ABSTRACT
A popular approach to the simulation of multivariate, non-normal data in the social sciences is to define a multivariate normal distribution first, and then alter its lower-dimensional marginals to achieve the shape of the distribution intended by the researchers. A consequence of this process is that the correlation structure is altered, so further methods are needed to specify an intermediate correlation matrix in the multivariate normal distribution step. Most of the techniques available in the literature estimate this intermediate correlation matrix bivariately (i.e., correlation by correlation), risking the possibility of generating a non-positive definite matrix. The present article addresses this issue by offering an algorithm that estimates all elements of the intermediate correlation matrix simultaneously, through stochastic approximation. A small simulation study demonstrates the feasibility of the present method to induce the correlation structure both in simulated and empirical data.
Subject(s)
Algorithms , Humans , Monte Carlo Method , Computer SimulationABSTRACT
OBJECTIVES: Multiple health behaviour change is a viable strategy to promote health outcomes. An example is the use of running behaviour to support smoking cessation in the group-mediated Run to Quit program. On the basis that changes in running and smoking identity were related to changes in running and smoking behaviour among individuals in the Run to Quit program, the purpose of this study was to extend these findings by examining key predictors of change in both running and smoking identity. METHODS: We analyzed data collected from 450 adult individuals (70.67% female, and 92.44% white) during the program evaluation of Run to Quit from 2016 to 2018. Participants completed assessments at week 1 (baseline), week 3 (mid-program), and week 10 (follow-up) of the program. Relevant predictor variables for change in identity were identified by drawing from theory (identity theory, identity control theory, physical activity self-definition model, social identity theory) and past research regarding exercise and smoking identity. Potential predictors of changes in running and smoking identity included changes in behaviour, self-efficacy, perceptions of the social environment (task and social cohesion, descriptive norms), as well as smoking identity and running identity, respectively. Two regression models, using residualized change scores (for each variable) and relative Pratt indices, were constructed for both running and smoking identity. RESULTS: Changes in running self-efficacy, running frequency, and individual attractions to the group exercise tasks were significant and meaningful predictors of change in running identity, whereas changes in objectively measured smoking behaviour and running identity were significant and meaningful predictors of change in smoking identity. CONCLUSION: Consistent with identity theories and past research, ensuring individuals develop a sense of efficacy and enjoy group exercise tasks both represent viable strategies to enhance exercise identity. Including an exercise component within smoking cessation programs may help individuals replace their existing smoking identity with a healthier exercise identity.
Subject(s)
Running , Smoking Cessation , Adult , Female , Humans , Male , Health Promotion , Smoking , Tobacco SmokingABSTRACT
Importance: During the COVID-19 pandemic, health care workers (HCWs) reported a significant decline in their mental health. One potential health behavior intervention that has been shown to be effective for improving mental health is exercise, which may be facilitated by taking advantage of mobile application (app) technologies. Objective: To determine the extent to which a 12-week app-based exercise intervention can reduce depressive symptoms, burnout, and absenteeism in HCWs, compared with a wait list control condition. Design, Setting, and Participants: A 2-group randomized clinical trial was conducted, with participants screened from April 6 to July 4, 2022. Participants were recruited from an urban health care organization in British Columbia, Canada. Participants completed measures before randomization and every 2 weeks thereafter. Interventions: Exercise condition participants were asked to complete four 20-minute sessions per week using a suite of body weight interval training, yoga, barre, and running apps. Wait-listed control participants received the apps at the end of the trial. Main Outcomes and Measures: The primary outcome consisted of the between-group difference in depressive symptoms measured with the 10-item Center for Epidemiological Studies Depression Scale. The secondary outcomes corresponded to 3 subfacets of burnout (cynicism, emotional exhaustion, and professional efficacy) and absenteeism. Intention-to-treat analyses were completed with multilevel structural equation modeling, and Feingold effect sizes (ES) were estimated every 2 weeks. Results: A total of 288 participants (mean [SD] age, 41.0 [10.8] years; 246 [85.4%] women) were randomized to either exercise (n = 142) or wait list control (n = 146) conditions. Results revealed that ESs for depressive symptoms were in the small to medium range by trial's end (week 12, -0.41 [95% CI, -0.69 to -0.13]). Significant and consistent treatment effects were revealed for 2 facets of burnout, namely cynicism (week 12 ES, -0.33 [95% CI, -0.53 to -0.13]) and emotional exhaustion (week 12 ES, -0.39 [95% CI, -0.64 to -0.14]), as well as absenteeism (r = 0.15 [95% CI, 0.03-0.26]). Adherence to the 80 minutes per week of exercise decreased from 78 (54.9%) to 33 (23.2%) participants between weeks 2 and 12. Conclusions and Relevance: Although exercise was able to reduce depressive symptoms among HCWs, adherence was low toward the end of the trial. Optimizing adherence to exercise programming represents an important challenge to help maintain improvements in mental health among HCWs. Trial Registration: ClinicalTrials.gov Identifier: NCT05271006.
