Advancing Ambulatory Assessment Studies on Psychopathic Traits: A Response to Commentaries

We thank the commentary authors for their constructive and diverse feedback. With few exceptions, we found ourselves in strong agreement with their viewpoints, all of which highlight exciting next steps for ambulatory assessment studies¹ focused on psychopathy. Our response is organized around two themes. First, we consider the generalizability of our results given some specific concerns raised by Verona (2025). Second, we reflect on the commentary authors’ various recommendations on how to extend and improve upon the target article’s approach to studying psychopathic traits in daily life. These themes are crucial to consider when designing future ambulatory assessment on interpersonal and affective (dys)function in psychopathy.

How Should Psychopathy Researchers Sample Individuals and their Experiences?

Verona (2025) questioned the generalizability of our findings, noting the absence of clinical or forensic samples and the lack of elevated psychopathy traits in our samples. Notably, Verona (2025) and Garofalo and colleagues (2025) diverge in their respective assessments on this issue, with Garofalo and colleagues (2025) outlining a rationale for why community-based studies can inform our understanding of severe forms of psychopathology. These views reflect a broader, long-standing debate in psychopathy research on whether psychopathy can be validly studied in non-forensic or non-clinical populations (Patrick, 2022). Addressing these concerns is particularly important since ambulatory assessment in mental health research can be resource intensive (Löchner et al., 2025), and such obstacles are likely to be more pronounced in psychiatric or forensic settings. Thus, it would be challenging to realize the promise of ambulatory assessment if forensic or psychiatric samples are required to study the momentary dynamics relevant to psychopathy.

Verona (2025) argues that the findings from Vize et al. (2025), “are not relevant to Cleckley’s conceptualization, developed in the 1940s based on his observations of psychiatric patients who seemed to exhibit a rare and prototypical phenotype, and also cannot speak to the broader literature on psychopathy assessments conducted with forensic samples.” (p. 9). We disagree, for three reasons. First, although it is well-known that different measures of psychopathy diverge in their operationalization of the construct, PPI-based instruments were explicitly designed to operationalize Cleckley’s model (Lilienfeld & Andrews, 1996). Second, psychopathic traits are dimensional and do not reflect a distinct, non-arbitrary class of individuals. This has been demonstrated in forensic samples of both men (Edens et al., 2006; Guay et al., 2007) and women (e.g., Walters et al., 2007), as well as in youth samples (e.g., Murrie et al., 2007) and mirrors findings for other clinical constructs (Haslam et al., 2012). Additionally, the nomological network of psychopathy is comparable across diverse kinds of samples (e.g., Vachon et al., 2012). Even in community samples, where only 1–2% of individuals show notable elevations in psychopathic traits, psychopathy is still robustly linked to outcomes like violence (Neumann & Hare, 2008), with effect sizes comparable to those in forensic samples (Vitacco et al., 2005). Consistent with Garofalo et al. (2025), we maintain that for many questions involving linear trait–outcome relations, like those addressed in our article, community samples are informative. Although community or student samples are not without limitations (e.g., restricted variance in relevant domains², lack of diversity), there is no compelling reason to restrict the study of Cleckley’s model to clinical or forensic populations.

Verona’s (2025) concern that few participants resembled the “prototypical” Clecklian psychopath touches on a related issue in psychopathy research. As we noted in the target article, scholars have suggested various hypotheses about the nature of relations between psychopathic traits and relevant outcomes, including curvilinear relations or trait-by-trait interactions. Specifically, consistent with Verona’s (2025) commentary, some theorists have argued for an “emergent” hypothesis (Lilienfeld et al. 2019), whereby psychopathy and other personality disorders, “reflect not purely additive combinations of features, but rather emergent properties reflecting specific configurations (read: statistical interactions) among them” (p. 583). However, evidence for these relations is limited (Benning & Smith, 2019; Crowe et al., 2021; Hunt et al., 2015; Kennealy et al., 2010; Sharpe et al., 2021), and recent work has raised conceptual and statistical concerns surrounding trait-by-trait interactions (Baranger et al., 2023; Vize et al., 2022a; Vize et al., 2022b). Thus, evidence suggests that trait-by-trait interactions are unlikely to account for psychopathy’s unique socio-affective deficits. This evidence also runs counter to Verona’s (2025) suggestion that these socio-affective deficits emerge only when studying prototypical cases of psychopathy. These points notwithstanding, ambulatory assessment may offer a way forward. It could clarify any unique contexts where specific psychopathy-related traits, such as boldness, antagonism, or disinhibition, are most likely to be expressed, advancing our understanding of how these traits relate to momentary functioning.

