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Facial Plast Surg 2022; 38(05): 468-476
DOI: 10.1055/a-1760-1422
Original Research

Multidimensionality of Patient-Reported Outcome Measures in Rhinoplasty Satisfaction

Valérie Verkest 
1   Department of Otorhinolaryngology, GZA Ziekenhuizen Campus Sint-Vincentius, Antwerp, Belgium
,
Laura Pingnet 
1   Department of Otorhinolaryngology, GZA Ziekenhuizen Campus Sint-Vincentius, Antwerp, Belgium
2   NKO, University Hospital Antwerp, Edegem, Antwerp, Belgium
,
Erik Fransen
3   Center of Statistics, University of Antwerp, StatUa, Antwerp, Belgium
,
Frank Declau
1   Department of Otorhinolaryngology, GZA Ziekenhuizen Campus Sint-Vincentius, Antwerp, Belgium
4   Department of Otorhinolaryngology, University of Antwerp Faculty of Medicine and Health Sciences, Wilrijk, Antwerp, Belgium
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Abstract

The FACE-Q rhinoplasty module (nose and nostrils), Utrecht questionnaire, and Nasal Obstruction Symptom Evaluation (NOSE) scale are validated Dutch patient-reported outcome measures (PROMs) to evaluate rhinoplasty satisfaction. The objective of this study was to analyze the dimensionality of the measured variables in these four existing questionnaires. Additionally, we investigated the ability of the PROMS to measure change. A prospective single-center study was performed in a consecutive cohort of 106 Dutch-speaking patients. Patients were invited to fill in four PROMs: FACE-Q rhinoplasty module (nose and nostrils), Utrecht questionnaire, and NOSE scale, preoperatively and 3 months postoperatively. Item quality was calculated in all four questionnaires. The ability of the questionnaires to differentiate between pre- and postoperative patients was determined with a binary logistic regression. Exploratory factor analysis was performed to determine the latent dimensions. Item quality was confirmed in all questionnaires. Backward binary logistic regression revealed that NOSE and FACE-Q nose module were the best discriminant factors pre- and postoperatively. Combination of these two questionnaires gave a specificity of 97.33% and a sensitivity of 94.52% to discriminate between pre- and postoperative cases. Exploratory factor analysis identified the presence of four dimensions: (1) cosmesis of the nose, (2) cosmesis of the nostrils, (3) nasal function, and (4) psychosocial well-being in rhinoplasty patients. Lack of factorial invariance in the preoperative phase, as compared with the postoperative phase, was detected, especially with the FACE-Q nose and to a lesser extent with the Utrecht questionnaire. The FACE-Q rhinoplasty modules (nose and nostrils), the Utrecht questionnaire, and NOSE scale measure different dimensions of rhinoplasty satisfaction and can be used complementary to each other to obtain a more holistic evaluation of rhinoplasty patients. However, the surgeon should keep in mind that lack of factorial invariance preoperative, as opposed to the postoperative phase, may influence the outcome of these questionnaires.

Keywords

patient-reported outcome measures - rhinoplasty - exploratory factor analysis - patient satisfaction


Publication History

Accepted Manuscript online:
03 February 2022

Article published online:
13 September 2022

© 2022. Thieme. All rights reserved.

