The Design, Development, and Implementation of a Web-Enabled Informatics Platform to Enhance the Well-being of Individuals Aged 18-24 Years: Protocol for an Experimental Study
Bibliographic record
Abstract
BACKGROUND: Well-being is multidimensional, complex, and dynamic in nature. It is an amalgam of physical and mental health, essential for disease prevention and the promotion of a healthy life. OBJECTIVE: This study aims to explore the features that impact the well-being of individuals between 18 and 24 years of age in an Indian setting. It further aims to design, develop, and evaluate the usefulness and effectiveness of a web-based informatics platform or stand-alone intervention to enhance the well-being of individuals aged 18-24 years in an Indian setting. METHODS: This study follows a mixed method approach to identify factors influencing the well-being of individuals in the age group of 18-24 years in an Indian setting. The college-going students in this age group from the states of Uttarakhand (urban settings of Dehradun) and Uttar Pradesh (urban settings of Meerut) will be enrolled. They will be randomly allocated to the control and intervention groups. The participants in the intervention group will have access to the web-based well-being platform. RESULTS: This study will examine the factors that influence the well-being of individuals aged 18-24 years. It will also facilitate the design and development of the web-based platform or stand-alone intervention, which will enhance the well-being of individuals in the age group of 18-24 years in an Indian setting. Furthermore, the results of this study will help generate a well-being index for individuals to plan tailored interventions. The 60 in-depth interviews have been conducted as of September 30, 2022. CONCLUSIONS: The study will help understand the factors that influence the well-being of individuals. The findings of this study will help in the design and development of the web-based platform or stand-alone intervention to enhance the well-being of individuals in the age group of 18-24 years in an Indian setting. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/38632.
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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 | 0.028 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.042 | 0.008 |
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".