal (Huang et al., 2014) or their decisions to engage in social interactions (Hong and Sun, 2012; Van Acker et al., 2016).

And there are some indications that responses to others’ emotions manifest through peripheral temperature changes. This is why, in line with previous work (IJzerman et al., 2015b), we have reason to believe that the “weather report” we have used as a metaphor relies on peripheral temperature to provide people with information on the basis of which they adapt to social situations. “Spending” this on others should thus only happen if we expect to be “paid back” in the future. Wagemans and IJzerman (2015, unpublished) for example found that peripheral temperature increases, but only if the relationship is communal. Szymkow et al. (2013) and IJzerman et al. (2015b) find that people estimate temperature higher, but only if the target is trustworthy (and only if lab temperatures are lower; Ebersole et al., 2016; IJzerman et al., 2016). Finally, people’s need to thermoregulate is higher, but again only if they perceive others as trustworthy (i.e., are securely attached; Vergara et al., 2017, unpublished).

In other words, there is considerable variation in the degree to which we (literally) warm up to others. There is also variation in the degree to which we perceive benefits from others in relation to thermoregulation and consequently the degree to which people “spend” their thermoregulation on others. This “spending” should be contingent not only on one’s past experiences, but also on the quality of the relationship. With novel technological

6We stress that the relationship between social thermoregulation and health to date has only been found in correlational studies, and no prospective studies have been conducted.

inventions it becomes possible to study these dynamics in a methodologically sound fashion, cost e�ciently, and in real time.


The key to understanding temperature prediction systems – and how they help us adapt to social contexts – is the economy of action (Pro�tt, 2006; Schnall et al., 2010; Beckes and Coan, 2011; Coan and Sbarra, 2015). The premise is simple: organisms need to take in more energy than they exert, and overspending the energy expenditure budget is a threat to allostatic balance. In other animals, the metabolic costs of thermoregulation are decreased when regulated socially (Gilbert et al., 2006). We believe that social emotion regulation is (partly) rooted in the need to maintain temperature homeostasis and that helping to regulate another’s sadness will cost to support if our own periphery rises in peripheral temperature. We will thus only o�er emotion regulation if we suspect the other to “pay back” in the future (and we ask, is the relationship with the other is communal?).

In other words, the ‘economy’ of relationships can be understood by calculating who in the social network “pays” for survival and – in more modern days and relationships – who “pays” by facilitating day-to-day emotional functioning. Human relationships are therefore a bit like being modern- type penguins, but then in the sense that people’s “modern” emotional systems are reliant on much older (penguin) systems. We think that this modern emotional system could rely on a “temperature monetizing system” that helps us regulate and bargain toward temperature homeostasis (Satino�, 1978, 1982; Anderson, 2010). At present, there is virtually no research detailing how thermoregulation and metabolism relate to social emotion regulation, but there is some support for the fact that attachment-like processes rely on metabolic regulation. For example, people who are more avoidant in their relationship orientation have higher levels of fasting glucose, indicating a higher reliance on their own metabolic resources (Coan and Sbarra, 2015; Ein-Dor et al., 2015; see also Henriksen et al., 2014; IJzerman et al., 2015a).

Relationships and Co-thermoregulation One of the goals of a relationship is thus to maintain a form of “temperature homeostasis”; keeping track of the health of the relationship through temperature helps us maintain an optimized social network. Despite the considerable evidence linking thermoregulation to social behaviors and cognitions, the underlying dynamics we need to understand to e�ectively integrate social thermoregulation theory into therapy are still highly speculative. We know that our need for social warmth relies on our need for physical warmth; we also know that the lack

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of high quality relationships is metabolically costly; we further know that high quality relationships protect us from the cold; and we also know that both experiencing emotions ourselves and seeing emotions in others are associated with peripheral temperature changes in ourselves. Based on these di�erent, but converging literatures, we thus strongly suspect that people co- thermoregulate close others by warming one’s skin or hugging the other when sad, and that both acts are metabolically costly. Yet, whether this is true, and how they exactly interrelate is not at all clear.7

We further strongly suspect that co-thermoregulation can be responsive or unresponsive, based on how reliable the partners perceive the relationship to be (communality), or how reliable they themselves perceive the world in general to be (attachment style). With “responsive co-thermoregulation” – a new term we would like to introduce for relationship research and therapy – we mean the (non-conscious) regulation of each other’s temperature toward homeostasis in dyads. The degree to which one participates is thus contingent upon perceived social predictability (i.e., a combination between attachment and communality of the relationship). Unresponsive co-thermoregulation would thus imply not hugging the partner when he or she is sad, and not increasing peripheral temperature when the other is in need. What constitutes responsive and unresponsive co- thermoregulation is still in need of very specific classification.

