Skip to main content
Top
Gepubliceerd in: Journal of Psychopathology and Behavioral Assessment 1/2020

10-04-2019

A Bifactor Model of the Straightforward Attentional Control Scale

Auteurs: Matt R. Judah, Kevin G. Saulnier, Nathan M. Hager, Nicholas P. Allan

Gepubliceerd in: Journal of Psychopathology and Behavioral Assessment | Uitgave 1/2020

Log in om toegang te krijgen
share
DELEN

Deel dit onderdeel of sectie (kopieer de link)

  • Optie A:
    Klik op de rechtermuisknop op de link en selecteer de optie “linkadres kopiëren”
  • Optie B:
    Deel de link per e-mail

Abstract

Prior studies suggest that the Attentional Control Scale (ACS) consists of two correlated factors. These models do not include a general factor, though this is assumed often in theory and practice. Using an adult North American sample collected through Amazon Mechanical Turk (N = 419), we examined a revised version of the ACS with positive keying of all items (Straightforward Attentional Control Scale; ACS-S) to avoid the potential of a factor produced by mixing positively and negatively keyed items. Exploratory factor analysis using a bifactor approach was used to examine the structure of the ACS-S, which consisted of a general factor and a nuisance variance factor. There was mixed evidence of good fit for the full 20-item version of the ACS, but fit was good for a reduced 12-item version of the ACS-S. The full and reduced version were highly correlated (r = .98). Exploratory structural equation modeling suggested that the general factor of the ACS-S was negatively related to depression and both anxious arousal, as reflected by panic symptoms, and anxious apprehension, as reflected by worry. The findings suggest that perceived attentional control is uniquely related to depression and both dimensions of anxiety. ACS-S Short scores were tested as a moderator of the association between anxious apprehension and anxious arousal. The association between these anxiety dimensions was weaker at higher levels of perceived attentional control. Our findings suggest that the ACS-S is best represented as a single dimension of beliefs about attentional control which can be scored by totaling the items and that the ACS-S uniquely related to the internalizing symptoms we assessed. The findings also contribute to the understanding of how anxiety dimensions are influenced by perceived attentional control.
Literatuur
go back to reference Bardeen, J. R., & Fergus, T. A. (2016). Emotional distress intolerance, experiential avoidance, and anxiety sensiivity: The buffering effect of attentional control on associations with posttraumatic stress symptoms. Journal of Psychopathology and Behavioral Assessment, 38, 320–329. https://doi.org/10.1007/s10862-015-9522-x.CrossRef Bardeen, J. R., & Fergus, T. A. (2016). Emotional distress intolerance, experiential avoidance, and anxiety sensiivity: The buffering effect of attentional control on associations with posttraumatic stress symptoms. Journal of Psychopathology and Behavioral Assessment, 38, 320–329. https://​doi.​org/​10.​1007/​s10862-015-9522-x.CrossRef
go back to reference Bentler, P. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107(2), 238–246. https://doi.org/res Bentler, P. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107(2), 238–246. https://​doi.​org/​res
go back to reference Hayes, A. F. (2017a). Introduction to mediation, moderation, and conditional Process analysis: A regression-based approach (2nd ed.). New York, NY: The Guilford Press. Hayes, A. F. (2017a). Introduction to mediation, moderation, and conditional Process analysis: A regression-based approach (2nd ed.). New York, NY: The Guilford Press.
go back to reference Hayes, A. F. (2017b). The PROCESS macro for SPSS and SAS (version 3.2). Hayes, A. F. (2017b). The PROCESS macro for SPSS and SAS (version 3.2).
go back to reference Johnson, P. O., & Neyman, J. (1936). Tests of certain linear hypotheses and their application to some educational problems. Statistical Research Memoirs, 1, 57–93. Johnson, P. O., & Neyman, J. (1936). Tests of certain linear hypotheses and their application to some educational problems. Statistical Research Memoirs, 1, 57–93.
go back to reference Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141–151.CrossRef Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141–151.CrossRef
go back to reference Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus User’s Guide (Seventh ed.). CA: Los Angeles. Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus User’s Guide (Seventh ed.). CA: Los Angeles.
