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Posting behaviour patterns in an online smoking cessation social network: implications for intervention design and
Benjamin Healey1, Janet Hoek1, Richard Edwards2
1Department of Marketing, University of Otago, Dunedin, New Zealand.
Online Cessation Support Networks (OCSNs) show usage patterns with peak activity tied to seasonality and weekdays. Highly engaged users drive most interactions, suggesting targeted interventions for minimally engaged users in OCSNs.
Area of Science:
- Digital Health
- Public Health
- Behavioral Science
Background:
- Online Cessation Support Networks (OCSNs) are effective for smoking cessation.
- Limited research exists on OCSN usage patterns over time.
- Understanding temporal dynamics is crucial for optimizing OCSN interventions.
Purpose of the Study:
- To identify usage patterns in New Zealand's largest OCSN over two years.
- To explore implications for OCSN intervention design and evaluation.
- To investigate the prediction of low user engagement using early interaction data.
Main Methods:
- Analysis of 133,096 OCSN interactions from 2011-2012.
- Metrics included aggregate activity, user posting, longevity, and commenting.
- Binary logistic regression used to predict low user engagement.
Main Results:
- Aggregate activity showed repeating peaks and troughs related to seasonality and day of the week.
- A small group of Highly Engaged Users (69 users) contributed 69% of interactions in 2012.
- Early interaction data accurately identified Minimally Engaged Users (AUROC=0.94).
Conclusions:
- Future research should focus on interventions promoting activity among specific user groups or at key times.
- Early usage data can identify users for targeted re-engagement strategies.
- Network growth did not significantly improve first-time user persistence; multiple evaluation measures are recommended.
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