Study protocol of a randomised controlled trial on SISU, a software agent providing a brief self-help intervention for adults with low psychological well-being
Bibliographic record
Abstract
INTRODUCTION: Only a minority of people living with mental health problems are getting professional help. As digitalisation moves on, the possibility of providing internet/mobile-based interventions (IMIs) arises. One type of IMIs are fully automated conversational software agents (chatbots). Software agents are computer programs that can hold conversations with a human by mimicking a human conversational style. Software agents could deliver low-threshold and cost-effective interventions aiming at promoting psychological well-being in a large number of individuals. The aim of this trial is to evaluate the clinical effectiveness and acceptance of the brief software agent-based IMI SISU in comparison with a waitlist control group. METHODS AND ANALYSIS: Within a two-group randomised controlled trial, a total of 120 adult participants living with low well-being (Well-being Scale/WHO-5) will be recruited in Germany, Austria and Switzerland. SISU is based on therapeutic writing and acceptance and commitment therapy-based principles. The brief intervention consists of three modules. Participants work through the intervention on 3 consecutive days. Assessment takes place before (t1), during (t2) and after (t3) the interaction with SISU, as well as 4 weeks after randomisation (t4). Primary outcome is psychological well-being (WHO-5). Secondary outcomes are emotional well-being (Flourishing Scale), psychological flexibility (Acceptance and Action Questionnaire-II), quality of life (Assessment of Quality of Life -8D), satisfaction with the intervention (Client Satisfaction Questionnaire-8) and side effects (Inventory for the assessment of negative effectsof psychotherapy). Examined mediators and moderators are sociodemographic variables, personality (Big Five Inventory-10), emotion regulation (Emotion Regulation Questionnaire), alexithymia (Toronto Alexithymia Scale-20), centrality of events (Centrality of Events Scale), treatment expectancies (Credibility Expectancy Questionnaire) and technology alliance (Inventory of Technology Alliance-Online Therapy). Data analysis will be based on intention-to-treat principles. SISU guides participants through a 3-day intervention. ETHICS AND DISSEMINATION: This trial has been approved by the ethics committee of the Ulm University (No. 448/18, 18.02.2019). Results will be submitted for publication in a peer-reviewed journal and presented at conferences. TRIAL REGISTRATION: The trial is registered at the WHO International Clinical Trials Registry Platform via the German Clinical Trials Register (DRKS): DRKS00016799 (date of registration: 25 April 2019). In case of important protocol modifications, trial registration will be updated. This is protocol version number 1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.030 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.069 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".