Subject(s)
Absenteeism , Depression , Adult , Female , Humans , Male , British Columbia , Burnout, Psychological , Depression/therapy , Pandemics , Middle AgedABSTRACT
BACKGROUND: A methodological review of 78 empirical articles focusing on the neurodevelopmental outcomes of at-risk infants was conducted. AIMS: To examine ways language and terminology are used to describe methods, present results, and/or state conclusions in studies published during 1994-2005, a decade reflecting major advances in neurodevelopmental research and in medical intervention. More specifically, to investigate to what extent the design of the study and the language in the results section aligned in regard to causality. METHODS: A process of search and selection of studies published in pediatric journals was conducted through Google Scholar. Criteria of inclusion and exclusion, following PRISMA, were used. Selected studies reported neurodevelopmental outcomes of infants and young children considered at-risk, and were further categorized accordingly to their study designs. Language use in regard to whether the presentation and interpretation of results may convey causal relationships between birth risk factors and neurodevelopmental outcomes was examined following two analytical steps. RESULTS: Forty out of 78 studies, (51.28 %) used causality-implying language (e.g., effect, predict, influence) notwithstanding that the study design was non-causal. CONCLUSIONS: Anticipating the next generation of neurodevelopmental-outcomes research, a framework that aims to raise awareness of the importance of language use and the impact of causality-related terms often used in longitudinal studies is proposed. The objective is to avoid ambiguities and misunderstandings around causal or non-causal connections between birth risk factors and developmental outcomes across diverse audiences, including early intervention practitioners working directly with infants and their families.
Subject(s)
Child Development , Nervous System , Child, Preschool , Humans , Infant , Nervous System/growth & development , Causality , Language , ResearchABSTRACT
OBJECTIVE: Psychological need satisfaction, from a self-determination theory (SDT) perspective, has been applied extensively to understand predictors of exercise behaviour. Dweck proposed a psychological needs framework that includes basic needs (optimal predictability, competence, acceptance), compound needs derived from combinations of basic needs (self-esteem/status, trust, control), and a superordinate compound need for self-coherence that includes identity and meaning. The purpose was to examine whether psychological needs operationalized within Dweck's model account for variance in exercise behaviour in ways that the SDT model does not. METHODS AND MEASURES: A community sample of 403 adults completed measures of demographics, psychological needs, and exercise motivation at Time 1, and self-reported moderate-to-vigorous minutes of exercise at both Times 1 and 2 four weeks later. RESULTS: Two structural equation models operationalizing Dweck's needs framework and SDT (basic needs and motivation) were examined in relation to exercise behaviour. In both models, exercise identity and integrated regulation (conceptually similar) were the most salient correlates of prospectively measured exercise behaviour, and both accounted for the relationship between competence and exercise behaviour. CONCLUSION: The results support the importance of identity in the context of exercise behaviour. Future research should investigate factors associated with adopting and maintaining an exercise identity.
ABSTRACT
BACKGROUND: Previous research suggests that there is a bidirectional relationship between incidental affect (i.e., how people feel in day-to-day life) and physical activity behavior. However, many inconsistencies exist in the body of work due to the lag interval between affect and physical activity measurements. PURPOSE: Using a novel continuous-time analysis paradigm, we examined the temporal specificity underlying the dynamic relationship between positive and negative incidental affective states and moderate-to-vigorous physical activity (MVPA). METHODS: A community sample of adults (n = 126, Mage = 27.71, 51.6% Male) completed a 14-day ambulatory assessment protocol measuring momentary positive and negative incidental affect six times a day while wearing a physical activity monitor (Fitbit). Hierarchical Bayesian continuous-time structural equation modeling was used to elucidate the underlying dynamics of the relationship between incidental affective states and MVPA. RESULTS: Based on the continuous-time cross-effects, positive and negative incidental affect predicted subsequent MVPA. Furthermore, engaging in MVPA predicted subsequent positive and negative incidental affect. Incidental affective states had a greater relative influence on predicting subsequent MVPA compared to the reciprocal relationship. Analysis of the discrete-time coefficients suggests that cross-lagged effects increase as the time interval between measurements increase, peaking at about 8 h between measurement occasions before beginning to dissipate. CONCLUSIONS: The results provide support for a recursive relationship between incidental affective states and MVPA, which is particularly strong at 7-9 hr time intervals. Future research designs should consider these medium-term dynamics, for both theory development and intervention.
