Psychometric properties, mood profile clusters, and predictive effectiveness of the Brunel Mood Scale in a Singaporean context

Psychometric properties, mood profile clusters, and predictive effectiveness of the Brunel Mood Scale in a Singaporean context

The relationship between affective states and performance has been an enduring area of interest and is well-established in sport and exercise psychology (e.g., Hanin, 1997; Beedie, Terry, & Lane, 2000). However, previous studies in this area did not always provide clear definitions of the mood or emotion construct, which plagued subsequent investigations (Lane, Beedie, & Devonport, 2011). The present research investigated the relationships between mood responses and performance, where mood is defined as “a set of feelings, ephemeral in nature, varying in intensity and duration, and usually involving more than one emotion” (Lane & Terry, 2000, p. 17). In order to assess transient mood states, there is a need to use validated and culturally-relevant psychometric tools. One such instrument is the 24-item Brunel Mood Scale (BRUMS; Terry, Lane, Lane & Keohane, 1999; Terry, Lane, & Fogarty, 2003), a derivative of the Profile of Mood States (POMS; McNair, Lorr, & Droppleman, 1971, 1992), with six mood subscales (i.e., Tension, Depression, Anger, Vigour, Fatigue, and Confusion). The BRUMS has undergone rigorous validity testing using four different samples (Terry, Lane et al., 2003) and has been shown to be a psychometrically robust inventory for assessing mood responses across a range of contexts and cultures (e.g., Terry, Potgieter, & Fogarty, 2003; Terry, Malekshahi, & Delva, 2012; Zhang, Si, Chung, Du, & Terry, 2014).

To date, the BRUMS has not yet been extensively researched in Singapore, which is a multicultural Asian society. Thus, the first aim of the present research was to establish the factorial validity of the BRUMS for use in Singapore, and to develop a set of local norms. The six-factor mood measurement model was tested on a sample of 1,444 English-speaking Singaporean participants aged from 18 to 65 years, including 954 who were involved in sport. Structural equation modelling showed a good fit of the measurement model to the data (CFI = .956, TLI =.950, RMSEA = .052). Multisample analyses supported the invariance of the measurement model in different subsamples based on gender, age group and sport participation. Concurrent measures correlated with the BRUMS subscale scores, in line with theoretical predictions. Internal consistency and test-retest reliability coefficients were acceptable, supporting the psychometric integrity of the BRUMS for use in Singapore. The second aim was to confirm if previously identified mood profile clusters (see Parsons-Smith, Terry, & Machin, 2017), namely the iceberg profile, inverse Everest profile, inverse iceberg profile, shark fin profile, submerged profile, and surface profile were also present in a Singaporean sample. A seeded k-means cluster analysis with a prescribed six-cluster solution was conducted using raw scores cluster centroids derived from Quartiroli, Parsons-Smith, Fogarty, Kuan, and Terry (2018) and the same six mood profile clusters were identified, providing evidence of the cross-cultural generalisability of these mood profiles.

With the locally validated BRUMS and local norms confirmed, the final aim was to examine the relationship between mood and performance among a group of elite pistol shooters. Shooters who performed above average were found to more consistently report a submerged mood profile pre-competition, providing initial evidence of the utility of mood profiling in pistol shooting. In summary, the establishment of the factorial and concurrent validity of the BRUMS, the cross-cultural generalisability of mood profiles in the Singaporean context, and the demonstration of the utility of mood profiling in pistol shooting set the stage for future studies to examine the antecedents, correlates, and behavioural consequences of mood responses among Singaporean samples. This includes examining the utility of mood profiling in clinical and non-clinical settings, across a range of sport, high performance, occupational and health contexts, as a tool for performance prediction, or as an indicator of mental health.