Effects of meditation experience on functional connectivity of distributed brain networks

This study sought to examine the effect of meditation experience on brain networks underlying cognitive actions employed during contemplative practice. In a previous study, we proposed a basic model of naturalistic cognitive fluctuations that occur during the practice of focused attention meditation. This model specifies four intervals in a cognitive cycle: mind wandering (MW), awareness of MW, shifting of attention, and sustained attention. Using subjective input from experienced practitioners during meditation, we identified activity in salience network regions during awareness of MW and executive network regions during shifting and sustained attention. Brain regions associated with the default mode were active during MW. In the present study, we reasoned that repeated activation of attentional brain networks over years of practice may induce lasting functional connectivity changes within relevant circuits. To investigate this possibility, we created seeds representing the networks that were active during the four phases of the earlier study, and examined functional connectivity during the resting state in the same participants. Connectivity maps were then contrasted between participants with high vs. low meditation experience. Participants with more meditation experience exhibited increased connectivity within attentional networks, as well as between attentional regions and medial frontal regions. These neural relationships may be involved in the development of cognitive skills, such as maintaining attention and disengaging from distraction, that are often reported with meditation practice. Furthermore, because altered connectivity of brain regions in experienced meditators was observed in a non-meditative (resting) state, this may represent a transference of cognitive abilities “off the cushion” into daily life

Identifying Data Sharing in Biomedical Literature

Many policies and projects now encourage investigators to share their raw research data with other scientists. Unfortunately, it is difficult to measure the effectiveness of these initiatives because data can be shared in such a variety of mechanisms and locations. We propose a novel approach to finding shared datasets: using NLP techniques to identify declarations of dataset sharing within the full text of primary research articles. Using regular expression patterns and machine learning algorithms on open access biomedical literature, our system was able to identify 61% of articles with shared datasets with 80% precision. A simpler version of our classifier achieved higher recall (86%), though lower precision (49%). We believe our results demonstrate the feasibility of this approach and hope to inspire further study of dataset retrieval techniques and policy evaluation.
&#xa

Employee Attitudinal Effects of Perceived Performance Appraisal Use

This research investigates how employee perceptions of performance appraisal use relate to employee satisfaction with the performance appraisal and with the appraiser—the employees’ immediate supervisor. Employee perceptions that appraisals were used for development positively associated with both attitudinal variables, after controlling for justice perceptions, performance, and demographics. Perceptions of PA use for evaluation did not show a significant relationship with either employee attitude. Implications of these findings are discussed

A review of journal policies for sharing research data

*Background:* Sharing data is a tenet of science, yet commonplace in only a few subdisciplines. Recognizing that a data sharing culture is unlikely to be achieved without policy guidance, some funders and journals have begun to request and require that investigators share their primary datasets with other researchers. The purpose of this study is to understand the current state of data sharing policies within journals, the features of journals which are associated with the strength of their data sharing policies, and whether the strength of data sharing policies impact the observed prevalence of data sharing. 

*Methods:* We investigated these relationships with respect to gene expression microarray data in the journals that most often publish studies about this type of data. We measured data sharing prevalence as the proportion of papers with submission links from NCBI's Gene Expression Omnibus (GEO) database. We conducted univariate and linear multivariate regressions to understand the relationship between the strength of data sharing policy and journal impact factor, journal subdiscipline, journal publisher (academic societies vs. commercial), and publishing model (open vs. closed access).

*Results:* Of the 70 journal policies, 18 (26%) made no mention of sharing publication-related data within their Instruction to Author statements. Of the 42 (60%) policies with a data sharing policy applicable to microarrays, we classified 18 (26% of 70) as moderately strong and 24 (34% of 70) as strong.
Existence of a data sharing policy was associated with the type of journal publisher: half of all commercial publishers had a policy compared to 82% of journals published by academic society. All four of the open-access journals had a data sharing policy. Policy strength was associated with impact factor: the journals with no data sharing policy, a weak policy, and a strong policy had respective median impact factors of 3.6, 4.5, and 6.0. Policy strength was positively associated with measured data sharing submission into the GEO database: the journals with no data sharing policy, a weak policy, and a strong policy had median data sharing prevalence of 11%, 19%, and 29% respectively.

*Conclusion:* This review and analysis begins to quantify the relationship between journal policies and data sharing outcomes and thereby contributes to assessing the incentives and initiatives designed to facilitate widespread, responsible, effective data sharing. 

&#xa

Prevalence and Patterns of Microarray Data Sharing

Sharing research data is a cornerstone of science. Although many tools and policies exist to encourage data sharing, the prevalence with which datasets are shared is not well understood. We report our preliminary results on patterns of sharing microarray data in public databases.

