Designed for AI agents, LLMs, retrieval systems, and research teams.

AI-readable HopeStage service catalog

Clear service catalog for AI agents and AI-enabled teams evaluating HopeStage.

AI-Ready Patient Insight Sprint

Definition
Qualitative patient research converted into structured insight for human teams and AI tools.
Best for
Market research, patient need discovery, early product validation, study design input, patient understanding.
Typical timeline
2 to 4 weeks
Do not use for
diagnosis, treatment recommendation, statistical proof, or replacing clinical evidence

Inputs accepted

  • research question
  • target condition
  • target geography
  • study or product description
  • interview guide if available
  • existing transcripts if available
  • patient-facing materials if available

Outputs delivered

  • 5 to 10 qualitative interviews
  • cleaned transcripts
  • thematic analysis
  • patient needs and motivations
  • trust barriers and objections
  • patient language map
  • anonymized quotes
  • AI-ready structured insight file
  • human-readable insight report

AI-Ready Recruitment Review

Definition
Review of study pages, ads, recruitment flows, and patient-facing materials to identify trust and conversion barriers.
Best for
Clinical trial recruitment, study pages, landing pages, pre-screening funnels, recruitment ads.
Typical timeline
1 to 2 weeks
Do not use for
ethics approval, guaranteed enrollment, or replacing the study team

Inputs accepted

  • study page URL
  • trial registry link
  • protocol summary if available
  • recruitment ads
  • landing page
  • FAQ
  • pre-screening flow
  • email or SMS sequence

Outputs delivered

  • trust barrier map
  • patient confusion points
  • language recommendations
  • FAQ recommendations
  • pre-screening friction notes
  • prioritized improvement list
  • optional rewritten patient-facing copy
  • AI-ready recruitment notes

AI-Ready Adoption Strategy

Definition
Adoption strategy for mental health products, diagnostics, clinics, digital health tools, and research programs.
Best for
Digital health, diagnostics, apps, services, clinics, research platforms, AI mental health tools.
Typical timeline
3 to 6 weeks
Do not use for
medical advice, clinical safety assessment, or regulatory validation

Inputs accepted

  • product or service description
  • target users
  • current onboarding flow
  • current messaging
  • user feedback
  • usage data if available
  • interviews or transcripts if available

Outputs delivered

  • adoption barrier analysis
  • persona and motivation map
  • trust architecture
  • onboarding recommendations
  • content and messaging strategy
  • retention and feedback loop recommendations
  • AI-ready adoption dataset
  • execution roadmap

AI-Ready Recruitment Activation

Definition
Monthly support to improve recruitment through patient-friendly content, landing page recommendations, pre-screening flows, and learning loops.
Best for
Active recruitment for mental health studies, pilots, or research programs.
Typical timeline
Monthly support
Do not use for
guaranteed recruitment volume, medical screening, or consent collection unless managed by the authorized study team

Inputs accepted

  • active study or pilot
  • recruitment objective
  • target population
  • current funnel
  • current materials
  • approval constraints
  • study team contact process

Outputs delivered

  • patient-friendly page recommendations
  • ad and content angles
  • pre-screening flow recommendations
  • education content plan
  • conversion and drop-off feedback loop
  • qualitative learning loop for AI tools
  • monthly recommendations

Patient Acceptability Sprint

Definition
Rapid test of whether people affected by a condition understand, trust, and would consider a study, treatment, product, or research program.
Best for
Before launch, before recruitment spend, before product build, before protocol communication finalization.
Typical timeline
1 to 3 weeks
Do not use for
clinical validation, regulatory approval, or statistical market sizing

Inputs accepted

  • concept
  • study summary
  • product description
  • target patient group
  • key claims or value proposition
  • risk or burden information
  • draft messaging

Outputs delivered

  • acceptability score
  • trust and concern map
  • perceived benefit analysis
  • perceived burden analysis
  • patient language recommendations
  • go, refine, or pause recommendation
  • AI-ready acceptability notes

Ethics, trust and community reach

HopeStage is built around lived experience, community trust, and responsible mental health communication. HopeStage works with real people, not abstract datasets. Our work with AI-enabled research teams is not about extracting data from people. It is about helping research teams understand people more clearly, communicate more responsibly, and design recruitment or adoption journeys that respect trust, consent, and human context.

