Communicating Effectively when Engaging People with Lived Experience in Mental Health and Substance use Health Research: A Qualitative Descriptive Study
Bibliographic record
Abstract
Background. People with lived experience of mental health and/or substance use challenges and families (PWLE/F) are increasingly engaged in research, providing positive impacts. However, effective engagement can be challenging, including ensuring effective communication. This qualitative study sought to understand the communication preferences of PWLE/F who are engaged in mental health and substance use health research. Method. A total of 18 participants (aged 19 to 79) took part in one of four focus group discussions. A semi-structured interview guide was used to facilitate the discussions. Focus group transcripts were analyzed using codebook thematic analysis. PWLE/F were engaged in all stages of the study in the form of a PWLE/F Advisory Group. Results. Four themes were generated from the data: 1) Communicate in trusting and respectful ways, 2) Use an accessible communication style, 3) Employ effective communication approaches before, during, and after meetings, and 4) Use technology effectively to support engagement. Each theme is illustrated by several subthemes and representative quotes. Conclusions. Clear communication can help support strong engagement practices, where everyone involved has the opportunity to contribute. Friendly, accessible, jargon-free communication can help people with lived experience and families feel authentically engaged, but departs from typical scientific communication styles and may require specific effort for some groups to achieve. Communication should be continuous, throughout the engagement cycle. Technology can be used to help support this. Attending to clear communication throughout the research and engagement lifecycle is a key consideration that can help achieve an authentic PWLE/F engagement climate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".