Children differ in their sensitivity to positive and negative environmental influences, which can be measured with the Highly Sensitive Child (HSC) scale. The present study introduces the HSC-21, an adaptation of the original 12 item scale with new items and factor structure that are meant to be more informative than the original ones. The psychometric properties of the HSC-21 were investigated in 1,088 children across Belgium and the Netherlands, including child and mother reports. Results showed evidence for (a) bifactor model with a general sensitivity factor and two specific factors (i.e., Ease of Excitation–Low Sensory Threshold and Aesthetic Sensitivity); (b) (partial) measurement invariance across gender, developmental stage, country, and informants; (c) moderate child–mother agreement; (d) good reliability; (e) normally distributed item scores; and (f) meaningful associations with personality and temperament across both samples. No evidence was found for HSC-21 as a moderator in the relationship between parenting and problem behaviors.
AchenbachT. M. (1991). Manual for the child behavior checklist/4-18 and 1991 profile. University of Vermont.
2.
ArbuckleJ. L. (1996). Full information estimation in the presence of incomplete data. In MarcoulidesG. A.SchumackerR. E. (Eds.), Advanced structural equation modeling: Issues and Techniques (pp. 243-277). Lawrence Erlbaum.
3.
AronE. N.AronA. (1997). Sensory-processing sensitivity and its relation to introversion and emotionality. Journal of Personality and Social Psychology, 73(2), 345-368. https://doi.org/10.1037/0022-3514.73.2.345
BoatengG. O.NeilandsT. B.FrongilloE. A.Melgar-QuiñonezH. R.YoungS. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in public health, 6, 149-149. https://doi.org/10.3389/fpubh.2018.00149
BrownT. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). Guilford Press.
10.
BurnhamK. P.AndersonD. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods & Research, 33(2), 261-304. https://doi.org/10.1177/0049124104268644
11.
ByrneB. M.ShavelsonR. J.MuthénB. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105(3), 456-466. https://doi.org/10.1037/0033-2909.105.3.45
12.
CapaldiD. M.RothbartM. K. (1992). Development and validation of an early adolescent temperament measure. The Journal of Early Adolescence, 12(2), 153-173. https://doi.org/10.1177/0272431692012002002
13.
CaspiA.SugdenK.MoffittT. E.TaylorA.CraigI. W.HarringtonH.McClayJ.MillJ.MartinJ.BraithwaiteA.PoultonR. (2003). Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene. Science, 301(5631), 386-389. https://doi.org/10.1126/science.1083968
14.
ChenF. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464-504. https://doi.org/10.1080/10705510701301834
15.
CohenJ. (1988). Statistical power analysis for the behavioral sciences. Routledge Academic.
16.
DunnT. J.BaguleyT.BrunsdenV. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399-412. https://doi.org/10.1111/bjop.12046
17.
El-SheikhM.KellerP. S.ErathS. A. (2007). Marital conflict and risk for child maladjustment over time: Skin conductance level reactivity as a vulnerability factor. Journal of Abnormal Child Psychology, 35(5), 715-727. https://doi.org/10.1007/s10802-007-9127-2
18.
EvansD. E.RothbartM. K. (2007). Developing a model for adult temperament. Journal of Research in Personality, 41(4), 868-888. https://doi.org/10.1016/j.jrp.2006.11.002
19.
EvansD. E.RothbartM. K. (2008). Temperamental sensitivity: Two constructs or one?Personality and Individual Differences, 44(1), 108-118. https://doi.org/10.1016/j.paid.2007.07.016
20.
GomesC. M. A.AlmeidaL. S.NúñezJ. C. (2017). Rationale and applicability of exploratory structural equation modeling (ESEM) in psychoeducational contexts. Psicothema, 29(3), 396-401. https://doi.org/10.7334/psicothema2016.369
GrevenC. U.LionettiF.BoothC.AronE. N.FoxE.SchendanH. E.PluessM.BruiningH.AcevedoB.BijttebierP.HombergJ. (2019). Sensory processing sensitivity in the context of environmental sensitivity: A critical review and development of research agenda. Neuroscience & Biobehavioral Reviews, 98(March), 287-305. https://doi.org/10.1016/j.neubiorev.2019.01.009
23.
