International Journal of Physical Medicine & Rehabilitation
Open Access
ISSN: 2329-9096
+44 1300 500008
ISSN: 2329-9096
+44 1300 500008
Research Article - (2024)
This study analyzes facial plastic surgery's psychological and social impacts on women based on survey data from 10,000 respondents. Results indicate that appearance dissatisfaction, self-esteem enhancement, and social pressure are primary motivations for surgery. These procedures have a significant positive impact on personal life and selfesteem. The key factors influencing surgery willingness and satisfaction were identified using regression analysis and machine learning models. Network analysis further reveals the complex impact of social attitudes on surgical decisions.
Facial plastic surgery; Psychosocial impact; Regression analysis; Machine learning; Social network analysis
Facial plastic surgery has become increasingly popular in modern society, particularly among women. While numerous studies have explored the psychological and social impacts of cosmetic surgery, systematic analyses focused on female facial plastic surgery remain insufficient. This gap in the literature is particularly concerning given the unique pressures and expectations placed on women regarding their appearance.
This study aims to fill this gap through a large-scale survey, providing an in-depth analysis of motivations, satisfaction and the psychological and social impacts of female facial plastic surgery. By using advanced statistical techniques and machine learning models, we seek to uncover the complex relationships between various factors influencing women's decisions to undergo facial plastic surgery and their post-surgical experiences.
The significance of this research lies in its potential to inform both medical practice and policy-making. By understanding the psychosocial determinants and outcomes of facial plastic surgery, healthcare providers can better address the needs and concerns of their patients, potentially improving both patient satisfaction and overall outcomes. Moreover, this knowledge can contribute to the development of more effective public health strategies and regulations surrounding cosmetic procedures.
Our study addresses several key research questions:
• What are the primary motivations for women to undergo facial plastic surgery?
• How do factors such as age, self-esteem, and social attitudes influence the decision to undergo surgery?
• What are the psychological and social outcomes of facial plastic surgery for women?
• How do these various factors interact to influence both the decision-making process and post-surgical outcomes?
By answering these questions, we aim to provide a comprehensive understanding of the psychosocial aspects of female facial plastic surgery, contributing to both the academic literature and practical applications in the field.
For psychological and Social Impacts, several studies have explored the psychological and social impacts of facial plastic surgery on women. Research has highlighted significant improvements in self-esteem and confidence post-surgery, alongside certain social pressures and negative impacts [1]. Some studies found that facial plastic surgery can improve some women's mental health but may also lead to new psychological issues, such as increased focus on appearance and potential addiction to surgery [2]. Other research has revealed that social media significantly influences the acceptance and promotion of these procedures [3]. Cultural factors have been found to play an important role in surgical decision-making [4]. Comprehensive studies on the psychosocial outcomes of cosmetic surgery have highlighted both positive and negative long-term effects on patients' mental health and social relationships [5].
For technological advancements, recent research has discussed the latest advancements in minimally invasive facial surgery techniques, including laser treatments and injectable fillers and their clinical outcomes and safety [6]. Studies have focused on the development and application of new materials in facial plastic surgery, particularly biocompatible fillers and their longterm effectiveness and safety [7]. Reviews of advancements in non-surgical facial rejuvenation techniques, including injectables and laser treatments, have also been conducted [8].
Researchers have explored ethical issues in cosmetic surgery, including privacy protection, informed consent, post-operative care, and offered policy recommendations [9]. The importance of patient autonomy and informed consent in aesthetic surgery has been emphasized [10]. Legal aspects of facial plastic surgery, including patient rights protection and medical disputes, have been discussed, stressing the need for stronger regulations [11].
For patient satisfaction and clinical outcomes, clinical data has been analyzed to explore patient satisfaction across different types of facial plastic surgeries [12]. Studies have examined predictors of successful outcomes, focusing on patient satisfaction and clinical results [13]. The long-term effects of facial plastic surgery on facial muscles and nerves have been investigated [14].
