Developing Annotation Guidelines for CSAM Prevention Interventions: Psychosocial Risk and Protective Factors Grounded in Research and Clinical Practice
Proceedings of the Sixth Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments in cooperation with the MENTAL.ai consortium
Abstract
This work discusses sexual offending, specifically child sexual abuse material (CSAM), in the context of prevention. We introduce a domain-specific, span-level annotation scheme and guidelines to identify psychosocial risk and protective factors in therapist-led, anonymous chat interventions with voluntarily help-seeking individuals concerned about their pedophilic interests and the risk of CSAM use. The scheme is grounded in previous research and clinical experience, and intended for within-intervention guidance and longitudinal tracking, rather than actuarial risk scoring. Annotating a pilot subset (8 clients, 31 sessions), inter-annotator agreement was moderate but improved after calibration, which is consistent with the linguistic and clinical ambivalence present in the data. We track a session-wise Protective Ratio, i.e., the share of protective factors among all coded factors, and examine its behaviour over time during the intervention and around self-reported relapse within clients. In exploratory automation, LLM-based span extraction outperforms BERT baselines but overall performance remains limited by small data and mixed-evidence spans. While complete anonymisation of the corpus is in progress, we release the label scheme, guidelines, and non-sensitive artefacts of our analyses.