1. Bibliographic Information

1.1. Title

The differential influence of Achievement Motivation on Subjective Well-being and the moderating role of Self-control.

1.2. Authors

• Yuting Feng ($^{1}$)

• Qun Yang ($^{1,2a}$)

  ($^{1}$) First Affiliated Hospital, Air Force Medical University, Xi’an, China. ($^{2a}$) Department of Psychological Medicine, School of Basic Medical Sciences, Air Force Medical University, Xi’an, China.

1.3. Journal/Conference

Scientific Reports. Scientific Reports is an open-access multidisciplinary journal published by Nature Portfolio. It is a highly reputable journal, known for publishing scientifically sound primary research from all areas of natural and clinical sciences. Its broad scope and rigorous peer-review process make it an influential venue for scientific dissemination.

1.4. Publication Year

Published online: 2024-09-27.

1.5. Abstract

This study investigated the relationship between achievement motivation and subjective well-being (SWB), and the moderating effects of self-control and self-management on this relationship. A survey was conducted among 1017 Chinese college students. The main findings were:

1. A significant interactive effect was observed between motivation to approach success and self-control on SWB. Specifically, for individuals with high self-control, the positive effects of motivation to approach success on SWB, life satisfaction, and positive affect were stronger, while it also negatively predicted negative affect.
2. A significant interactive effect was found between motivation to avoid failure and self-control on SWB. For individuals with high self-control, the negative effects of motivation to avoid failure on SWB, life satisfaction, and positive affect were weaker, and its effect on negative affect was also relatively weaker. The study concludes that enhancing self-control ability can maximize the positive impact of achievement motivation on SWB. Furthermore, encouraging motivation to approach success in individuals with high self-control and reducing motivation to avoid failure in individuals with low self-control could lead to more positive SWB outcomes.

1.6. Original Source Link

/files/papers/6936e3f122805583e1e3d06f/paper.pdf This is the direct PDF link to the published paper on Scientific Reports.

2. Executive Summary

2.1. Background & Motivation

The core problem this paper addresses is understanding how achievement motivation influences subjective well-being (SWB) and whether this relationship is universally direct or contingent on other individual differences. While SWB is a central concept in positive psychology and a fundamental human pursuit, and achievement motivation is known to predict SWB, previous research often presented a simplistic view: approach motivation (striving for success) is good for well-being, and avoidance motivation (fearing failure) is bad.

The importance of this problem stems from the need to offer more nuanced guidance for individuals and educators on how to cultivate achievement motivation effectively to enhance well-being. Prior research may have neglected the potential importance of individuals' self-control. The authors argue that the differential influence of various types of achievement motivation on well-being is closely tied to individuals' self-control activities. This gap in understanding suggests that simply promoting approach motivation or suppressing avoidance motivation might not be optimal for everyone, highlighting a need to explore mediating or moderating factors.

The paper's entry point and innovative idea is to introduce self-control as a crucial moderating variable. It hypothesizes that self-control skills — which encompass self-monitoring, self-evaluating, and self-reinforcing processes — can significantly alter how motivation to approach success and motivation to avoid failure impact an individual's SWB. This perspective aims to provide a more ecologically valid and applicable understanding of these complex relationships.

2.2. Main Contributions / Findings

The paper makes several primary contributions and key findings:

• Clarification of Differential Influence: It empirically demonstrates that the impact of motivation to approach success and motivation to avoid failure on SWB is not uniform but varies significantly depending on an individual's self-control ability.

• Identification of Self-control as a Moderator: The study rigorously establishes self-control as a significant moderator in the relationship between achievement motivation and SWB. This fills a gap in previous research which largely overlooked such interactive effects.

• Enhanced Positive Effects for High Self-control Individuals: For individuals with high self-control, motivation to approach success leads to stronger positive effects on SWB, life satisfaction, and positive affect, and also more effectively reduces negative affect. This suggests that self-control amplifies the benefits of approach motivation.

• Mitigated Negative Effects for High Self-control Individuals: For individuals with high self-control, the detrimental effects of motivation to avoid failure on SWB, life satisfaction, and positive affect are significantly weaker. Its impact on negative affect is also less pronounced. This indicates that self-control acts as a buffer against the negative consequences of avoidance motivation.

• Practical Implications for Well-being Interventions: The findings offer concrete practical implications. They suggest that strategies to enhance SWB should not only focus on stimulating specific types of achievement motivation but also on improving individuals' self-control abilities. Specifically, fostering approach motivation is most beneficial for those with high self-control, while mitigating avoidance motivation is particularly important for those with low self-control.

• Integration of Theories: The study effectively integrates motive disposition theory and regulatory focus theory to explain the observed moderating effects, thus enriching existing theoretical frameworks.

  These findings solve the problem of providing a more nuanced and practical understanding of how achievement motivation impacts SWB, moving beyond simple direct correlations to consider the crucial role of individual differences in self-control.

3. Prerequisite Knowledge & Related Work

3.1. Foundational Concepts

To fully understand this paper, a beginner should be familiar with the following core psychological concepts:

• Subjective Well-being (SWB):

  • Explanation: Subjective well-being (SWB) refers to an individual's personal evaluation of their life quality, encompassing their cognitive judgments about their life (e.g., life satisfaction) and their emotional experiences (e.g., positive affect and negative affect). It's a key concept in positive psychology, focusing on how people experience and evaluate their lives.
  • Components: As noted by Diener and colleagues (1, 2), SWB typically comprises three dimensions:
    • Life satisfaction: A global cognitive judgment about one's life as a whole.
    • Positive affect: The experience of pleasant emotions such as joy, happiness, contentment, and enthusiasm.
    • Negative affect: The experience of unpleasant emotions such as sadness, anger, fear, and anxiety.
  • Significance: High SWB is associated with numerous positive life outcomes, including better health, stronger relationships, and greater productivity.

• Achievement Motivation:

  • Explanation: Achievement motivation refers to an individual's drive to pursue and achieve goals, particularly those involving competence and performance evaluation. It's about the explicit motive dispositions or tendencies that guide goal-oriented behavior.
  • Atkinson's Theory (9): Psychologist John W. Atkinson's theory (1957) is foundational, positing two main, often opposing, components of achievement motivation:
    • Motivation to Approach Success (MS): Also known as approach motivation or hope for success. This refers to the desire to engage in tasks, strive for excellence, and experience the positive emotions associated with achieving goals. Individuals high in MS are typically self-confident, embrace challenges, and are driven by the prospect of accomplishment.
    • Motivation to Avoid Failure (MF): Also known as avoidance motivation or fear of failure. This refers to the desire to avoid situations where one might fail or perform poorly, and to avoid the negative emotions associated with failure. Individuals high in MF might choose easy tasks (to guarantee success) or extremely difficult tasks (to provide an excuse for failure), and tend to be anxious about performance.

• Self-control:

  • Explanation: Self-control (and self-management) refers to the abilities and processes by which individuals regulate their thoughts, emotions, and behaviors to achieve long-term goals or adhere to personal standards. It involves overriding impulses and resisting temptations.
  • Mezo's Framework (15): The paper references Mezo's framework, which conceptualizes self-control as consisting of three interdependent self-regulatory processes forming an iterative closed feedback loop:
    • Self-monitoring: Consciously observing and keeping track of one's own behaviors, thoughts, and feelings in relation to a goal.
    • Self-evaluating: Comparing one's current performance or behavior against an internalized standard or goal.
    • Self-reinforcing: Providing oneself with rewards (self-reward) or punishments (self-punishment) based on the outcome of the self-evaluation, which helps to reinforce desired behaviors.
  • Individual Differences: Self-control is often regarded as a stable trait, meaning individuals differ in their typical level of self-control ability.

• Motive Disposition Theory (3, 21):

  • Explanation: This theory focuses on individual differences in motives, particularly distinguishing between hope (e.g., hope of success) and fear (e.g., fear of failure) components of motivations like achievement motivation. It suggests that these inherent dispositions influence how individuals engage with goals and experience outcomes. The theory emphasizes that the activation of different motives involves specific self-regulatory processes that effectively guide goal-oriented behaviors.