go back to reference Newman, M. G., Holmes, M., Zuellig, A. R., Kachin, K. E., & Behar, E. (2006). The reliability and validity of the Panic Disorder Self-Report: A new diagnostic screening measure of panic disorder. Psychological Assessment, 18, 49-61. Newman, M. G., Holmes, M., Zuellig, A. R., Kachin, K. E., & Behar, E. (2006). The reliability and validity of the Panic Disorder Self-Report: A new diagnostic screening measure of panic disorder. Psychological Assessment, 18, 49-61.
go back to reference Norman, D. A., & Shallice, T. (1986). Attention to action. In R. J. Davidson, G. E. Schwartz, & D. Shapiro (Eds.), Consciousness and Self-Regulation. Springer; Boston (pp. 1-18). Norman, D. A., & Shallice, T. (1986). Attention to action. In R. J. Davidson, G. E. Schwartz, & D. Shapiro (Eds.), Consciousness and Self-Regulation. Springer; Boston (pp. 1-18).
go back to reference Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on Amazon mechanical Turk. Judgment and Decision making, 5. Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on Amazon mechanical Turk. Judgment and Decision making, 5.
go back to reference Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31, 437–448.CrossRef Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31, 437–448.CrossRef
go back to reference Putman, P., Verkuil, B., Arias-Garcia, E., Pantazi, I., & van Schie, C. (2014). EEG theta/beta ratio as a potential biomarker for attentional control and resilience against deleterious effects of stress on attention. Cognitive, Affective, & Behavioral Neuroscience, 14, 782–791. https://doi.org/10.3758/s13415-013-0238-7.CrossRef Putman, P., Verkuil, B., Arias-Garcia, E., Pantazi, I., & van Schie, C. (2014). EEG theta/beta ratio as a potential biomarker for attentional control and resilience against deleterious effects of stress on attention. Cognitive, Affective, & Behavioral Neuroscience, 14, 782–791. https://​doi.​org/​10.​3758/​s13415-013-0238-7.CrossRef
go back to reference Quigley, L., Wright, C. A., Dobson, K. S., & Sears, C. R. (2017). Measuring attentional control ability or beliefs? Evaluation of the factor structure and convergent validity of the attentional control scale. Journal of Psychopathology and Behavioral Assessment, 39, 742–754. https://doi.org/10.1007/s10862-017-9617-7.CrossRef Quigley, L., Wright, C. A., Dobson, K. S., & Sears, C. R. (2017). Measuring attentional control ability or beliefs? Evaluation of the factor structure and convergent validity of the attentional control scale. Journal of Psychopathology and Behavioral Assessment, 39, 742–754. https://​doi.​org/​10.​1007/​s10862-017-9617-7.CrossRef
go back to reference Raykov, T. (2012). Scale construction and development using structural equation modeling. In R.H. Holyle (Ed.),Handbook of structural equation modeling. New York: Guilford Press. (pp. 472-492). Raykov, T. (2012). Scale construction and development using structural equation modeling. In R.H. Holyle (Ed.),Handbook of structural equation modeling. New York: Guilford Press. (pp. 472-492).
go back to reference Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Boston, MA: Pearson/Allyn & Bacon. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Boston, MA: Pearson/Allyn & Bacon.
go back to reference Williams, P. G., Rau, H. K., Suchy, Y., Thorgusen, S. R., & Smith, T. W. (2017). On the validity of self-report assessment of cognitive abilities: Attentional control scale associations with cognitive performance, emotional adjustment, and personality. Psychological Assessment, 29, 519–530. https://doi.org/10.1037/pas0000361.CrossRefPubMed Williams, P. G., Rau, H. K., Suchy, Y., Thorgusen, S. R., & Smith, T. W. (2017). On the validity of self-report assessment of cognitive abilities: Attentional control scale associations with cognitive performance, emotional adjustment, and personality. Psychological Assessment, 29, 519–530. https://​doi.​org/​10.​1037/​pas0000361.CrossRefPubMed
Metagegevens
Titel
A Bifactor Model of the Straightforward Attentional Control Scale
Auteurs
Matt R. Judah
Kevin G. Saulnier
Nathan M. Hager
Nicholas P. Allan
Publicatiedatum
10-04-2019
Uitgeverij
Springer US
Gepubliceerd in
Journal of Psychopathology and Behavioral Assessment / Uitgave 1/2020
Print ISSN: 0882-2689
Elektronisch ISSN: 1573-3505
DOI
https://doi.org/10.1007/s10862-019-09737-y

Andere artikelen Uitgave 1/2020

Journal of Psychopathology and Behavioral Assessment 1/2020 Naar de uitgave