A Review of Controlling Motivational Strategies from a Self-Determination Theory Perspective: Implications for Sports Coaches

The aim of this paper is to present a preliminary taxonomy of six controlling strategies, primarily based on the parental and educational literatures, which we believe are employed by coaches in sport contexts. Research in the sport and physical education literature has primarily focused on coaches’ autonomysupportive behaviours. Surprisingly, there has been very little research on the use of controlling strategies. A brief overview of the research which delineates each proposed strategy is presented, as are examples of the potential manifestation of the behaviours associated with each strategy in the context of sports coaching. In line with self-determination theory (Deci & Ryan, 1985; Ryan & Deci, 2002), we propose that coach behaviours employed to pressure or control athletes have the potential to thwart athletes’ feelings of autonomy, competence,and relatedness, which, in turn, undermine athletes’ self-determined motivation and contribute to the development of controlled motives. When athletes feel pressured to behave in a certain way, a variety of negative consequences are expected to ensue which are to the detriment of the athletes’ well-being. The purpose of this paper is to raise awareness and interest in the darker side of sport participation and to offer suggestions for future research in this area

Gammaretrovirus-mediated correction of SCID-X1 is associated with skewed vector integration site distribution in vivo

We treated 10 children with X-linked SCID (SCID-X1) using gammaretrovirus-mediated gene transfer. Those with sufficient follow-up were found to have recovered substantial immunity in the absence of any serious adverse events up to 5 years after treatment. To determine the influence of vector integration on lymphoid reconstitution, we compared retroviral integration sites (RISs) from peripheral blood CD3(+) T lymphocytes of 5 patients taken between 9 and 30 months after transplantation with transduced CD34(+) progenitor cells derived from 1 further patient and I healthy donor. Integration occurred preferentially in gene regions on either side of transcription start sites, was clustered, and correlated with the expression level in CD34(+) progenitors during transduction. In contrast to those in CD34(+) cells, RISs recovered from engrafted CD3(+)T cells were significantly overrepresented within or near genes encoding proteins with kinase or transferase activity or involved in phosphorus metabolism. Although gross patterns of gene expression were unchanged in transduced cells, the divergence of RIS target frequency between transduced progenitor cells and post-thymic T lymphocytes indicates that vector integration influences cell survival, engraftment, or proliferation

Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone

Effect of priming interval on reactogenicity, peak immunological response, and waning after homologous and heterologous COVID-19 vaccine schedules: exploratory analyses of Com-COV, a randomised control trial

Background: Priming COVID-19 vaccine schedules have been deployed at variable intervals globally, which might influence immune persistence and the relative importance of third-dose booster programmes. Here, we report exploratory analyses from the Com-COV trial, assessing the effect of 4-week versus 12-week priming intervals on reactogenicity and the persistence of immune response up to 6 months after homologous and heterologous priming schedules using the vaccines BNT162b2 (tozinameran, Pfizer/BioNTech) and ChAdOx1 nCoV-19 (AstraZeneca). Methods: Com-COV was a participant-masked, randomised immunogenicity trial. For these exploratory analyses, we used the trial's general cohort, in which adults aged 50 years or older were randomly assigned to four homologous and four heterologous vaccine schedules using BNT162b2 and ChAdOx1 nCoV-19 with 4-week or 12-week priming intervals (eight groups in total). Immunogenicity analyses were done on the intention-to-treat (ITT) population, comprising participants with no evidence of SARS-CoV-2 infection at baseline or for the trial duration, to assess the effect of priming interval on humoral and cellular immune response 28 days and 6 months post-second dose, in addition to the effects on reactogenicity and safety. The Com-COV trial is registered with the ISRCTN registry, 69254139 (EudraCT 2020–005085–33). Findings: Between Feb 11 and 26, 2021, 730 participants were randomly assigned in the general cohort, with 77–89 per group in the ITT analysis. At 28 days and 6 months post-second dose, the geometric mean concentration of anti-SARS-CoV-2 spike IgG was significantly higher in the 12-week interval groups than in the 4-week groups for homologous schedules. In heterologous schedule groups, we observed a significant difference between intervals only for the BNT162b2–ChAdOx1 nCoV-19 group at 28 days. Pseudotyped virus neutralisation titres were significantly higher in all 12-week interval groups versus 4-week groups, 28 days post-second dose, with geometric mean ratios of 1·4 (95% CI 1·1–1·8) for homologous BNT162b2, 1·5 (1·2–1·9) for ChAdOx1 nCoV-19–BNT162b2, 1·6 (1·3–2·1) for BNT162b2–ChAdOx1 nCoV-19, and 2·4 (1·7–3·2) for homologous ChAdOx1 nCoV-19. At 6 months post-second dose, anti-spike IgG geometric mean concentrations fell to 0·17–0·24 of the 28-day post-second dose value across all eight study groups, with only homologous BNT162b2 showing a slightly slower decay for the 12-week versus 4-week interval in the adjusted analysis. The rank order of schedules by humoral response was unaffected by interval, with homologous BNT162b2 remaining the most immunogenic by antibody response. T-cell responses were reduced in all 12-week priming intervals compared with their 4-week counterparts. 12-week schedules for homologous BNT162b2 and ChAdOx1 nCoV-19–BNT162b2 were up to 80% less reactogenic than 4-week schedules. Interpretation: These data support flexibility in priming interval in all studied COVID-19 vaccine schedules. Longer priming intervals might result in lower reactogenicity in schedules with BNT162b2 as a second dose and higher humoral immunogenicity in homologous schedules, but overall lower T-cell responses across all schedules. Future vaccines using these novel platforms might benefit from schedules with long intervals. Funding: UK Vaccine Taskforce and National Institute for Health and Care Research