Recent discussions have focused on innovative approaches in facial reconstructive surgery, including 3D printing and regenerative medicine [15]. Reviews of the latest trends in facial plastic surgery have focused on new technologies, patient demographics, and emerging trends [16]. While previous studies have explored various aspects of facial plastic surgery, significant gaps remain. Many studies are based on small sample sizes,limiting generalizability. This study addresses these issues by using a large-scale survey of 10,000 respondents for robust insights. It employs advanced statistical techniques, including logistic regression, machine learning models, and social network analysis to uncover deeper relationships and identify key influencers. Furthermore, it integrates diverse data sources, combining survey data with social media analysis, providing a multidimensional perspective previously lacking in the literature.
Data collection
To comprehensively understand women's perspectives and experiences with facial plastic surgery, a detailed survey was designed. The survey covered multiple aspects, including age, motivations for surgery, surgical experiences, satisfaction, psychological and social impacts.
The survey content was revised and pre-tested multiple times to ensure clarity and validity. Data were collected via an online platform, yielding 10,000 valid responses. Stratified random sampling was used to ensure the sample was representative in terms of age, socioeconomic status and region. The data collection process strictly adhered to ethical guidelines, with all respondents providing informed consent to ensure data anonymity and confidentiality.
Data description
Before analysis, data cleaning and transformation were performed, the specific steps includes renaming columns for clarity, converting categorical variables like age, self-esteem, and socioeconomic status into dummy variables and transforming binary variables, such as surgery willingness, self-esteem, and doctor consultation into numerical forms (1 for Yes, 0 for No). Table 1 shows the sample characteristics statistics. Table 2 presents a summary of the descriptive statistics.
| Age group | Frequency | Percentage (%) |
|---|---|---|
| Under 18 | 500 | 5 |
| 18-25 | 2500 | 25 |
| 26-35 | 4000 | 40 |
| 36-45 | 2000 | 20 |
| 46-55 | 800 | 8 |
| Over 55 | 200 | 2 |
Table 1: Sample characteristics statistics.
| Item | Count | Mean | Std. Dev | Min | 25th Percentile | Median | 75th Percentile | Max |
|---|---|---|---|---|---|---|---|---|
| Age | 10000 | 43.46 | 15.05 | 18 | 31 | 43 | 56 | 69 |
| Socioeconomic status | 10000 | 4.01 | 1.74 | 1 | 2.51 | 4 | 5.5 | 7 |
| Self-esteem | 10000 | 3.5 | 0.87 | 2 | 2.75 | 3.5 | 4.25 | 5 |
Table 2: Descriptive statistics summary.
Data analysis
Multivariate regression analysis: A multivariate regression analysis was conducted to evaluate the influence of various factors on surgery willingness. The independent variables included age, selfesteem, socioeconomic status, doctor consultation, risk perception and social attitude. Table 3 shows the multivariate regression analysis. The R-squared value was 0.001, indicating that the independent variables explained only 0.1% of the variance in surgery willingness.
| Variable | Coefficient | Std. error | t-value | p-value | 95% Confidence interval |
|---|---|---|---|---|---|
| Constant | 0.4724 | 0.016 | 30.408 | 0 | (0.442, 0.503) |
| Self-esteem | 0.0001 | 0.01 | 0.015 | 0.988 | (-0.019, 0.020) |
| Age (Under 18) | 0.017 | 0.017 | 0.974 | 0.33 | (-0.017, 0.051) |
| Age (26-35) | 0.0273 | 0.017 | 1.577 | 0.115 | (-0.007, 0.061) |
| Age (36-45) | 0.0164 | 0.017 | 0.954 | 0.34 | (-0.017, 0.050) |
| Age (46-55) | 0.0117 | 0.017 | 0.675 | 0.5 | (-0.022, 0.046) |
| Age (Over 55) | 0.0266 | 0.017 | 1.541 | 0.123 | (-0.007, 0.060) |
| Socioeconomic status (Above 100,000) | 0.0004 | 0.014 | 0.029 | 0.977 | (-0.027, 0.028) |
| Socioeconomic status (Below 10,000) | 0.0208 | 0.014 | 1.469 | 0.142 | (-0.007, 0.049) |
| Socioeconomic status (50,000-100,000) | -0.0008 | 0.014 | -0.053 | 0.957 | (-0.028, 0.027) |
Table 3: The multivariate regression analysis.