Acknowledging that relationships are complex and that multiple factors contribute to successful regulation, further caution is warranted in applying this perspective on co- thermoregulation in therapy. That is, the perceived social predictability can be accurate or inaccurate as in some situations being non-responsive to one’s partner’s emotions might be functional. When one’s partner has a very bad temper or can be abusive, avoiding one’s partner’s anger – as opposed to engaging – can be considered more beneficial. Thus, part of classifying responsive versus unresponsive co-thermoregulation is the understanding of the social context in which co- thermoregulation occurs.


We have acknowledged that the dynamics of co- thermoregulation are yet unclear. Specifically, it is unclear how strong, in which situation, and for which types of emotion one’s peripheral temperature should in- or decrease. At the same time, the available evidence supports the idea that understanding co-thermoregulation is vital to achieve

7We have not even scratched the surface of the interrelationship between peripheral temperature changes and facial expression of emotions. We think it is likely that peripheral temperature changes are connected to facial expressions and other manifestations of emotions, which are thus dynamically connected to co-regulate emotions. Furthermore, we also have not even considered the link between individual di�erences in empathy or perspective taking. We suspect such relationships to exist, but how these links should be understood is beyond the scope of this article.

optimal social functioning. Thermoregulation has further been implicated in (mental) health, such as depression (Pechlivanova et al., 2010), insomnia (Bach et al., 2002; Van den Heuvel et al., 2004; Pechlivanova et al., 2010), anxiety (Parry, 2007), and many others. Furthermore, physiological processes related to thermoregulation (like catabolization of Brown Adipose Tissue) have become linked to tumor growth (Shellock et al., 1986; Lee et al., 2010) or late onset obesity (Himms-Hagen, 1979, 1989, 1990; Van Marken Lichtenbelt et al., 2009). In other words, proper (social) thermoregulation seems vital for having optimal health.

Relationships, health, and thermoregulation are strongly interdependent, and understanding and applying thermo- regulation may well-present one of the most important advances in modern (relationship) therapy. The reason why integrating thermoregulation into modern therapy has become feasible is because of advances in a field called “eHealth” (short for electronic health), a field that has become trendy in clinical research, mostly due to obvious benefits in saving costs, time, and the lower threshold to receive therapy. The most common applications of eHealth have been to seek a reduction of costs, by for example moving part of the therapy process online (and thus decreasing the amount of hours invested in providing therapy or assessments). For STT, eHealth can also quickly help us decrease costs of research by advancing our understanding through measurements. Could it be that – because of all the intimate links between relationships, thermoregulation, and health, that STT can quickly and fundamentally transform and optimize the type of care we can receive, thereby optimize the quality of our social networks?

Application of Co-thermoregulation into Current Therapies The application of STT into eHealth is likely most e�cacious by adding it to an existing intervention known as Emotionally Focused Therapy (EFT). EFT is a short-term relationship therapy focusing on (co-regulatory) patterns in interaction (Johnson, 1999; Johnson et al., 1999; Greenberg, 2004). Various potential patterns of interaction in relationships are described and targeted through this type of therapy, one that is rooted in attachment theory (Bowlby, 1969). One example that shows these dynamics and its roots in attachment theory is the pattern that details how quality and emotionally unresponsive interactions often leading to stonewalling or emotionally “attacking” each other in the relationship (like Gottman and Levenson’s, 1992, classification a non-regulated couple).

