1. bookVolume 7 (2020): Issue 2 (December 2020)
Journal Details
License
Format
Journal
eISSN
2354-0036
First Published
16 Apr 2015
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2 times per year
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English
access type Open Access

Giving the Art Greater weight in Art Psychology: RizbA, a Questionnaire for Formal Picture Analysis

Published Online: 26 Jan 2021
Page range: 373 - 410
Received: 09 Sep 2020
Accepted: 22 Nov 2020
Journal Details
License
Format
Journal
eISSN
2354-0036
First Published
16 Apr 2015
Publication timeframe
2 times per year
Languages
English
Abstract

In empirical art psychology and creativity research most studies focus on the psychological correlates of art. Only few go beyond treating artworks as categorical data (e.g. abstract vs. representational) and consider artworks in detail. In part this is due to the lack of reliable quantitative measurements. The rating instrument for two-dimensional pictorial works (RizbA) makes a difference to current research designs. The current study validates the questionnaire on a representative sample of contemporary visual art, consisting of 318 images depicting works by artists from different cultural areas dated to the 21st century. In a randomized test-retest design, the pictorial material was rated by 506 (T1) and 238 (T2) art experts using RizbA. Statistical quality criteria, such as item difficulty, capacity of differentiation, test-retest reliability, and intraclass correlation were calculated. Principal component analysis (PCA) and indices of factor similarity were computed. The overall test’s capacity for differentiation yields partial eta-squared of .31 (T1) and .40 (T2). Test-retest reliability is .86. PCA reveals an eight-factor solution, which is largely consistent across both measurement points. Tucker’s coefficient of congruence ranges between |.71| and |1.00|. Intraclass correlation coefficients are .86 (T1) and .73 (T2). This study indicates generalizability of the questionnaire to contemporary artworks. Although a conclusion on the factors’ structure cannot be drawn yet, results are very promising. As the first reliable quantitative tool for formal picture analysis, RizbA allows more detailedexamination of visual art and its psychological correlates. This broadens research methodology by giving art greater weight in art psychology and creativity research.

Keywords

Baltes-Götz, B. (2013). Behandlung fehlender Werte in SPSS und Amos [Dealing with missing values in SPSS and Amos]. Universität Trier.Search in Google Scholar

Belting, H., Dilly, H., Kemp, W., Sauerländer, W., & Warnke, M. (1996). Kunstgeschichte: Eine Einführung [Art history: An introduction]. In H. Belting, H. Dilly, W. Kemp, W. Sauerländer, & M. Warnke (Eds.) (6th ed.). Reimer.Search in Google Scholar

Brown, J. D. (2009). Principal components analysis and exploratory factor analysis: Definitions, differences, and choices. Statistics, 13(1).Search in Google Scholar

Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81.10.1037/h0046016Search in Google Scholar

Cattaneo, M. (1994). Addressing culture and values in the training of art therapists. Art Therapy, 11(3), 184–186. https://doi.org/10.1080/07421656.1994.1075908110.1080/07421656.1994.10759081Search in Google Scholar

Chan, W., Ho, R. M., Leung, K., Chan, D. K.-S., & Yung, Y.-F. (1999). An alternative method for evaluating congruence coefficients with Procrustes rotation: A bootstrap procedure. Psychological Methods, 4(4), 378.10.1037/1082-989X.4.4.378Search in Google Scholar

Chatterjee, A., Widick, P., Sternschein, R., Smith, W. B., & Bromberger, B. (2010). The assessment of art attributes. Empirical Studies of the Arts, 28(2), 207–222. https://doi.org/10.2190/EM.28.2.f10.2190/EM.28.2.fSearch in Google Scholar

Cliff, N. (1966). Orthogonal rotation to congruence. Psychometrika, 31(1), 33–42.10.1007/BF02289455Search in Google Scholar

Cohen, B. M., & Mills, A. (2015). The Diagnostic Drawing Series (DDS) at thirty: Art therapy assessment and research. In D. Gussak & R. M Rosal, The Wiley handbook of art therapy (p. 558–568). Wiley-Blackwell.10.1002/9781118306543.ch53Search in Google Scholar