Subject(s)
Exercise , Fitness Trackers , Adult , Humans , Male , Female , Bayes Theorem , Exercise/psychology , EmotionsABSTRACT
PURPOSE: Mixture item response theory (MixIRT) models can be used to uncover heterogeneity in responses to items that comprise patient-reported outcome measures (PROMs). This is accomplished by identifying relatively homogenous latent subgroups in heterogeneous populations. Misspecification of the number of latent subgroups may affect model accuracy. This study evaluated the impact of specifying too many latent subgroups on the accuracy of MixIRT models. METHODS: Monte Carlo methods were used to assess MixIRT accuracy. Simulation conditions included number of items and latent classes, class size ratio, sample size, number of non-invariant items, and magnitude of between-class difference in item parameters. Bias and mean square error in item parameters and accuracy of latent class recovery were assessed. RESULTS: When the number of latent classes was correctly specified, the average bias and MSE in model parameters decreased as the number of items and latent classes increased, but specification of too many latent classes resulted in modest decrease (i.e., < 10%) in the accuracy of latent class recovery. CONCLUSION: The accuracy of MixIRT model is largely influenced by the overspecification of the number of latent classes. Appropriate choice of goodness-of-fit measures, study design considerations, and a priori contextual understanding of the degree of sample heterogeneity can guide model selection.
Subject(s)
Models, Statistical , Quality of Life , Humans , Quality of Life/psychology , Computer Simulation , Data Collection , Patient Reported Outcome MeasuresABSTRACT
The central limit theorem (CLT) is one of the most important theorems in statistics, and it is often introduced to social sciences researchers in an introductory statistics course. However, the recent replication crisis in the social sciences prompts us to investigate just how common certain misconceptions of statistical concepts are. The main purposes of this article are to investigate the misconceptions of the CLT among social sciences researchers and to address these misconceptions by clarifying the definition and properties of the CLT in a manner that is approachable to social science researchers. As part of our article, we conducted a survey to examine the misconceptions of the CLT among graduate students and researchers in the social sciences. We found that the most common misconception of the CLT is that researchers think the CLT is about the convergence of sample data to the normal distribution. We also found that most researchers did not realize that the CLT applies to both sample means and sample sums, and that the CLT has implications for many common statistical concepts and techniques. Our article addresses these misconceptions of the CLT by explaining the preliminaries needed to understand the CLT, introducing the formal definition of the CLT, and elaborating on the implications of the CLT. We hope that through this article, researchers can obtain a more accurate and nuanced understanding of how the CLT operates as well as its role in a variety of statistical concepts and techniques. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
ABSTRACT
Physical activity behaviour displays temporal variability, and is influenced by a range of dynamic psychological processes (e.g., affect) and shaped by various co-occurring events (e.g., social/environmental factors, interpersonal dynamics). Yet, most physical activity research tends not to examine the dynamic psychological processes implicated in adopting and maintaining physical activity. Intensive longitudinal methods (ILM) represent one particularly salient means of studying the complex psychological dynamics that underlie and result from physical activity behaviour. With the increased recent interest in using intensive longitudinal data to understand specific dynamic psychological processes, the field of exercise and health psychology is well-positioned to draw from state-of-the-art measurement and statistical approaches that have been developed and operationalised in other fields of enquiry. The purpose of this review is to provide an overview of some of the fundamental dynamic measurement and modelling approaches applicable to the study of physical activity behaviour change, as well as the dynamic psychological processes that contribute to such change.
Subject(s)
Exercise , HumansABSTRACT
This two-part study examined Dweck's psychological needs model in relation to exercise-related well-being and particularly focused on the basic need for optimal predictability and compound needs for identity and meaning. In Part 1 (N = 559), using exploratory factor analysis, scores derived from items assessing optimal predictability (prediction of affect and instrumental utility in exercise) were empirically distinct from scores derived from items assessing competence, relatedness, and autonomy. In Part 2, participants from Part 1 (N = 403) completed measures of exercise-related well-being 4 weeks after baseline assessment. Prediction of affect was the most consistent predictor of subsequent exercise-related well-being. An implication of these findings is that optimal predictability (primarily prediction of affect) represents a unique experience that may be necessary for thriving in the context of exercise. Prediction of affect should be targeted in experimental designs to further understand its relationship with exercise-related well-being.
