this is my study and the analsyis already done on it = The dataset includes:

OGS components and total scores (e.g., Alignment, Marginal Ridge, Overjet, etc.).

Rater evaluations for smile esthetics using a Visual Analogue Scale (VAS) for both Photo and Video formats.

Final columns give the mean photo score and mean video score for each patient.

Next Steps Based on Your Protocol:
We'll now perform the statistical tests as outlined in your protocol:

Descriptive statistics for:

ABO-OGS scores

Mean VAS scores (Photo and Video)

Pearson correlation between OGS total score and:

Mean photo score

Mean video score

Independent t-test or Mann-Whitney U test between:

Orthodontists’ vs Laypersons’ VAS scores (if group labels are identifiable)

Paired t-test or Wilcoxon signed-rank test between:

Mean photo score vs mean video score (within the same patients)

Inter-rater reliability using ICC (Intraclass Correlation Coefficient) for raters' scores

Let’s begin with the descriptive stats and correlations. 

✅ Summary of Descriptive Statistics (n = 38)
Measure	OGS Total Score	Mean Photo VAS	Mean Video VAS
Mean	19.55	7.58	8.06
Standard Deviation	5.46	0.41	0.40
Minimum	8	6.75	7.34
Maximum	29	8.50	8.90

📊 Pearson Correlation Results
Correlation Between	Pearson r	p-value
OGS Total vs Photo VAS	0.136	0.417
OGS Total vs Video VAS	0.039	0.818

🔍 Interpretation:

Both correlations are very weak and not statistically significant (p > 0.05).

This suggests that objective smile scores (OGS) do not correlate well with subjective esthetic ratings from photos or videos.

Next, I’ll:

Compare photo vs video scores using a paired t-test.

Analyze inter-rater reliability using ICC.

