On the social signal function of emotional crying: Broadening the perspective to social interactions in daily life.

Emotional crying is a potent signal that can influence how social interactions unfold. Although the social signal function of crying has been mostly studied in experimental approaches involving hypothetical scenarios with strangers as targets, we propose that daily social interactions should be considered to address aspects of external validity. We conducted three retrospective studies (total N = 2,277; convenience samples; Studies 2 and 3 were preregistered; data were collected in 2022 and 2023) and found that individuals primarily observed close others crying in their daily lives; a boundary condition that was hardly reflected in former studies. Crying episodes were typically characterized by tears and changes in facial expression, vocalizations, and gestures, whereas isolated emotional tears, were rarely reported. Participants indicated that they frequently helped close others, but that helping strangers was the exception. The level of familiarity with the target also influenced the form of help provided. Furthermore, the crying person was rated as less warm and less competent when crying (vs. in general or in a neutral situation). Additional analyses suggest that question order effects and recall biases are no plausible alternative explanations of our findings. Taken together, these results call into question the validity of the experimental approaches used in this line of research. We discuss strategies for future study of the social signal function of crying in nonhypothetical scenarios with reference to the "generalizability crisis" of psychological science. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Inducing empathy affects cardiovascular reactivity reflected in changes in high-frequency heart rate variability.

Empathy represents an emotional trigger of prosocial emotions and social engagement behaviour as previous research demonstrates. Departing from literature indicating that parasympathetic mechanisms are associated with the preparation of social engagement behaviour, the present research investigates how feeling with another person affects empathising individuals' cardiovascular reactivity reflecting influences of parasympathetic mechanisms. Specifically, individuals' high-frequency heart rate variability (HF-HRV) while being instructed to feel with a target person in need reacting with a specific emotional response to a need-causing event (with anger or sadness) was investigated. Results of one experiment (N = 124) revealed that inducing empathy with needy target persons results in increases of HF-HRV - irrespective of their emotional reaction. No relation between cardiovascular indices and self-reported prosocial behaviour was found. Accordingly, these findings indicate that inducing empathy affects phasic vagal activity implied by parasympathetic mechanisms whereas the association of cardiovascular reactivity and social engagement behaviour needs further investigation.

Using a Telegram chatbot as cost-effective software infrastructure for ambulatory assessment studies with iOS and Android devices.

In this work, we present an innovative and cost-effective approach to run ambulatory assessment (AA) studies on participants' smartphones via Telegram Messenger. Our approach works both for Android and iOS devices. The population of potential participants in a given country or region consists of all individuals who (a) are in possession of a smartphone, (b) are willing to install Telegram Messenger, and (c) live in an environment providing constant connection to the Internet. In our new approach to AA, participants are asked to subscribe to a Telegram chatbot that provides them with links to brief surveys at specified points in time in their everyday lives via short notifications. We developed a user-friendly Python script that allows for the flexible editing of the chatbot's settings, e.g., the number of surveys per day. All common survey software designed for mobile devices can be used to present surveys to participants. This means that data collection takes place exclusively via the selected survey software, not via Telegram. With our approach, AA studies can be carried out among iOS and Android users cost-effectively and reliably while data security is ensured. Initial data from a pilot study show that studies of this kind are feasible, and the procedure is accepted by participants. Our Python script is licensed under General Public License (GPLv3) and therefore freely available and editable: https://github.com/Raze97/Telegram-Survey-Bot.