Psychological characteristics of developing excellence in elite youth football players in English professional academies.

This mixed-longitudinal prospective study examined the development of psychological characteristics of developing excellence in relation to the career progression of elite youth football players. In a 20-month period, 111 academy football players aged 11-16 completed the Psychological Characteristics of Developing Excellence Questionnaire (PCDEQ) on 1-5 occasions. This combination of single and repeated assessments resulted in a mixed-longitudinal sample of 226 completed PCDEQs. Players were then prospectively tracked, and their scholarship status assessed at follow-up, at age U17. Multilevel modelling revealed that coping with performance and developmental pressures scores increased with age, and that Category 1-2 academy scholars (4.35 ± 0.61) scored higher than Category 3-4 academy scholars (3.99 ± 0.67) and non-scholars (4.02 ± 0.78) (p < .05). Evaluating performances and working on weaknesses scores increased with age for Category 1-2 academy scholars (U12-U14 vs. U15-U16 = 5.16 ± 0.48 vs. 5.38 ± 0.45), compared to non-scholars (U12-U14 vs. U15-U16 = 5.11 ± 0.59 vs. 5.03 ± 0.71) (p < .05). Imagery use during practice and competition scores decreased with age (U12-U14 vs. U15-U16 = 4.45 ± 0.66 vs. 4.29 ± 0.70) (p < .05). A blend of PCDEs may facilitate optimal career progression. Football academies should develop players' PCDEs, with a particular focus on developing their coping skills and their ability to realistically evaluate performances and work on weaknesses.

Improving the psychological evaluation of exercise referral: Psychometric properties of the Exercise Referral Quality of Life Scale.

There is a growing need to assess the psychological outcomes of exercise referral and the National Institute of Health and Care Excellence has called for the routine assessment of life-quality. However, a quality of life scale specific to the requirements of exercise referral is currently unavailable. Therefore, the aim of this study was to produce a quality of life measure for this purpose. The Exercise Referral Quality of Life Scale is a 22-item measure comprising three domains: mental and physical health, injury pain and illness and physical activity facilitators. Exploratory factor analysis determined the initial factor structure and was subsequently confirmed by confirmatory factor analysis. Additional scale properties were also assessed. The scale contributes to the global need for improved consistent psychological outcome assessment of exercise referral.

A randomized trial to determine the impact on compliance of a psychophysical peripheral cue based on the Elaboration Likelihood Model.

OBJECTIVE: Non-compliance in clinical studies is a significant issue, but causes remain unclear. Utilizing the Elaboration Likelihood Model of persuasion, this study assessed the psychophysical peripheral cue 'Interactive Voice Response System (IVRS) call frequency' on compliance. METHODS: 71 participants were randomized to once daily (OD), twice daily (BID) or three times daily (TID) call schedules over two weeks. Participants completed 30-item cognitive function tests at each call. Compliance was defined as proportion of expected calls within a narrow window (+/- 30 min around scheduled time), and within a relaxed window (-30 min to +4 h). Data were analyzed by ANOVA and pairwise comparisons adjusted by the Bonferroni correction. RESULTS: There was a relationship between call frequency and compliance. Bonferroni adjusted pairwise comparisons showed significantly higher compliance (p=0.03) for the BID (51.0%) than TID (30.3%) for the narrow window; for the extended window, compliance was higher (p=0.04) with OD (59.5%), than TID (38.4%). CONCLUSION: The IVRS psychophysical peripheral cue call frequency supported the ELM as a route to persuasion. The results also support OD strategy for optimal compliance. Models suggest specific indicators to enhance compliance with medication dosing and electronic patient diaries to improve health outcomes and data integrity respectively.