Harvard Dataverse hosts anonymized survey responses from 622 participants examining digital device usage, online activity diversity, and psychological well-being. The dataset, created by Md Jafrin Hossain, covers pre-COVID, during-COVID, and post-COVID periods. It includes variables on device usage frequency, health symptom indicators, and well-being scores based on an adapted Ryff scale.
Use Cases
- Analyze associations between digital behavior patterns and psychological well-being based on survey variables.
- Cluster participants into behavioral groups based on device usage frequency and online activity categories.
- Investigate changes in self-reported health effects across pre-COVID, during-COVID, and post-COVID periods.
- Model correlations between online activity diversity and well-being scores using statistical methods.
Strengths
- Survey data from 622 participants provides a substantive sample size.
- Covers three distinct time periods: pre-COVID, during-COVID, and post-COVID.
- Includes psychological well-being scores based on an adapted Ryff scale.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- Harvard Dataverse
- Collection Method
- Anonymized survey responses.
- Time Range
- Covers pre-COVID, during-COVID, and post-COVID periods.
- Freshness
- Last updated 2026-04-13 15:12:20; freshness should be verified.
- Geography
- null