AI for Mental Health and Behavioural Therapy Training Course – Online, 21–25 Feb 2027

AI for Mental Health and Behavioural Therapy is a 1-week training course for psychologists, therapists, counsellors and mental health service managers, in which each participant prepares a digital therapy tool safety review for an app, chatbot or screening tool their service uses or is considering. Waiting lists are long and clients already bring mood apps and chatbot conversations into sessions. Jupiter Prime Training offers AI for Mental Health and Behavioural Therapy to practising clinicians.

Why AI for Mental Health and Behavioural Therapy Matters Now

Three groups shape the subject today. Clients turn to mood trackers and conversational agents between sessions, sometimes in crisis. Service managers face demand that far exceeds therapist capacity and look to guided digital programmes to extend reach. Professional and ethics bodies expect practitioners to protect confidentiality and keep human judgement at the centre of risk decisions. A service that handles this well widens access and spots relapse earlier; one that handles it badly exposes vulnerable clients to unsafe advice and data misuse. The course draws on ISO/IEC 42001 (Artificial Intelligence Management System) and the NIST AI Risk Management Framework (AI RMF).

Who Gains Most from AI for Mental Health and Behavioural Therapy

• Practitioners who deliver cognitive behavioural and other talking therapies
• Counsellors who support clients between sessions through apps or messaging
• Clinicians who carry out risk assessment and safety planning
• Service managers who commission digital therapy platforms
• Clinical leads who supervise therapists and set practice standards

Therapy services gain most when a therapist, a clinical supervisor and a service manager attend together.

AI for Mental Health and Behavioural Therapy Capabilities

The outcomes centre on the therapeutic relationship: where digital tools support it and where they must give way to a human clinician.

• Appraise the evidence and safety design of a digital CBT programme — the decision to offer it to clients
• Weigh mood tracking and passive sensing data against clinical interview findings — treating therapists
• Test a conversational support agent for crisis detection and escalation — crisis teams and clients
• Assess language-based risk screening for false reassurance and bias — clinical supervisors
• Specify consent and confidentiality rules for client data in digital tools — information governance leads
• Communicate the limits of AI support in plain terms — clients and families

Key AI for Mental Health and Behavioural Therapy Terms

• Digital cognitive behavioural therapy (dCBT) — structured CBT delivered through an app or web programme, with or without therapist guidance.
• Ecological momentary assessment — repeated short mood or symptom ratings captured in daily life, often by smartphone prompts.
• Conversational agent — software that holds text or voice dialogue with a client, offering support, psychoeducation or exercises.
• Therapeutic alliance — the working bond and shared goals between client and therapist, a strong predictor of therapy outcomes.
• Risk screening from language — automated scanning of client text or speech for signs of self-harm or crisis.
• Stepped care — a service model matching clients to the least intensive effective support and stepping up when needed.

AI for Mental Health and Behavioural Therapy Day by Day

Day 1: The Digital Mental Health Landscape

• Stepped Care Model Mapping — Where Digital Tools Fit in Treatment Pathways
• Mood Apps, Chatbots and Guided Programmes — Sorting Tool Categories
• Evidence Appraisal for Digital Interventions — Trials Versus Marketing Claims
• Client Expectations and Digital Literacy — Matching Tools to People
• Ethical Principles for Therapy Technology — Autonomy, Beneficence and Non-Maleficence

Day 2: Measurement and Mood Tracking

• Ecological Momentary Assessment Design — Prompt Frequency and Client Burden
• Passive Sensing From Phones and Wearables — Sleep and Activity Signals
• Routine Outcome Measures in Apps — Tracking Progress Between Sessions
• Relapse Signature Detection — Early Warning Conversations With Clients
• Dashboard Review in Supervision — Using Data Without Losing the Person

Day 3: Digital CBT and Conversational Support

• Guided Versus Self-Guided dCBT — Therapist Time and Adherence
• Conversational Agent Scripts — Psychoeducation, Exercises and Boundaries
• Crisis Detection and Escalation Rules — Hand-Off to Human Responders
• Therapeutic Alliance With Blended Care — Keeping the Relationship Central
• Cultural and Language Adaptation — Relevance for Diverse Client Groups

Day 4: Risk, Confidentiality and Oversight

• Language-Based Risk Screening — Sensitivity, False Reassurance and Bias
• Client Data Consent and Sharing — Third-Party Apps and Records
• ISO/IEC 42001 and NIST AI RMF for Therapy Services — Accountability Roles
• Adverse Event and Harm Reporting — Learning From Digital Incidents
• Clinical Supervision of Blended Care — Standards for Practitioners

Day 5: Practising the Digital Therapy Tool Safety Review

• Tool Profile and Evidence Summary — Applying Day 1 Appraisal
• Measurement Plan — Applying Day 2 Tracking Methods
• Escalation and Alliance Safeguards — Applying Day 3 Design Checks
• Confidentiality and Risk Controls — Applying Day 4 Oversight Methods
• Digital Therapy Tool Safety Review — Sign-Off by the Clinical Lead

Applying AI for Mental Health and Behavioural Therapy After the Course

• Test one conversational agent used by clients with scripted crisis phrases and record how and when it escalates
• Introduce ecological momentary assessment for a small group of consenting clients and review the data in supervision

AI for Mental Health and Behavioural Therapy Questions (FAQ)

What is AI for Mental Health and Behavioural Therapy and why does it matter now?

AI for Mental Health and Behavioural Therapy is the safe use of mood tracking, digital CBT, chatbots and risk screening alongside human therapy. It matters now because clients already use these tools and services cannot meet demand alone.

Which roles gain most from AI for Mental Health and Behavioural Therapy?

Psychologists, therapists, counsellors and mental health service managers gain most. You benefit if you deliver talking therapies, carry out risk assessment, supervise practitioners or commission digital therapy platforms.

How does AI for Mental Health and Behavioural Therapy differ from a general clinical AI course?

AI for Mental Health and Behavioural Therapy focuses on talking therapies and client relationships. A general clinical AI course covers hospital decision support; this one covers dCBT, conversational agents, mood data, crisis escalation and therapeutic alliance.

What do you bring back from AI for Mental Health and Behavioural Therapy?

You bring back a digital therapy tool safety review for one app, chatbot or screening tool. It covers evidence, measurement, escalation safeguards and confidentiality controls.

AI for Mental Health and Behavioural Therapy: The Way Forward

The digital therapy tool safety review first informs whether a service should offer a specific app or chatbot to clients, and with what safeguards. Therapists, supervisors and service managers use it to agree escalation rules and consent wording. After the first months of use, revisit its crisis escalation findings, because real client language differs from test scripts.