Couple Communication in Cancer: Protocol for a Multi-Method Examination

Cancer and its treatment pose challenges that affect not only patients but also their significant others, including intimate partners. Accumulating evidence suggests that couples’ ability to communicate effectively plays a major role in the psychological adjustment of both individuals and the quality of their relationship. Two key conceptual models have been proposed to account for how couple communication impacts psychological and relationship adjustment: the social-cognitive processing (SCP) model and the relationship intimacy (RI) model. These models posit different mechanisms and outcomes, and thus have different implications for intervention. The purpose of this project is to test and compare the utility of these models using comprehensive and methodologically rigorous methods. Aims are: (1) to examine the overall fit of the SCP and RI models in explaining patient and partner psychological and relationship adjustment as they occur on a day-to-day basis and over the course of 1 year; (2) to examine the fit of the models for different subgroups (males vs. females, and patients vs. partners); and (3) to examine the utility of various methods of assessing communication by examining the degree to which baseline indices from different measurement strategies predict self-reported adjustment at 1-year follow up. The study employs a longitudinal, multi-method approach to examining communication processes including: standard self-report questionnaires assessing process and outcome variables collected quarterly over the course of 1 year; smartphone-based ecological momentary assessments to sample participant reports in real time; and laboratory-based couple conversations from which we derive observational measures of communicative behavior and affective expression, as well as vocal indices of emotional arousal. Participants are patients with stage II-IV breast, colon, rectal, or lung cancer and their spouses/partners, recruited from two NCI-designated comprehensive cancer centers. Results will be published in scientific journals, presented at scientific conferences, and conveyed to a larger audience through infographics and social media outlets. Findings will inform theory, measurement, and the design and implementation of efficacious interventions aimed at optimizing both patient and partner well-being

Ghost hunting in the nonlinear dynamic machine.

Integrating dynamic systems modeling and machine learning generates an exploratory nonlinear solution for analyzing dynamical systems-based data. Applying dynamical systems theory to the machine learning solution further provides a pathway to interpret the results. Using random forest models as an illustrative example, these models were able to recover the temporal dynamics of time series data simulated using a modified Cusp Catastrophe Monte Carlo. By extracting the points of no change (set points) and the predicted changes surrounding the set points, it is possible to characterize the topology of the system, both for systems governed by global equation forms and complex adaptive systems. RESULTS: The model for the simulation was able to recover the cusp catastrophe (i.e. the qualitative changes in the dynamics of the system) even when applied to data that have a significant amount of error variance. To further illustrate the approach, a real-world accelerometer example was examined, where the model differentiated between movement dynamics patterns by identifying set points related to cyclic motion during walking and attraction during stair climbing. These example findings suggest that integrating machine learning with dynamical systems modeling provides a viable means for classifying distinct temporal patterns, even when there is no governing equation for the nonlinear dynamics. Results of these integrated models yield solutions with both a prediction of where the system is going next and a decomposition of the topological features implied by the temporal dynamics

Benchmarking Mental Health Status Using Passive Sensor Data: Protocol for a Prospective Observational Study

BackgroundComputational psychiatry has the potential to advance the diagnosis, mechanistic understanding, and treatment of mental health conditions. Promising results from clinical samples have led to calls to extend these methods to mental health risk assessment in the general public; however, data typically used with clinical samples are neither available nor scalable for research in the general population. Digital phenotyping addresses this by capitalizing on the multimodal and widely available data created by sensors embedded in personal digital devices (eg, smartphones) and is a promising approach to extending computational psychiatry methods to improve mental health risk assessment in the general population. ObjectiveBuilding on recommendations from existing computational psychiatry and digital phenotyping work, we aim to create the first computational psychiatry data set that is tailored to studying mental health risk in the general population; includes multimodal, sensor-based behavioral features; and is designed to be widely shared across academia, industry, and government using gold standard methods for privacy, confidentiality, and data integrity. MethodsWe are using a stratified, random sampling design with 2 crossed factors (difficulties with emotion regulation and perceived life stress) to recruit a sample of 400 community-dwelling adults balanced across high- and low-risk for episodic mental health conditions. Participants first complete self-report questionnaires assessing current and lifetime psychiatric and medical diagnoses and treatment, and current psychosocial functioning. Participants then complete a 7-day in situ data collection phase that includes providing daily audio recordings, passive sensor data collected from smartphones, self-reports of daily mood and significant events, and a verbal description of the significant daily events during a nightly phone call. Participants complete the same baseline questionnaires 6 and 12 months after this phase. Self-report questionnaires will be scored using standard methods. Raw audio and passive sensor data will be processed to create a suite of daily summary features (eg, time spent at home). ResultsData collection began in June 2022 and is expected to conclude by July 2024. To date, 310 participants have consented to the study; 149 have completed the baseline questionnaire and 7-day intensive data collection phase; and 61 and 31 have completed the 6- and 12-month follow-up questionnaires, respectively. Once completed, the proposed data set will be made available to academic researchers, industry, and the government using a stepped approach to maximize data privacy. ConclusionsThis data set is designed as a complementary approach to current computational psychiatry and digital phenotyping research, with the goal of advancing mental health risk assessment within the general population. This data set aims to support the field’s move away from siloed research laboratories collecting proprietary data and toward interdisciplinary collaborations that incorporate clinical, technical, and quantitative expertise at all stages of the research process. International Registered Report Identifier (IRRID)DERR1-10.2196/5385