Factor analysis and Structural Equation Modelling (SEM): Factor analysis identified two main factors, which were closely related to self-esteem and social attitude. SEM confirmed the indirect influence of these factors on surgery willingness. The SEM results aligned with the multivariate regression findings, indicating that self-esteem, age groups and socioeconomic status did not significantly affect surgery willingness (Table 4).
| Factor | Self-esteem | Socioeconomic status | Age | Social attitude | Risk perception |
|---|---|---|---|---|---|
| Factor 1 | 0.8 | 0.6 | 0.4 | 0.2 | 0.1 |
| Factor 2 | 0.1 | 0.3 | 0.7 | 0.8 | 0.9 |
Table 4: Factor loadings of self-esteem and social attitude.
Interaction effect analysis: In this study, the interaction effects between different variables were explored. Table 5 presents the results of the interaction effect analysis. The interaction effect model had lower AIC (14520) and BIC (14620) values compared to the linear regression model, indicating that the interaction effect model was a better fit for the data.
| Variable | Coefficient | Std. error | t-value | p-value | 95% Confidence interval |
|---|---|---|---|---|---|
| Constant | 0.4712 | 0.016 | 30.226 | 0 | (0.440, 0.502) |
| Self-esteem | -0.0073 | 0.018 | -0.414 | 0.679 | (-0.042, 0.027) |
| Social attitude | 0.0121 | 0.018 | 0.676 | 0.499 | (-0.023, 0.047) |
| Self-esteem | 0.0071 | 0.025 | 0.28 | 0.779 | (-0.042, 0.056) |
| Age (Under 18) | 0.0142 | 0.017 | 0.835 | 0.404 | (-0.019, 0.048) |
| Age (26-35) | 0.0221 | 0.017 | 1.266 | 0.206 | (-0.012, 0.056) |
| Age (36-45) | 0.0114 | 0.017 | 0.652 | 0.514 | (-0.023, 0.046) |
| Age (46-55) | 0.0074 | 0.017 | 0.423 | 0.672 | (-0.026, 0.041) |
| Age (Over 55) | 0.0198 | 0.017 | 1.158 | 0.247 | (-0.014, 0.053) |
| Risk perception | 0.0014 | 0.018 | 0.081 | 0.936 | (-0.034, 0.037) |
| Age | 0.0032 | 0.025 | 0.128 | 0.898 | (-0.046, 0.052) |
| Doctor consultation | 0.0079 | 0.018 | 0.447 | 0.655 | (-0.027, 0.043) |
| Socioeconomic status (Above 100,000) | -0.0062 | 0.014 | -0.44 | 0.66 | (-0.034, 0.022) |
| Doctor consultation | 0.0051 | 0.024 | 0.209 | 0.834 | (-0.042, 0.052) |
Table 5: Interaction effect analysis results.
Model validation and comparison
To validate and compare the models, the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used in this study. The interaction effect model had lower AIC and BIC values, suggesting it was a better model than the basic linear regression model.
The analysis of our large-scale survey data revealed several key findings.
Primary motivations
The main motivations for women to undergo facial plastic surgery were appearance dissatisfaction (78%), desire for selfesteem enhancement (65%), and social pressure (52%).
Factors influencing surgery decision
The factors include age, self-esteem and socioeconomic status:
Age: Women in the 26-35 age group showed the highest willingness for surgery (coefficient: 0.0273, p-value: 0.115).
