How to foster perceived partner responsiveness: High-quality listening is key

Adults with Attention-Deficit/Hyperactivity Disorder (ADHD) often face significant deficits in executive function and adverse work-related outcomes. This study aimed to explore the role of executive function deficits in job burnout of employees with ADHD. We hypothesized that employees with ADHD, relative to employees without ADHD, will experience higher levels of job burnout and deficits in executive function. We also hypothesized that the ADHD-job burnout relationship would be mediated through executive function deficits, specifically by selfmanagement to time and self-organization/problem-solving. A field study with 171 employees provided support for the research hypotheses and mediation model in which the employees’ ADHD-job burnout relationship was mediated through executive function deficits. Additional mediation analyses indicated that the specific executive function of self-management to time and self-organization/problem-solving mediated the effect of ADHD on job burnout and its facets. Specifically, for physical fatigue, the mediation was realized through self-management to time, and for emotional exhaustion and cognitive weariness, the mediation was significant through selforganization/problem-solving. The present findings shed light on the relevance of referring ADHD among employees, their vulnerability to job burnout, and the role of executive function deficits in job burnout of employees with ADHD.

Conversational artificial intelligence (AI) can be harnessed to provide supportive parasocial interactions that rival or even exceed social support from human interactions. High-quality listening in human conversations fosters social connection that heals interpersonal wounds and lessens loneliness. While AI can furnish advice, listening involves the speakers’ perceptions of positive intention, a quality that AI can only simulate. Can such deep-seated support be provided by AI? This research examined two previously siloed areas of knowledge: the healing capabilities of human interpersonal listening, and the potential for AI to produce parasocial experiences of connection. Three experiments (N = 668) addressed this question through manipulating conversational AI listening to test effects on perceived listening, psychological needs, and state loneliness. We show that when prompted, AI could provide high-quality listening, characterized by careful attention and a positive environment for self-expression. More so, AI’s high-quality listening was perceived as better than participants’ average human interaction (Studies 1–3). Receiving high-quality listening predicted greater relatedness (Study 3) and autonomy (Studies 2 and 3) need satisfaction after participants discussed rejection (Study 2–3), loneliness (Study 3), and isolating attitudes (Study 3). Despite this, we did not observe downstream lessening of loneliness typically observed in human interactions, even for those who were high in trait loneliness (Study 3). These findings clearly contrast with research on human interactions and hint at the potential power, but also the limits, of AI in replicating supportive human interactions.