ImmekusJ. C.SnyderK.RalstonP. A. (2019). Multidimensional item response theory for factor structure assessment in educational psychology research. Frontiers in Education, 4, Article 45. https://doi.org/https://doi.org/10.3389/feduc.2019.00045
24.
KlineR. B. (2005). Principles and practice of structural equation modeling (2nd ed.). Guilford Press.
25.
LaidraK.AllikJ.HarroM.MerenäkkL.HarroJ. (2006). Agreement among adolescents, parents, and teachers on adolescent personality. Assessment, 13(2), 187-196. https://doi.org/10.1177/1073191106287125
26.
LearyM. R. (2008). Introduction to behavioral research methods (5th ed.). Pearson Education.
27.
LionettiF.AronA.AronE. N.BurnsG. L.JagiellowiczJ.PluessM. (2018). Dandelions, tulips and orchids: Evidence for the existence of low-sensitive, medium-sensitive and high-sensitive individuals. Translational Psychiatry, 8(1), Article 24. https://doi.org/10.1038/s41398-017-0090-6
28.
LionettiF.AronE. N.AronA.KleinD. N.PluessM. (2019). Observer-rated environmental sensitivity moderates children’s response to parenting quality in early childhood. Developmental Psychology, 55(1), 2389-2402. https://doi.org/https://doi.org/10.1037/dev0000795
29.
LittleR. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198-1202. https://doi.org/10.1080/01621459.1988.10478722
30.
Lorenzo-SevaU.TimmermanM. E.KiersH. A. (2011). The Hull method for selecting the number of common factors. Multivariate Behavioral Research, 46(2), 340-364. https://doi.org/10.1080/00273171.2011.564527
31.
MarshH. W.MorinA. J. S.ParkerP. D.KaurG. (2014). Exploratory structural equation modeling: An integration of the best features of exploratory and confirmatory factor analysis. Annual Review of Clinical Psychology, 10(1), 85-110. https://doi.org/10.1146/annurev-clinpsy-032813-153700
32.
McCraeR. R.CostaP. T. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52(1), 81-90. https://doi.org/10.1037/0022-3514.52.1.81
33.
McDonaldR. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum.
34.
MenardS. (1995). Applied logistic regression analysis (Series: Quantitative applications in the social sciences). Sage.
35.
MervieldeI.De FruytF.De ClercqB. (2009). HiPIC: Hiërarchische Persoonlijkheidsvragenlijst voor Kinderen [HiPIC: Hierarchical Personality Questionnaire for children]. Hogrefe.
36.
NocentiniA.MenesiniE.PluessM. (2018). The personality trait of environmental sensitivity predicts children’s positive response to school-based antibullying intervention. Clinical Psychological Science, 6(6), 848-859. https://doi.org/10.1177/2167702618782194
37.
OsteenP. (2010). An introduction to using multidimensional item response theory to assess latent factor structures. Journal of the Society for Social Work and Research, 1(2), 66-82. https://doi.org/10.5243/jsswr.2010.6
38.
PluessM. (2015). Individual differences in environmental sensitivity. Child Development Perspectives, 9(3), 138-143. https://doi.org/10.1111/cdep.12120
39.
PluessM.AssaryE.LionettiF.LesterK. J.KrapohlE.AronE.AronA. (2018). Environmental sensitivity in children: Development of the Highly Sensitive Child scale and identification of sensitivity groups. Developmental Psychology, 54(1), 51-70. https://doi.org/10.1037/dev0000406
40.
PluessM.BoniwellI. (2015). Sensory-processing sensitivity predicts treatment response to a school-based depression prevention program: Evidence of vantage sensitivity. Personality and Individual Differences, 82(August), 40-45. https://doi.org/10.1016/j.paid.2015.03.011
41.
RafteryA. E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111-163. https://doi.org/10.2307/271063
42.
ReckaseM. D. (2009). Multidimensional item response theory. Springer.