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  • References

  • 1 Hackworth S. ISAPS International Survey On Aesthetic/Cosmetic Procedures Performed In 2015. <Accessed February 19, 2022> https://www.isaps.org/wp-content/uploads/2017/10/2016-ISAPS-Results-1.pdf
    PubMedGoogle Scholar
  • 2 Guillemin F, Bombardier C, Beaton D. Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J Clin Epidemiol 1993; 46 (12) 1417-1432
    CrossrefPubMedGoogle Scholar
  • 3 Barone M, Cogliandro A, Di Stefano N, Tambone V, Persichetti P. A systematic review of patient-reported outcome measures after rhinoplasty. Eur Arch Otorhinolaryngol 2017; 274 (04) 1807-1811
    CrossrefPubMedGoogle Scholar
  • 4 Ishii LE, Tollefson TT, Basura GJ. et al. Clinical practice guideline: improving nasal form and function after rhinoplasty executive summary. Otolaryngol Head Neck Surg 2017; 156 (02) 205-219
    CrossrefPubMedGoogle Scholar
  • 5 van Zijl FVWJ, Mokkink LB, Haagsma JA, Datema FR. Evaluation of measurement properties of patient-reported outcome measures after rhinoplasty: a systematic review. JAMA Facial Plast Surg 2019; 21 (02) 152-162
    CrossrefPubMedGoogle Scholar
  • 6 Kandathil CK, Saltychev M, Abdelwahab M, Spataro EA, Moubayed SP, Most SP. Minimal clinically important difference of the standardized cosmesis and health nasal outcomes survey. Aesthet Surg J 2019; 39 (08) 837-840
    CrossrefPubMedGoogle Scholar
  • 7 Mokkink LB, Terwee CB, Knol DL. et al. Protocol of the COSMIN study: COnsensus-based Standards for the selection of health Measurement INstruments. BMC Med Res Methodol 2006; 6: 2
    CrossrefPubMedGoogle Scholar
  • 8 World medical association declaration of Helsinki. https://www.wma.net/wp-content/uploads/2016/11/DoH-Oct1996.pdf . Accessed February 19, 2022
    PubMedGoogle Scholar
  • 9 Stewart MG, Witsell DL, Smith TL, Weaver EM, Yueh B, Hannley MT. Development and validation of the Nasal Obstruction Symptom Evaluation (NOSE) scale. Otolaryngol Head Neck Surg 2004; 130 (02) 157-163
    CrossrefPubMedGoogle Scholar
  • 10 Klassen AF, Cano SJ, East CA. et al. Development and psychometric evaluation of the FACE-Q scales for patients undergoing rhinoplasty. JAMA Facial Plast Surg 2016; 18 (01) 27-35
    Google Scholar
  • 11 Klassen AF, Cano SJ, Scott A, Snell L, Pusic AL. Measuring patient-reported outcomes in facial aesthetic patients: development of the FACE-Q. Facial Plast Surg 2010; 26 (04) 303-309
    Google Scholar
  • 12 Lohuis PJFM, Hakim S, Duivesteijn W, Knobbe A, Tasman AJ. Benefits of a short, practical questionnaire to measure subjective perception of nasal appearance after aesthetic rhinoplasty. Plast Reconstr Surg 2013; 132 (06) 913e-923e
    CrossrefPubMedGoogle Scholar
  • 13 Watkins MW. Exploratory factor analysis: a guide to best practice. J Black Psychol 2018; 44 (03) 219-246
    CrossrefPubMedGoogle Scholar
  • 14 Nolte E. Factorial invariance. In: Michalos AC. ed. Encyclopedia of Quality of Life and Well-Being Research. Dordrecht: Springer; 2014: 2146-2148
    Google Scholar
  • 15 Camilli G, Geis E. Stochastic approximation EM for large-scale exploratory IRT factor analysis. Stat Med 2019; 38 (21) 3997-4012
    CrossrefPubMedGoogle Scholar
  • 16 Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika 1965; 30 (02) 179-185
    CrossrefPubMedGoogle Scholar
  • 17 Cattell RB. The Scree test for the number of factors. Multivariate Behav Res 1966; 1 (02) 245-276
    CrossrefPubMedGoogle Scholar
  • 18 Norman GR, Streiner DL. Biostatistics: The Bare Essentials. 4th ed. Shelton CT: People's Medical Publishing; 2014.
    PubMed
  • 19 Browne MW, Cudeck R. Alternative ways of assessing model fit. Sociol Methods Res 1992; 21 (02) 230-258
    CrossrefPubMedGoogle Scholar
  • 20 Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling Multidisciplinary J 1999; 6 (01) 1-55
    CrossrefPubMedGoogle Scholar
  • 21 Kortekaas MF, Bartelink MEL, de Groot E. et al. The Utrecht questionnaire (U-CEP) measuring knowledge on clinical epidemiology proved to be valid. J Clin Epidemiol 2017; 82: 119-127
    CrossrefPubMedGoogle Scholar
  • 22 Lomax RESRG. A Beginner's Guide to Structural Equation Modeling. 4th edition. New York: Routledge; 2015
    Google Scholar
  • 23 Makowski D. The psycho package: an efficient and publishing-oriented workflow for psychological science. J Open Source Softw 2018; 3: 470
    CrossrefPubMedGoogle Scholar
  • 24 Gerbing DW, Hamilton JG. Viability of exploratory factor analysis as a precursor to confirmatory factor analysis. Struct Eq Model Multidisc J 1996; 3 (01) 62-72
    CrossrefPubMedGoogle Scholar