Reasons for non-participation in scleroderma support groups.
Bibliographic record
Abstract
OBJECTIVES: Peer-led support groups are an important resource for people living with many rare diseases, including scleroderma (systemic sclerosis, SSc). Little is known, however, about the accessibility of SSc support groups and factors that may discourage people from participating in these groups. The objective of this study was to identify reasons why people with SSc do not participate in SSc support groups. METHODS: Canadians with SSc were recruited to complete the Canadian Scleroderma Patient Survey of Health Concerns and Research Priorities. Data from respondents who answered the question "Have you participated in SSc support groups?" with "No" were analyzed. Frequencies of participants who responded (1) I'm not interested, (2) None are easily available, and (3) Other (please specify) were tallied. A content analysis approach was used to code the open-ended responses to this question. RESULTS: A total of 280 respondents provided a reason for non-participation in SSc support groups. Key reasons for not participating in support groups included: (1) Not interested or no perceived need (36%); (2) No local support group available (35%); (3) Lack of awareness of the existence of SSc support groups (13%); (4) Practical barriers (6%); (5) Emotional factors (4%); (6) Uncertainty about whether to attend (4%); and (7) Negative perceptions about support groups (3%). CONCLUSIONS: SSc organizations may be able to address current limitations in the accessibility and effectiveness of SSc support groups by implementing online support groups, as well as by providing support group leaders training to help establish and sustain successful SSc support groups.
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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".