Would you also like to split the raters into laypersons vs orthodontists, or should I continue assuming all scores are grouped?  = study =  INTRODUCTION:
The perception of facial esthetics has long been recognized as a fundamental motivator for individuals seeking orthodontic treatment. Among the numerous components of facial attractiveness, the smile holds a particularly influential role in how individuals are perceived socially and psychologically.1 As such, understanding and optimizing smile esthetics is not only critical for achieving clinical success but also for fulfilling patients’ subjective expectations. In recent years, the field of orthodontics has witnessed a paradigm shift from purely functional outcomes towards an integrated approach that considers facial harmony, dental alignment, and esthetic balance. This holistic perspective is especially relevant in patients with skeletal discrepancies, such as Class II malocclusion, where dental and skeletal imbalances have a pronounced impact on smile characteristics.
Class II malocclusion, characterized by a retrusive mandible in relation to the maxilla, is one of the most prevalent types of skeletal malocclusion, with a reported global prevalence ranging from 15% to 20% depending on ethnicity and population group.2 These cases often present with distinctive soft tissue and dentofacial features, such as a convex facial profile, excessive overjet, deep bite, and lip incompetence, all of which can negatively influence smile esthetics.3 The esthetic concerns in Class II patients are often more pronounced than in Class I individuals, making esthetic evaluation and outcome assessment particularly important in this subgroup.4 Despite its high prevalence and clinical significance, there is a relative scarcity of research focusing specifically on the subjective and objective esthetic outcomes in this population.5
In clinical practice, orthodontic treatment success is often evaluated using standardized and objective metrics such as the American Board of Orthodontics Objective Grading System (ABO-OGS).6 This system quantifies treatment outcomes through the analysis of dental casts and panoramic radiographs, assigning scores based on parameters including tooth alignment, marginal ridge height, occlusal contacts, and root angulation.7 Although ABO-OGS provides a valuable framework for assessing technical proficiency, it may not adequately reflect the patient's or the general public’s perception of a successful esthetic result.8 This is particularly pertinent when considering the growing demand for treatment outcomes that are not only functionally sound but also visually pleasing.9
Smile esthetics, however, is a multifactorial construct influenced by the dynamic interaction of teeth, lips, gingiva, and facial musculature during speech and expression.10 Traditional evaluations based solely on static photographs fail to capture the dynamic essence of a smile, potentially overlooking key esthetic attributes such as smile arc, lip mobility, and buccal corridor changes during natural smiling.11 Consequently, there is a rising interest in incorporating dynamic assessments, including video recordings, into the esthetic evaluation process. Videos provide a more comprehensive representation of the smile in motion, offering insights that are often missed in static assessments.
The divergence between clinical objectivity and subjective esthetic perception has fueled interest in interdisciplinary and multi-perspective evaluations.12 Numerous studies have highlighted discrepancies between orthodontists' assessments and laypersons’ perceptions of smile attractiveness.13,14 Orthodontists, trained to notice minute dental discrepancies, often emphasize symmetry, occlusal relationships, and technical perfection. In contrast, laypersons tend to focus on broader esthetic cues such as tooth color, alignment, and the harmony between the smile and the overall facial appearance.15 Understanding these perceptual differences is essential in bridging the gap between clinical outcomes and patient satisfaction.16
In this context, our study aims to investigate the correlation between objective orthodontic treatment outcomes, as measured by the ABO-OGS, and subjective assessments of smile esthetics by both orthodontic residents and laypersons in a sample of patients with Class II skeletal malocclusion. By integrating static photographic and dynamic video-based evaluations, we seek to determine whether high OGS scores correlate with higher esthetic ratings and to identify any perceptual differences between trained professionals and individuals without dental education. Such an investigation is expected to shed light on the alignment—or lack thereof—between technical excellence and perceived beauty in orthodontic treatment, especially in cases where skeletal discrepancies present added esthetic challenges.
Furthermore, the outcomes of this study may inform future treatment planning and evaluation protocols, helping orthodontists better predict which clinical changes will translate into visible esthetic improvements in the eyes of patients and the public. With Class II malocclusion being the most prevalent among the skeletal classes, findings from this study may have wide-reaching implications, ultimately contributing to more patient-centered, esthetically oriented orthodontic care.
RATIONALE:
While objective grading systems such as the ABO Objective Grading System (OGS) help quantify treatment outcomes, they may not always align with layperson perceptions of smile esthetics. Most previous studies have focused on general orthodontic outcomes or Class I malocclusion. Given the higher prevalence and unique esthetic concerns of Class II skeletal discrepancies, a focused evaluation is warranted. Furthermore, dynamic smile analysis via video has emerged as a more representative measure of esthetics compared to static images alone.

OBJECTIVES:
Primary Objectives: To assess the correlation between ABO-OGS scores and smile esthetic ratings by orthodontists and laypersons in patients with Class II skeletal malocclusion.
Secondary Objectives: 
•	To evaluate differences in esthetic perception between orthodontic residents and laypersons.
•	To compare static (photographs) versus dynamic (video) evaluations of smile esthetics. 
•	To determine whether higher ABO-OGS scores correspond with higher perceived esthetic scores.  

OPERATIONAL DEFINITIONS:
Class II Skeletal Malocclusion:17
A malocclusion where the mandible is retruded relative to the maxilla, diagnosed using cephalometric criteria (e.g., ANB angle > 4°).
ABO-OGS (Objective Grading System):18
A standardized system developed by the American Board of Orthodontics to evaluate post-treatment dental casts and radiographs based on multiple parameters such as alignment, occlusion, and root angulation.
Static Smile Assessment:19
Evaluation of smile esthetics using standardized frontal photographs in repose and smiling.
Dynamic Smile Assessment: 
Evaluation of smile esthetics using standardized frontal video clips showing natural smile transitions.
Visual Analogue Scale (VAS): 
A 10-point scale where raters indicate their perception of smile attractiveness, with 0 being the least attractive and 10 being the most attractive.
Layperson: 
An individual with no formal training in dentistry or orthodontics.