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155.10.1037/0033-2909.112.1.155Search in Google Scholar

Colver, M. C., & El-Alayli, A. (2016). Getting aesthetic chills from music: The connection between openness to experience and frisson. Psychology of Music, 44(3), 413–427. https://doi.org/10.1177/030573561557235810.1177/0305735615572358Search in Google Scholar

Commare, L., Rosenberg, R., & Leder, H. (2018). More than the sum of its parts: Perceiving complexity in painting. Psychology of Aesthetics, Creativity, and the Arts, 12(4), 380. https://doi.org/10.1037/aca000018610.1037/aca0000186Search in Google Scholar

Coster, J. D. (2012). Converting effect sizes. http://www.stat-help.com/spreadsheets.htmlSearch in Google Scholar

Cropley, A. (1997). Creativity: A bundle of paradoxes. Gifted and Talented International, 12(1), 8–14.10.1080/15332276.1997.11672859Search in Google Scholar

Epstein, C. (2019). Bildlicher Ausdruck von Depression: Erprobung des Ratinginstruments RizbA an Bildstichproben aus dem klinischen Kunsttherapiesetting [Pictorial expression of depression: Testing the ratinginstrument RizbA on image samples from a clinical art therapy setting]. Witten/Herdecke University. Zenodo database. https://doi.org/10.5281/zenodo.3365921Search in Google Scholar

Fechner, G. T. (1876). Vorschule der Ästhetik [Preschool of aesthetics] (Vol. 1). Breitkopf & Härtel.Search in Google Scholar

Fetz, K., Vogt, H., Ostermann, T., Schmitz, A., & Schulz-Quach, C. (2018). Evaluation of the palliative symptom burden score (PSBS) in a specialised palliative care unit of a university medical centre-a longitudinal study. BMC palliative care, 17(1), 92. https://doi.org/10.1186/s12904-018-0342-010.1186/s12904-018-0342-0Search in Google Scholar

Fraiberger, S. P., Sinatra, R., Resch, M., Riedl, C., & Barabási, A.-L. (2018). Quantifying reputation and success in art. Science. https://doi.org/10.1126/science.aau722410.1126/science.aau7224Search in Google Scholar

Gantt, L. (2016). The Formal Elements Art Therapy Scale (FEATS). In D. Gussak & M. Rosal (Eds.), The Wiley handbook of art therapy (pp. 569–578). Wiley-Blackwell.Search in Google Scholar

GLAM Wiki. (2020). GLAM Outreach Wiki: Galleries, Libraries, Archives, Museums. https://outreach.wikimedia.org/wiki/GLAMSearch in Google Scholar

Gridley, M. C. (2006). Concrete and abstract thinking styles and art preferences in a sample of serious art collectors. Psychological Reports, 98(3), 853–857.10.2466/pr0.98.3.853-857Search in Google Scholar

Gridley, M. C. (2013). Preference for abstract art according to thinking styles and personality. North American Journal of Psychology, 15(3), 463–481.Search in Google Scholar

Guadagnoli, E., & Velicer, W. F. (1988). Relation of sample size to the stability of component patterns. Psychological Bulletin, 103(2), 265–275.10.1037/0033-2909.103.2.265Search in Google Scholar

Hager, M., Hagemann, D., Danner, D., & Schankin, A. (2012). Assessing aesthetic appreciation of visual artworks: The construction of the Art Reception Survey (ARS). Psychology of Aesthetics, Creativity, and the Arts, 6(4), 320–333. https://doi.org/10.1037/a002877610.1037/a0028776Search in Google Scholar

Haller, C. S., & Courvoisier, D. S. (2010). Personality and thinking style in different creative domains. Psychology of Aesthetics, Creativity, and the Arts, 4(3), 149–160. https://doi.org/10.1037/a001708410.1037/a0017084Search in Google Scholar

