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Background: We examined the feasibility and outcomes of Artificial Intelligence (AI) as a virtual coach in guided self-help (GSH-AI) compared to pure self-help (PSH). Method: Participants (N = 85 undergraduate university students; M age = 20.65 years [SD = 2.38]; 84 % female) were randomised to PSH (N = 42) or GSH-AI (N = 43). The intervention was a brief 11-module online cognitive behaviour therapy for perfectionism intervention completed over 4-weeks. GSH-AI participants were given suggested questions to ask AI for guidance in completing the intervention. Data were collected at baseline, 4- and 8-weeks post-randomisation. Results: Engagement was good, only one person in each group did not use any modules; module completion was equivalent across conditions (6.67, SD = 3.22 and 6.18, SD = 3.42 respectively). Between baseline and post-intervention people in the GSH-AI condition showed an almost 3.5 times increase in preferring support to be received from AI versus other modes of support. Only 52 % and 22 % of participants completed 4- and 8-week post-randomisation surveys, with no differences in psychological outcomes between the PSH and GSH-AI groups. Main effects of time indicated moderate to large within-group effect size improvements for disordered eating, stress, anxiety, and perfectionism. Conclusions: Qualitative feedback indicated that AI was initially acceptable as a guide and became even more acceptable after it had been experienced. Fully powered trials are required to determine the impact of AI guidance on outcomes, and whether type of AI platform (customised versus generic) and type of mental health disorder interact with its effects.

The Coastal and Marine Ecological Classification Standard (CMECS) was applied to four portions of Acadia National Park, USA, focusing on intertidal rocky and tidal flat habitats. Side-scan sonar coupled with multi-phase echo sounder bathymetry are the primary data sources used to map the seafloor, coupled with underwater video imagery and surface grab samples for grain size and macrofaunal analysis. The CMECS Substrate, Geoform, and Biotic components were effective in describing the study areas. However, integrating the CMECS components to define Biotopes was more challenging due to the limited number of grab samples available and because the dominant species within a given map unit is largely inconsistent. While Biotopes ultimately could not be defined in this study, working within the CMECS framework to create statistically significant biotopes revealed the complexity of these study areas that may otherwise have been overlooked. This study demonstrates the effectiveness of the CMECS classification, including the framework’s ability to be flexible in communicating information.

Perfectionism is a transdiagnostic process associated with a range of psychological disorders. Cognitive Behaviour Therapy for Perfectionism (CBT-P) has been demonstrated as efficacious across guided and unguided internet delivered interventions in reducing perfectionism and psychopathology. The aim of this pilot study was to understand perceptions and acceptability of an artificial intelligence supplemented CBT-P intervention (AI-CBT-P) in young people with lived experience of anxiety and depression (n = 8; age range 19–29 years, M = 24 years, SD = 3.77; 50 % female, 38 % male, 12 % non-binary). Young people reported that they were frequent users of artificial intelligence for study, work and general information, were positive about the intervention and using artificial intelligence for guidance in a self-help intervention, but also noted several concerns. Young people perceived numerous benefits to AI-CBT-P, including ease of access, low cost, lack of stigma and benefits for individuals with social anxiety. Overall, young people appear to be interested in, and have a positive view of, AI-CBT-P. Further research is now required to examine the feasibility and acceptability of the intervention.