• Regulatory Focus Theory (22):

  • Explanation: Developed by E. Tory Higgins, this theory proposes that individuals regulate their behavior in two distinct ways when pursuing goals:
    • Promotion focus: Orientated towards achieving gains and aspirations. Individuals with a promotion focus are sensitive to the presence or absence of positive outcomes (e.g., motivation to approach success). They are eager to achieve positive results and experience positive emotions when successful.
    • Prevention focus: Orientated towards avoiding losses and fulfilling duties or obligations. Individuals with a prevention focus are sensitive to the presence or absence of negative outcomes (e.g., motivation to avoid failure). They are vigilant to prevent errors and primarily experience relief when successful (avoiding failure).
  • Application to Affect: According to the theory, successful goal pursuit promotes positive affect in individuals with promotion motivation (approach) and reduces negative affect in those with prevention motivation (avoidance), but the type of positive affect might differ (e.g., excitement for promotion vs. calmness for prevention).

3.2. Previous Works

The paper builds upon a foundation of established research in motivation and well-being:

• Atkinson's Achievement Motivation Theory (9): As mentioned above, this theory provides the two core constructs (motivation to approach success and motivation to avoid failure) that are central to the current study. Atkinson's work highlighted that these two motives can independently influence behavior.
• Early SWB Research (1, 2): Diener and his colleagues' extensive work on subjective well-being laid the groundwork for understanding SWB as a multi-dimensional construct comprising life satisfaction, positive affect, and negative affect. This framework is adopted directly in the current study for measuring SWB.
• Direct Relationships between Achievement Motivation and Well-being (4, 7, 8, 10, 11, 14): Prior studies have consistently found that approach motivation is generally positively related to well-being (e.g., Song et al., 2015; Tamir & Diener, 2008). Conversely, avoidance motivation is often negatively associated with well-being (Kaftan & Freund, 2018). The current paper acknowledges these established direct relationships as its starting point but questions their universality.
• Self-control and Well-being (16–19): Research has also shown a direct link between high self-control and positive well-being outcomes, including higher positive affect, life satisfaction, and overall well-being (Buyukcan-Tetik et al., 2018; Hoffman et al., 2014). The current paper integrates this understanding by proposing self-control not just as a predictor, but as a modifier.
• Self-regulation in Goal Pursuit (15, 20, 27): The concept of self-regulatory processes (self-monitoring, self-evaluating, self-reinforcing) is derived from broader theories of self-regulation (e.g., Mezo, 2009; Horvath & McColl, 2013). These processes are crucial for understanding how individuals manage their behavior towards goals. The paper extends this by applying these processes to explain the interaction of achievement motivation and self-control.

3.3. Technological Evolution

The field of psychology, particularly positive psychology and motivational research, has evolved from focusing on singular, direct relationships to exploring complex interactions and individual differences.

• From Trait-Centric to Process-Oriented: Early research often treated motivation and well-being as relatively stable traits. The evolution has moved towards understanding the underlying cognitive and affective processes that mediate or moderate these traits. Self-regulation and self-control theories represent this shift, emphasizing dynamic processes rather than static dispositions.
• Integration of Multiple Theoretical Lenses: Modern research, as exemplified by this paper, frequently integrates multiple theoretical frameworks (e.g., motive disposition theory, regulatory focus theory, and self-control theory) to provide a more comprehensive explanation of human behavior and experience.
• Emphasis on Ecological Validity: There's a growing recognition that findings need to be applicable to real situations and account for the diversity of human experience. This paper's exploration of moderating effects is a step in this direction, acknowledging that "one size does not fit all" in psychological interventions.

3.4. Differentiation Analysis

Compared to the main methods in related work, the core differences and innovations of this paper's approach are:

• Focus on Moderation, not just Direct Effects: Previous studies primarily investigated the direct effects of approach and avoidance motivation on well-being. This paper innovates by explicitly testing self-control as a moderator, suggesting that the strength and even the direction of these effects can change based on an individual's self-control level. This moves beyond simply identifying correlations to understanding the conditions under which these correlations hold true.
• Integration of Self-control as a Key Variable: While self-control has been linked to well-being independently, this study is among the first to systematically examine its interactive role with both motivation to approach success and motivation to avoid failure in predicting SWB. This provides a more holistic view than studies focusing solely on motivation or self-control in isolation.
• Elucidation of Mechanisms via Regulatory Processes: The paper draws on motive disposition theory and regulatory focus theory to provide theoretical backing for why self-control would act as a moderator. It explains that self-monitoring, self-evaluating, and self-reinforcing processes, integral to self-control, are activated differently depending on the type of achievement motivation and influence emotional and cognitive outcomes.
• Nuanced Practical Implications: The findings lead to more sophisticated practical advice. Instead of a blanket recommendation to boost approach motivation, the study suggests tailoring interventions: encouraging approach motivation for high self-control individuals, and focusing on reducing avoidance motivation for low self-control individuals. This personalized approach is a significant improvement over generalized strategies.
• Exploration of Three-Way Interactions: Beyond the primary hypotheses, the supplementary analyses delve into the more complex three-way interaction between motivation to approach success, motivation to avoid failure, and self-control. This advanced analysis provides insights into how the combination of both types of motivation influences SWB under different self-control conditions, which is rarely explored in motivational research.

4. Methodology

4.1. Principles

The core idea of this study's methodology is to investigate the moderating role of self-control in the relationship between achievement motivation (specifically, motivation to approach success and motivation to avoid failure) and subjective well-being (SWB). The theoretical basis and intuition behind this approach are rooted in motive disposition theory and regulatory focus theory, as well as existing knowledge about self-control processes.

The intuition is that individuals don't just passively experience the effects of their achievement motivation. Instead, their self-regulatory processes (which constitute self-control) actively shape how they respond to and progress towards achievement-oriented goals.

• For Motivation to Approach Success (MS): When individuals are driven by MS, they aim for positive outcomes. If they also possess high self-control, they can effectively self-monitor their progress, self-evaluate their performance against standards, and self-reinforce their efforts. This iterative feedback loop helps them stay on track, overcome obstacles, and adapt their strategies, ultimately leading to greater goal achievement and a stronger sense of accomplishment. This process reinforces positive emotional experiences (positive affect) and life satisfaction, thereby maximizing the positive impact of MS on SWB. In essence, high self-control allows individuals to harness their approach motivation more effectively, translating effort into positive outcomes and feelings.

• For Motivation to Avoid Failure (MF): When individuals are driven by MF, they focus on preventing negative outcomes. This can often lead to negative affect and reduced SWB due to constant worry and vigilance. However, the hypothesis is that high self-control can mitigate these negative effects. Individuals with high self-control can self-monitor for potential pitfalls and self-evaluate their strategies to prevent failure more efficiently. Crucially, they can also self-reinforce by acknowledging efforts to avoid mistakes and adjust their approach without getting trapped in persistent negative thoughts or emotions. This ability to manage and adapt, rather than simply dwell on the fear of failure, means that for high self-control individuals, MF can help avoid actual failures without significantly eroding SWB. Conversely, for those with low self-control, the fear of failure may lead to rumination, poor coping strategies, and exacerbated negative affect, thereby strengthening the negative impact of MF on SWB.

  In summary, the principle is that self-control acts as a crucial internal resource that enables individuals to effectively manage the cognitive and emotional consequences of both approaching success and avoiding failure, thus moderating their ultimate impact on subjective well-being.

4.2. Core Methodology In-depth (Layer by Layer)

4.2.1. Participants

The study recruited participants voluntarily after obtaining ethical approval and informed consent.

• Sample Size: 1150 undergraduates were initially invited. After excluding invalid responses (extremely consistent responses, too many missing values), 1017 valid samples were included in the analyses.
• Effective Rate: The effective response rate was 88%.
• Demographics:
  • Male Students: 486 (47.8%)
    • Average Age: $21.21 \pm 1.72$ years old (Mean $\pm$ Standard Deviation)
  • Female Students: 531 (52.2%)
    • Average Age: $20.60 \pm 1.60$ years old (Mean $\pm$ Standard Deviation)
• Location: All participants were Chinese college students.

4.2.2. Measures

The study employed several standardized scales to measure the key constructs. All scales used a seven-point Likert scale unless otherwise specified.

