Uwe Altmann

Throughout life, strong social connections foster well-being. Expressing self-relevant information can strengthen these connections. We aim to understand the role of responders’ responsive behavior in promoting speakers’ expressivity and interpersonal closeness by investigating responders’ individual contributions to dyadic movement synchrony. Taking a dyadic perspective, we hypothesized that responders’ motor following (i.e., movement alignment with speakers) is associated with speakers’ perceived closeness and expressivity, and that speakers’ closeness is linked to their own expressivity. We explored interindividual differences with the example of adult age. We analyzed 101 videos of dyadic conversations among unacquainted younger (20–31) and older (69–80) women paired in age-homogeneous or age-heterogeneous dyads. Motor following was assessed via video analyses, expressivity with behavioral coding, and closeness using self-reports. Contrary to our hypotheses, responders’ motor following was not significantly associated with speakers’ perceived closeness or expressivity. However, exploratory analyses considering age as a moderator revealed that among older, but not younger, speakers, responders’ increased motor following was associated with higher perceived closeness. As hypothesized, participants’ higher closeness was linked to their own higher expression of thoughts and feelings. Unexpectedly, participants’ expressivity was linked to their own motor following, suggesting both behaviors reflect conversational engagement. We speculate that older adults may perceive motor following as responsive, possibly indicating age-related differences in social processes.

In triadic social interaction, autonomic coordination is dynamic and may be poorly captured by session‐level synchrony estimates. We propose a state‐based framework to quantify time‐varying interpersonal synchrony during a laboratory group decision‐making task (Desert Survival Task) using concurrently recorded electrodermal activity (EDA) and ECG‐derived heart rate variability (HRV). Twelve triads (36 participants) with complete physiological recordings were analyzed. Signals were segmented into overlapping 60 s windows (1 s step). For each participant, window‐level features were extracted (EDA: 4 features; HRV: 74 features), standardized within individuals, and converted to dyadic divergence vectors (absolute differences) for the three dyads in each triad. Divergence vectors (combined EDA plus HRV) were reduced with PCA (95% variance retained) and clustered using a single global k ‐means model trained on pooled windows to yield five discrete synchrony states shared across triads. States were ordered along the first principal component (PC1) of the divergence space, with its orientation chosen so that State 0 corresponded to the highest‐synchrony state (HSS). Triad‐level state metrics quantified both prevalence and temporal stability: fractional occupancy rate (FOR), mean dwell time (MDT), and conditional long‐run fraction (CLRF; ≥ 10 s runs). Empirical triads showed a graded continuum of synchrony across states and a strong bias toward the HSS. Surrogate validation using a leave‐one‐fixed Iterative Amplitude Adjusted Fourier Transform (IAAFT) null applied at the signal level demonstrated that HSS occupancy and stability exceeded chance alignment (FOR; p < 0.001; MDT and CLRF; p < 0.001). Convergent validity of the proposed state representation was further supported by continuous signal‐based benchmarks: compared with State 4, State 0 showed lower dynamic time warping distances and higher lag‐optimized physiological linkage (max R ² ) for both EDA and HRV (all p < 0.001). In contrast, group‐mean anxiety measures (SPIN, STAI) were not reliably associated with HSS prevalence or stability in this sample. These findings suggest that discrete synchrony states capture interpretable, non‐random coordination regimes in triads and provide a complementary framework for characterizing the temporal organization of autonomic synchrony beyond conventional continuous synchrony measures.

The meaning of a smile during conversation depends on what is beingsaid, yet psychotherapy research has historically analyzed facial movements independently ofcontext. We introduce a methodology that links both partners’ smiling in a dyadic setting tothe sentiment of a speech turn (positive, neutral, negative). Using open-weight models on localhardware only, we transcribed and diarized attachment interviews, annotated the sentiment ofthe participant’s speech turns with a large language model (LLM), and analyzed individual smiling and smile synchrony as a function of that sentiment. We applied linear mixed models totest for differences in smiling according to sentiment. Across 70 interviews and 1,294 speechturns, only the interviewer’s smiling differed significantly according to the sentiment of whatthe participant was saying (interviewer d = .51, q < .001; participant d = .05, q = .165); thepair smiled simultaneously more often during positive than negative turns (d = .21, p < .001).By conditioning smiling on what is being said — sentiment annotated from the conversationas it unfolds rather than created by experimental instruction — our method enables the kind ofcontext-sensitive analysis contemporary theories call for. The pipeline is open and reproducible,runs entirely on local hardware so that no data leave the site, and can be easily modified for anyannotation scheme or clinical setting.

The therapeutic alliance is a strong predictor of treatment outcome. Recent research emphasizes distinguishing between trait-like and state-like alliance. This study used the Social Relations Model (SRM) to analyze the variance attributable to the different trait and state components. Specifically, we focused on the bond component of the alliance and examined the extent to which SRM elements - Perceiver effect (evaluating relationships consistently), Target effect (being consistently perceived by others), and Relationship effect (influences specific to the dyad) contribute to the bond variance, and their associations with treatment outcome. Bond ratings of 118 patients with major depressive disorder receiving psychodynamic psychotherapy, and three treatment-agents (therapists, case managers and interviewers) were analyzed, using the Working Alliance Inventory. Outcomes were assessed using the Hamilton Rating Scale for Depression. Variance partitioning of the elements showed that the perceiver effect accounted for the largest proportion of bond rating variance for patients and treatment-agents. The relationship effect (of patients and treatment-agents) emerged as a significant predictor of treatment outcome. Applying SRM across psychotherapy advances understanding of trait/state-like bond contributions to outcomes. Our findings underscore the potential of the unique relationship to capture processes of change, beyond stable patients' and therapists' characteristics.

