What is Goal Setting Health Score? How to interpret the score? Is it scientifically based?

What is Goal Setting Health Score?

This is a comprehensive score (0-100) that evaluates whether your goal setting is scientific and reasonable through AI + algorithms. It analyzes from 6 dimensions:

Phased Focus Detects whether the number of goals you're pursuing simultaneously exceeds a reasonable amount, ensuring concentration
Goal Similarity Analyzes the overlap rate between new goals and ongoing goals
Core Values Alignment Evaluates the consistency between goals and users' deep values* (*e.g., setting "high-intensity social" goals but actually preferring solitude)
SMART Specificity Analysis Checks if goals meet SMART principles (vague goals like "become more successful")
Conflict Analysis Identifies time/resource conflicts with existing goals (e.g., setting both "2-hour daily fitness" and "overtime project")
External Information Assessment Calibrates feasibility with environmental data (e.g., industry average promotion cycle)

What's the difference between 80 and 50 points in Goal Setting Health Score?

Reference Standards:

· 90+ points: Perfect Setting, goals align with reality, laying a solid foundation for goal achievement

· 80-89 points: Generally Reasonable, goal setting is generally reasonable, balancing personal capabilities and external conditions

· 60-79 points: Needs Optimization, some key areas still have room for improvement

· <60 points: Needs Improvement, many unreasonable aspects exist

How to improve Goal Setting Health Score?

You can optimize goal setting through the following ways to improve your Goal Setting Health Score:

· Reduce the number of goals, focus on core tasks

· Fully consider time conflicts, allocate resources reasonably

· Enhance the alignment between goals and values

· Complete the "5 Whys Test" to find deep motivations (e.g., "Why do you want a promotion?" → "Desire for professional recognition")

· Remove goals driven by social expectations but lacking internal motivation

· Improve goal specificity and measurability

· Reference external data to calibrate feasibility, prevent unrealistic goals

Is the scoring scientific? Is there theoretical support?

Our scoring system strictly follows psychological and management theories, combined with big data validation, ensuring scientific and practical assessment. Here are the core supporting foundations:

1.Theoretical Foundations

· SMART Principle (Classic goal management model): Detects whether goals meet: Specific (S), Measurable (M), Achievable (A), Relevant (R), Time-bound (T)

· Goal Systems Theory (MIT Human Dynamics Lab): Analyzes resource conflicts and priority coordination between multiple goals

· Self-Determination Theory (Deci & Ryan): Evaluates goal motivation quality (intrinsic drive vs external pressure)

· Implementation Intention Theory (Gollwitzer): Improves goal executability through "stage breakdown"

2. Data Validation

· User Goal Database Analysis: Validates strong correlation between scores and goal achievement rates (goals with health score ≥80 have 2.3x higher success rate)

· Machine Learning Dynamic Optimization: Real-time weight adjustment based on user behavior data (e.g., modification frequency, completion rate)

"Why do different people get different scores for the same goal?"

· Due to differences in personal resources (time/ability/values), AI provides personalized calibration

"Can I completely rely on this score?"

· The score is an auxiliary tool, final decisions should consider your personal situation

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2.Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268.

3.Gollwitzer, P. M. (1999). Implementation intentions: Strong effects of simple plans. American Psychologist, 54(7), 493–503.

4.Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.

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6.Sheeran, P., et al. (2021). Goal pursuit: Current state of the science and future directions. Nature Reviews Psychology, 1, 236–248.

7.Kahneman, D. (1973). Attention and Effort. Prentice-Hall.

8.Doran, G. T. (1981). There's a S.M.A.R.T. way to write management's goals and objectives. Management Review, 70(11), 35–36.