Toward an Improved Understanding of Work Motivation Profiles

The present research proposes an improved understanding of work motivation by identifying employees’ motivational profiles while taking into account the dual global and specific nature of work motivation proposed by self-determination theory (SDT). To document the construct validity of these latent profiles, we relied on the circumplex model of employees’ well-being to investigate whether they differed in terms of burnout, work satisfaction, and work addiction. Results from analyses conducted among a sample of 955 employees revealed five distinct profiles characterized by differing levels of global and specific forms of motivation: Intrinsically Motivated, Poorly Motivated, Driven, Conflicted, and Self-Determined. Lower levels of burnout and work satisfaction were associated with profiles characterized by higher global levels of self-determination and more autonomous forms of motivation, matching theoretical expectations. Interestingly, work addiction was highest in the Driven profile and lowest in the Self-Determined profile, suggesting that autonomous forms of motivation are not always able to buffer the adverse effects of controlled forms of motivation. Our results also suggest that the specific qualities of work motivations are just as important as the global levels of self-determination in the identification of work motivation profiles.     

A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial

Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological markers related to suicide, computer science provides opportunities to understand suicide thought markers. In this novel prospective, multimodal, multicenter, mixed demographic study, we used machine learning to measure and fuse two classes of suicidal thought markers: verbal and nonverbal. Machine learning algorithms were used with the subjects’ words and vocal characteristics to classify 379 subjects recruited from two academic medical centers and a rural community hospital into one of three groups: suicidal, mentally ill but not suicidal, or controls. By combining linguistic and acoustic characteristics, subjects could be classified into one of the three groups with up to 85% accuracy. The results provide insight into how advanced technology can be used for suicide assessment and prevention.     

Splenium development and early spoken language in human infants

The association between developmental trajectories of language‐related white matter fiber pathways from 6 to 24 months of age and individual differences in language production at 24 months of age was investigated. The splenium of the corpus callosum, a fiber pathway projecting through the posterior hub of the default mode network to occipital visual areas, was examined as well as pathways implicated in language function in the mature brain, including the arcuate fasciculi, uncinate fasciculi, and inferior longitudinal fasciculi. The hypothesis that the development of neural circuitry supporting domain‐general orienting skills would relate to later language performance was tested in a large sample of typically developing infants. The present study included 77 infants with diffusion weighted MRI scans at 6, 12 and 24 months and language assessment at 24 months. The rate of change in splenium development varied significantly as a function of language production, such that children with greater change in fractional anisotropy (FA) from 6 to 24 months produced more words at 24 months. Contrary to findings from older children and adults, significant associations between language production and FA in the arcuate, uncinate, or left inferior longitudinal fasciculi were not observed. The current study highlights the importance of tracing brain development trajectories from infancy to fully elucidate emerging brain–behavior associations while also emphasizing the role of the splenium as a key node in the structural network that supports the acquisition of spoken language.     

国内十省市在校青少年理想、动机和兴趣的研究

这个研究采用独特而新颖的方法,在国内十个省市内进行。 研究指出,目前中学生大多数是有理想的,总的趋势是健康的,主流是好的。 研究表明,理想是人生观的核心与方向,要进行理想教育,重要的途径在于激发学习动机和培养学习兴趣,学校教育工作要注意处理好理想、动机和兴趣三者关系。既抓方向,又抓动力。     

论现代临床医学发展的人文走向

我们不能用静止的眼光看待当代的医学。在整个“以人为本”的环境背景和其它因素的影响下,近二十多年以来,现代医学正在开始走出人性冷漠的阴影,出现了一些重要的人文走向,尽管这还只是开始,但无疑给人们以希望和信心。     

The integration of familiarity and recollection information in short-term recognition: modeling speed-accuracy trade-off functions

Dual process models postulate familiarity and recollection as the basis of the recognition process. We investigated the time-course of integration of the two information sources to one recognition judgment in a working memory task. We tested 24 subjects with a response signal variant of the modified Sternberg recognition task (Oberauer, 2001) to isolate the time course of three different probe types indicating different combinations of familiarity and source information. We compared two mathematical models implementing different ways of integrating familiarity and recollection. Within each model, we tested three assumptions about the nature of the familiarity signal, with familiarity having (a) only positive values, indicating similarity of the probe with the memory list, (b) only negative values, indicating novelty, or (c) both positive and negative values. Both models provided good fits to the data. A model combining the outputs of both processes additively (Integration Model) gave an overall better fit to the data than a model based on a continuous familiarity signal and a probabilistic all-or-none recollection process (Dominance Model).     

Neuropsychological Measures that Predict Progression from Mild Cognitive Impairment to Alzheimer's type dementia in Older Adults: a Systematic Review and Meta-Analysis

This study aimed to determine the extent to which cognitive measures can predict progression from mild cognitive impairment (MCI) to Alzheimer’s type dementia (AD), assess the predictive accuracy of different cognitive domain categories, and determine whether accuracy varies as a function of age and length of follow-up. We systematically reviewed and meta-analyzed data from longitudinal studies reporting sensitivity and specificity values for neuropsychological tests to identify individuals with MCI who will develop AD. We searched articles in Medline, Cochrane, EMBASE, PsycINFO, and the Web of Science. Methodological quality was assessed using the STARDem and QUADAS standards. Twenty-eight studies met the eligibility criteria (2365 participants) and reported predictive values from 61 neuropsychological tests with a 31-month mean follow-up. Values were pooled to provide combined accuracy for 14 cognitive domains. Many domains showed very good predictive accuracy with high sensitivity and specificity values (≥ 0.7). Verbal memory measures and many language tests yielded very high predictive accuracy. Other domains (e.g., executive functions, visual memory) showed better specificity than sensitivity. Predictive accuracy was highest when combining memory measures with a small set of other domains or when relying on broad cognitive batteries. Cognitive tests are excellent at predicting MCI individuals who will progress to dementia and should be a critical component of any toolkit intended to identify AD at the pre-dementia stage. Some tasks are remarkable as early indicators, whereas others might be used to suggest imminent progression.