The predictive power of movement and electrodermal activity (EDA) synchrony has been demonstrated in various studies. Although most studies have examined each synchrony modality separately, a growing interest in the simultaneous investigation of multiple modalities has emerged. Previous research has demonstrated the importance of disentangling within and between‐dyad effects, however within and between‐therapist effects have yet to be investigated. The aim of the present study was to test whether movement and EDA synchrony (measured both within and between therapists) predict across‐session symptom change in two types of interventions (emotion‐focused vs. cognitive). The results are based on 990 session segments of 90 clients with test anxiety who were treated with a six‐session treatment program by 22 therapists, treating 3–15 clients each. Movement synchrony (on the basis of motion energy analysis (MEA) values) and EDA synchrony were quantified using cross‐correlations. Symptom severity was assessed before each session using the state test anxiety measure. Movement and EDA synchrony correlated negatively (−0.19, p < .001). Moreover, higher movement synchrony as well as an interaction between movement and EDA synchrony was significantly associated with symptom improvement within, but not between therapists. In addition, an interaction between EDA synchrony and cognitive (versus emotion‐focused) interventions was significantly associated with symptom improvement. These results provide initial evidence that therapists' average levels of synchrony may matter less than how synchronous they are with a specific client.

Purpose: Cancer is associated with an urgent need for understandable and reliable information, which is often not satisfied by information available online. Therefore, as part of the PIKKO project, a web-based knowledge database (WDB) was introduced to provide cancer patients with quality-assured, evidence-based information. This paper aims to provide insights into the usage (Who? How? What?) and the effects regarding health literacy of the WDB. Methods: A patient survey and automatically generated logfile data were evaluated. Two user groups, patients and patient navigators (PNs), were compared. Results: The 13 PNs were responsible for 1/3 of all accesses over the entire duration of the project. The 413 patients used WDB twice on average and spent an average of 12 min per session online (PNs: 9 min per session, more frequently). The top 3 topics of interest were ‘therapy’, ‘nutrition’ and ‘carcinogenesis’ for the patients, and ‘therapy’, ‘naturopathy’ and ‘legal regulations/support’ for the PNs. Of the patients surveyed, 69% said that WDB was helpful in making informed decisions, 76% found the information they wanted and 90% thought WDB was an appropriate way to provide information. Conclusion: Our WDB provided important information about cancer and its treatment on a digital way both, to patients and PNs. In routine cancer care, the WDB can improve health literacy and informed decision-making. Trial registration: This study was retrospectively registered in the German Clinical Trial Register under DRKS00016703 (21 Feb 2019, retrospectively registered). https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00016703

In clinical research, the dependence of the results on the methods used is frequently discussed. In research on nonverbal synchrony, human ratings or automated methods do not lead to congruent results. Even when automated methods are used, the choice of the method and parameter settings are important to obtain congruent results. However, these are often insufficiently reported and do not meet the standard of transparency and reproducibility. This tutorial is aimed at researchers who are not familiar with the software Praat and R and shows in detail how to extract acoustic features like fundamental frequency or speech rate from video or audio files in conversations. Furthermore, it is presented how vocal synchrony indices can be calculated from these characteristics to represent how well two interaction partners vocally adapt to each other. All used scripts as well as a minimal example, can be found on the Open Science Framework and Github.

Purpose: Many concepts for accompanying and supporting cancer patients exist and have been studied over time. One of them was PIKKO (a German acronym for “Patient information, communication and competence empowerment in oncology”), which combined a patient navigator, socio-legal and psychological counseling (with psychooncologists), courses dealing with various supportive aspects, and a knowledge database with validated and easy-to-understand disease-related information. The aim was to increase the patients' health-related quality of life (HRQoL), self-efficacy as well as health literacy and to reduce psychological complaints such as depression and anxiety. Methods: To this purpose, an intervention group was given full access to the modules in addition to treatment as usual, while a control group received only treatment as usual. Over twelve months, each group was surveyed up to five times. Measurements were taken using the SF12, PHQ-9, GAD, GSE, and HLS-EU-Q47. Results: No significant differences were found in scores on the mentioned metrics. However, each module was used many times and rated positively by the patients. Further analyses showed a tendency higher score in health literacy with higher intensity of use of the database and higher score in mental HRQoL with higher intensity of use of counseling. Conclusion: The study was affected by several limitations. A lack of randomization, difficulties in recruiting the control group, a heterogeneous sample, and the COVID-19 lockdown influenced the results. Nevertheless, the results show that the PIKKO support was appreciated by the patients and the lack of measurable effects was rather due to the mentioned limitations than to the PIKKO intervention. Trial registration: This study was retrospectively registered in the German Clinical Trial Register under DRKS00016703 (21.02.2019, retrospectively registered). https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00016703