Subject(s)
Personal Autonomy , Personal Satisfaction , Exercise , Humans , Models, Psychological , Surveys and QuestionnairesABSTRACT
The current technological age has created exponential growth in the availability of technology and data in every industry, including sport. It is tempting to get caught up in the excitement of purchasing and implementing technology, but technology has a potential dark side that warrants consideration. Before investing in technology, it is imperative to consider the potential roadblocks, including its limitations and the contextual challenges that compromise implementation in a specific environment. A thoughtful approach is therefore necessary when deciding whether to implement any given technology into practice. In this article, we review the vision and pitfalls behind technology's potential in sport science and medicine applications and then present a critical decision-making framework of 4 simple questions to help practitioners decide whether to purchase and implement a given technology.
Subject(s)
Sports Medicine , Sports , Technology , Delay Discounting , Humans , Risk Assessment , Sports Medicine/methods , Sports Medicine/trends , Technology/methods , Technology/trendsABSTRACT
Simulations concerning the distributional assumptions of coefficient alpha are contradictory. To provide a more principled theoretical framework, this article relies on the Fréchet-Hoeffding bounds, in order to showcase that the distribution of the items play a role on the estimation of correlations and covariances. More specifically, these bounds restrict the theoretical correlation range [-1, 1] such that certain correlation structures may be unfeasible. The direct implication of this result is that coefficient alpha is bounded above depending on the shape of the distributions. A general form of the Fréchet-Hoeffding bounds is derived for discrete random variables. R code and a user-friendly shiny web application are also provided so that researchers can calculate the bounds on their data.
ABSTRACT
This study introduces a novel differential item functioning (DIF) method based on propensity score matching that tackles two challenges in analyzing performance assessment data, that is, continuous task scores and lack of a reliable internal variable as a proxy for ability or aptitude. The proposed DIF method consists of two main stages. First, propensity score matching is used to eliminate preexisting group differences before the test, ideally creating equivalent groups as in a randomized experimental study. Then, linear mixed effects models are adopted to perform DIF analysis based on the matched data set. We demonstrate this propensity DIF method using a high-stakes functional English language proficiency test. DIF due to education was investigated in the writing component, which consists of two continuously scored performance-based tasks. Although the proposed method is demonstrated in the context of language testing, it can be applied to other types of performance assessments.
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BACKGROUND: To examine the extent to which group-based exercise programs, informed by self-categorisation theory, result in improvements in psychological flourishing and reductions in age- and gender-related stigma consciousness among older adults. METHODS: In the study, older adults (N = 485, ≥ 65 years) were randomised to similar age same gender (SASG), similar age mixed gender (SAMG), or "standard" mixed age mixed gender (MAMG) group-based exercise programs. Flourishing and stigma consciousness were assessed on six occasions during the 24-week intervention and represented secondary trial outcomes. Multilevel growth models examined the effects of the interventions on flourishing and stigma consciousness over time. RESULTS: Participants in the SASG and SAMG conditions demonstrated, on average, higher levels of flourishing, relative to the MAMG condition, over the course of the 24 weeks (p < .05). Additionally, participants demonstrated lower levels of age- and gender-related stigma consciousness in both the SASG and SAMG conditions relative to the MAMG condition (p < .05). No time by group interaction effects were observed for either flourishing or stigma consciousness. CONCLUSIONS: The results provide some support for the utility of group exercise programs, informed by self-categorisation theory, to enhance psychological flourishing and reduce stigma consciousness among older adults.
Subject(s)
Ageism/psychology , Aging/psychology , Exercise Therapy/psychology , Group Processes , Self Concept , Sexism/psychology , Social Stigma , Aged , Aged, 80 and over , Female , Humans , Male , Psychological Theory , Treatment OutcomeABSTRACT
Chalmers recently published a critique of the use of ordinal α proposed in Zumbo et al. as a measure of test reliability in certain research settings. In this response, we take up the task of refuting Chalmers' critique. We identify three broad misconceptions that characterize Chalmers' criticisms: (1) confusing assumptions with consequences of mathematical models, and confusing both with definitions, (2) confusion about the definitions and relevance of Stevens' scales of measurement, and (3) a failure to recognize that a measurement for a true quantity is a choice, not an absolute. On dissection of these misconceptions, we argue that Chalmers' critique of ordinal α is unfounded.
