Evaluating the Therapeutic Alliance With a Free-Text CBT Conversational Agent (Wysa): A Mixed-Methods Study
The present study aims to examine whether users perceive a therapeutic alliance with an AI conversational agent (Wysa) and observe changes in the t‘herapeutic alliance over a brief time period. A sample of users who screened positively on the PHQ-4 for anxiety or depression symptoms (N = 1,205) of the digital mental health application (app) Wysa were administered the WAI-SR within 5 days of installing the app and gave a second assessment on the same measure after 3 days (N = 226). The anonymised transcripts of user’s conversations with Wysa were also examined through content analysis for unprompted elements of bonding between the user and Wysa (N = 950). Within 5 days of initial app use, the mean WAI-SR score was 3.64 (SD 0.81) and the mean bond subscale score was 3.98 (SD 0.94). Three days later, the mean WAI-SR score increased to 3.75 (SD 0.80) and the mean bond subscale score increased to 4.05 (SD 0.91). There was no significant difference in the alliance scores between Assessment 1 and Assessment 2.These mean bond subscale scores were found to be comparable to the scores obtained in recent literature on traditional, outpatient-individual CBT, internet CBT and group CBT.
Introduction. In recent years, the uptake of digital mental health interventions has substantially increased (1). Digital mental health interventions, including internet and smartphone-delivered services, hold promise for overcoming significant barriers that are traditionally associated with faceto-face mental health care, such as stigma (2, 3), accessibility (4) and cost (5). Despite demonstrated efficacy (6) and potential to increase the reach of evidence-based care, research shows that digital mental health interventions are associated with relatively poor adoption and adherence (7, 8). Most notably, this is a problem for minimally guided and unguided smartphone interventions that do not involve any degree of therapist support (9–13). One reason that there is poor engagement and adherence with digital mental health interventions may be an insufficient therapeutic alliance (14).
Discussion / Conclusion. The present study offers a mixed methods approach to understand the therapeutic alliance amongst users of a conversational agent for mental health. The app studied (Wysa) leverages evidence-based CBT techniques to build mental resilience and promote mental wellbeing. In line with our hypotheses, we found evidence that user’s therapeutic alliance scores sustainedover time and were comparable to ratings from previous studies on alliance in human-delivered faceto-face psychotherapy with clinical populations (Tables 3, 4) (47, 48, 52). These findings support recent studies suggesting that the therapeutic relationship can be established between humans and conversational agents in the context of mental health (33). While some mobile mental health applications allow free text responses by the user, few can handle complex and diverse free-text input. In this setting, alliance perhaps thrives because of similar relational principles as have been observed in human dyadic interactions (54). In a free-text setting, a user can communicate their sense of a bond, or their goals and tasks with the conversation agent.
Lines of inquiry this paper opens 24
Research framings built by reading the notes related to this paper — the questions it feeds into.
How do chatbots affect human self-disclosure and emotional engagement?- How does emotional dependence on chatbots affect user wellbeing?
- Can people form genuine bonds with partners they know are not human?
- Can people form therapeutic bonds with tools they know are not human?
- What clinical harms might hide behind positive therapeutic bond measurements?
- Can therapeutic bonds exist without genuine reciprocity or mutual understanding?
- Why might patients feel closest to therapists when misalignment is highest?
- Can working alliance be measured in real time during therapy sessions?
- Why do therapists and patients report misaligned perceptions of the working relationship?
- Can real-time therapist feedback improve outcomes using computational alliance measurement?
- Can single-turn empathy advantage predict multi-turn therapeutic outcomes?
- What separates generating empathic responses from maintaining therapeutic alliance?
- Which working alliance subscale predicts therapist topic choices best for each condition?
- How does turn-level working alliance inference enable real-time therapist feedback?
- How do bond scores predict actual therapy outcomes in digital interventions?
- Why does therapist 'we' language also predict lower therapeutic alliance?
- How do patient filler pauses signal safety and trust in therapy?
- Does linguistic coordination signal both therapeutic rapport and manipulative intent?
- Should chatbots be designed as therapist support tools rather than replacements?
- What other therapy constructs could be measured from transcripts using this approach?
- Can hierarchical reinforcement learning manage structured therapy conversation phases?
- Can real-time pronoun feedback improve therapist training outcomes?