Development of the Electronic Social Network Assessment Program Using the Center for eHealth and Wellbeing Research Roadmap
Bibliographic record
Abstract
BACKGROUND: The number of Web-based psychological and behavioral interventions is growing. Beyond their theoretical underpinnings, a key factor to the success of these interventions is how they are designed and developed to ensure usability over a new method of delivery. Our team has adapted ecomapping, a tool for visualizing family caregiver social network resources, for the Web. Here, we describe how we designed and developed the electronic Social Network Assessment Program (eSNAP) Web-based tool using a framework of the Center for eHealth and Wellbeing Research (CeHRes) Roadmap for Web-based intervention development. The CeHRes Roadmap is still new in terms of tool development and we showcase an example of its application. OBJECTIVE: The aim of our study was to provide an example of the application of the Web-based intervention development process using the CeHRes Roadmap for other research teams to follow. In doing so, we are also sharing our pilot work to enhance eSNAP's acceptance and usability for users and the feasibility of its implementation. METHODS: We describe the development of the eSNAP app to support family caregivers of neuro-oncology patients. This development is based on the 5 iterative stages of the CeHRes Roadmap: contextual inquiry, value specification, design, operationalization, and summative evaluation. Research activities to support eSNAP development prior to implementation included literature review, focus groups, and iterative rounds of interviews. RESULTS: Key lessons learned in developing the eSNAP app broadly fell under a theme of translating theoretical needs and ideas to the real world. This included how to prioritize needs to be addressed at one time, how the modality of delivery may change design requirements, and how to develop a tool to fit within the context it will be used. CONCLUSIONS: Using the CeHRes Roadmap to develop Web-based interventions such as eSNAP helps to address potential issues by outlining important intervention development milestones. In addition, by encouraging inclusion of users and other stakeholders in the process, Web-based intervention developers using the Roadmap can identify what will work in the real world and increase feasibility and effectiveness.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".