Hanich, J., Wagner, V., Shah, M., Jacobsen, T., & Menninghaus, W. (2014). Why we like to watch sad films. The pleasure of being moved in aesthetic experiences. Psychology of Aesthetics, Creativity, and the Arts, 8(2), 130–143. https://doi.org/10.1037/a003569010.1037/a0035690Search in Google Scholar

Hayn-Leichsenring, G. U., Kenett, Y. N., Schulz, K., & Chatterjee, A. (2020). Abstract art paintings, global image properties, and verbal descriptions: An empirical and computational investigation. Acta Psychologica, 202, 102936. https://doi.org/10.1016/j.actpsy.2019.10293610.1016/j.actpsy.2019.102936Search in Google Scholar

Ishizu, T., & Zeki, S. (2011). Toward a brain-based theory of beauty. PloS One, 6(7), https://doi.org/10.1371/journal.pone.0021852.10.1371/journal.pone.0021852Search in Google Scholar

Janßen, B. (2018). Erprobung des Ratinginstruments für zweidimensionale bildnerische Arbeiten (RizbA): Ansatz zu einer möglichen Untersuchung des bildnerischen Ausdrucks von Schmerz in gemalten Bildern von Menschen mit chronischer Schmerzsymptomatik [Testing the rating instrument for two-dimensional pictorial works (RizbA): Pilot study for investigating pictorial expression in pictures painted by people with chronic pain symptoms]. HKS – University of Applied Sciences and Arts, Ottersberg. Zenodo database. https://doi.org/10.5281/zenodo.3407808Search in Google Scholar

Jerusalem, J. L. L. (2020, February 20). Rizba für alle: Überprüfung der Einsatzmöglich-keiten eines Ratinginstruments für zweidimensionale bildnerische Arbeiten (RizbA) und des neu dazu erstellten Manuals [Rizba for everyone: Review of the possible uses of a rating instrument for two-dimensional pictorial works (RizbA) and the newly created manual]. Witten/Herdecke University, Witten. Open Science Framework. https://doi.org/10.17605/OSF.IO/FVJZMSearch in Google Scholar

Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163. https://doi.org/10.1016/j.jcm.2016.02.01210.1016/j.jcm.2016.02.012Search in Google Scholar

LeBreton, J. M., & Senter, J. L. (2008). Answers to 20 questions about interrater reliability and interrater agreement. Organizational Research Methods, 11(4), 815–852. https://doi.org/0.1177/109442810629664210.1177/1094428106296642Search in Google Scholar

Leder, H., Belke, B., Oeberst, A., & Augustin, D. (2004). A model of aesthetic appreciation and aesthetic judgments. British Journal of Psychology, 95(4), 489–508. https://doi.org/10.1348/000712604236981110.1348/0007126042369811Search in Google Scholar

Leder, H., Gerger, G., Dressler, S. G., & Schabmann, A. (2012). How art is appreciated. Psychology of Aesthetics, Creativity, and the Arts, 6(1), 2–10. https://doi.org/10.1037/a002639610.1037/a0026396Search in Google Scholar

Leder, H., Tinio, P. P., Brieber, D., Kröner, T., Jacobsen, T., & Rosenberg, R. (2018). Symmetry Is Not a Universal Law of Beauty. Empirical Studies of the Arts, 37(1), 104–114. https://doi.org/10.1177/027623741877794110.1177/0276237418777941Search in Google Scholar

Lee, K., & Ashton, M. C. (2009). The HEXACO Personality Inventory - Revised: A measure of the six major dimensions of personality. http://hexaco.orgSearch in Google Scholar

Leiner, D. (2018). SoSci Survey. https://www.soscisurvey.deSearch in Google Scholar

Levine, T. R., & Hullett, C. R. (2002). Eta squared, partial eta squared, and misreporting of effect size in communication research. Human Communication Research, 28(4), 612–625.10.1111/j.1468-2958.2002.tb00828.xSearch in Google Scholar

Lin, T. H. (2010). A comparison of multiple imputation with EM algorithm and MCMC method for quality of life missing data. Quality & Quantity, 44(2), 277–287. https://doi.org/10.1007/s11135-008-9196-510.1007/s11135-008-9196-5Search in Google Scholar

