Navigating Social Cognitive Impairments in Schizophrenia Spectrum Disorders: Protocol for a Pilot Pre-Post Quasi-Experimental Study for Remote Avatar-Assisted Cognitive Remediation Therapy
Bibliographic record
Abstract
BACKGROUND: Social cognitive impairments are prevalent in schizophrenia spectrum disorder (SSD) and have detrimental effects on functioning. Cognitive remediation (CR) has shown its efficacy in improving social cognitive impairments, although the transfer of these skills to daily life and the personalization of these interventions remain challenging. RC2S (Remédiation Cognitive de la Cognition Sociale dans la Schizophrénie; Cognitive remediation of social cognition in Schizophrenia) is a French CR that combines the learning of strategies and practice using paper-and-pencil exercises and digital relational simulations. This French program was designed as an in-person intervention. OBJECTIVE: This project aims to culturally adapt the RC2S program, in French-Canadian and North American English and to assess the feasibility, acceptability, safety, and implementation of a remote version in people with SSD. An exploratory objective is to assess the preliminary effect of remote RC2S on goal attainment, social cognition, and psychosocial outcomes. METHODS: We will use a pre-post quasi-experimental design. First, the translation and cultural adaptation in North American English and French-Canadian of RC2S is presented. Then, 20 participants aged ≥18 years with a diagnosis of SSD, presenting with a subjective or an objective impairment in social cognition, will be included to receive RC2S. In addition, 5 therapists will be included as research participants to assess their perspective on RC2S. Participants with SSD will undergo a baseline remote assessment of their social cognition, clinical symptoms, and functioning. They will then start remote RC2S for 24 biweekly individual 1-hour sessions with a therapist. Following the case formulation and goal setting, participants will complete personalized paper-and-pencil exercises to develop strategies and integrative digital relational simulations, during which they will help an avatar navigate through a variety of social contexts and relationships. The last 2 sessions are dedicated to the transfer to daily life. All participants will complete in-session questionnaires assessing therapeutic alliance, motivation, acceptability, feasibility, and implementation. Following RC2S, the participants with SSD will repeat the same assessment as the baseline. Descriptive statistics will be used to summarize the data about acceptability, feasibility, safety, and implementation. To assess the preliminary effect of RC2S, an intention-to-treat approach will be used with linear mixed models for repeated measures with fixed effects of time. RESULTS: So far, 45% (9/20) of participants with SSD (mean age 37.9, SD 9.3 years) have completed the project. They received a mean of 20.5 out of 24 (SD 3.5) sessions of RC2S. A total of 5 therapists also completed the project. CONCLUSIONS: Improving social cognitive impairments is an important target in SSD to promote functional recovery. Using digital technologies to address these impairments and deliver the intervention is a promising approach to increase the ecological validity of CR and access to the intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT05017532; https://classic.clinicaltrials.gov/ct2/show/NCT05017532. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54251.
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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 | 0.019 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.058 | 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".