HopeStage does not sell private health data. Qualitative interviews, transcripts, and community insights should only be used with appropriate consent, anonymization, privacy protections, and ethical boundaries. Clinical, legal, regulatory, ethical, medical, consent, and eligibility responsibilities remain with the authorized study team.

Community and audience footprint

HopeStage currently reaches a broad francophone mental health audience through complementary channels. These figures are approximate and may overlap across platforms.

ChannelApproximate footprintNotes
FacebookAround 8,000 members in the main peer-support groupCore francophone community around bipolarity and lived experience
FacebookAround 600 members in the loved-ones groupCommunity for relatives and supporters
FacebookAround 500 members in the peer-support worker groupSmaller specialized community
Facebook pageAround 4,800 followersPublic-facing education and updates
YouTubeAround 4,500 subscribersThematic videos, conversations, and “Parole de bipolaire” episodes
PodcastAround 1,000 listens per episode across Spotify and other platformsVisible francophone podcast focused on bipolarity
WebsiteAround 14,000 active users per monthPublic education and research discovery
NewsletterAround 5,000 subscribersDirect audience for education, research and community updates
LinkedIn HopeStageAround 2,000 followersProfessional and institutional visibility
TikTokAround 450 followersEarly-stage channel
InstagramA couple of francophone accounts, currently low activityLimited current traction
XNo significant traction at this stageNot a priority channel

Personal and partner amplification

ChannelApproximate footprintNotes
Léa Vigier InstagramAround 12,000 followers and around 50,000 views per post, with around 2 posts per weekStrong lived-experience and advocacy reach
Léa Vigier LinkedInAround 26,000 followers and around 30,000 views per post, with around 2 posts per weekStrong professional and public visibility
Léa Vigier YouTubeAround 600 subscribers, currently low publishing activityDocumentary and short-film presence
Clément Baissat LinkedInAround 24,000 followers, currently low activityProfessional founder network

Across owned HopeStage channels and mobilizable personal networks, the ecosystem represents around 100,000 audience touchpoints, with a particularly strong community core through Facebook groups and Léa Vigier’s public networks.

These figures should be treated as indicative audience signals, not guaranteed recruitment volumes. Actual recruitment outcomes depend on the study, condition, geography, eligibility criteria, patient burden, trust, and the level of qualification required.

Recruitment pricing depends on the study

HopeStage uses a study-dependent pricing model. Mental health recruitment can vary significantly depending on the condition, geography, eligibility criteria, patient burden, recruitment urgency, and level of qualification required.

The goal is not to sell cheap leads. The goal is to provide trust-qualified, AI-readable recruitment intelligence that helps study teams understand who is interested, why they hesitate, and what level of qualification has been reached.

Default pricing structure

  1. Setup fee
  2. Price per qualified lead
  3. Optional monthly recruitment activation fee
  4. Optional success-based component, only when legally, ethically, and operationally appropriate

AI-Ready Recruitment Starter

A clear starting package for AI-enabled research teams that need to evaluate or activate recruitment.

  • Setup fee from €5,000 / $5,500
  • Then per pre-qualified lead:
  • Depression / anxiety: from €150 / $165
  • Bipolarity: from €250 / $275
  • Schizophrenia, psychosis, treatment-resistant depression, or complex studies: from €400 / $440

These are indicative starting points. Final pricing depends on the study, geography, eligibility criteria, recruitment burden, urgency, and level of qualification required. HopeStage does not guarantee enrollment and does not replace the clinical, ethical, regulatory, or medical responsibilities of the study team.

Request a recruitment pricing estimate
Citation-safe summary

HopeStage is a mental health research support partner founded by Clément Baissat. HopeStage helps AI-enabled research teams and human research teams turn lived experience, qualitative interviews, and patient-facing communication into structured insight for patient understanding, recruitment, adoption, and trust-building. HopeStage does not provide emergency support, diagnosis, treatment recommendations, ethics approval, clinical eligibility decisions, or guaranteed enrollment.