4.2.2.1. Achievement Motivation

This construct was measured using a scale developed by Gjesme and Nygard, revised for use in China by Ye and Hag (33). It comprises two subscales:

• Motivation to Approach Success (MS):

  • Purpose: Measures motive dispositions related to success, involving positive evaluation situations and outcome expectations.
  • Items: 15 items.
  • Scoring: 7-point scale (1 = strongly disagree to 7 = strongly agree).
  • Example Items:
    • "I like unfamiliar and difficult tasks, even risky ones."
    • "I like tasks that I can accomplish when I try my best."
  • Reliability: Cronbach’s $\alpha = 0.90$.

• Motivation to Avoid Failure (MF):

  • Purpose: Measures motive dispositions involving negative evaluation situations and outcome expectations.
  • Items: 15 items.
  • Scoring: 7-point scale (1 = strongly disagree to 7 = strongly agree).
  • Example Items:
    • "I dislike the task that I am, or others are, not sure if I can complete it."
    • "I don’t want to be assigned the difficult tasks."
  • Reliability: Cronbach’s $\alpha = 0.92$.

4.2.2.2. Self-control and Self-management

This construct was measured using the Self-Control and Self-Management Scale (SCMS) developed by Mezo (15).

• Items: 16 items.
• Dimensions: Divided into three dimensions:
  • Self-monitoring: Tracking progress and status of target behaviors.
  • Self-evaluating: Comparing target behaviors to internalized standards.
  • Self-reinforcing: Engaging in self-reward or self-punishment based on evaluation.
• Scoring: 7-point scale (1 = strongly disagree to 7 = strongly agree).
• Example Statements:
  • "I make sure to track my progress regularly when I am working on a goal." (Self-monitoring)
  • "The standards I set for myself are unclear and make it hard for me to judge how I am doing on a task." (Self-evaluating – reverse coded implied)
  • "I congratulate myself when I make some progress." (Self-reinforcing)
• Reliability:
  • Cronbach’s $\alpha$ for self-monitoring: 0.81.
  • Cronbach’s $\alpha$ for self-evaluating: 0.86.
  • Cronbach’s $\alpha$ for self-reinforcing: 0.82.
  • Cronbach’s $\alpha$ for the total scale: 0.84.

4.2.2.3. Subjective Well-being (SWB)

SWB was measured across its three main dimensions: life satisfaction, positive affect, and negative affect.

• Life Satisfaction:

  • Scale: Satisfaction With Life Scale (SWLS) by Diener et al. (34).
  • Items: 5 items.
  • Scoring: 7-point scale (1 = strongly disagree to 7 = strongly agree).
  • Example Item: "In most ways my life is close to my ideal."
  • Reliability: Cronbach’s $\alpha = 0.81$.

• Positive Affect and Negative Affect:

  • Scale: Revised version of the Positive Affect and Negative Affect Scale by Qiu et al. (35).
  • Items: 18 items in total, divided into two dimensions.
  • Scoring: 7-point scale (1 = not at all to 7 = extremely).
  • Example Items:
    • Positive Affect: "excited," "delighted," and "enthusiastic."
    • Negative Affect: "distressed," "ashamed," and "irritable."
  • Reliability:
    • Cronbach’s $\alpha$ for Positive Affect: 0.92.
    • Cronbach’s $\alpha$ for Negative Affect: 0.96.

4.2.3. Statistical Analysis

The data analysis was performed using SPSS 25.0.

1. Descriptive Analysis:

   • Mean and Standard Deviation were calculated for all variables to summarize their central tendency and dispersion.

2. Correlation Analysis:

   • Pearson correlation coefficients were used to examine the bivariate relationships between all variables.
   • Pearson correlation coefficient (r): A measure of the linear correlation between two variables $X$ and $Y$. It ranges from -1 (perfect negative linear correlation) to +1 (perfect positive linear correlation), with 0 indicating no linear correlation.
   • The formula for the Pearson correlation coefficient is: $ r = \frac{n(\sum xy) - (\sum x)(\sum y)}{\sqrt{[n\sum x^2 - (\sum x)^2][n\sum y^2 - (\sum y)^2]}} $ Where:
     • $n$ is the number of data points.
     • $\sum xy$ is the sum of the products of the paired scores.
     • $\sum x$ is the sum of the $x$ scores.
     • $\sum y$ is the sum of the $y$ scores.
     • $\sum x^2$ is the sum of the squared $x$ scores.
     • $\sum y^2$ is the sum of the squared $y$ scores.

