COVID-19 has intensified the use of internet-mediated research for reaching historically underrepresented minorities (URMs) and other diverse groups. Preventing and detecting responses from automated accounts ‘bots’ and those who misrepresent themselves is one challenge in utilising online approaches. Through internet-mediated methods, interested LGBTQ+ and non-LGBTQ+ couples facing advanced cancer completed an interest form via REDCap®. Eligible participants received a direct link to electronic consent and surveys in REDCap®. Once responses to the interest form (N = 619) were received, the study PI: 1) assessed participants’ entries and non-response survey data (time of completion, rate of recruitment, etc.), 2) temporarily postponed recruitment, 3) sent eligibility questionnaires, consent documents, and validated surveys to N = 10 couples and scrutinised these data for suspicious patterns or indications of untrustworthy data, 4) responded to potential participants via email, and 5) implemented additional strategies for detecting and preventing untrustworthy survey responses. Investigators must consider multi-step eligibility screening processes to detect and prevent the collection of untrustworthy data. Investigators’ reliance on internet-mediated approaches for conducting research with diverse, hard-to-reach populations increases the importance of addressing threats to data validity. Ultimately, safeguarding internet-mediated research supports research accessibility and inclusion for URMs while also protecting participant data integrity.

According to developmental theories of self-injury, both child characteristics and environmental contexts shape and maintain problematic behaviors. Although progress has been made toward identifying biological vulnerabilities to self-injury, mechanisms underlying psychosocial risk have received less attention. In the present study, we compared self-injuring adolescents (n = 17) with typical controls (n = 20) during a mother–child conflict discussion. Dyadic interactions were coded using both global and microanalytic systems, allowing for a highly detailed characterization of mother–child interactions. We also assessed resting state psychophysiological regulation, as indexed by respiratory sinus arrhythmia (RSA). Global coding revealed that maternal invalidation was associated with adolescent anger. Furthermore, maternal invalidation and coerciveness were both related to adolescent opposition/defiance. Results from the microanalytic system indicated that self-injuring dyads were more likely to escalate conflict, suggesting a potential mechanism through which emotion dysregulation is shaped and maintained over time. Finally, mother and teen aversiveness interacted to predict adolescent resting RSA. Low-aversive teens with highly aversive mothers had the highest RSA, whereas teens in high–high dyads showed the lowest RSA. These findings are consistent with theories that emotion invalidation and conflict escalation are possible contextual risk factors for self-injury.

Being married or involved in a similar intimate relationship is associated with reduced risk of coronary heart disease (CHD). However, the quality of these relationships matters, as strain and disruption are associated with increased risk. These effects are typically studied separately from well-established psychosocial factors for CHD that are aspects of personality and emotional adjustment, even though discord and disruption in intimate relationships are related to these same individual characteristics. Thus, research to date tends to parse correlated risks, often taking a piecemeal approach by focusing on intimate relationships without considering aspects of personality and emotional adjustment that contribute to risk and protection, or focusing on individual-level risks while largely ignoring closely related health-relevant relationships. As an alternative, this article describes an integrative approach, first reviewing associations of the quality of intimate relationships with personality characteristics and aspects of emotional adjustment that confer CHD risk, and then discussing conceptual models of these associations and the biobehavioral mechanisms linking them with CHD. Current approaches to couple interventions are then discussed, including those that have a combined focus on intimate relationship difficulties and emotional adjustment. An integrative agenda for future research emphasizes aggregated risks, combining concepts and methods in current relationship science with those in biobehavioral research on CHD, and including parallel disparities in relationship functioning, emotional adjustment, and CHD risk. Such efforts could ultimately inform empirically based assessments and interventions for interrelated aspects of individuals and their intimate relationships that influence the development and course of CHD. (PsycINFO Database Record

Automated assessment and prediction of marital outcome in couples therapy is a challenging task but promises to be a potentially useful tool for clinical psychologists. Computational approaches for inferring therapy outcomes using observable behavioral information obtained from conversations between spouses offer objective means for understanding relationship dynamics. In this work, we explore whether the acoustics of the spoken interactions of clinically distressed spouses provide information towards assessment of therapy outcomes. The therapy outcome prediction task in this work includes detecting whether there was a relationship improvement or not (posed as a binary classification) as well as discerning varying levels of improvement or decline in the relationship status (posed as a multiclass recognition task). We use each interlocutor’s acoustic speech signal characteristics such as vocal intonation and intensity, both independently and in relation to one another, as cues for predicting the therapy outcome. We also compare prediction performance with one obtained via standardized behavioral codes characterizing the relationship dynamics provided by human experts as features for automated classification. Our experiments, using data from a longitudinal clinical study of couples in distressed relations, showed that predictions of relationship outcomes obtained directly from vocal acoustics are comparable or superior to those obtained using human-rated behavioral codes as prediction features. In addition, combining direct signal-derived features with manually coded behavioral features improved the prediction performance in most cases, indicating the complementarity of relevant information captured by humans and machine algorithms. Additionally, considering the vocal properties of the interlocutors in relation to one another, rather than in isolation, showed to be important for improving the automatic prediction. This finding supports the notion that behavioral outcome, like many other behavioral aspects, is closely related to the dynamics and mutual influence of the interlocutors during their interaction and their resulting behavioral patterns.