ANALYSIS ON USE OF THE FITBIT SYSTEM TO PROMOTE HEALTHY BEHAVIOR CHANGE IN OVERWEIGHT AND OBESE ADOLESCENTS
Bibliographic record
Abstract
BACKGROUND: One in three Canadian Children are overweight or obese. Wearable activity trackers such as the FitbitTM system (wristband + App) may represent an effective tool for promoting healthier behaviors in overweight/obese youth. OBJECTIVES: In this pilot study, our primary objective was to establish the feasibility of using the Fitbit System to promote health behavior change in overweight/obese youth by assessing participant adherence to our intervention and the required human resources to support the study. Our secondary objective was to determine youth perspectives on the acceptability of, and satisfaction with the Fitbit System. DESIGN/METHODS: Participants wore Fitbit pedometers for 24-weeks, and for 12-weeks of follow-up. Data collected included weekly objective Fitbit data (i.e. step count, active minutes, time in bed, etc.) and subjective data (i.e. goal setting, motivating factors, frequency of data checking) using monthly questionnaires. A physical activity questionnaires (PAQ) and ASA24™-kid Self-administrated food log were completed at baseline and after 24-weeks of Fitbit use. RESULTS: 18 overweight and obese adolescents were recruited (12 F). Average step count decreased over time (R2 = - 0.22, p = 0.02). Fitbit daytime (R2 = - 0.85, p < 0.001) and nighttime (R2 = - 0.69, p < 0.001) use declined progressively over 24-weeks and in the 12-week follow-up period. Food logging adherence was poor throughout. Participants were not motivated to set new goals. In the final survey, participants reported they enjoyed the Fitbit (median Likert Score 4 out 4) and 9/15 participants said they would continue to use Fitbit System. Pre- and post PAQ scores did not change significantly (t30 = 0.07, p = 0.47). Only 1 participant completed the post-study ASA24 questionnaire preventing pre and post intervention comparison. The research team provided 58 reminders to participants to sync their Fitbit data with their App, conducted 77 phone calls, sent and received 36 emails, and had 7 face-to-face meetings with study participants during the study period. CONCLUSION: Long-term Fitbit use attenuated over time. Participants’ self-reported use of Fitbit and goal setting was low. Poor response rates on surveys limited our analysis, despite frequent reminders by the research team. The human resources required to conduct this pilot study indicate a larger study is likely unfeasible. On its own, the Fitbit system may not be an effective means to promote adoption of healthier behaviors in overweight and obese adolescents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".