Social Media Use Training for Adults with Intellectual Disabilities: A Pilot Study
Bibliographic record
Abstract
People with intellectual disability use social media; however, there are barriers preventing them from using and benefiting from social media to the same extent as others. Some barriers include lack of knowledge, limited skills and inaccessibility. This pilot study used a sequential mixed method design to explore the outcomes of a social media training program for adults with intellectual disability aimed at social media use and increased social networks of participants. Six participants (mean age 35.7 years) participated in training focused on cyber safety and support to use individualised social media use goals. The Canadian Occupational Performance Measure, Goal Attainment Scale, and Circles of Communication Partners tools were used to examine the outcomes of training and changes in the participants’ social networks. Semi-structured interviews with participants and one staff member provided insight into participants’ experiences and perceptions of training outcomes. Findings indicated that participants achieved some of their goals and communicated with more people online after training compared to before training. Preliminary outcomes suggest that social media use training may assist adults with intellectual disability to strengthen social connections, gain digital literacy skills, and increase self-confidence online. Further research is needed with a larger sample, including a control group.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".