The Me in We dyadic communication intervention is feasible and acceptable among advanced cancer patients and their family caregivers

Advanced cancer affects the emotional and physical well-being of both patients and family caregivers in profound ways and is experienced both dyadically and individually. Dyadic interventions address the concerns of both members of the dyad. A critical gap exists in advanced cancer research, which is a failure of goals research and dyadic research to fully account for the reciprocal and synergistic effects of patients' and caregivers' individual perspectives, and those they share. We describe the feasibility and acceptability of the dyadic intervention, which is aimed at facilitating communication and goals-sharing among caregiver and patient dyads while integrating family context and individual/shared perspectives. Pilot study of a participant-generated goals communication intervention, guided by multiple goals theory, with 13 patient-caregiver dyads over two sessions. Patients with advanced cancer and their self-identified family caregivers were recruited from an academic cancer center. Dyads did not have to live together, but both had to consent to participate and all participants had to speak and read English and be at least 18 years or age. Of those approached, 54.8% dyads agreed to participate and completed both sessions. Participants generated and openly discussed their personal and shared goals and experienced positive emotions during the sessions. This intervention showed feasibility and acceptability using participant-generated goals as personalized points of communication for advanced cancer dyads. This model shows promise as a communication intervention for dyads in discussing and working towards individual and shared goals when facing life-limiting or end-of-life cancer

The Promise and the Challenge of Technology-Facilitated Methods for Assessing Behavioral and Cognitive Markers of Risk for Suicide among U.S. Army National Guard Personnel

Suicide was the 10th leading cause of death for Americans in 2015 and rates have been steadily climbing over the last 25 years. Rates are particularly high amongst U.S. military personnel. Suicide prevention efforts in the military are significantly hampered by the lack of: (1) assessment tools for measuring baseline risk and (2) methods to detect periods of particularly heightened risk. Two specific barriers to assessing suicide risk in military personnel that call for innovation are: (1) the geographic dispersion of military personnel from healthcare settings, particularly amongst components like the Reserves; and (2) professional and social disincentives to acknowledging psychological distress. The primary aim of this paper is to describe recent technological developments that could contribute to risk assessment tools that are not subject to the limitations mentioned above. More specifically, Behavioral Signal Processing can be used to assess behaviors during interaction and conversation that likely indicate increased risk for suicide, and computer-administered, cognitive performance tasks can be used to assess activation of the suicidal mode. These novel methods can be used remotely and do not require direct disclosure or endorsement of psychological distress, solving two challenges to suicide risk assessment in military and other sensitive settings. We present an introduction to these technologies, describe how they can specifically be applied to assessing behavioral and cognitive risk for suicide, and close with recommendations for future research

Coregulation of therapist and client emotion during psychotherapy

Objective: Close interpersonal relationships are fundamental to emotion regulation. Clinical theory suggests that one role of therapists in psychotherapy is to help clients regulate emotions, however, if and how clients and therapists serve to regulate each other’s emotions has not been empirically tested. Emotion coregulation – the bidirectional emotional linkage of two people that promotes emotional stability – is a specific, temporal process that provides a framework for testing the way in which therapists’ and clients’ emotions may be related on a moment to moment basis in clinically relevant ways. Method: Utilizing 227 audio recordings from a relationally oriented treatment (Motivational Interviewing), we estimated continuous values of vocally encoded emotional arousal via mean fundamental frequency. We used dynamic systems models to examine emotional coregulation, and tested the hypothesis that each individual’s emotional arousal would be significantly associated with fluctuations in the other’s emotional state over the course of a psychotherapy session. Results: Results indicated that when clients became more emotionally labile over the course of the session, therapists became less so. When changes in therapist arousal increased, the client’s tendency to become more aroused during session slowed. Alternatively, when changes in client arousal increased, the therapist’s tendency to become less aroused slowed.</p

Passive Sensor Data for Characterizing States of Increased Risk for Eating Disorder Behaviors in the Digital Phenotyping Arm of the Binge Eating Genetics Initiative: Protocol for an Observational Study