MATERIALS AND METHODS:
Study Design: Cross-sectional observational study.
Sample Selection:
•	Inclusion Criteria:
o	Post-treatment orthodontic patients diagnosed with Class II skeletal malocclusion.
o	Aged 15–30 years.
o	No history of craniofacial syndromes or trauma.
o	Complete set of post-treatment records (casts, panoramic radiograph, photographs, and smile videos).
•	Exclusion Criteria:
o	Incomplete treatment records.
o	Poor quality images or videos.
o	Cases with orthognathic surgery.
Sample Size:
The sample size for this study was calculated based on power analysis using statistical parameters similar to those in the parent article by Kantharaju et al. (2021). Assuming a moderate expected correlation (r = 0.5) between objective (ABO-OGS) and subjective (VAS) esthetic scores, with a significance level of 5% and power of 90%, the required sample size was estimated to be approximately 38 cases. This was calculated using a standard formula for correlation studies. However, considering feasibility and alignment with similar published research, a minimum of 38 cases was selected for inclusion in this study.  
Data Collection:
1.	Clinical Records:
o	Dental casts and panoramic radiographs evaluated using ABO-OGS by calibrated orthodontic residents.
2.	Smile Assessment:
o	Standardized photographs (frontal smile and repose).
o	Standardized 5–10 second video clips of natural smile (frontal view).
3.	Evaluation Panels:
o	Group A: Orthodontic residents (n=10).
o	Group B: Laypersons (n=10).
o	All raters will score smiles using the VAS scale for both photos and videos.
Calibration and Blinding:
•	Orthodontists will be calibrated on the use of ABO-OGS.
•	All evaluators will be blinded to the patients’ identity and OGS scores.
DATA COLLECTION:
The starting time of data collection will be July 2025. Post-treatment records of    patients with Class II skeletal malocclusion, aged 15 to 30 years and treated without orthognathic surgery, will be selected from the orthodontic department archives. After obtaining informed consent, records including dental casts or digital models, panoramic radiographs, standardized extraoral photographs (frontal at rest and full smile), and frontal-view smile videos (5–10 seconds) will be collected. All data will be anonymized and assigned unique codes to ensure confidentiality. Three calibrated orthodontic residents will independently assess the dental casts and radiographs using the ABO Objective Grading System (OGS), with average scores calculated for analysis.
Smile esthetics will be subjectively evaluated by two groups: orthodontic residents and laypersons. Evaluators will rate anonymized static photographs and dynamic smile videos using a Visual Analogue Scale (VAS) ranging from 0 (least attractive) to 10 (most attractive). The order of presentation will be randomized to minimize bias, and all scores will be recorded and securely stored for statistical analysis.

DATA ANALYSIS:
•	Descriptive Statistics: Mean and standard deviation of OGS scores and VAS ratings.
•	Inferential Statistics:
o	Pearson correlation to evaluate relationships between OGS scores and VAS ratings.
o	Independent t-tests or Mann-Whitney U tests to compare orthodontists' vs. laypersons' scores.
o	Paired t-tests or Wilcoxon tests to compare static vs. dynamic smile evaluations.
o	Inter-rater reliability assessed using Intraclass Correlation Coefficient (ICC).
•	Significance set at p < 0.05.

STRENGTHS AND LIMITATIONS:
Strengths:
•	Focus on Class II malocclusion, a highly prevalent clinical condition.
•	Inclusion of dynamic smile analysis, providing a more realistic assessment of smile esthetics.
•	Use of both objective clinical grading and subjective perception from diverse evaluator groups.
Limitations:
•	Subjective nature of esthetic ratings may introduce bias despite blinding.
•	Limited generalizability due to sample being drawn from a single center.
•	Video evaluation may be influenced by lighting and recording conditions.




ETHICAL CONSIDERATIONS: 
ERC approval will be taken from university ethical review committee as the pictures and videos of patients would be taken.