Adapting, updating and translating the Social Functioning Scale to assess social, recreational and independent functioning among youth with psychosis in diverse sociocultural contexts
Bibliographic record
Abstract
AIM: To compare social, recreational and independent functioning among persons with psychosis across two geo-cultural contexts, we adapted the well-established Social Functioning Scale (SFS) and translated it into French and Tamil. We present the development and psychometric testing of this adaptation, the SFS-Early Intervention. METHODS: Sixteen items were added to reflect contemporary youth activities (e.g., online games) and 31 items adapted to enhance applicability and/or include context-specific examples (e.g., 'church activity' replaced with 'religious/spiritual activity'). Psychometric properties and participant feedback were evaluated. RESULTS: Test-retest reliability (ICCs) ranged from 0.813 to 0.964. Internal consistency (Cronbach's α) ranged from .749 to .936 across sites and languages. Correlations with original subscales were high. The scale was rated easy to complete and understand. CONCLUSIONS: The SFS-Early Intervention is a promising patient-reported measure of social, recreational and independent functioning. Our approach shows that conceptually sound existing measures are adaptable to different times and contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".