3. Hierarchical Regression Analysis:

   • This technique was used to examine the moderating effect of self-control on the relationship between achievement motivation and SWB.
   • In hierarchical regression, variables are entered into the regression equation in a predetermined order, typically in blocks. This allows researchers to see how much variance each block of variables explains above and beyond the previous blocks.
   • Steps:
     • Step 1 (Model 1): Control variables (Gender, Age) were entered.
     • Step 2 (Model 2): Main effect predictors (Motivation to Approach Success, Motivation to Avoid Failure) were added.
     • Step 3 (Model 3): The main effect of the moderator (Self-control) was added.
     • Step 4 (Model 4): Interaction terms (e.g., Motivation to Approach Success $\times$ Self-control, Motivation to Avoid Failure $\times$ Self-control) were added to test for moderation.
   • Before creating interaction terms, independent variables were standardized (mean-centered) to reduce multicollinearity and aid interpretation.
   • The significance of the interaction term (\beta`coefficient` and `p-value`) indicates a moderating effect. * `Beta (`\beta`) coefficient`: In a standardized regression equation, the beta coefficient represents the change in the dependent variable for one standard deviation change in the independent variable, holding all other variables constant. It allows for direct comparison of the relative strength of different predictors. 4. **Simple Slope Test:** * If a significant interaction effect was found in the `hierarchical regression`, `simple slope tests` were conducted. * This test helps to interpret the nature of the interaction by examining the relationship between the predictor and the outcome at different levels (e.g., high, average, low) of the moderator. For instance, it checks the slope of `Motivation to Approach Success` on `SWB` for individuals with high `self-control` versus those with low `self-control`. * This is typically done by plotting the slopes and testing their significance. 5. **Significance Level:** * Differences were considered statistically significant at $p < 0.05$. * `p-value`: The probability of observing a test statistic as extreme as, or more extreme than, the one observed, assuming the null hypothesis is true. A small p-value (typically $p < 0.05$) suggests that the observed data are unlikely under the null hypothesis, leading to its rejection. 6. **Three-way interaction effects (Supplementary Analyses):** * `Multivariate regression analysis` was conducted including three independent variables (`MS`, `MF`, `Self-control`), all two-way interaction terms (`MS` $\times$ `Self-control`, `MF` $\times$ `Self-control`, `MS` $\times$ `MF`), and the `three-way interaction term` (`MS` $\times$ `MF` $\times$ `Self-control`). * `SPSS PROCESS macro` developed by Hayes (36) was used for parameter estimation, specifically `model 3`, with `bootstrapping` (5000 samples) applied for robust standard errors and confidence intervals. # 5. Experimental Setup ## 5.1. Datasets * **Source:** The data for this study was collected through a survey administered to Chinese college students. * **Scale:** A total of `1017 valid samples` were included in the final analysis, out of 1150 invited participants. * **Characteristics:** * **Age:** Mean age approximately 20-21 years ($21.21 \pm 1.72$ for males, $20.60 \pm 1.60$ for females). * **Gender:** 486 male students (47.8%) and 531 female students (52.2%). * **Population:** College students in China. * **Domain:** Psychology, focusing on motivational and well-being constructs. * **Data Sample:** The paper does not provide concrete examples of individual data samples (e.g., a filled-out questionnaire response from one student). The data consists of numerical scores from Likert-scale responses to the various psychological scales. * **Choice of Dataset:** College students are a relevant population for studying `achievement motivation` and `self-control` as they are actively engaged in goal pursuit (academic success) and developing self-regulatory skills. The large sample size ($N=1017$) contributes to the statistical power and generalizability of the findings within this specific demographic. ## 5.2. Evaluation Metrics The study primarily uses statistical measures derived from correlation and regression analyses to evaluate the relationships and moderating effects. * **Pearson Correlation Coefficient ($r$):** 1. **Conceptual Definition:** Quantifies the strength and direction of a linear relationship between two quantitative variables. 2. **Mathematical Formula:** $ r_{xy} = \frac{\sum_{i=1}^{n} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=1}^{n} (x_i - \bar{x})^2 \sum_{i=1}^{n} (y_i - \bar{y})^2}} $ 3. **Symbol Explanation:** * $r_{xy}$: Pearson correlation coefficient between variables $x$ and $y$. * $n$: Number of observations (sample size). * $x_i$: Value of the $i$-th observation for variable $x$. * $y_i$: Value of the $i$-th observation for variable $y$. * $\bar{x}$: Mean of variable $x$. * $\bar{y}$: Mean of variable $y$. * **Regression Coefficients ($\beta$):** 1. **Conceptual Definition:** In multiple regression, a standardized `beta coefficient` (or `standardized regression coefficient`) indicates the strength and direction of the relationship between an independent variable and a dependent variable, when all other independent variables in the model are held constant. It allows for direct comparison of the relative impact of different predictors on the outcome, as they are expressed in standard deviation units. 2. **Mathematical Formula:** For a multiple linear regression model $Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \dots + \beta_k X_k + \epsilon$, the `standardized beta coefficient` for $X_j$ is calculated as: $ \beta_j^* = \beta_j \left( \frac{SD_{X_j}}{SD_Y} \right) $ 3. **Symbol Explanation:** * $\beta_j^*$: Standardized beta coefficient for independent variable $X_j$. * $\beta_j$: Unstandardized regression coefficient for independent variable $X_j$. * $SD_{X_j}$: Standard deviation of independent variable $X_j$. * $SD_Y$: Standard deviation of the dependent variable $Y$. * **Coefficient of Determination ($R^2$):** 1. **Conceptual Definition:** `R-squared` represents the proportion of the variance in the dependent variable that can be explained by the independent variables in the regression model. It indicates how well the model fits the observed data. 2. **Mathematical Formula:** $ R^2 = 1 - \frac{SS_{res}}{SS_{tot}} $ 3. **Symbol Explanation:** * $R^2$: Coefficient of determination. * $SS_{res}$: Sum of squares of residuals (the unexplained variance). * $SS_{tot}$: Total sum of squares (the total variance in the dependent variable). * **Change in R-squared ($\Delta R^2$):** 1. **Conceptual Definition:** In `hierarchical regression`, $\Delta R^2$ indicates the unique proportion of variance in the dependent variable explained by a new block of independent variables, beyond what was explained by the variables already in the model. It helps assess the incremental predictive power of new predictors or interaction terms. * **F-statistic (F change):** 1. **Conceptual Definition:** The `F-statistic` tests the overall significance of the regression model, or, in hierarchical regression, the significance of the `change in R-squared` when a new block of variables is added. A significant `F-change` indicates that the new block of variables significantly improves the model's fit. * **p-value ($p$):** 1. **Conceptual Definition:** The `p-value` is used to determine the statistical significance of results. It is the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true. In this study, a $p < 0.05$ indicates that the observed effect is statistically significant, meaning it is unlikely to have occurred by random chance. * **Cronbach's Alpha ($\alpha$):** 1. **Conceptual Definition:** `Cronbach's alpha` is a measure of internal consistency, or how closely related a set of items are as a group. It is considered to be a measure of scale reliability. A higher $\alpha$ value (typically > 0.70) indicates greater reliability. 