SAGITTAL PLANE RESISTANCE TORQUE IN ANKLE BRACES

Ligaments of the ankle joint complex are among the most frequently damaged structures during sports and physical activity (Eils et al., 2002). One common intervention used to prevent ankle ligament injury is the application of lace-up style ankle braces. These braces, usually made of non stretch nylon materials, increase the mechanical stability at the ankle joint by restricting the allowable range of motion thereby limiting strain on joint ligaments. Ankle braces are primarily designed to restrict motion in the frontal plane to limit ankle inversion and eversion without impeding the plantar-dorsi flexion (PF) motion (Eils et al., 2002). However, studies examining the effect of bracing on ankle motion during drop jumping have found a significant reduction in sagittal plane ankle motion while braced (DiStefano et al., 2008). Previous studies have examined isolated ankle range of motion restriction around the PF axis with different brace types (e.g. Eils et al 2002), but these studies were not able to distinguish the resistance torque due to the brace alone. The purpose of the present study was to measure the passive mechanical resistance torque around the ankle PF axis generated by a range of commercially available ankle braces while moving through the sagittal plane

Initial validation of the Brief Assessment of Service Satisfaction in Persons with an Intellectual Disability (BASSPID)

Individuals with an intellectual disability often require intensive services to promote their social participation to the fullest extent. As such, measuring satisfaction with these services appears essential to enhance the quality of life of individuals with an intellectual disability and to improve service delivery within agencies. Thus, the purpose of the study was to conduct an initial validation of the Brief Assessment of Service Satisfaction in Persons with an Intellectual Disability (BASSPID), a 15-item questionnaire designed to assess service satisfaction. To examine the structure, reliability, and validity of the BASSPID, we interviewed 98 individuals with an intellectual disability and 23 parents. Overall, the BASSPID contained one scale, which had strong content and convergent validity as well as items easily understandable for individuals with an intellectual disability. Furthermore, the questionnaire had good internal consistency and adequate test-retest reliability. However, parents generally overestimated the perceived satisfaction of their child. The study suggests that the BASSPID may be useful to assess the satisfaction of individuals with an intellectual disability, but more research is needed to examine its potential impact on improving service quality

Using differential reinforcement of high rates of behavior to improve work productivity : a replication and extension

Background: Due to deficits in adaptive and cognitive functioning, productivity may pose challenges for individuals with intellectual disability in the workplace.Method: Using a changing‐criterion embedded in a multiple baseline across partici‐pants design, we examined the effects of differential reinforcement of high rates of behaviour (DRH) on the rate of data entry (i.e., productivity) in four adults with intel‐lectual disability.Results: Although the DRH procedure increased the rate of correct data entry in all four participants, none of the participants achieved the criterion that we set with novice undergraduate students.Conclusions: Our results indicate that DRH is an effective intervention to increase rate of correct responding in individuals with intellectual disability, but that achiev‐ing the same productivity as workers without disability may not always be possible

Tutorial : applying machine learning in behavioral research

Machine-learning algorithms hold promise for revolutionizing how educators and clinicians make decisions. However, researchers in behavior analysis have been slow to adopt this methodology to further develop their understanding of human behavior and improve the application of the science to problems of applied significance. One potential explanation for the scarcity of research is that machine learning is not typically taught as part of training programs in behavior analysis. This tutorial aims to address this barrier by promoting increased research using machine learning in behavior analysis. We present how to apply the random forest, support vector machine, stochastic gradient descent, and k-nearest neighbors algorithms on a small dataset to better identify parents of children with autism who would benefit from a behavior analytic interactive web training. These step-by-step applications should allow researchers to implement machine-learning algorithms with novel research questions and datasets

Stereotypic head twirls, but not pacing, are related to a ‘pessimistic’-like judgment bias among captive tufted capuchins (Cebus apella)

Abnormal stereotypic behaviour is widespread among captive non-human primates and is generally associated with jeopardized well-being. However, attributing the same significance to all of these repetitive, unvarying and apparently functionless behaviours may be misleading, as some behaviours may be better indicators of stress than others. Previous studies have demonstrated that the affective state of the individual can be inferred from its bias in appraising neutral stimuli in its environment. Therefore, in the present study, in order to assess the emotional state of stereotyping individuals, 16 captive tufted capuchins (Cebus apella) were tested on a judgment bias paradigm and their faecal corticoid levels were measured in order to assess the intensity of the emotional state. Capuchins with higher levels of stereotypic head twirls exhibited a negative bias while judging ambiguous stimuli and had higher levels of faecal corticoids compared to subjects with lower levels of head twirls. Levels of stereotypic pacing, however, were not correlated with the monkeys’ emotional state. This study is the first to reveal a positive correlation between levels of stereotypic behaviour and a ‘pessimistic’-like judgment bias in a non-human primate by employing a recently developed cognitive approach. Combining cognitive tests that evaluate the animals’ affective valence (positive or negative) with hormonal measurements that provide information on the strength of the emotional state conduces to a better understanding of the animals’ affective state and therefore to their well-being

Machine Learning to Analyze Single-Case Data: A Replication and Extension

Recently, Lanovaz et al. (2020) have found that machine learning algorithms may adequately control for Type I error rate and power when analyzing single-case graphs. However, the study limited most of its analyses to simulated datasets. To replicate and extend this study, we applied the four machine learning models developed by Lanovaz et al. (2020) to a previously published nonsimulated dataset. On average, the four models produced lower proportions of false positives than well-established methods to analyze AB graphs (i.e., the dual-criteria and conservative dual-criteria methods). These results support the use of machine learning to analyze single-case graphs, but further replication by an independent research team using educational and clinical data remains necessary