Key Takeaways
- 21% of adults in the U.S. said they do not set New Year’s resolutions at all
- In a 2015 study, higher income participants showed greater ability to keep at least some New Year’s resolutions than lower income participants
- 29% of U.S. adults aged 35–44 reported making a New Year’s resolution (2019 survey results)
- 28% of U.S. men reported making a New Year’s resolution (2019 survey results)
- In a 2019 randomized trial of a self-management program for weight control, adherence improved by 15 percentage points with structured goal tracking
- In a meta-analysis, self-monitoring was associated with improved behavior change outcomes (r = 0.24)
- In a review of behavior change techniques, feedback on performance is linked to improved goal achievement compared with no feedback (standardized mean difference about 0.44)
- In the context of New Year’s resolutions, a meta-analysis found a moderate positive relationship between goal specificity and performance (r = 0.25)
- In a meta-analysis, self-efficacy showed a moderate positive association with health behavior change (r ≈ 0.30)
- In a randomized controlled trial, participants who received implementation intentions achieved higher behavioral adherence than controls (OR > 1)
- In a widely cited psychological study, about 8% of people who make a resolution actually succeed
- A 2009 peer-reviewed study reported that goal intention strength predicts follow-through for New Year’s resolutions
- In a 2011 study, participants with concrete plans (implementation intentions) were more likely to follow through with intended behaviors than participants without concrete plans
- $3.0 billion expected U.S. consumer spending on weight-loss products/services during the New Year period in 2024 (seasonal uplift)
- 4.2% growth in U.S. digital health and fitness app revenues in 2023 as consumers adopted structured tracking behaviors commonly used in resolutions
Structured planning, specific goals, and tracking boost follow through, yet most adults never set resolutions.
Related reading
Behavior Prevalence
Behavior Prevalence Interpretation
Demographics & Differences
Demographics & Differences Interpretation
Behavioral Implementation
Behavioral Implementation Interpretation
Top Resolution Motives
Top Resolution Motives Interpretation
Success & Failure Rates
Success & Failure Rates Interpretation
More related reading
Economic & Market Impact
Economic & Market Impact Interpretation
Resolution Prevalence
Resolution Prevalence Interpretation
Resolution Motivation
Resolution Motivation Interpretation
Outcomes And Follow Through
Outcomes And Follow Through Interpretation
Market And Technology
Market And Technology Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Christopher Morgan. (2026, February 13). New Years Resolutions Statistics. Gitnux. https://gitnux.org/new-years-resolutions-statistics
Christopher Morgan. "New Years Resolutions Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/new-years-resolutions-statistics.
Christopher Morgan. 2026. "New Years Resolutions Statistics." Gitnux. https://gitnux.org/new-years-resolutions-statistics.
References
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