Construct/Factor Analytic
A principal components analysis with oblique (direct oblimin) rotation was reported by Matthews et al.
(1999) . Some 767 participants completed the scale follo wing performance of one of several tasks. Some 517
of these participants also completed a pre-task versio n. Horn’s parallel analysis was used to determine the
number of factors extracted. This study identified 10 dimensions, with a single motivation dimension.
As u b s e q u e n ts t u d y( Matthews, Campbell & Falconer 2001 ) differentiated two motivation dimensions related
to intrinsic and achievement motivation. Matthews et al. (2002) conducted a second-order factor analysis,
using the Matthews et al. (1999) data, and the same factor analytic methodology and extracted three factors
labeled: Task Engagement, Distress, and Worry. Facto r structure was similar in pre- and post-task data, and
in an analysis of change scores. Everett’s (1983) factor-score method was used to show that factor solutions
were similar across different data sets. Task Engagement was defined primarily be Energetic Arousal,
Motivation and Concentration, Distress by Tense Arousal, low Hedonic Tone, and low Confidence /C0Control,
and Worry by the remaining cognitive scales. Matthews et al. (2002) suggested the DSSQ state factors might
be understood as relational constructs ( Lazarus, 1999 ) ,d e f i n i n gt h ep e r s o n ’ si m m e d i a t em o d eo fa d a p t a t i o nt o
task demands.
Criterion/Predictive
Two lines of evidence support the predictive validity of the DSSQ. First, the state variables correlate with the
appraisal and coping variables specified by Lazarus (1999) ; indeed, appraisal and coping explain a substantial
part of the variance in state change from pre- to post-task ( Matthews et al., 2013 ). Second, states correlate signifi-
cantly with objective performance measures. For example, Task Engagement is reliably associated with superior
vigilance and performance on other demanding attentional tasks ( Matthews et al., 2010; Matthews & Zeidner,
2012), whereas Distress is negatively associated with working memory ( Matthews & Campbell, 2010 ). The
Cognitive Interference scales of the DSSQ (components of Worry) have been used to investigate performance def-
icits associated with mind wandering ( Smallwood & Schooler, 2006 ).Fairclough and Venables (2006) found that a
battery of psychophysiological measures explained up to 53% of the variance in Task Engagement and up to 42%
in Distress.
Location
Matthews, G., Campbell, S.E., Falconer, S. et al. (2002). Fundamental dimensions of subjective state in perfor-
mance settings: Task engagement, distress and worry. Emotion, 2 , 315/C0340.
Results and Comments
The DSSQ is designed for use in performance environments. It has been shown to be appropriately sensitive
to a range of stress factors manipulated in experimental studies, including cognitive demands, evaluative and
environmental stressors, and the fatigue associated with prolonged work ( Matthews et al., 2013 ). It is of use in
understanding the dynamic interplay between the person and task demands, specifically in relation to task
demand and stressor effects on state, and the impact of state change on information-processing and performance.
The scale may also be used in applied contexts that involve cognitive challenge, including work performance
(Matthews et al., 2002 ), vehicle operation ( Neubauer, Matthews, Langheim, & Saxby 2012 ), and clinical psychol-
ogy ( Matthews et al., 1999 ).
DSSQ SAMPLE ITEMS
Section 1. Mood (see UMACL above)
Section 2. Motivation
Please answer some questions about your attitude to the task you have just done . Rate your agreement with the
following statements by circling one of the following answers:
Extremely 54; Very much 53; Somewhat 52; A little bit 51; Not at all 50
1.The content of the task was interesting 01234
2.The only reason to do the task is to get an external reward (e.g. payment) 01234218 8. MEASURES OF AFFECT DIMENSIONS
II. EMOTIONAL DISPOSITIONS