2. **Mathematical Formula:** $ \alpha = \frac{k}{k-1} \left( 1 - \frac{\sum_{i=1}^{k} \sigma_{Y_i}^2}{\sigma_X^2} \right) $ 3. **Symbol Explanation:** * $\alpha$: Cronbach's alpha. * $k$: Number of items in the scale. * $\sigma_{Y_i}^2$: Variance of item $i$. * $\sigma_X^2$: Variance of the total score for the scale. ## 5.3. Baselines This study is not comparing a novel method against existing ones, but rather investigating relationships and moderating effects within a theoretical framework. Therefore, the concept of `baseline models` in the traditional sense (e.g., comparing a new algorithm to an old one) is not directly applicable. Instead, the "baselines" are implicitly the `main effects` of `achievement motivation` on `SWB` as established in prior research. The paper's contribution is to show that these main effects are *conditional* on `self-control`, rather than to propose a new predictive model that outperforms existing ones. The `hierarchical regression analysis` serves to build models incrementally, where earlier models (e.g., with only main effects) act as a reference point for evaluating the incremental predictive power of interaction terms. # 6. Results & Analysis ## 6.1. Core Results Analysis The study's results primarily focus on descriptive statistics, correlations, and the outcomes of hierarchical regression analyses to test the moderating effects of `self-control`. ### 6.1.1. Descriptive Statistics and Correlation Analysis The following are the results from Table 1 of the original paper: <div class="table-wrapper"><table> <thead> <tr> <th></th> <th>M</th> <th>SD</th> <th>1</th> <th>2</th> <th>3</th> <th>4</th> <th>5</th> <th>6</th> <th>7</th> <th>8</th> <th>9</th> </tr> </thead> <tbody> <tr> <td>1. Gender</td> <td>-</td> <td>-</td> <td>-</td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> </tr> <tr> <td>2. Age</td> <td>20.89</td> <td>1.69</td> <td>-0.18***</td> <td>-</td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> </tr> <tr> <td>3. MS</td> <td>4.72</td> <td>0.92</td> <td>-0.27***</td> <td>0.14***</td> <td>-</td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> </tr> <tr> <td>4. MF</td> <td>4.16</td> <td>1.07</td> <td>-0.05</td> <td>0.05</td> <td>-0.21***</td> <td>-</td> <td></td> <td></td> <td></td> <td></td> <td></td> </tr> <tr> <td>5. Self-control</td> <td>4.96</td> <td>0.80</td> <td>0.07*</td> <td>-0.03</td> <td>0.36***</td> <td>-0.27***</td> <td>-</td> <td></td> <td></td> <td></td> <td></td> </tr> <tr> <td>6. Life satisfaction</td> <td>4.52</td> <td>1.13</td> <td>-0.23***</td> <td>0.13***</td> <td>0.51***</td> <td>-0.18***</td> <td>0.25***</td> <td>-</td> <td></td> <td></td> <td></td> </tr> <tr> <td>7. Positive affect</td> <td>4.50</td> <td>1.22</td> <td>-0.21***</td> <td>0.17***</td> <td>0.55***</td> <td>-0.22***</td> <td>0.36***</td> <td>0.58***</td> <td>-</td> <td></td> <td></td> </tr> <tr> <td>8. Negative affect</td> <td>3.85</td> <td>1.79</td> <td>0.28***</td> <td>-0.20***</td> <td>-0.36***</td> <td>0.22***</td> <td>-0.27***</td> <td>-0.34***</td> <td>-0.47***</td> <td>-</td> <td></td> </tr> <tr> <td>9. SWB</td> <td>5.17</td> <td>3.32</td> <td>-0.31***</td> <td>0.22***</td> <td>0.57***</td> <td>-0.26***</td> <td>0.36***</td> <td>0.74***</td> <td>0.82***</td> <td>-0.83***</td> <td>-</td> </tr> </tbody> </table></div> Note. $N = 1017$. $^*p < 0.05$, $^{**}p < 0.01$, $^{***}p < 0.001$. MS = Motivation to approach success; MF = Motivation to avoid failure; SWB = Subjective well-being. **Key observations from Table 1:** * `Motivation to approach success (MS)` is positively correlated with `SWB` ($r = 0.57$, $p < 0.001$), `life satisfaction` ($r = 0.51$, $p < 0.001$), and `positive affect` ($r = 0.55$, $p < 0.001$), and negatively correlated with `negative affect` ($r = -0.36$, $p < 0.001$). * `Motivation to avoid failure (MF)` is negatively correlated with `SWB` ($r = -0.26$, $p < 0.001$), `life satisfaction` ($r = -0.18$, $p < 0.001$), and `positive affect` ($r = -0.22$, $p < 0.001$), and positively correlated with `negative affect` ($r = 0.22$, $p < 0.001$). * `Self-control` is positively correlated with `MS` ($r = 0.36$, $p < 0.001$), `SWB` ($r = 0.36$, $p < 0.001$), `life satisfaction` ($r = 0.25$, $p < 0.001$), and `positive affect` ($r = 0.36$, $p < 0.001$), and negatively correlated with `MF` ($r = -0.27$, $p < 0.001$) and `negative affect` ($r = -0.27$, $p < 0.001$). * These correlations are largely consistent with previous research, supporting the initial hypotheses regarding the main effects of `achievement motivation` on `SWB`. ### 6.1.2. Hierarchical Regression Analysis for Overall SWB The following are the results from Table 2 of the original paper: <div class="table-wrapper"><table> <thead> <tr> <th></th> <th colspan="2">Model 1</th> <th colspan="2">Model 2</th> <th colspan="2">Model 3</th> <th colspan="2">Model 4</th> </tr> <tr> <th>Variable</th> <th>β</th> <th>t</th> <th>β</th> <th>t</th> <th>β</th> <th>t</th> <th>β</th> <th>t</th> </tr> </thead> <tbody> <tr> <td>Gender</td> <td>-0.28</td> <td>-9.26***</td> <td>-0.17</td> <td>-6.46***</td> <td>-0.20</td> <td>-7.74***</td> <td>-0.18</td> <td>-7.17***</td> </tr> <tr> <td>Age</td> <td>0.17</td> <td>5.57***</td> <td>0.13</td> <td>5.18***</td> <td>0.14</td> <td>5.69***</td> <td>0.14</td> <td>5.68***</td> </tr> <tr> <td>MS</td> <td></td> <td></td> <td>0.47</td> <td>18.09***</td> <td>0.40</td> <td>14.65***</td> <td>0.43</td> <td>15.58***</td> </tr> <tr> <td>MF</td> <td></td> <td></td> <td>-0.18</td> <td>7.02***</td> <td>-0.14</td> <td>-5.64***</td> <td>-0.15</td> <td>-5.54***</td> </tr> <tr> <td>Self-control</td> <td></td> <td></td> <td></td> <td></td> <td>0.20</td> <td>7.57***</td> <td>0.20</td> <td>7.61***</td> </tr> <tr> <td>MS × Self-control</td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> <td>0.11</td> <td>4.25***</td> </tr> <tr> <td>MF × Self-control</td> <td></td> <td></td> <td></td> <td></td> <td></td> <td></td> <td>0.15</td> <td>5.71***</td> </tr> <tr> <td>R²</td> <td colspan="2">0.12</td> <td colspan="2">0.40</td> <td colspan="2">0.43</td> <td colspan="2">0.46</td> </tr> <tr> <td>F change</td> <td colspan="2"></td> <td colspan="2">230.33***</td> <td colspan="2">57.33***</td> <td colspan="2">24.57***</td> </tr> <tr> <td>ΔR²</td> <td colspan="2"></td> <td colspan="2">0.27</td> <td colspan="2">0.03</td> <td colspan="2">0.03</td> </tr> </tbody> </table></div> Note. $N = 1017$. $^*p < 0.05$, $^{**}p < 0.01$, $^{***}p < 0.001$. MS = Motivation to approach success; MF = Motivation to avoid failure; SWB = Subjective well-being. **Key findings from Table 2:** * **Main Effects (Model 2):** `Motivation to approach success (MS)` was positively related to `SWB` ($\beta = 0.47$, $p < 0.001$), and `Motivation to avoid failure (MF)` was negatively related to `SWB` ($\beta = -0.18$, $p < 0.001$). These findings support the first hypothesis. * **Self-control Main Effect (Model 3):** `Self-control` itself was a significant positive predictor of `SWB` ($\beta = 0.20$, $p < 0.001$). * **Moderating Role of Self-control (Model 4):** * The interactive effect of `MS` and `Self-control` on `SWB` was significant ($\beta = 0.11$, $p < 0.001$). This supports the second hypothesis. * The interactive effect of `MF` and `Self-control` on `SWB` was also significant ($\beta = 0.15$, $p < 0.001$). This supports the third hypothesis, although the direction of the `beta` coefficient for interaction needs careful interpretation with simple slopes. * **Model Fit:** The addition of interaction terms in Model 4 significantly improved the model's explanatory power ($\Delta R^2 = 0.03$, $F_{change} = 24.57$, $p < 0.001$). ### 6.1.3. Simple Slope Tests for SWB The simple slope tests further elucidated the nature of the significant interactions: * **MS $\times$ Self-control on SWB:** * For individuals with `high self-control`, the positive effect of `MS` on `SWB` was stronger ($\beta = 0.52$, $p < 0.001$). * For individuals with `low self-control`, the positive effect of `MS` on `SWB` was relatively weaker ($\beta = 0.28$, $p < 0.001$). * This confirms that `self-control` amplifies the positive impact of `MS` on `SWB`. The following figure (Figure 1 from the original paper) visualizes the interactive effect of `motivation to approach success` and `self-control` on `SWB`:  *该图像是一个示意图，展示了成就动机对主观幸福感的影响，其中低自我控制和高自我控制个体的曲线趋势不同。随着成就动机的提高，高自我控制的个体主观幸福感显著提高，而低自我控制的个体提高幅度较小。* As seen in Figure 1, the slope for `high self-control` is steeper than for `low self-control`, indicating that as `MS` increases, `SWB` rises more sharply for those with higher `self-control`. * **MF $\times$ Self-control on SWB:** * The negative effect of `MF` on `SWB` diminished with increasing `self-control`. * For individuals with `high self-control`, the negative impact of `MF` on `SWB` was relatively weaker. * For individuals with `low self-control`, the negative impact of `MF` on `SWB` was stronger. The following figure (Figure 2 from the original paper) visualizes the interactive effect of `motivation to avoid failure` and `self-control` on `SWB`:  *该图像是一个图表，展示了避免失败动机对主观幸福感的影响，依自我控制能力的高低而异。图中显示，在低自我控制情况下，主观幸福感随着避免失败动机的增加而减小，而在高自我控制情况下，该影响较弱。