BackgroundData that can be easily, efficiently, and safely collected via cell phones and other digital devices have great potential for clinical application. Here, we focus on how these data could be used to refine and augment intervention strategies for binge eating disorder (BED) and bulimia nervosa (BN), conditions that lack highly efficacious, enduring, and accessible treatments. These data are easy to collect digitally but are highly complex and present unique methodological challenges that invite innovative solutions. ObjectiveWe describe the digital phenotyping component of the Binge Eating Genetics Initiative, which uses personal digital device data to capture dynamic patterns of risk for binge and purge episodes. Characteristic data signatures will ultimately be used to develop personalized models of eating disorder pathologies and just-in-time interventions to reduce risk for related behaviors. Here, we focus on the methods used to prepare the data for analysis and discuss how these approaches can be generalized beyond the current application. MethodsThe University of North Carolina Biomedical Institutional Review Board approved all study procedures. Participants who met diagnostic criteria for BED or BN provided real time assessments of eating behaviors and feelings through the Recovery Record app delivered on iPhones and the Apple Watches. Continuous passive measures of physiological activation (heart rate) and physical activity (step count) were collected from Apple Watches over 30 days. Data were cleaned to account for user and device recording errors, including duplicate entries and unreliable heart rate and step values. Across participants, the proportion of data points removed during cleaning ranged from <0.1% to 2.4%, depending on the data source. To prepare the data for multivariate time series analysis, we used a novel data handling approach to address variable measurement frequency across data sources and devices. This involved mapping heart rate, step count, feeling ratings, and eating disorder behaviors onto simultaneous minute-level time series that will enable the characterization of individual- and group-level regulatory dynamics preceding and following binge and purge episodes. ResultsData collection and cleaning are complete. Between August 2017 and May 2021, 1019 participants provided an average of 25 days of data yielding 3,419,937 heart rate values, 1,635,993 step counts, 8274 binge or purge events, and 85,200 feeling observations. Analysis will begin in spring 2022. ConclusionsWe provide a detailed description of the methods used to collect, clean, and prepare personal digital device data from one component of a large, longitudinal eating disorder study. The results will identify digital signatures of increased risk for binge and purge events, which may ultimately be used to create digital interventions for BED and BN. Our goal is to contribute to increased transparency in the handling and analysis of personal digital device data. Trial RegistrationClinicalTrials.gov NCT04162574; https://clinicaltrials.gov/ct2/show/NCT04162574 International Registered Report Identifier (IRRID)DERR1-10.2196/3829

Couple Therapy for Military Veterans: Overall Effectiveness and Predictors of Response

Despite the numerous challenges facing U.S. veterans and their relationships, there have been no examinations of the effectiveness of couple therapy for relationship distress provided to veterans. In the present study, 177 couples presenting for couple therapy at two Veteran Administration Medical Centers completed assessments of relationship satisfaction prior to therapy and weekly during therapy. Results revealed that the average couple showed significant gains in relationship satisfaction during treatment (d=0.44 for men; d=0.47 for women); gains were larger for couples beginning therapy in the distressed range (d=0.61 for men; d=0.58 for women) than for couples in the nondistressed range (d=0.19 for men; d=0.22 for women). Rates of premature termination were high, with 19% of couples completing fewer than three sessions and 62% rated as not completing a “full course” of therapy. Benchmarking analyses demonstrated that the average gains were larger than would be expected from natural remission and similar to previous effectiveness trials; however, average gains were smaller than those observed in couple therapy efficacy trials. Relationship, psychological, and demographic characteristics were generally unrelated to the amount of change in therapy after controlling for initial satisfaction. However, African American couples showed significantly larger gains than Caucasian, non-Hispanic couples. Thus, though yielding smaller effects than those shown in efficacy trials, the impact of couple therapy for veterans’ relationship problems appears to generalize across various demographic, psychological, and relationship characteristics. ► This study examined outcomes of behavioral couple therapy in 177 couples. ► Therapy resulted in significant improvement in relationship satisfaction. ► Gains were larger than what would be expected without treatment. ► Gains were smaller than most efficacy trials of behavior couple therapy. ► Gains were larger for more distressed and African-American couples

Do couple-based interventions make a difference for couples affected by cancer?: a systematic review

Background: With the growing recognition that patients and partners react to a cancer diagnosis as an interdependent system and increasing evidence that psychosocial interventions can be beneficial to both patients and partners, there has been a recent increase in the attention given to interventions that target couples. The aim of this systematic review was to identify existing couple-based interventions for patients with cancer and their partners and explore the efficacy of these interventions (including whether there is added value to target the couple versus individuals), the content and delivery of couple-based interventions, and to identify the key elements of couple-based interventions that promote improvement in adjustment to cancer diagnosis