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This study examined the spoken narrative skills of a group of bilingual Mandarin–English speaking 3–6-year-olds (N = 25) in Australia, using a remote online story-retell task. Bilingual preschoolers are an understudied population, especially those who are speaking typologically distinct languages such as Mandarin and English which have fewer structural overlaps compared to language pairs that are typologically closer, reducing cross-linguistic positive transfer. We examined these preschoolers’ spoken narrative skills as measured by macrostructures (the global organization of a story) and microstructures (linguistic structures, e.g., total number of utterances, nouns, verbs, phrases, and modifiers) across and within each language, and how various factors such as age and language experiences contribute to individual variability. The results indicate that our bilingual preschoolers acquired spoken narrative skills similarly across their two languages, i.e., showing similar patterns of productivity for macrostructure and microstructure elements in both of their two languages. While chronological age was positively correlated with macrostructures in both languages (showing developmental effects), there were no significant correlations between measures of language experiences and the measures of spoken narrative skills (no effects for language input/output). The findings suggest that although these preschoolers acquire two typologically diverse languages in different learning environments, Mandarin at home with highly educated parents, and English at preschool, they displayed similar levels of oral narrative skills as far as these macro−/micro-structure measures are concerned. This study provides further evidence for the feasibility of remote online assessment of preschoolers’ narrative skills.
Objective: There is a lack of brief rating scales for the reliable assessment of psychotherapeutic skills, which do not require intensive rater training and/or a high level of expertise. Thus, the objective is to validate a 14-item version of the Clinical Communication Skills Scale (CCSS-S).
Methods: Using a sample of N = 690 video-based ratings of role-plays with simulated patients, we calculated a confirmatory factor analysis and an exploratory structural equation modeling (ESEM), assessed convergent validities, determined inter-rater reliabilities and compared these with those who were either psychology students, advanced psychotherapy trainees, or experts.
Results: Correlations with other competence rating scales were high (rs > 0.86–0.89). The intraclass correlations ranged between moderate and good [ICC(2,2) = 0.65–0.80], with student raters yielding the lowest scores. The one-factor model only marginally replicated the data, but the internal consistencies were excellent (α = 0.91–95). The ESEM yielded a two-factor solution (Collaboration and Structuring and Exploration Skills).
Conclusion: The CCSS-S is a brief and valid rating scale that reliably assesses basic communication skills, which is particularly useful for psychotherapy training using standardized role-plays. To ensure good inter-rater reliabilities, it is still advisable to employ raters with at least some clinical experience. Future studies should further investigate the one- or two-factor structure of the instrument.
For life-long learning, an effective learning strategy repertoire is particularly important during acquisition of knowledge in lower secondary school—an educational level characterized with transition into more autonomous learning environments with increased complex academic demands. Using latent profile analysis, we explored the occurrence of different secondary school learner profiles depending on their various combinations of cognitive and metacognitive learning strategy use, as well as their differences in perceived autonomy support, intrinsic motivation, and gender. Data were collected from 576 ninth grade students in Uganda using self-report questionnaires. Four learner profiles were identified: competent strategy user, struggling user, surface-level learner, and deep-level learner profiles. Gender differences were noted in students’ use of elaboration and organization strategies to learn Physics, in favor of girls. In terms of profile memberships, significant differences in gender, intrinsic motivation and perceived autonomy support were also noted. Girls were 2.4–2.7 times more likely than boys to be members of the competent strategy user and surface-level learner profiles. Additionally, higher levels of intrinsic motivation predicted an increased likelihood membership into the deep-level learner profile, while higher levels of perceived teacher autonomy predicted an increased likelihood membership into the competent strategy user profile as compared to other profiles. Further, implications of the findings were discussed.
There is an ongoing debate about how to test and operationalize self-control. This limited understanding is in large part due to a variety of different tests and measures used to assess self-control, as well as the lack of empirical studies examining the temporal dynamics during the exertion of self-control. In order to track changes that occur over the course of exposure to a self-control task, we investigate and compare behavioral, subjective, and physiological indicators during the exertion of self-control. Participants completed both a task requiring inhibitory control (Go/No-Go task) and a control task (two-choice task). Behavioral performance and pupil size were measured during the tasks. Subjective vitality was measured before and after the tasks. While pupil size and subjective vitality showed similar trajectories in the two tasks, behavioral performance decreased in the inhibitory control-demanding task, but not in the control task. However, behavioral, subjective, and physiological measures were not significantly correlated. These results suggest that there is a disconnect between different measures of self-control with high intra- and interindividual variability. Theoretical and methodological implications for self-control theory and future empirical work are discussed.
Basic psychological needs theory postulates that a social environment that satisfies individuals’ three basic psychological needs of autonomy, competence, and relatedness leads to optimal growth and well-being. On the other hand, the frustration of these needs is associated with ill-being and depressive symptoms foremost investigated in non-clinical samples; yet, there is a paucity of research on need frustration in clinical samples. Survey data were compared between adult individuals with major depressive disorder (MDD; n = 115; 48.69% female; 38.46 years, SD = 10.46) with those of a non-depressed comparison sample (n = 201; 53.23% female; 30.16 years, SD = 12.81). Need profiles were examined with a linear mixed model (LMM). Individuals with depression reported higher levels of frustration and lower levels of satisfaction in relation to the three basic psychological needs when compared to non-depressed adults. The difference between depressed and non-depressed groups was significantly larger for frustration than satisfaction regarding the needs for relatedness and competence. LMM correlation parameters confirmed the expected positive correlation between the three needs. This is the first study showing substantial differences in need-based experiences between depressed and non-depressed adults. The results confirm basic assumptions of the self-determination theory and have preliminary implications in tailoring therapy for depression.