Low Base-Rate Behaviors Relevant to Psychopathy

Verona (2025) also raised a related but distinct concern regarding the frequency and nature of interpersonal conflicts when using non-clinical or non-forensic samples. We agree that individuals with high psychopathy scores are likely to experience more frequent or severe interpersonal conflict than those in community or convenience samples. Consequently, mean levels of psychopathic traits, particularly those related to antagonism and disinhibition, do have important implications for the sampling frame needed to adequately capture specific kinds of interpersonal events relevant to psychopathy (e.g., acts of aggression). Evidence from other intensive longitudinal studies confirms these behaviors are rare, even in clinical populations. For example, in a two-week daily diary study with undergraduates, physical aggression occurred in fewer than 1% of entries, and other antisocial acts (verbal aggression, taking advantage of others) were also infrequent (0.27–9% of all records; Roche et al., 2023). Likewise, in a 100-day study of adults with personality disorders, manipulativeness, impulsivity, and hostility were among the least reported momentary traits (Wright & Simms, 2016). Thus, Verona (2025) rightly highlights the need for designs tailored to capturing low frequency but consequential behaviors to strengthen the generalizability of our results. With these considerations in mind, we turn to the comments on how to build upon our initial results to further our knowledge of socio-affective processes relevant to psychopathy.

Designing Ambulatory Assessment Studies of Psychopathy

Each commentary suggested numerous future directions for ambulatory assessment research on psychopathy. Both Krämer & Wrzus (2025) and Sanchez-Lopez (2025) highlighted the importance of broadening the scope of the assessment of the interpersonal situation. Sanchez-Lopez (2025) and Garofalo and colleagues (2025) also highlighted ways that assessments of affect and affective responses can be strengthened by considering more fine-grained assessments of affect beyond negative and positive affect (Sanchez-Lopez, 2025) as well as different components of emotional experiences such as emotion regulation (Garofalo et a., 2025). Last, Verona (2025) called attention to the broader tendency in psychopathy research to overlook other sources of variance outside the individual that contribute to maladaptive behaviors associated with psychopathy (e.g., distal contextual factors such as neighborhood poverty; Verona & Fox, 2025). There is considerable value in each of these perspectives, and they offer important and exciting ways to expand on our results. Thus, using the perspectives offered by the commentary authors as starting points, we expand on their insights to elaborate how ambulatory assessment methods can advance psychopathy research, and potentially address longstanding debates in the field.

The Role of Time in Ambulatory Assessment Studies of Psychopathy

Ambulatory assessment designs are relatively novel in psychopathy research. As a result, we are in strong agreement with Krämer and Wrzus (2025) that more descriptive work is needed to guide ambulatory assessment studies on psychopathy. Of particular importance is the emphasis Krämer and Wrzus (2025) place on the role of time as it relates to interpersonal and affective dynamics.

Our study found largely null results for the moderating effects of psychopathy traits on momentary socio-affective processes. For example, individuals high in Impulsive Antisociality did not report different affective reactions following perceived negative interactions. These null effects, however, likely depend on the time scale used. Future studies should test whether such effects emerge over shorter intervals (e.g., within 15 minutes of an event). Additionally, many valuable insights can be drawn from descriptive research. Though callousness and lack of empathy are hallmark features of psychopathy, we know very little about the timescale of their expression in daily life. Are there ebbs and flows in callous responses to the emotions of others following relevant interpersonal interactions? Are callous responses consistent across and within different types of relationships (e.g., romantic partners vs. work colleagues)? Descriptive research can help fill in these general knowledge gaps and lay the groundwork for future confirmatory work.