Lorenzo-Seva, U., & Ten Berge, J. M. (2006). Tucker’s congruence coefficient as a meaningful index of factor similarity. Methodology, 2(2), 57–64. https://doi.org/10.1027/1614-1881.2.2.57Search in Google Scholar

Maclagan, D. (1999). Getting the feel: Problems of research in the fields of psychological aesthetics and art therapy - The struggle with incarnation & the negative sublime. The Arts in Psychotherapy, 5(26), 303–311.10.1016/S0197-4556(99)00027-1Search in Google Scholar

Marengo, L., Fazekas, G., & Tombros, A. (2017). The Interaction of Casual Users with Digital Collections of Visual Art. An Exploratory Study of the WikiArt Website. International Conference on Human-Computer Interaction. Springer.Search in Google Scholar

Martindale, C. (2007). Recent trends in the psychological study of aesthetics, creativity, and the arts. Empirical Studies of the Arts, 25(2), 121–141. https://doi.org/10.2190/B637-1041-2635-16NN10.2190/B637-1041-2635-16NNSearch in Google Scholar

McCrae, R. R., Zonderman, A. B., Costa Jr, P. T., Bond, M. H., & Paunonen, S. V. (1996). Evaluating replicability of factors in the Revised NEO Personality Inventory: Confirmatory factor analysis versus Procrustes rotation. Journal of Personality and Social Psychology, 70(3), 552.10.1037/0022-3514.70.3.552Search in Google Scholar

McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1(1), 30. https://doi.org/1082–989X/96/S3.0010.1037/1082-989X.1.1.30Search in Google Scholar

Menninghaus, W., Bohrn, I. C., Altmann, U., Lubrich, O., & Jacobs, A. M. (2014). Sounds funny? Humor effects of phonological and prosodic figures of speech. Psychology of Aesthetics, Creativity, and the Arts, 8(1), 71. https://doi.org/10.1037/a003530910.1037/a0035309Search in Google Scholar

Menninghaus, W., Wagner, V., Wassiliwizky, E., Schindler, I., Hanich, J., Jacobsen, T., & Koelsch, S. (2018). What are aesthetic emotions? Psychological Review, 126(2), 171–195. https://doi.org/10.1037/rev000013510.1037/rev0000135Search in Google Scholar

Mersch, D. (2019). Ästhetisches Denken: Kunst als Theoria [Aesthetic thinking: Art as theoria]. In D. Mersch, S. Sasse, & S. Zanetti (Eds.), Ästhetische Theorie [Aesthetic theory] (pp. 241–259). Diaphanes.Search in Google Scholar

Mills, A. (2003). The diagnostic drawing series. In C. Malchiodi (Ed.), The handbook of art therapy (p. 401–209).Search in Google Scholar

Mohammad, S. M., & Kiritchenko, S. (2018). Wikiart emotions: An annotated dataset of emotions evoked by art. Paper presented at the Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018).Search in Google Scholar

Moosbrugger, H., & Kelava, A. (2007). Testtheorie und Fragebogenkonstruktion [Test theory and questionnaire design] (2nd ed.). Springer.Search in Google Scholar

Moshagen, M., Hilbig, B. E., & Zettler, I. (2014). Faktorenstruktur, psychometrische Eigenschaften und Messinvarianz der deutschsprachigen Version des 60-item HEXA-CO Persönlichkeitsinventars [Factor structure, psychometric characteristics and measurement invariance of the German version of the 60-item HEXACO personality inventory]. Diagnostica. https://doi.org/10.1026/0012-1924/a00011210.1026/0012-1924/a000112Search in Google Scholar

Mosquera, G. (1992). The Marco Polo syndrome: Some problems around art and Eurocentrism. Third Text, 6(21), 35–41. https://doi.org/10.1080/0952882920857638210.1080/09528829208576382Search in Google Scholar

