Cory Beaumont, Adam Ibrahim, Kelley Strohacker, FACSM. University of Tennessee, Knoxville, Knoxville, TN.

Because readiness-to-exercise is a multidimensional concept, it is important to determine which factor is most important for guiding person-specific adjustments to the exercise workload (i.e., ‘autoregulation’). Adapting exercise volume and intensity to match an individual’s current condition may promote long-term exercise adherence by reducing unfavorable exercise experiences. To date, the structural features of multivariate, readiness-related items have not been examined using integral (i.e., pre-exercise) data. PURPOSE: Determine the dimensionality of readiness-to-exercise in a pre-resistance exercise context. METHODS: Adults (N=189, 62.4% women, 33±12 years, 87.8% Caucasian, 97.4% performing resistance exercise ≥ 2x/wk, 56.7% reporting this frequency ≥ 1 year), completed an anonymous survey that contained 51 items obtained from validated instruments measuring constructs previously determined to underlie readiness-to-exercise. Respondents indicated the degree to which they experienced each item using “right now” ratings on a 6-pt Likert Scale (1=definitely not, 6=extremely). Basic demographic information and typical exercise behaviors were also provided. Data suitability was assessed using Kaiser-Meyer-Olkin (KMO) and Bartlett’s Test of Sphericity. Factors were retained if eigenvalues ≥ 1. A principal axis factor analysis (promax rotation) was then conducted to assess factor structure. RESULTS: The raw data were suitable for factor analysis (KMO = 0.89, Bartlett’s Test of Sphericity <.001). Eleven factors were retained which explained 59% of the variance in the dataset. Based on item loading, the first three factors were interpreted as ‘Activation’ (tired, drowsy, wide awake; 29.1%), ‘Tension’ (uneasy, nervous/on edge; 7.4%), and ‘Calmness’ (relaxed, composed, content; 4.7%). The remaining eight factors each explained <3% of the model variance. CONCLUSIONS: When multivariate data from a pre-exercise context are mathematically modeled, feelings relating to activation (energy vs. fatigue) converge as the most important factor (i.e., explaining the most variance). While pre-exercise activation states have been associated with experiential aspects of exercise from a nomothetic perspective, it would also be useful to investigate if this structure and subsequent associations with target dependent variables can be replicated at the idiographic level to refine person-specific exercise modifications.

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