ABSTRACT
Background: The 3rd Regional Comparative and Explanatory Study reports, analyses and compares academic results in mathematics, sciences, and reading for 15 Latin American countries. Validity is the foundation of a testing procedure, and the process of validation is important to the overall success of educational assessment as a whole. This methodological study deals specifically with an ecological point of view which includes and situates the person, process, context, and time of the testing situation. These descriptions indicate specific events showing how and what variables at the individual, school, or country level can give a deep understanding of the response process. The aims were to investigate ecological explanations of differential item functioning. Method: The study analysed the science test given in 2013 to 6th grade students and the data pool consisted of 12,657 students from 2,609 schools and 15 countries. A progressive inclusion of the variance distribution in different Bernoulli logistic regression models was carried out. Results: The analyses showed the presence of differential item functioning in 32% of the science items. Conclusions: The main source of differential item functioning was related to the human development level of the participating countries
Antecedentes: el tercer Estudio Regional Comparativo y Explicativo informa, analiza y compara los resultados académicos en matemáticas, ciencias y lectura de 15 países latinoamericanos. La validez es el fundamento del procedimiento de prueba y el proceso de validación es clave para el éxito de la evaluación educativa en general. Este estudio metodológico se enfoca desde un punto de vista ecológico que sitúa a la persona, el proceso, el contexto y el tiempo donde se desarrolla la prueba. Estas descripciones señalan eventos específicos cómo y qué variables a nivel individual, escuela o país pueden dar un entendimiento profundo del proceso de respuesta. El objetivo fue investigar el funcionamiento diferencial del ítem desde un marco ecológico. Método: se analizó la prueba de ciencias aplicada en 2013 a los alumnos de 6º grado, los datos abarcan a 12.657 alumnos, 2.609 escuelas y 15 países. Se realizó una inclusión progresiva de niveles de distribución de la varianza en diferentes modelos de regresión logística Bernoulli. Resultados: los análisis mostraron la presencia de funcionamiento diferencial del ítem en el 32% de la prueba de ciencias. Conclusión: la principal fuente de funcionamiento diferencial del ítem se ve asociado al nivel de desarrollo humano de los países participantes
Subject(s)
Humans , Male , Female , Child , Educational Measurement/statistics & numerical data , Linear Models , SchoolsABSTRACT
BACKGROUND: The 3rd Regional Comparative and Explanatory Study reports, analyses and compares academic results in mathematics, sciences, and reading for 15 Latin American countries. Validity is the foundation of a testing procedure, and the process of validation is important to the overall success of educational assessment as a whole. This methodological study deals specifically with an ecological point of view which includes and situates the person, process, context, and time of the testing situation. These descriptions indicate specific events showing how and what variables at the individual, school, or country level can give a deep understanding of the response process. The aims were to investigate ecological explanations of differential item functioning. METHOD: The study analysed the science test given in 2013 to 6th grade students and the data pool consisted of 12,657 students from 2,609 schools and 15 countries. A progressive inclusion of the variance distribution in different Bernoulli logistic regression models was carried out. RESULTS: The analyses showed the presence of differential item functioning in 32% of the science items. CONCLUSIONS: The main source of differential item functioning was related to the human development level of the participating countries.
Subject(s)
Educational Measurement/statistics & numerical data , Child , Female , Humans , Linear Models , Male , SchoolsSubject(s)
Athletes , Research Design/standards , Self Report , Sports Medicine/standards , Humans , Reproducibility of ResultsABSTRACT
OBJECTIVES: To systematically identify and qualitatively review the statistical approaches used in prospective cohort studies of team sports that reported intensive longitudinal data (ILD) (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Since longitudinal research can be improved by aligning the (1) theoretical model, (2) temporal design and (3) statistical approach, we reviewed the statistical approaches used in these studies to evaluate how closely they aligned these three components. DESIGN: Methodological review. METHODS: After finding 6 systematic reviews and 1 consensus statement in our systematic search, we extracted 34 original prospective cohort studies of team sports that reported ILD (>20 observations per athlete) and examined the relationship between athletic workloads and injuries. Using Professor Linda Collins' three-part framework of aligning the theoretical model, temporal design and statistical approach, we qualitatively assessed how well the statistical approaches aligned with the intensive longitudinal nature of the data, and with the underlying theoretical model. Finally, we discussed the implications of each statistical approach and provide recommendations for future research. RESULTS: Statistical methods such as correlations, t-tests and simple linear/logistic regression were commonly used. However, these methods did not adequately address the (1) themes of theoretical models underlying workloads and injury, nor the (2) temporal design challenges (ILD). Although time-to-event analyses (eg, Cox proportional hazards and frailty models) and multilevel modelling are better-suited for ILD, these were used in fewer than a 10% of the studies (n=3). CONCLUSIONS: Rapidly accelerating availability of ILD is the norm in many fields of healthcare delivery and thus health research. These data present an opportunity to better address research questions, especially when appropriate statistical analyses are chosen.