Some have claimed EFT to be the most researched and most e�ective couple’s therapy (Johnson et al., 1999; Wiebe and Johnson, 2016), with 10 sessions of EFT improving dyadic adjustment of the relationship, and others regard it as a form of exposure therapy, exposing the couples to experiences that are emotionally taxing within the relationship (Greenman and Johnson, 2013). A few sessions of EFT have also been found to elicit greater emotional dependency on the partner (allowing to “distribute” the risk), as handholding after EFT reduced the stress experienced after electric shock through

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Coan et al.’s (2006) handholding paradigm (Johnson et al., 2013). Johnson et al.’s (1999) ideas are reminiscent of Gottman and Levenson’s (1992) idea of the “regulated couple” where a positive marital exchange, as a “bidirectional linkage of oscillating patterns. . .(between partners)” contributes to the marriage’s success. In more recent research, this view was supplemented with lower level interactions, not only by being vulnerable and o�oading stress to others (Beckes and Coan, 2011; Butler and Randall, 2013), but now also by our proposal to o�oading temperature regulation to the environment through what we have called the “temperature monetizing system.”

At present, we know that people in high quality relationships increase in peripheral temperature when the other is stressed (Vuorenkoski et al., 1969). The central proposal of STT would be to adjust (i.e., re-associate) peripheral temperatures in a relationship to specific social situations but only if one’s perception of social predictability within the relationship is misaligned. One could thus liken STT to better known neurofeedback paradigms (e.g., Lubar et al., 1995). Altering one’s peripheral temperature without attention to context will certainly not reliably alter the relationship dynamic. Integrating STT into EFT in other words is complex. Not only is it hard for therapists to assess the level of co-regulation in real life, at present it is still unclear when temperature in- or decreases (and how strongly) occur in communal relationships to di�erent emotions by the partner, and it is thus unclear when co- thermoregulation is responsive and when not. Furthermore, some types of emotions are probably reliant on co-regulation (e.g., a “cooling” state like sadness) whereas this may not be true for other emotions (e.g., a “heating” state like anger).8 In addition, it is unclear how frequently one should manipulate peripheral temperature to support the relationship more permanently. What is clear is that STT has the potential to transform EFT by seamlessly tracking couples’ physiology in daily life.

Finally, STT is not a replacement for therapy related to higher order cognition, but should complement existing therapies (like Cognitive Behavioral Therapy and EFT) by addressing lower level dynamics. This is also why not all couples may benefit from aiding the relationship for the sake of staying together. Some clients might be at the end of a relationship and be better o� having the therapist mediate their separation than putting time and e�ort in trying to save the relationship. The challenges seem various and daunting. But we suppose most of these issues are resolvable. We

8This is likely true because the regulation of body temperature can be understood asymmetrically: decreases in temperature are regulated socially, while this is not true of increases in temperature. This is highly contingent on the asymmetry of thermoregulatory systems: increases in core temperature are immediately dangerous for body and brain, whereas this is not true for decrease in temperature (thermosensitive neurons that detect increases in temperature are also more prominent in the hypothalamus, while thermoreceptors detecting coldness are more prominent in the skin; Hensel, 1974; Guyton, 1991). The idea of this asymmetry is also confirmed in the experimental literature: priming of trustworthiness (versus agency) in relationships leads to temperature increases under colder ambient conditions, but not under warmer ambient conditions (Ebersole et al., 2016; IJzerman et al., 2016). In addition, co-thermoregulation is certainly not the only aspect of co-regulation. Specifically, research across (human and non-human) animals also shows the importance of risk distribution (Ebensperger, 2001; Coan et al., 2006).

will now outline the steps to create the most e�cacious STT by doing research during therapists’ EFT sessions with couples.


With the advent of novel technologies, the gap between research and therapy decreases dramatically. For that reason, we describe how thermoregulatory dynamics can be researched during EFT sessions. We hope that interventions can be created based on this research. Between therapy sessions, therapists and researchers can monitor couples’ temperature, location, and proximity continuously for longer periods of time from a distance while the couples live their regular lives. Whereas most eHealth focuses on becoming more e�cient in therapy, once the mechanisms are clearly defined, such real time monitoring can have considerable (practical) transformative consequences as compared to normal EFT, because therapists can start tapping into lower level dynamics. Again, exactly how this could be achieved needs to be researched in between therapy sessions. One of the advantages is that once protocols for STT are developed, the therapist will not simply have to recreate di�cult and emotional interactions, but can instead track his or her clients in their daily lives.

The tools to start such a research endeavor between EFT sessions with tracking are within reach: smartphones and smartwatches have become available with accurate temperature sensors that can measure continuously and