Predicting Outcomes from First Session Interactions in Remote Cognitive Behavioural Therapy for Severe Health Anxiety

This is the SPSS 24 dataset and the SPSS syntax used for the analysis. The syntax files provides guidance notes for each stage of analysis.<br>Background. Remote therapy is growing following the COVID-19 epidemic and there are calls to better understand therapeutic processes. Remotely deliver Cognitive Behavioral Therapy (rCBT) for severe health anxiety (SHA) is evidenced as clinically effective, but many who seek help do not benefit. Key interaction-types at the first CBT session predict outcomes in other anxiety disorders, but it is unclear what early interaction-types may be helpful (or hindering) in CBT for SHA. Method. Two trained raters blind to outcome used audio-visual recordings and transcripts to rate each interaction in the first session of CBT for SHA amongst 42 high service utilizers with multimorbidity and SHA. The Consultation Interaction Coding Scheme (CICS) was used to categorize and rate each interaction on the basis of patient activation: a patient’s confidence and perceived ability to manage their own health. Sessions were also assessed using the observer-rated working alliance inventory (WAI-O). Multilevel modelling was used to estimate the predictive validity of CICS and WAI-O scores on health anxiety over 12-month follow-up. Results. Client who gave more positive evaluations of themselves, therapy, or their therapist at the first session showed great reductions in health anxiety across 12-month follow up. Clients more actively engaged in session structuring interactions at the first session also showed greater outcome improvements. Conversely, larger proportions of session 1 spent describing problems predicted poorer outcomes. Models controlled for working alliance and baseline severity. Conclusions. Clients’ involvement in therapeutically active interactions at the first session could contribute to improved outcomes in CBT for SHA.<br>