43.
RevelleW.ZinbargR. E. (2008). Coefficients alpha, beta, omega, and the glb: Comments on Sijtsma. Psychometrika, 74(1), Article 145. https://doi.org/10.1007/s11336-008-9102-z
44.
RigdonE. E. (1996). CFI versus RMSEA: A comparison of two fit indexes for structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 3(4), 369-379. https://doi.org/10.1080/10705519609540052
45.
RodriguezA.ReiseS. P.HavilandM. G. (2015). Evaluating bifactor models: Calculating and interpreting statistical indices. Psychological Methods, 21(2), 137-150. https://doi.org/10.1037/met0000045
46.
SatorraA.BentlerP. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In EyeA. V.CloggC. C. (Eds.), Latent variables analysis: Applications for developmental research (pp. 399-419). Sage.
47.
SchmittN.GolubovichJ.LeongF. T. (2011). Impact of measurement invariance on construct correlations, mean differences, and relations with external correlates: An illustrative example using Big Five and RIASEC measures. Assessment, 18(4), 412-427. https://doi.org/10.1177/1073191110373223
48.
SellbomM.TellegenA. (2019). Factor analysis in psychological assessment research: Common pitfalls and recommendations. Psychological Assessment, 31(12), 1428-1441. https://doi.org/http://dx.doi.org/10.1037/pas0000623
49.
SharknessJ.DeAngeloL. (2011). Measuring student involvement: A comparison of classical test theory and item response theory in the construction of scales from student surveys. Research in Higher Education, 52(5), 480-507. https://doi.org/10.1007/s11162-010-9202-3
50.
SijtsmaK. (2008). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), Article 107. https://doi.org/10.1007/s11336-008-9101-0
51.
SlagtM.DubasJ. S.van AkenM. A. G.EllisB. J.DekovicM. (2018). Sensory processing sensitivity as a marker of differential susceptibility to parenting. Developmental Psychology, 54(3), 543-558. https://doi.org/10.1037/dev0000431
52.
SmolewskaK. A.McCabeS. B.WoodyE. Z. (2006). A psychometric evaluation of the Highly Sensitive Person Scale: The components of sensory-processing sensitivity and their relation to the BIS/BAS and “Big Five.”Personality and Individual Differences, 40(6), 1269-1279. https://doi.org/10.1016/j.paid.2005.09.022
53.
SoenensB.VansteenkisteM.LuyckxK.GoossensL. (2006). Parenting and adolescent problem behavior: An integrated model with adolescent self-disclosure and perceived parental knowledge as intervening variables. Developmental Psychology, 42(2), 305-318. https://doi.org/10.1037/0012-1649.42.2.305
54.
SteinmetzH. (2013). Analyzing observed composite differences across groups: Is partial measurement invariance enough?Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(1), 1-12. https://doi.org/10.1027/1614-2241/a000049
55.
Van de SchootR.LugtigP.HoxJ. (2012). A checklist for testing measurement invariance. European Journal of Developmental Psychology, 9(4), 486-492. https://doi.org/10.1080/17405629.2012.686740
56.
Van LeeuwenK.VermulstA.KroesG.De MeyerR.VeermanJ. W. (2018). Handleiding VSOG. Verkorte Schaal voor Ouderlijk Gedrag [Brief Scale of parental behavior]. Praktikon BV.
57.
WeynS.Van LeeuwenK.PluessM.LionettiF.GrevenC. U.GoossensL.ColpinH.Van Den NoortgateW.VerschuerenK.BastinM.Van HoofE.De FruytF.BijttebierP. (2019). Psychometric properties of the Highly Sensitive Child scale across developmental stage, gender, and country. Current Psychology. Advance online publication. https://doi.org/10.1007/s12144-019-00254-5
58.
ZinbargR. E.RevelleW.YovelI.LiW. (2005). Cronbach’s α, Revelle’s β, and Mcdonald’s ωH: Their relations with each other and two alternative conceptualizations of reliability. Psychometrika, 70(1), 123-133. https://doi.org/10.1007/s11336-003-0974-7
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