Dementia as one of the most prevalent diseases urges for a better understanding of the central mechanisms responsible for clinical symptoms, and necessitates improvement of actual diagnostic capabilities. The brainstem nucleus locus coeruleus (LC) is a promising target for early diagnosis because of its early structural alterations and its relationship to the functional disturbances in the patients. In this study, we applied our improved method of localisation-based LC resting-state fMRI to investigate the differences in central sensory signal processing when comparing functional connectivity (fc) of a patient group with mild cognitive impairment (MCI, n = 28) and an age-matched healthy control group (n = 29). MCI and control participants could be differentiated in their Mini-Mental-State-Examination (MMSE) scores (p < .001) and LC intensity ratio (p = .010). In the fMRI, LC fc to anterior cingulate cortex (FDR p < .001) and left anterior insula (FDR p = .012) was elevated, and LC fc to right temporoparietal junction (rTPJ, FDR p = .012) and posterior cingulate cortex (PCC, FDR p = .021) was decreased in the patient group. Importantly, LC to rTPJ connectivity was also positively correlated to MMSE scores in MCI patients (p = .017). Furthermore, we found a hyperactivation of the left-insula salience network in the MCI patients. Our results and our proposed disease model shed new light on the functional pathogenesis of MCI by directing to attentional network disturbances, which could aid new therapeutic strategies and provide a marker for diagnosis and prediction of disease progression.
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training.
In recent years digital technologies have become a major means for providing health-related services and this trend was strongly reinforced by the current Coronavirus disease 2019 (COVID-19) pandemic. As it is well-known that regular physical activity has positive effects on individual physical and mental health and thus is an important prerequisite for healthy aging, digital technologies are also increasingly used to promote unstructured and structured forms of physical activity. However, in the course of this development, several terms (e.g., Digital Health, Electronic Health, Mobile Health, Telehealth, Telemedicine, and Telerehabilitation) have been introduced to refer to the application of digital technologies to provide health-related services such as physical interventions. Unfortunately, the above-mentioned terms are often used in several different ways, but also relatively interchangeably. Given that ambiguous terminology is a major source of difficulty in scientific communication which can impede the progress of theoretical and empirical research, this article aims to make the reader aware of the subtle differences between the relevant terms which are applied at the intersection of physical activity and Digital Health and to provide state-of-art definitions for them.
Numerical magnitude information is assumed to be spatially represented in the form of a mental number line defined with respect to a body-centred, egocentric frame of reference. In this context, spatial language skills such as mastery of verbal descriptions of spatial position (e.g., in front of, behind, to the right/left) have been proposed to be relevant for grasping spatial relations between numerical magnitudes on the mental number line. We examined 4- to 5-year-old’s spatial language skills in tasks that allow responses in egocentric and allocentric frames of reference, as well as their relative understanding of numerical magnitude (assessed by a number word comparison task). In addition, we evaluated influences of children’s absolute understanding of numerical magnitude assessed by their number word comprehension (montring different numbers using their fingers) and of their knowledge on numerical sequences (determining predecessors and successors as well as identifying missing dice patterns of a series). Results indicated that when considering responses that corresponded to the egocentric perspective, children’s spatial language was associated significantly with their relative numerical magnitude understanding, even after controlling for covariates, such as children’s SES, mental rotation skills, and also absolute magnitude understanding or knowledge on numerical sequences. This suggests that the use of egocentric reference frames in spatial language may facilitate spatial representation of numbers along a mental number line and thus seem important for preschoolers’ relative understanding of numerical magnitude.
In intervention research, single-case experimental designs are an important way to gain insights into the causes of individual changes that yield high internal validity. They are commonly applied to examine the effectiveness of classroom-based interventions to reduce problem behavior in schools. At the same time, there is no consensus on good design characteristics of single-case experimental designs when dealing with behavioral problems in schools. Moreover, specific challenges arise concerning appropriate approaches to analyzing behavioral data. Our study addresses the interplay between the test power of piecewise regression analysis and important design specifications of single-case research designs. Here, we focus on the influence of the following specifications of single-case research designs: number of measurement times, the initial frequency of the behavior, intervention effect, and data trend. We conducted a Monte-Carlo study. First, simulated datasets were created with specific design conditions based on reviews of published single-case intervention studies. Following, data were analyzed using piecewise Poisson-regression models, and the influence of specific design specifications on the test power was investigated. Our results indicate that piecewise regressions have a high potential of adequately identifying the effects of interventions for single-case studies. At the same time, test power is strongly related to the specific design specifications of the single-case study: Few measurement times, especially in phase A, and low initial frequencies of the behavior make it impossible to detect even large intervention effects. Research designs with a high number of measurement times show robust power. The insights gained are highly relevant for researchers in the field, as decisions during the early stage of conceptualizing and planning single-case experimental design studies may impact the chance to identify an existing intervention effect during the research process correctly.