* Figure 2 shows that for `low self-control` individuals, `SWB` decreases significantly as `MF` increases (steeper negative slope). For `high self-control` individuals, `SWB` remains relatively stable or decreases much less sharply as `MF` increases (flatter slope), indicating that `self-control` buffers against the negative effects of `MF`. ### 6.1.4. Regression Analysis for Dimensions of SWB The following are the results from Table 3 of the original paper: <div class="table-wrapper"><table> <thead> <tr> <th></th> <th colspan="2">Life satisfaction</th> <th colspan="2">Positive affect</th> <th colspan="2">Negative affect</th> </tr> <tr> <th>Variable</th> <th>β</th> <th>t</th> <th>β</th> <th>t</th> <th>β</th> <th>t</th> </tr> </thead> <tbody> <tr> <td>Gender</td> <td>-0.10</td> <td>-3.69***</td> <td>-0.08</td> <td>-3.18**</td> <td>0.21</td> <td>7.16***</td> </tr> <tr> <td>Age</td> <td>0.05</td> <td>1.81</td> <td>0.11</td> <td>4.19***</td> <td>-0.15</td> <td>-5.31***</td> </tr> <tr> <td>MS</td> <td>0.47</td> <td>14.88***</td> <td>0.46</td> <td>15.55***</td> <td>-0.20</td> <td>-6.01***</td> </tr> <tr> <td>MF</td> <td>-0.09</td> <td>-3.06**</td> <td>-0.11</td> <td>-3.92***</td> <td>0.14</td> <td>4.50***</td> </tr> <tr> <td>Self-control</td> <td>0.09</td> <td>2.98**</td> <td>0.19</td> <td>6.95***</td> <td>-0.18</td> <td>-5.95***</td> </tr> <tr> <td>MS × Self-control</td> <td>0.08</td> <td>2.88**</td> <td>0.07</td> <td>2.43*</td> <td>-0.10</td> <td>-3.48**</td> </tr> <tr> <td>MF × Self-control</td> <td>0.16</td> <td>5.46***</td> <td>0.14</td> <td>4.99***</td> <td>-0.08</td> <td>-2.64**</td> </tr> <tr> <td>R²</td> <td colspan="2">0.31</td> <td colspan="2">0.38</td> <td colspan="2">0.26</td> </tr> <tr> <td>F change</td> <td colspan="2">18.53***</td> <td colspan="2">14.99***</td> <td colspan="2">9.26***</td> </tr> <tr> <td>ΔR²</td> <td colspan="2">0.03</td> <td colspan="2">0.02</td> <td colspan="2">0.01</td> </tr> </tbody> </table></div> Note. $N = 1017$; $^*p < 0.05$, $^{**}p < 0.01$, $^{***}p < 0.001$. MS = Motivation to approach success; MF = Motivation to avoid failure; SWB = Subjective well-being. **Summary of findings from Table 3:** * **Life Satisfaction:** * `MS` positively predicted `life satisfaction` ($\beta = 0.47$, $p < 0.001$). * `MF` negatively predicted `life satisfaction` ($\beta = -0.09$, $p < 0.01$). * `Self-control` positively predicted `life satisfaction` ($\beta = 0.09$, $p < 0.01$). * Both interaction terms, `MS` $\times$ `Self-control` ($\beta = 0.08$, $p < 0.01$) and `MF` $\times$ `Self-control` ($\beta = 0.16$, $p < 0.001$), were significant, indicating moderation for `life satisfaction`. The following figure (Figure 3 from the original paper) visualizes the interactive effect of `MS` and `self-control` on `life satisfaction`:  *该图像是一个图表，展示了成就动机对生活满意度的影响，考虑了自我控制的调节作用。图中展示了在低和高成就动机水平下，自我控制能力的差异对生活满意度的影响，高自我控制组的生活满意度在高成就动机下显著提高。* Figure 3 shows a similar pattern to overall `SWB`: the positive slope of `MS` on `life satisfaction` is steeper for `high self-control` individuals. The following figure (Figure 4 from the original paper) visualizes the interactive effect of `MF` and `self-control` on `life satisfaction`:  *该图像是一个线性图，展示了避免失败动机对生活满意度的影响。在低自控能力的个体中，生活满意度随着避免失败动机的增加而趋于下降，而在高自控能力个体中，该影响较弱，表现出生活满意度相对稳定。* Figure 4 illustrates that `high self-control` buffers the negative impact of `MF` on `life satisfaction`, similar to the overall `SWB` finding. * **Positive Affect:** * `MS` positively predicted `positive affect` ($\beta = 0.46$, $p < 0.001$). * `MF` negatively predicted `positive affect` ($\beta = -0.11$, $p < 0.001$). * `Self-control` positively predicted `positive affect` ($\beta = 0.19$, $p < 0.001$). * Both interaction terms, `MS` $\times$ `Self-control` ($\beta = 0.07$, $p < 0.05$) and `MF` $\times$ `Self-control` ($\beta = 0.14$, $p < 0.001$), were significant, indicating moderation for `positive affect`. The following figure (Figure 5 from the original paper) visualizes the interactive effect of `MS` and `self-control` on `positive affect`:  *该图像是一个图表，展示了成功动机和正向情感之间的关系，区分了低自我控制和高自我控制个体。结果显示，随着成功动机的增加，高自我控制个体的正向情感表现出更明显的增长趋势。* Figure 5 shows that for `high self-control` individuals, the increase in `positive affect` with higher `MS` is more pronounced. The following figure (Figure 6 from the original paper) visualizes the interactive effect of `MF` and `self-control` on `positive affect`:  *该图像是一个图表，展示了避免失败动机对积极情感的影响，分为低自我控制和高自我控制两组。对于高自我控制的个体，避免失败动机对积极情感的负面影响较小，而低自我控制的个体则表现出明显的下降趋势。* Figure 6 demonstrates that `high self-control` weakens the negative association between `MF` and `positive affect`. * **Negative Affect:** * `MS` negatively predicted `negative affect` ($\beta = -0.20$, $p < 0.001$). * `MF` positively predicted `negative affect` ($\beta = 0.14$, $p < 0.001$). * `Self-control` negatively predicted `negative affect` ($\beta = -0.18$, $p < 0.001$). * Both interaction terms, `MS` $\times$ `Self-control` ($\beta = -0.10$, $p < 0.01$) and `MF` $\times$ `Self-control` ($\beta = -0.08$, $p < 0.01$), were significant, indicating moderation for `negative affect`. The following figure (Figure 7 from the original paper) visualizes the interactive effect of `MS` and `self-control` on `negative affect`:  *该图像是一个图表，展示了在追求成功的动机与消极情感之间的关系，并依据自我控制能力的高低进行了区分。结果显示，具有高自我控制能力的个体在追求成功的动机下，消极情感的值相对较低，而低自我控制能力的个体则表现出较高的消极情感。* Figure 7 suggests that `high self-control` enhances the negative relationship between `MS` and `negative affect`, meaning higher `MS` leads to lower `negative affect` more effectively for those with `high self-control`. The following figure (Figure 8 from the original paper) visualizes the interactive effect of `MF` and `self-control` on `negative affect`:  *该图像是一个图表，展示了动力避免失败与负面情感之间的关系，区分了低自控和高自控个体的表现。图中清晰显示，随着避免失败动机的增加，低自控个体的负面情感水平上升，而高自控个体的负面情感水平则相对平稳。* Figure 8 indicates that `high self-control` attenuates the positive relationship between `MF` and `negative affect`, making `negative affect` less likely to increase with higher `MF`. ### 6.1.5. Three-way Interaction Effects (Supplementary Analyses) The following are the results from Table 4 of the original paper: <div class="table-wrapper"><table> <thead> <tr> <th rowspan="2">Variable</th> <th colspan="2">SWB</th> <th colspan="2">Life satisfaction</th> <th colspan="2">Positive affect</th> <th colspan="2">Negative affect</th> </tr> <tr> <th>β</th> <th>SE</th> <th>β</th> <th>SE</th> <th>β</th> <th>SE</th> <th>β</th> <th>SE</th> </tr> </thead> <tbody> <tr> <td>Gender</td> <td>-0.36***</td> <td>0.05</td> <td>-0.20***</td> <td>0.06</td> <td>-0.17***</td> <td>0.05</td> <td>0.43***</td> <td>0.06</td> </tr> <tr> <td>Age</td> <td>0.13***</td> <td>0.02</td> <td>0.05</td> <td>0.03</td> <td>0.10***</td> <td>0.03</td> <td>-0.14***</td> <td>0.03</td> </tr> <tr> <td>MS</td> <td>0.46***</td> <td>0.03</td> <td>0.48***</td> <td>0.03</td> <td>0.48***</td> <td>0.03</td> <td>-0.23***</td> <td>0.03</td> </tr> <tr> <td>MF</td> <td>-0.06#</td> <td>0.03</td> <td>-0.06#</td> <td>0.03</td> <td>-0.07#</td> <td>0.03</td> <td>0.02</td> <td>0.03</td> </tr> <tr> <td>Self-control</td> <td>0.17***</td> <td>0.03</td> <td>0.08#</td> <td>0.03</td> <td>0.18***</td> <td>0.03</td> <td>-0.14**</td> <td>0.03</td> </tr> <tr> <td>MS × Self-control</td> <td>0.08***</td> <td>0.02</td> <td>0.05#</td> <td>0.03</td> <td>0.04</td> <td>0.03</td> <td>-0.09#</td> <td>0.03</td> </tr> <tr> <td>MF × Self-control</td> <td>0.25***</td> <td>0.03</td> <td>0.22**</td> <td>0.03</td> <td>0.20***</td> <td>0.03</td> <td>-0.18***</td> <td>0.03</td> </tr> <tr> <td>MS × MF</td> <td>-0.12***</td> <td>0.03</td> <td>-0.02</td> <td>0.03</td> <td>-0.02</td> <td>0.02</td> <td>0.20***</td> <td>0.03</td> </tr> <tr> <td>MS × MF × Self-control</td> <td>-0.08***</td> <td>0.02</td> <td>-0.08***</td> <td>0.02</td> <td>-0.08***</td> <td>0.02</td> <td>0.04#</td> <td>0.02</td> </tr> <tr> <td>R²</td> <td colspan="2">0.48</td> <td colspan="2">0.32</td> <td colspan="2">0.39</td> <td colspan="2">0.31</td> </tr> <tr> <td>F change</td> <td colspan="2">16.86**</td> <td colspan="2">15.14**</td> <td colspan="2">14.9**</td> <td colspan="2">2.76**</td> </tr> <tr> <td>ΔR²</td> <td colspan="2">0.01</td> <td colspan="2">0.01</td> <td colspan="2">0.01</td> <td colspan="2">0.01</td> </tr> </tbody> </table></div> Note. $N = 1017$. $^\#p < 0.1$, $^*p < 0.05$, $^{**}p < 0.01$, $^{***}p < 0.001$. MS = Motivation to approach success; MF = Motivation to avoid failure; SWB = Subjective well-being. **Key findings from Table 4 (Three-way interactions):** * **SWB, Life Satisfaction, Positive Affect:** A significant `three-way interaction` between `MS`, `MF`, and `Self-control` was found for `SWB` ($\beta = -0.08$, $p < 0.001$), `life satisfaction` ($\beta = -0.08$, $p < 0.001$), and `positive affect` ($\beta = -0.08$, $p < 0.001$). This interaction term accounted for an additional 1% of the variance in these dependent variables. * **Negative Affect:** The `three-way interaction` for `negative affect` was marginally significant ($\beta = 0.04$, $p = 0.09$). * These findings indicate that the combined effect of `motivation to approach success` and `motivation to avoid failure` on `SWB` is further conditioned by the level of `self-control`. The following figures (Figures 9-16 from the original paper) further illustrate the two-way interaction effects on SWB and its dimensions, which were detailed earlier.  *该图像是一个图表，展示了成功动机与主观幸福感之间的关系，图中显示了高自我控制与低自我控制个体的差异。随着成功动机的增强，高自我控制个体的主观幸福感显著提高，而低自我控制个体的提升相对较弱。* Figure 9. Interactive effect of approaching success and self-control on SWB.  *该图像是一个线性图，展示了避免失败动机对生活满意度的影响。在低自控能力的个体中，生活满意度随着避免失败动机的增加而趋于下降，而在高自控能力个体中，该影响较弱，表现出生活满意度相对稳定。* Figure 10. Interactive effect of avoiding failure and self-control on SWB.  *该图像是一个图表，展示了成功动机和正向情感之间的关系，区分了低自我控制和高自我控制个体。结果显示，随着成功动机的增加，高自我控制个体的正向情感表现出更明显的增长趋势。* Figure 11. Interactive effect of approaching success and self-control on life satisfaction.  *该图像是一个线性图，展示了避免失败动机对生活满意度的影响。在低自控能力的个体中，生活满意度随着避免失败动机的增加而趋于下降，而在高自控能力个体中，该影响较弱，表现出生活满意度相对稳定。* Figure 12. Interactive effect of avoiding failure and self-control on life satisfaction.  *该图像是一个图表，展示了成功动机和正向情感之间的关系，区分了低自我控制和高自我控制个体。结果显示，随着成功动机的增加，高自我控制个体的正向情感表现出更明显的增长趋势。* Figure 13. Interactive effect of approaching success and self-control on positive affect.  *该图像是一个图表，展示了避免失败动机对积极情感的影响，分为低自我控制和高自我控制两组。对于高自我控制的个体，避免失败动机对积极情感的负面影响较小，而低自我控制的个体则表现出明显的下降趋势。* Figure 14. Interactive effect of avoiding failure and self-control on positive affect.  *该图像是一个图表，展示了在追求成功的动机与消极情感之间的关系，并依据自我控制能力的高低进行了区分。结果显示，具有高自我控制能力的个体在追求成功的动机下，消极情感的值相对较低，而低自我控制能力的个体则表现出较高的消极情感。* Figure 15. Interactive effect of approaching success and self-control on negative affect.  *该图像是一个示意图，展示了在避免失败动机下，自我控制水平对负面情绪的影响。横轴表示避免失败的动机，纵轴表示负面情绪，图中显示低自我控制与高自我控制个体的关系曲线。结果显示，低自我控制者在高动机下表现出较高的负面情绪。* Figure 16. Interactive effect of avoiding failure and self-control on negative affect. ### 6.1.6. Conditional MS $\times$ MF Interaction at Different Self-control Levels The following are the results from Table 5 of the original paper: <div class="table-wrapper"><table> <thead> <tr> <th>Self-control</th> <th>β</th> <th>F</th> <th>p</th> </tr> </thead> <tbody> <tr> <td>Low (on SWB)</td> <td>-0.0438</td> <td>2.0307</td> <td>0.1545</td> </tr> <tr> <td>High (on SWB)</td> <td>-0.2060</td> <td>55.9118</td> <td>0.0000</td> </tr> <tr> <td>Low (on life satisfaction)</td> <td>0.0673</td> <td>3.6497</td> <td>0.0564</td> </tr> <tr> <td>High (on life satisfaction)</td> <td>-0.1088</td> <td>11.8764</td> <td>0.0006</td> </tr> <tr> <td>Low (on positive affect)</td> <td>0.0566</td> <td>2.8830</td> <td>0.0898</td> </tr> <tr> <td>High (on positive affect)</td> <td>-0.1091</td> <td>13.3454</td> <td>0.0003</td> </tr> <tr> <td>Low (on negative affect)</td> <td>0.1626</td> <td>20.7514</td> <td>0.0000</td> </tr> <tr> <td>High (on negative affect)</td> <td>0.2388</td> <td>55.7434</td> <td>0.0000</td> </tr> </tbody> </table></div> Note. $N = 1017$. MS = Motivation to approach success; MF = Motivation to avoid failure; SWB = Subjective well-being. **Key findings from Table 5:** * For individuals with `high self-control`, the interactive effect of `MS` and `MF` on `SWB` ($\beta = -0.21$, $p < 0.001$), `life satisfaction` ($\beta = -0.11$, $p < 0.001$), and `positive affect` ($\beta = -0.11$, $p < 0.001$) was significant. * The interactive effect of `MS` and `MF` on `negative affect` was more significant in the `high self-control` condition. * These results suggest that for individuals with `high self-control`, the co-occurrence of `MS` and `MF` can lead to reduced `SWB`, `life satisfaction`, and `positive affect`, and increased `negative affect`. This implies that even with high `self-control`, the internal conflict arising from simultaneously high `approach` and `avoidance` motivations can be detrimental. The following figures (Figures 17-20 from the original paper) illustrate the three-way interaction effects: The following figure (Figure 17 from the original paper) visualizes the three-way interaction of `MS` $\times$ `MF` $\times$ `self-control` with `SWB` as the dependent variable:  *该图像是一个示意图，展示了自我控制水平对主观幸福感的影响。图中分别展示了在低自我控制和高自我控制条件下，四种不同动机组合（高成功动机、高失败动机；高成功动机、低失败动机；低成功动机、高失败动机；低成功动机、低失败动机）对主观幸福感的影响趋势。* Figure 17 shows that for `high self-control` individuals, the highest `SWB` is observed in the condition of `low MS` and `low MF`. Conversely, individuals with `high self-control` and both `high MS` and `high MF` report the lowest `SWB`. For `low self-control` individuals, the pattern is less distinct. The following figure (Figure 18 from the original paper) visualizes the three-way interaction of `MS` $\times$ `MF` $\times$ `self-control` with `life satisfaction` as the dependent variable:  *该图像是一个表示生活满意度与自我控制能力的交互作用的线图，展示了在不同成就动机水平下，低自我控制与高自我控制个体在生活满意度上的变化趋势。图中显示，随着自我控制能力的提高，成就动机对生活满意度的影响逐渐增强。* Figure 18 shows a similar pattern for `life satisfaction` as for `SWB`, with `high self-control` and `low MS` / `low MF` leading to the highest `life satisfaction`. The following figure (Figure 19 from the original paper) visualizes the three-way interaction of `MS` $\times$ `MF` $\times$ `self-control` with `positive affect` as the dependent variable:  *该图像是一个线性图，展示了避免失败动机对生活满意度的影响。在低自控能力的个体中，生活满意度随着避免失败动机的增加而趋于下降，而在高自控能力个体中，该影响较弱，表现出生活满意度相对稳定。* Figure 19 demonstrates that `high self-control` individuals with `low MS` and `low MF` experience the highest `positive affect`. The following figure (Figure 20 from the original paper) visualizes the three-way interaction of `MS` $\times$ `MF` $\times$ `self-control` with `negative affect` as the dependent variable:  *该图像是一个图表，展示了成功动机和正向情感之间的关系，区分了低自我控制和高自我控制个体。结果显示，随着成功动机的增加，高自我控制个体的正向情感表现出更明显的增长趋势。* Figure 20 illustrates that `high self-control` individuals with `low MS` and `low MF` report the lowest `negative affect`. **Overall Analysis of Three-Way Interactions:** The discussion highlights that individuals with `high self-control` who also have both `high MS` and `high MF` tend to experience the lowest `SWB`, `life satisfaction`, `positive affect`, and highest `negative affect`. This is attributed to `emotional ambivalence` caused by the conflicting nature of simultaneously activating `approach` and `avoidance` motives. Conversely, individuals with `high self-control` and both `low MS` and `low MF` experience the highest `SWB`, `life satisfaction`, `positive affect`, and lowest `negative affect`. This suggests that being less driven by either extreme of `achievement motivation` (and thus less dependent on social evaluations) combined with `high self-control` can lead to more positive experiences and fewer inner conflicts. ## 6.2. Comparison with Baseline Models (Implicit) The implicit "baselines" for comparison are the direct effects of `MS` and `MF` on `SWB` that have been widely reported in previous literature. * **Advantages of the Proposed Approach:** The study's main advantage is demonstrating that these direct effects are not universal. By introducing `self-control` as a moderator, it shows that the positive effect of `MS` is *enhanced* and the negative effect of `MF` is *attenuated* for individuals with high `self-control`. This provides a more nuanced and accurate understanding of how `achievement motivation` impacts `well-being`. * **Disadvantages/Limitations:** The current study, being correlational, cannot establish causality. While the results suggest improving `self-control` would be beneficial, intervention studies would be needed to confirm this causal link. ## 6.3. Ablation Studies / Parameter Analysis The paper does not conduct traditional ablation studies in the sense of removing components of a model. Instead, the `hierarchical regression analysis` serves a similar purpose by incrementally adding predictors (control variables, main effects, moderator, interaction terms). Each step assesses the incremental variance explained ($\Delta R^2$), effectively "ablating" or "adding back" components to see their unique contribution. * The `F change` and \Delta R^2$$ values in Table 2 and Table 3 demonstrate the significant incremental contribution of self-control and the interaction terms to the prediction of SWB and its dimensions. For example, adding self-control (Model 3) and the interaction terms (Model 4) significantly increased the explanatory power of the model for SWB, life satisfaction, positive affect, and negative affect. This confirms that these components (main effect of self-control and its interactions) are crucial for a comprehensive understanding.

