Asynchronous online focus groups for research with people living with amyotrophic lateral sclerosis and family caregivers: usefulness, acceptability and lessons learned
Bibliographic record
Abstract
BACKGROUND: People with amyotrophic lateral sclerosis (ALS) face disability- and travel-related barriers to research participation. We investigate the usefulness and acceptability of asynchronous, online focus groups (AOFGs) for research involving people affected by ALS (patients and family caregivers) and outline lessons learned. METHODS: The ALS Talk Project, consisting of seven AOFGs and 100 participants affected by ALS, provided context for this investigation. Hosted on the secure itracks Board™ platform, participants interacted in a threaded web forum structure. Moderators posted weekly discussion questions and facilitated discussion. Data pertaining to methodology, participant interaction and experience, and moderator technique were analyzed using itracks and NVivo 12 analytics (quantitative) and conventional content analysis and the constant-comparative approach (qualitative). RESULTS: There was active engagement within groups, with post lengths averaging 111.48 words and a complex network of branching interactions between participants. One third of participant responses included individual reflections without further interaction. Participants affirmed their co-group members, offered practical advice, and discussed shared and differing perspectives. Moderators responded to all posts, indicating presence and probing answers. AOFGs facilitated qualitative and quantitative data-gathering and flexible response to unanticipated events. Although total participation fell below 50% after 10-12 weeks, participants valued interacting with peers in an inclusive, confidential forum. Participants used a variety of personal devices, browsers, and operating systems when interacting on the online platform. CONCLUSIONS: This methodological examination of AOFGs for patient-centred investigations involving people affected by ALS demonstrates their usefulness and acceptability, and advances knowledge of online research methodologies. Lessons learned include: early identification of research goals and participant needs is critical to selecting an AOFG platform; although duration longer than 10-12 weeks may be burdensome in this population, participants were positive about AOFGs; AOFGs offer real world flexibility enabling response to research challenges and opportunities; and, AOGFs can effectively foster safe spaces for sharing personal perspectives and discussing sensitive topics. With moderators playing an important role in fostering engagement, AOFGs facilitated rich data gathering and promoted reciprocity by fostering the exchange of ideas and interaction between peers. Findings may have implications for research involving other neurologically impaired and/or medically vulnerable populations.
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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 | 0.070 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".