Questions concerning time dovetail nicely with Garofalo and colleagues’ (2025) comments on different stages of emotional experience spanning the generation to regulation of emotions. Implicit in this stage-like understanding of emotional experiences is the need to consider the role of time. To study the dynamics of emotion regulation will likely require more precise time scales. One promising approach is the so-called “micro-burst” design, which increases the temporal precision of momentary assessments but also leveraging the strengths of event-contingent sampling.³ Returning to the example of callous responses to the emotions of others, researchers could use event-contingent microbursts to deliver brief, but frequent momentary surveys of relevant affect items (e.g., guilt, remorse, sympathy) immediately following interpersonal events where an interaction partner expresses distress. This would allow researchers to examine the general trajectory of affective responses to the distress of others, but also examine whether relevant psychopathic personality traits impact the general affective trajectory or regulation of affect following such events (e.g., see Kaurin et al., 2025). Another approach would be to build on the extensive use of laboratory paradigms in psychopathy (Matusiewicz et al., 2018) to demonstrate how socioaffective dynamics assessed in the laboratory may map onto socioaffective dynamics tied to psychopathy in daily life. This approach weds the precision and control offered by experimental design with the ecological validity of ambulatory assessment designs—a recent example that demonstrates the value of such an approach can be found in Edershile and colleagues (2024) investigation of how narcissistic grandiosity and vulnerability assessed in the laboratory during an experimental task related to socioaffective responses to status threats in daily life.

Assessing the Interpersonal Situation

Krämer and Wrzus (2025) and Sanchez-Lopez (2025) both stress the need to go beyond participants’ perceptions of their interactions, and we concur. Indeed, dyadic designs could be leveraged for many theoretically important research questions. For example, a dyadic design with romantic partners could be used to study affective responses to others’ distress, as partner-reported distress naturally serves as the most reliable indicator of such events, compared to the participants’ perceptions of others’ distress. Tools such as dynamic actor-partner interdependence models (Savord et al., 2023) can be incorporated to directly test a wide range of dyadic hypotheses with intensive longitudinal data, and Sanchez-Lopez (2025) highlights how dynamic network analysis would also be valuable for these questions.

As noted by Krämer and Wrzus (2025), passive sensing tools can also be incorporated to address some of the unique challenges for assessing interpersonal situations relevant to psychopathy. As highlighted above, severe interpersonal conflict will occur infrequently, even in high-risk samples. To effectively capture these events, much longer assessment periods are likely needed (i.e., a few days or one week will likely be insufficient), but this must be balanced with an assessment protocol that is not too intensive. Passive sensing may be one promising way that researchers can follow participants for extended periods, while only periodically administering in-depth assessments of rare interpersonal events. Importantly, Krämer and Wrzus (2025) point to studies where passive sensing tools have been used to trigger event-contingent self-report surveys, though there are still technical challenges in implementing these tools (e.g., see Hoemann et al., 2020 and van Halem et al., 2020). Recent work using less obtrusive passive sensing tools have shown that traits with strong ties to psychopathy (antagonism and disinhibition) reliably relate to features derived from smart phone sensors, suggesting additional promise in these tools for future psychopathy research. Specifically, Ringwald and colleagues (2025) found that antagonism was uniquely related to fewer outgoing phone calls and shorter duration of outgoing calls, and disinhibition was negatively related to maximum battery charge. In other work, data from wearable devices have been used alongside machine learning models to predict the onset of aggressive behavior (Imbiriba et al., 2023; Park et al., 2023). Thus, passive sensing tools may be one way to detect interpersonal events relevant to psychopathy and could be combined with micro-burst designs to effectively study low-base rate behaviors and their immediate socio-affective consequences.

Assessing Context, not Just Individuals

Verona (2025) rightly argues that psychopathy research should move beyond the individual to account for broader contextual influences on behavior. This perspective is especially vital for daily life studies. Ambulatory assessment tools, including passive sensors from phones and wearables, can help capture both proximal and distal contextual factors. These technologies are increasingly used to assess contextual influences on health and behavior (Chaix, 2018), and their integration into psychopathy research represents a key opportunity to broaden our assessment focus. As Verona (2025) emphasizes, our understanding of outcomes like antisocial behavior will be woefully incomplete if ambulatory assessment research overlooks the broader context of individuals’ daily lives that contribute to their socio-emotional experiences.

Ensuring Informative Results in Ambulatory Assessment Studies of Psychopathy

We end by considering Garofalo and colleagues (2025) points on the value of publishing null findings as a part of the ongoing process of testing and refining conceptual models of psychopathy. We strongly agree, and note that this also requires researchers ensure that null results are the product of well-powered, severe tests (Mayo & Spanos, 2011). Registered reports offer a powerful tool in this regard, helping mitigate publication bias and ensuring that both significant and null effects are meaningful (Chambers & Tzavella, 2022). Relatedly, both null and positive results alike are most valuable when peers can transparently evaluate the process that produced the results. To this end, we encourage psychopathy researchers interested in pursuing ambulatory assessment methods to incorporate research practices that maximize transparency (Kirtley et al., 2021; Langener et al., 2024).