Critical Team Composition Issues for Long-Distance and Long-Duration Space Exploration: A Literature Review, an Operational Assessment, and Recommendations for Practice and Research

Prevailing team effectiveness models suggest that teams are best positioned for success when certain enabling conditions are in place (Hackman, 1987; Hackman, 2012; Mathieu, Maynard, Rapp, & Gilson, 2008; Wageman, Hackman, & Lehman, 2005). Team composition, or the configuration of member attributes, is an enabling structure key to fostering competent teamwork (Hackman, 2002; Wageman et al., 2005). A vast body of research supports the importance of team composition in team design (Bell, 2007). For example, team composition is empirically linked to outcomes such as cooperation (Eby & Dobbins, 1997), social integration (Harrison, Price, Gavin, & Florey, 2002), shared cognition (Fisher, Bell, Dierdorff, & Belohlav, 2012), information sharing (Randall, Resick, & DeChurch, 2011), adaptability (LePine, 2005), and team performance (e.g., Bell, 2007). As such, NASA has identified team composition as a potentially powerful means for mitigating the risk of performance decrements due to inadequate crew cooperation, coordination, communication, and psychosocial adaptation in future space exploration missions. Much of what is known about effective team composition is drawn from research conducted in conventional workplaces (e.g., corporate offices, production plants). Quantitative reviews of the team composition literature (e.g., Bell, 2007; Bell, Villado, Lukasik, Belau, & Briggs, 2011) are based primarily on traditional teams. Less is known about how composition affects teams operating in extreme environments such as those that will be experienced by crews of future space exploration missions. For example, long-distance and long-duration space exploration (LDSE) crews are expected to live and work in isolated and confined environments (ICEs) for up to 30 months. Crews will also experience communication time delays from mission control, which will require crews to work more autonomously (see Appendix A for more detailed information regarding the LDSE context). Given the unique context within which LDSE crews will operate, NASA identified both a gap in knowledge related to the effective composition of autonomous, LDSE crews, and the need to identify psychological and psychosocial factors, measures, and combinations thereof that can be used to compose highly effective crews (Team Gap 8). As an initial step to address Team Gap 8, we conducted a focused literature review and operational assessment related to team composition issues for LDSE. The objectives of our research were to: (1) identify critical team composition issues and their effects on team functioning in LDSE-analogous environments with a focus on key composition factors that will most likely have the strongest influence on team performance and well-being, and 1 Astronaut diary entry in regards to group interaction aboard the ISS (p.22; Stuster, 2010) 2 (2) identify and evaluate methods used to compose teams with a focus on methods used in analogous environments. The remainder of the report includes the following components: (a) literature review methodology, (b) review of team composition theory and research, (c) methods for composing teams, (d) operational assessment results, and (e) recommendations

Suggested Practices for Making I-O Connections: Let’s Build Bridges and Grow I-O!

It may come as no surprise, but there are an awful lot of people who have no idea what I-O pychology is or what I-O psychologists do. Common reactions from new acquaintances include, “Ooo, I could really use some help organizing my home and be a more industrious person” or “Wow, that’s a mouthful” or “No really, what do you do for a living?” Perhaps even more alarming is the number of students across universities who aren’t introduced to I-O—even if they are psychology majors! We are struck by the number of prospective graduate students who tell us that they wouldn’t know that I-O existed had it not been for a chance encounter with an I-O psychologist. For every one of these talented young people who join the field, there are 10 more who don’t have that chance encounter and end up in a different field

The Use of Person-Organization Fit in Employment Decision Making: An Assessment of Its Criterion-Related Validity

Because measures of person-organization (P-O) fit are accountable to the same psychometric and legal standards used for other employment tests when they are used for personnel decision making, the authors assessed the criterion-related validity of P-O fit as a predictor of job performance and turnover. Meta-analyses resulted in estimated true criterion-related validities of .15 (k ϭ 36, N ϭ 5,377) for P-O fit as a predictor of job performance and .24 (k ϭ 8, N ϭ 2,476) as a predictor of turnover, compared with a stronger effect of .31 (k ϭ 109, N ϭ 108,328) for the more commonly studied relation between P-O fit and work attitudes. In contrast to the relations between P-O fit and work attitudes, the lower 95% credibility values for the job performance and turnover relations included zero. In addition, P-O fit's relations with job performance and turnover were partially mediated by work attitudes. Potential concerns pertaining to the use of P-O fit in employment decision making are discussed in light of these results. Keywords: person-organization fit, personnel selection, criterion-related validity, job performance, turnover Using meta-analytic procedures, the primary objective of this article is to investigate the criterion-related validity of personorganization (P-O) fit as a predictor of job performance and turnover. The construct of P-O fit originates from interactional psychology, which assumes that behavior is caused by the continuous interaction between the person and the environment Although there are many types of fit, including person-team (group) fit, person-vocation fit, and person-job fit (see In brief, we argue that although P-O fit may predict work attitudes P-O Fit and Work Attitudes Kristof (1996) defined P-O fit as "the compatibility between people and organizations that occurs when: (a) at least one entity provides what the other needs, or (b) they share similar fundamental characteristics, or (c) both" (p. 45)

