Evidence map›Paper›PMID 39930866›Full record

ArticleAesthetic surgery journal2025

Patient Factors That Impact FACE-Q Aesthetics Outcomes: An Exploratory Cross-sectional Regression Analysis.

Lucas Gallo, Isabella Churchill, Patrick Kim, Charlene Rae, Sophocles H Voineskos, Achilles Thoma, Andrea L Pusic, Stefan J Cano, Anne F Klassen

Abstract read
In one paragraph

Article in Aesthetic surgery journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Isabella ChurchillORCID 0000-0002-4101-0542
Sophocles H Voineskos
Andrea L Pusic
Stefan J Cano

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe FACE-Q Aesthetics is a validated tool for assessing patient-reported outcomes related to surgical and nonsurgical facial aesthetic treatments. Recognizing patient-specific variables that may influence FACE-Q scores is essential to control for potential confounders in research.

objectivesThis study aimed to identify factors that predict FACE-Q Aesthetics scale scores.

methodsA cross-sectional survey was conducted among an international cohort of participants recruited through the Prolific platform. Participants aged 20 years or older, who had undergone noninvasive facial aesthetic procedures within the past year, were included. Demographic and clinical information was collected, and univariable and multivariable linear regression analyses were employed to assess predictors of FACE-Q Face Overall, Psychological, and Social scale scores.

resultsA total of 1259 participants were analyzed, with an average age of 42.6 years (±11.9). The mean scores were 52.4 (±18.3) for the Face Overall scale, 56.5 (±23.7) for the Psychological scale, and 62.7 (±24.0) for the Social scale. Several factors were significantly associated (P < .05) with higher scores, including lower BMI, African American ethnicity, male gender, Fitzpatrick skin Type V, residence in the United States, financial stability, and residual effects of previous aesthetic treatments. Younger participants were more likely to report higher Face Overall scores (P < .05).

conclusionsThis study identified several patient characteristics that predict Face Overall, Psychological, and Social scale scores. These findings offer valuable insights into how patient-specific factors influence outcomes following facial aesthetic procedures and underscore the need to account for these variables in future research using the FACE-Q Aesthetics tool. LEVEL OF EVIDENCE: 3:

Indexed as

Cosmetic TechniquesEstheticsPatient Reported Outcome MeasuresAdultAgedCross-Sectional StudiesFaceFemaleHumansMaleMiddle AgedPatient SatisfactionYoung Adult

Identifiers

PMID39930866
PMCPMC12080882

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.