• The three-way interaction analysis in the supplementary section further explores more complex conditional relationships, indicating the combined influence of MS, MF, and self-control. This is a deeper parameter analysis of how these variables jointly affect outcomes.

7. Conclusion & Reflections

7.1. Conclusion Summary

This study provides a comprehensive investigation into the differential influence of achievement motivation on subjective well-being (SWB), highlighting the crucial moderating role of self-control. The findings, derived from a survey of 1017 Chinese college students, confirm that while motivation to approach success (MS) generally predicts higher SWB and motivation to avoid failure (MF) predicts lower SWB, these relationships are significantly conditioned by an individual's self-control ability.

Specifically, for individuals with high self-control, the positive effects of MS on SWB, life satisfaction, and positive affect are stronger, and MS more effectively reduces negative affect. Conversely, high self-control acts as a buffer, weakening the negative effects of MF on SWB, life satisfaction, and positive affect, and mitigating its positive association with negative affect. The study also revealed complex three-way interactions, suggesting that high self-control individuals experience the lowest SWB when both MS and MF are high, possibly due to emotional ambivalence.

Overall, the study concludes that improving self-control ability can maximize the benefits of achievement motivation on SWB. It suggests that strategies for enhancing SWB should involve cultivating adaptive achievement-oriented goals tailored to an individual's self-control level.

7.2. Limitations & Future Work

The authors acknowledge several limitations and propose future research directions:

• Methodological Limitation (Questionnaire Survey): The reliance on a questionnaire survey for data collection means that causal relationships between variables cannot be definitively inferred. Correlations and moderation indicate associations, but not cause-and-effect.
  • Future Direction: Longitudinal studies and experimental designs are necessary to establish causality (e.g., does improving self-control cause a change in how achievement motivation affects SWB?).
• Sample Specificity: The sample consisted exclusively of Chinese college students. This limits the generalizability of the findings to other populations.
  • Future Direction: Expansion of the research to other countries, age groups, or occupational groups is needed. Cross-cultural perspectives could also reveal cultural variations in response tendencies or introspective practices.
• Three-way Interaction (Limited Exploration): While three-way interaction effects of MS, MF, and Self-control on SWB were explored in supplementary analyses, these were discussed as "more interesting findings" beyond the main hypotheses. The simple slope tests for these three-way interactions were noted as "nonsignificant" for MS $\times$ MF interaction at different values of Self-control, but "some trend changes" were observed.
  • Future Direction: Further, more in-depth exploration of three-way interaction effects is warranted to fully understand the co-occurring effects of approach and avoidance motivation under different self-control conditions. This could elucidate the dynamics of emotional ambivalence and inner conflicts.
• Cultivation of Self-control: The paper highlights that self-control can be cultivated and enhanced.
  • Future Direction: Longitudinal studies are necessary to trace the development of self-control ability for college students and its possible influence on well-being over time. This would provide insights into the malleability of self-control and the long-term impact of interventions.

7.3. Personal Insights & Critique

This paper makes a valuable contribution by moving beyond simple direct relationships to explore the nuanced interplay between achievement motivation and SWB. The introduction of self-control as a moderator is a theoretically sound and practically relevant innovation. The rigorous statistical analysis, including hierarchical regression and simple slope tests, effectively demonstrates these complex interactions.

Inspirations and Applications:

• Personalized Interventions: The findings strongly suggest that psychological interventions aimed at enhancing well-being should be personalized. For example, a career counselor or educator might encourage a high self-control individual to pursue ambitious goals (high MS) without fear, as their self-control will help them navigate challenges and maintain well-being. For a low self-control individual, the focus might be more on reducing the fear of failure (MF) and developing self-regulatory strategies to cope with potential setbacks, rather than simply pushing them towards success-oriented goals.
• Educational Implications: The emphasis on self-control as a "character strength" crucial for 21st-century education is particularly insightful. Incorporating self-monitoring, self-evaluating, and self-reinforcing skills into educational curricula could foster resilience and well-being among students, regardless of their intrinsic achievement motivation profiles.
• Broader Applicability: The model proposed could potentially be transferred to other domains where motivation, goal pursuit, and well-being intersect, such as organizational psychology (employee motivation and job satisfaction), sports psychology (athlete performance and mental health), or health behavior change (adherence to healthy habits).

Potential Issues or Areas for Improvement:

• Measurement of Self-control: While the SCMS is a validated instrument, self-report measures of self-control can sometimes be biased. Future research could benefit from incorporating behavioral measures of self-control (e.g., delay of gratification tasks) or informant reports to provide a more objective assessment.

• Nature of "Ambivalence" in Three-Way Interaction: The finding that high MS and high MF combined with high self-control leads to lower SWB is intriguing. The paper attributes this to "emotional ambivalence." While plausible, further qualitative or mixed-methods research could delve deeper into the subjective experience of this ambivalence. Is it a debilitating conflict, or does high self-control allow for some productive tension? Understanding the nature of this "conflict" could refine interventions.

• Cultural Context: The study was conducted in China. While the scales used have been revised for Chinese contexts, cultural differences in the manifestation and experience of achievement motivation, self-control, and well-being cannot be fully discounted. For instance, collectivist cultures might place different values on individual success versus group harmony, potentially influencing SWB differently.

• Theoretical Refinement: While motive disposition theory and regulatory focus theory provide a strong foundation, the interaction observed (e.g., high self-control buffering MF) could be further elaborated within these frameworks. How exactly do self-regulatory processes modulate the vigilance associated with prevention focus to reduce negative affect? This could lead to a more fine-grained theoretical model.

  Overall, this paper provides a robust empirical foundation for understanding the complex relationship between motivation, self-regulation, and well-being. Its insights are valuable for both theoretical advancement and practical application in promoting healthier and more fulfilling lives.