Peer-to-Peer Health Communication in Older Adults’ Online Communities: Protocol for a Qualitative Netnographic Study and Co-Design Approach
Bibliographic record
Abstract
BACKGROUND: Online communities provide an environment in which people with similar health concerns can interact and access content that can support the self-management of long-term conditions (LTCs). Recently, the importance of online social networks as sources of health information and social support has been brought into focus with the emergence and widespread societal impacts of COVID-19. Although online communities exist for older adults, little is known about the specific health and self-care topics that older people discuss in such environments and how these relate to users' support needs and outcomes. A better understanding of users' needs and peer-to-peer communication in these communities is necessary to inform the design of information and communication technology (ICT) interventions that are relevant to older people and their peer supporters. OBJECTIVE: This study aims to use a two-phase, web-based ethnographic (netnography) and co-design approach to explore specific health care and self-care topics that older adults discuss in a UK-based online community and how peer supporters respond to these queries with informational and/or social support and engage with stakeholders to define the needs and requirements for new ICT-based interventions capable of reducing social isolation and facilitating LTC self-management support. METHODS: The first phase of the research will involve a qualitative netnographic analysis of posts in discussion forums in a publicly accessible online community. The second phase will involve co-design workshops with health care consumers (ie, older adults and carers) and service providers to determine the needs and requirements for new ICT-based interventions and digital innovations. Constructivist grounded theory will be used in the first phase; in the second phase, the co-design workshops will be audiorecorded and analyzed thematically. RESULTS: This research project is in progress. Permission was obtained from the website administrator to use materials from the social media forum; data collection for the first phase began in April 2020. The second phase of the study is expected to begin in late 2020. This study is due to be completed by the end of 2021. CONCLUSIONS: This study is the first, to the best of our knowledge, to combine qualitative netnography with an iterative co-design framework to specify the needs and requirements for new ICT-based interventions. The findings from this study will inform the next phase of the multiphase knowledge translation project and will provide insights into the potential of online peer health communities to reduce social isolation and facilitate chronic illness self-management support and self-care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/19834.
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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 | 0.040 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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".