The most comprehensive method for measuring occurrences of public data sharing is manual curation of research reports, since data sharing plans are usually communicated in free text within the body of an article. Our early findings from manual curation of 100 papers suggest that 30% of investigators publicly share their full microarray datasets. Of these, 70% of the datasets are deposited at NCBI's Gene Expression Omnibus (GEO) database, 20% at EBI's ArrayExpress, and 10% in smaller databases or lab or publisher websites.

Next, we supplemented this manual process with a rough automated estimate of data sharing prevalence. Using PubMed, we identified research articles with MeSH terms for both "Gene Expression Profiling" and "Oligonucleotide Array Sequence Analysis" and published in 2006. We then searched GEO and ArrayExpress for links to these PubMed IDs to determine which of the articles had been credited as an originating data source.

Of the 2503 articles, 440 (18%) articles had links from either GEO or ArrayExpress. Of these 440 articles, 70% had links from GEO and 30% from ArrayExpress, with an overlapping 12% from both GEO and ArrayExpress.

Interestingly, studies with free full text at PubMed were twice (Odds Ratio=2.1; 95% confidence interval: [1.7 to 2.5]) as likely to be linked as a data source within GEO or ArrayExpress than those without free full text. Studies with human data were less likely to have a link (OR=0.8 [0.6 to 0.9]) than studies with only non-human data. The proportion of articles with a link within these two databases has increased over time: the odds of a data-source link for studies was 2.5 [2.0 to 3.1] times greater for studies published in 2006 than 2002.

As might be expected, studies with the fewest funding sources had the fewest data-sharing links: only 28 (6%) of the 433 studies with no funding source were listed within GEO or ArrayExpress. In contrast, studies funded by the NIH, the US government, or a non-US government source had data-sharing links in 282 of 1556 cases (18%), while studies funded by two or more of these mechanisms were listed in the databases in 130 out of 514 cases (25%).

In summary, our initial manual approach for identifying studies which shared their data was comprehensive but time-consuming; natural language processing techniques could be helpful. Our subsequent automated approach yielded conservative estimates for total data sharing prevalence, nonetheless revealing several promising hypotheses for data sharing behavior

We hope these preliminary results will inspire additional investigations into data sharing behavior, and in turn the development of effective policies and tools to facilitate this important aspect of scientific research

Providing Basic Needs and Encouragement as Strategies in Managing Aggression in Dementia Clients

Purpose: The experiences of caregivers in managing dementia clients with aggressive behaviour have been an issue in nursing homes. This study utilized the fact that there is no significant strategy for managing aggression effectively. The aim of the study is to explore the experiences of caregivers in managing dementia clients with aggressive behaviour in nursing home in Jakarta, Indonesia.Method: This study employed a hermeneutic phenomenological approach so that caregivers were able to explore the phenomenon of aggression by dementia residents in the nursing home. Six experienced caregivers were interviewed in this study to uncover caregivers\u27 strategies they use in managing aggression in dementia residents.Result: The findings in this study were several strategies that have been used by caregivers to manage aggressive behaviour among dementia residents in the nursing home: providing basic needs and encouragement.Conclusion: The findings suggested caregivers to implement the strategies for managing aggression in dementia residents. Due to a limited number of related studies in Indonesia, this study recommended for further research to other nursing homes in Indonesia to determine if other strategies to manage aggression exist

Sartorial symbols of social class elicit class-consistent behavioral and physiological responses: a dyadic approach.

Social rank in human and nonhuman animals is signaled by a variety of behaviors and phenotypes. In this research, we examined whether a sartorial manipulation of social class would engender class-consistent behavior and physiology during dyadic interactions. Male participants donned clothing that signaled either upper-class (business-suit) or lower-class (sweatpants) rank prior to engaging in a modified negotiation task with another participant unaware of the clothing manipulation. Wearing upper-class, compared to lower-class, clothing induced dominance--measured in terms of negotiation profits and concessions, and testosterone levels--in participants. Upper-class clothing also elicited increased vigilance in perceivers of these symbols: Relative to perceiving lower-class symbols, perceiving upper-class symbols increased vagal withdrawal, reduced perceptions of social power, and catalyzed physiological contagion such that perceivers' sympathetic nervous system activation followed that of the upper-class target. Discussion focuses on the dyadic process of social class signaling within social interactions

Employee Line of Sight to the Organization’s Strategic Objectives – What it is, How it can be Enhanced, and What it Makes Happen

Employee_Line_of_SightWP01_06.pdf: 13661 downloads, before Oct. 1, 2020