RESUMO
BACKGROUND: For almost two decades, researchers and clinicians have argued that certain aspects of mental health treatment can be removed from clinicians' responsibilities and allocated to technology, preserving valuable clinician time and alleviating the burden on the behavioral health care system. The service delivery tasks that could arguably be allocated to technology without negatively impacting patient outcomes include screening, triage, and referral. OBJECTIVE: We pilot-tested a chatbot for mental health screening and referral to understand the relationship between potential users' demographics and chatbot use; the completion rate of mental health screening when delivered by a chatbot; and the acceptability of a prototype chatbot designed for mental health screening and referral. This chatbot not only screened participants for psychological distress but also referred them to appropriate resources that matched their level of distress and preferences. The goal of this study was to determine whether a mental health screening and referral chatbot would be feasible and acceptable to users. METHODS: We conducted an internet-based survey among a sample of US-based adults. Our survey collected demographic data along with a battery of measures assessing behavioral health and symptoms, stigma (label avoidance and perceived stigma), attitudes toward treatment-seeking, readiness for change, and technology readiness and acceptance. Participants were then offered to engage with our chatbot. Those who engaged with the chatbot completed a mental health screening, received a distress score based on this screening, were referred to resources appropriate for their current level of distress, and were asked to rate the acceptability of the chatbot. RESULTS: We found that mental health screening using a chatbot was feasible, with 168 (75.7%) of our 222 participants completing mental health screening within the chatbot sessions. Various demographic characteristics were associated with a willingness to use the chatbot. The participants who used the chatbot found it to be acceptable. Logistic regression produced a significant model with perceived usefulness and symptoms as significant positive predictors of chatbot use for the overall sample, and label avoidance as the only significant predictor of chatbot use for those currently experiencing distress. CONCLUSIONS: Label avoidance, the desire to avoid mental health services to avoid the stigmatized label of mental illness, is a significant negative predictor of care seeking. Therefore, our finding regarding label avoidance and chatbot use has significant public health implications in terms of facilitating access to mental health resources. Those who are high on label avoidance are not likely to seek care in a community mental health clinic, yet they are likely willing to engage with a mental health chatbot, participate in mental health screening, and receive mental health resources within the chatbot session. Chatbot technology may prove to be a way to engage those in care who have previously avoided treatment due to stigma.
RESUMO
OBJECTIVE: Misophonia is a psychiatric condition characterized by strong emotional and/or behavioral responses to auditory stimuli, leading to distress and functional impairment. Despite previous attempts to define and categorize this condition, misophonia is not currently included in the Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases. The lack of formal diagnostic consensus presents challenges for research aimed at assessing and treating this clinical presentation. METHODS: The current study presents clinical characteristics of youth (N = 47) with misophonia in the largest treatment-seeking sample to date. We examined demographic characteristics of the sample, frequency of comorbid disorders, frequency of specific misophonia symptoms (i.e., triggers, emotional and behavioral responses, and impairments), and caregiver-child symptom agreement. Misophonia symptoms were evaluated using a multimodal assessment including clinician, youth, and caregiver reports on empirically established misophonia measures, and concordance among measures was assessed. RESULTS: Youth seeking treatment for misophonia presented with marked misophonia symptoms and an array of comorbid conditions. Youth and caregivers identified various triggers of misophonia symptoms (e.g., chewing sounds, breathing sounds), as well as a wide range of emotional (e.g., anger, annoyance, disgust) and behavioral (e.g., aggression, avoidance) responses to triggers. Youth and caregivers exhibited high agreement on misophonia triggers but lower agreement on symptom severity and associated impairment. Compared to younger children (aged 8-13), older children (aged 14+) appeared to report symptom severity and associated impairment more reliably. CONCLUSION: Misophonia is a heterogenous and impairing clinical condition that warrants future investigation and evidence-based treatment development.