Nadal, M., Munar, E., Marty, G., & Cela-Conde, C. J. (2010). Visual complexity and beauty appreciation: Explaining the divergence of results. Empirical Studies of the Arts, 28(2), 173–191. https://doi.org/10.2190/EM.28.2.d10.2190/EM.28.2.dSearch in Google Scholar

O’Connor, B. P. (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, & Computers, 32(3), 396–402.10.3758/BF03200807Search in Google Scholar

O’Connor, B. P. (2018). SPSS, SAS, and MATLAB programs for determining the number of components and factors using parallel analysis and velicer’s MAP test. https://people.ok.ubc.ca/brioconn/nfactors/nfactors.htmlSearch in Google Scholar

Osborne, J. W., & Costello, A. B. (2004). Sample size and subject to item ratio in principal components analysis. Practical Assessment, Research & Evaluation, 9(11), 8.Search in Google Scholar

Osborne, J. W., & Costello, A. B. (2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan-Pacific Management Review, 12(2), 131–146.Search in Google Scholar

Pelowski, M., Markey, P. S., Forster, M., Gerger, G., & Leder, H. (2017). Move me, astonish me… delight my eyes and brain: The Vienna integrated model of top-down and bottom-up processes in art perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates. Physics of Life Reviews, 21, 80–125. https://doi.org/10.1016/j.plrev.2017.02.00310.1016/j.plrev.2017.02.003Search in Google Scholar

Penn Center for Neuroaesthetics. (2019). Resources. https://neuroaesthetics.med.upenn.edu/research.html-resourcesSearch in Google Scholar

Pigott, T. D. (2001). A review of methods for missing data. Educational Research and Evaluation, 7(4), 353–383.10.1076/edre.7.4.353.8937Search in Google Scholar

Raykov, T., & Little, T. D. (1999). A note on procrustean rotation in exploratory factor analysis: A computer intensive approach to goodness-of-fit evaluation. Educational and Psychological Measurement, 59(1), 47–57.10.1177/0013164499591004Search in Google Scholar

Rubin, D. B. (1996). Multiple imputation after 18+ years. Journal of the American Statistical Association, 91(434), 473–489.10.1080/01621459.1996.10476908Search in Google Scholar

Schafer, J. L., & Olsen, M. K. (1998). Multiple imputation for multivariate missing-data problems: A data analyst’s perspective. Multivariate Behavioral Research, 33(4), 545–571.10.1207/s15327906mbr3304_5Search in Google Scholar

Schoch, K. (2014, February 25). Ratinginstrument für zweidimensionale bildnerische Arbeiten: Methodische Arbeit zur Entwicklung eines psychologischen Tests zur Erfassung von bildnerischem Ausdruck [Rating instrument for two-dimensional pictorial works: Methodical development of a psychological test measuring pictorial expression]. University of Mannheim. Zenodo database. http://doi.org/10.5281/zenodo.1479744Search in Google Scholar

Schoch, K., Gruber, H., & Ostermann, T. (2017). Measuring art: Methodical development of a quantitative rating instrument measuring pictorial expression (RizbA). The Arts in Psychotherapy, 55, 73–79. https://doi.org/10.1016/j.aip.2017.04.01410.1016/j.aip.2017.04.014Search in Google Scholar

Schoch, K., & Ostermann, T. (under review). Psychometrics of art: Validation of RizbA, a quantitative rating instrument for pictorial expression.Search in Google Scholar

Schönemann, P. H. (1966). A generalized solution of the orthogonal procrustes problem. Psychometrika, 31(1), 1–10.10.1007/BF02289451Search in Google Scholar

Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420.10.1037/0033-2909.86.2.420Search in Google Scholar

Silvia, P. J. (2007). An introduction to multilevel modeling for research on the psychology of art and creativity. Empirical Studies of the Arts, 25(1), 1–20.10.2190/6780-361T-3J83-04L1Search in Google Scholar

Silvia, P. J., & Nusbaum, E. C. (2011). On personality and piloerection: Individual differences in aesthetic chills and other unusual aesthetic experiences. Psychology of Aesthetics, Creativity, and the Arts, 5(3), 208. https://doi.org/0.1037/a002191410.1037/a0021914Search in Google Scholar