Relating Ability and Personality to the Efficacy and Performance of Dyadic Teams

We examined the extent to which member ability and personality relate to differences in team performance and team efficacy in a task setting that simulated the high degree of role interdependence and human-technology interaction found in many military contexts. 168 male participants were assigned to dyadic teams and trained for two weeks to learn and perform a complex computer task that simulated the demands of a dynamic aviation environment. Participants also completed measures of general mental ability, psychomotor ability, and the Big Five personality traits (extraversion, openness, conscientiousness, agreeableness, and emotional stability). Team performance and team efficacy were assessed multiple times throughout training. Results indicated that ability was a critical determinant of both performance and efficacy, and personality traits yielded an incremental contribution to both performance and efficacy. In particular, psychomotor ability and conscientiousness were the strongest and most consistent factors associated with team effectiveness.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Field‐based adipose tissue quantification in sea turtles using bioelectrical impedance spectroscopy validated with CT scans and deep learning

Loss of adipose tissue in vertebrate wildlife species is indicative of decreased nutritional and health status and is linked to environmental stress and diseases. Body condition indices (BCI) are commonly used in ecological studies to estimate adipose tissue mass across wildlife populations. However, these indices have poor predictive power, which poses the need for quantitative methods for improved population assessments. Here, we calibrate bioelectrical impedance spectroscopy (BIS) as an alternative approach for assessing the nutritional status of vertebrate wildlife in ecological studies. BIS is a portable technology that can estimate body composition from measurements of body impedance and is widely used in humans. BIS is a predictive technique that requires calibration using a reference body composition method. Using sea turtles as model organisms, we propose a calibration protocol using computed tomography (CT) scans, with the prediction equation being: adipose tissue mass (kg) = body mass − (−0.03 [intercept] − 0.29 * length2/resistance at 50 kHz + 1.07 * body mass − 0.11 * time after capture). CT imaging allows for the quantification of body fat. However, processing the images manually is prohibitive due to the extensive time requirement. Using a form of artificial intelligence (AI), we trained a computer model to identify and quantify nonadipose tissue from the CT images, and adipose tissue was determined by the difference in body mass. This process enabled estimating adipose tissue mass from bioelectrical impedance measurements. The predictive performance of the model was built on 2/3 samples and tested against 1/3 samples. Prediction of adipose tissue percentage had greater accuracy when including impedance parameters (mean bias = 0.11%–0.61%) as predictor variables, compared with using body mass alone (mean bias = 6.35%). Our standardized BIS protocol improves on conventional body composition assessment methods (e.g., BCI) by quantifying adipose tissue mass. The protocol can be applied to other species for the validation of BIS and to provide robust information on the nutritional and health status of wildlife, which, in turn, can be used to inform conservation decisions at the management level

Six-Month Mortality among HIV-Infected Adults Presenting for Antiretroviral Therapy with Unexplained Weight Loss, Chronic Fever or Chronic Diarrhea in Malawi.

In sub-Saharan Africa, early mortality is high following initiation of antiretroviral therapy (ART). We investigated 6-month outcomes and factors associated with mortality in HIV-infected adults being assessed for ART initiation and presenting with weight loss, chronic fever or diarrhea, and with negative TB sputum microscopy

Convergence of Self-Report and Archival Crash Involvement Data: A Two-Year Longitudinal Follow-Up

This study constructively extends Arthur et al. (2001) by assessing the convergence of self-report and archival motor vehicle crash involvement and moving violations data in a 2-year longitudinal follow-up. The relationships among these criteria, conscientiousness, and driving speed were also assessed using both predictive and postdictive criterion-related validation designs. Data were collected from a 2-year follow-up sample of 334 participants. Results suggested a lack of convergence between self-report and archival data at both Time 1 and Time 2. In addition, the predictor/criterion relationships varied across research design and data source. An actual application of our findings is that the interpretation of relationships between specified predictors and crash involvement and moving violations must be made within the context of the criterion-related validation design and criterion data source. Specifically, predictive designs may produce results different from those of postdictive designs (which are more commonly used). Furthermore, self-report data appear to include a broader range of incidents (more crashes and tickets), and thus researchers should consider using self-report data when they are interested in including lower threshold crashes and tickets that may not be reported on state records (e.g., because of the completion of a defensive driving course)Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

A measurement of the millimetre emission and the Sunyaev-Zel'dovich effect associated with low-frequency radio sources

We present a statistical analysis of the millimetre-wavelength properties of 1.4GHz-selected sources and a detection of the Sunyaev–Zel’dovich (SZ) effect associated with the haloes that host them. We stack data at 148, 218 and 277GHz from the Atacama Cosmology Telescope at the positions of a large sample of radio AGN selected at 1.4GHz. The thermal SZ effect associated with the haloes that host the AGN is detected at the 5σ level through its spectral signature, representing a statistical detection of the SZ effect in some of the lowest mass haloes (average M 200 ≈ 10 13 M. h −1 70 ) studied to date. The relation between the SZ effect and mass (based on weak lensing measurements of radio galaxies) is consistent with that measured by Planck for local bright galaxies. In the context of galaxy evolution models, this study confirms that galaxies with radio AGN also typically support hot gaseous haloes. Adding Herschel observations allows us to show that the SZ signal is not significantly contaminated by dust emission. Finally, we analyse the contribution of radio sources to the angular power spectrum of the cosmic microwave background