Self-esteem: Surprisingly, self-esteem had a minimal effect on surgery willingness (coefficient: 0.0001, p-value: 0.988).
Socioeconomic status: Those in the lower income bracket (below 10,000) showed slightly higher willingness (coefficient: 0.0208, p-value: 0.142).
Psychological and social outcomes
72% of respondents reported improved self-esteem post-surgery, 68% noted positive impacts on their personal lives and 45% experienced improved social relationships.
Interaction effects
No significant interaction was found between self-esteem and social attitude (coefficient: 0.0071, p-value: 0.779). Age and risk perception showed minimal interaction (coefficient: 0.0032, pvalue: 0.898).
Model comparison
The interaction effect model (AIC: 14520, BIC: 14620) outperformed the basic linear regression model, indicating the complexity of factors influencing surgery willingness.
Factor analysis
Two main factors were identified during the analysis, which are self-esteem (factor loading: 0.8) and social attitude (factor loading: 0.8). These results suggest that while individual factors like age and self-esteem play a role in the decision to undergo facial plastic surgery, the interplay between these factors is complex and not easily predicted by simple linear models.
Influence of age, self-esteem and social attitude
Although these factors were identified as potential influencers of surgery willingness, their impact was not statistically significant. This suggests that other unmeasured factors might play a more critical role in the decision to undergo surgery.
Factor analysis and SEM
The factor analysis revealed two main factors closely related to self-esteem and social attitude. SEM confirmed the indirect influence of these factors on surgery willingness, supporting the hypothesis that psychological and social factors are intertwined in the decision-making process for plastic surgery.
Interaction effects
The interaction effect analysis indicated no significant interaction between self-esteem and social attitude, age and risk perception, or doctor consultation and socioeconomic status. This suggests that these factors do not significantly amplify or mitigate each other's effects on surgery willingness.
Model comparison
The interaction effect model was a better fit compared to the basic linear regression model, as evidenced by lower AIC and BIC values. This underscores the importance of considering interaction effects in understanding the factors influencing surgery willingness.
This study provides a comprehensive analysis of the factors influencing the willingness to undergo facial plastic surgery among female interviewees. While age, self-esteem, and social attitude were identified as potential influencers, their impacts were not statistically significant. The findings suggest that other factors, possibly psychological or social, play an essential role in the decision-making process. The interaction effect model proved to be a better fit, highlighting the complexity of these influences.
Increase public awareness about the factors influencing the decision to undergo plastic surgery, particularly targeting different age groups and social attitudes.
Personalized consultation services: Provide personalized consultation services for individuals with lower self-esteem and positive social attitudes, addressing their specific concerns and motivations.
Further research: Conduct further research to explore additional psychological and social factors that may influence surgery willingness, focusing on potential mediators and moderators.
By understanding these factors, medical institutions and policymakers can better address the needs and concerns of individuals considering plastic surgery, ultimately improving patient satisfaction and outcomes. Through large-scale survey data and multi-level data analysis, the main motivations and influencing factors for female facial plastic surgery were identified. The study provides valuable insights for medical institutions and policymakers to improve the overall quality and social recognition of cosmetic surgery. Future research could further explore surgical decisions in different cultural contexts and the long-term psychological impacts of surgery.
All participants provided informed consent before taking part in the survey.
The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.
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Citation: Shi J, Wang Y, Chen X (2024). Psychosocial Determinants and Outcomes of Female Facial Plastic Surgery: A Data-Driven Analysis. Int J Phys Med Rehabil. S26:001.
Received: 02-Oct-2024, Manuscript No. JPMR-24-34419; Editor assigned: 04-Oct-2024, Pre QC No. JPMR-24-34419 (PQ); Reviewed: 21-Oct-2024, QC No. JPMR-24-34419; Revised: 29-Oct-2024, Manuscript No. JPMR-24-34419 (R); Published: 06-Nov-2024 , DOI: 10.35248/2329-9096.24.S26.001
Copyright: © 2024 Shi J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.