Simon, H., & Verstegen, U. (2004). prometheus: Das verteilte digitale Bildarchiv für Forschung und Lehre. Neuartige Werkzeuge zur Bereitstellung von verteiltem Content für Wissenschaft und Forschung [prometheus: Digital image database for research and education. New tools for providing shared content for science and research]. Historical Social Research/Historische Sozialforschung, 247–257.Search in Google Scholar

Specht, S. M. (2007). Successive contrast effects for judgments of abstraction in artwork following minimal pre-exposure. Empirical Studies of the Arts, 25(1), 63–70.10.2190/W717-88W2-2233-12H3Search in Google Scholar

Streb, J. H. (1984). Thoughts on phenomenology, education, and art. Studies in Art Education, 25(3), 159–166. https://doi.org/10.1080/00393541.1984.11650370Search in Google Scholar

Stuhler-Bauer, A., & Elbing, U. (2003). Die phänomenologische Bilderfassung: Ein kunst-therapeutisches Instrument. [The phenomenological picture survey: An art therapeutic instrument]. Musik-, Tanz- und Kunsttherapie, 14, 32–46. https://doi.org/10.1026/0933-6885.14.1.32Search in Google Scholar

Suhr, D. D. (2005). Principal Component Analysis vs. Exploratory Factor Analysis. Proceedings of the thirtieth annual SAS® users group international conference, 203, 30.Search in Google Scholar

Suhr, D. D. (2006). Exploratory or confirmatory factor analysis? Statistics and Data Analysis, 31.Search in Google Scholar

Sullivan, P., & McCarthy, J. (2009). An experiential account of the psychology of art. Psychology of Aesthetics, Creativity, and the Arts, 3(3), 181. https://doi.org/10.1037/a001429210.1037/a0014292Search in Google Scholar

Tinio, P. P. (2013). From artistic creation to aesthetic reception: The mirror model of art. Psychology of Aesthetics, Creativity, and the Arts, 7(3), 265–275. https://doi.org/10.1037/a003087210.1037/a0030872Search in Google Scholar

Tröndle, M., & Tschacher, W. (2012). The physiology of phenomenology: The effects of artworks. Empirical Studies of the Arts, 30(1), 75–113.10.2190/EM.30.1.gSearch in Google Scholar

Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10.10.1007/BF02291170Search in Google Scholar

Walter, S., Eliasziw, M., & Donner, A. (1998). Sample size and optimal designs for reliability studies. Statistics in Medicine, 17(1), 101–110.10.1002/(SICI)1097-0258(19980115)17:1<101::AID-SIM727>3.0.CO;2-ESearch in Google Scholar

Wassiliwizky, E., Wagner, V., Jacobsen, T., & Menninghaus, W. (2015). Artelicited chills indicate states of being moved. Psychology of Aesthetics, Creativity, and the Arts, 9(4), 405. https://doi.org/10.1037/aca000002310.1037/aca0000023Search in Google Scholar

Wünsch, K. L. (2016). Comparing two groups’ factor structures: Pearson r and the coefficient of congruence. http://core.ecu.edu/psyc/wuenschk/MV/FA/FactorStructure-TwoGroups.docxSearch in Google Scholar

Wundt, W. M. (1874). Grundzüge der physiologischen Psychologie [Characteristics of physiological psychology] (Vol. 1). Engelman.Search in Google Scholar

Zaidel, D. W., Nadal, M., Flexas, A., & Munar, E. (2013). An evolutionary approach to art and aesthetic experience. Psychology of Aesthetics, Creativity, and the Arts, 7(1), 100. https://doi.org/10.1037/a002879710.1037/a0028797Search in Google Scholar

Zumbo, B. D., Sireci, S. G., & Hambleton, R. K. (2003). Revisiting exploratory methods for construct comparability: Is there something to be gained from the ways of old. Paper presented at the Annual Meeting of the National Council for Measurement in Education (NCME), Chicago, Illinois.Search in Google Scholar

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