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Wireless Monitoring of Changes in Crew Relations during Long-Duration Mission Simulation.

Johannes B, Sitev AS, Vinokhodova AG, Salnitski VP, Savchenko EG, Artyukhova AE, Bubeev YA, Morukov BV, Tafforin C, Basner M, Dinges DF, Rittweger J - PLoS ONE (2015)

Bottom Line: A correspondence of 95.7% with the survey video on day 475 confirmed external reliability.Correlation analyses of a sociometric questionnaire (r = .35-.55, p< .05) and an ethological group approach (r = .45-.66, p < 05) provided initial evidence of the method's validity as a measure of cohesion when taking behavioral and activity patterns into account (e.g. only including activity phases in the afternoon).This confirms our assumption that the registered amount of time spent together during free time is associated with the intensity of personal relationships.

View Article: PubMed Central - PubMed

Affiliation: Division of Space Physiology, Institute of Aerospace Medicine, German Aerospace Center (DLR), Cologne, Germany.

ABSTRACT
Group structure and cohesion along with their changes over time play an important role in the success of missions where crew members spend prolonged periods of time under conditions of isolation and confinement. Therefore, an objective system for unobtrusive monitoring of crew cohesion and possible individual stress reactions is of high interest. For this purpose, an experimental wireless group structure (WLGS) monitoring system integrated into a mobile psychophysiological system was developed. In the presented study the WLGS module was evaluated separately in six male subjects (27-38 years old) participating in a 520-day simulated mission to Mars. Two days per week, each crew member wore a small sensor that registered the presence and distance of the sensors either worn by the other subjects or strategically placed throughout the isolation facility. The registration between two sensors was on average 91.0% in accordance. A correspondence of 95.7% with the survey video on day 475 confirmed external reliability. An integrated score of the "crew relation time index" was calculated and analyzed over time. Correlation analyses of a sociometric questionnaire (r = .35-.55, p< .05) and an ethological group approach (r = .45-.66, p < 05) provided initial evidence of the method's validity as a measure of cohesion when taking behavioral and activity patterns into account (e.g. only including activity phases in the afternoon). This confirms our assumption that the registered amount of time spent together during free time is associated with the intensity of personal relationships.

No MeSH data available.


Related in: MedlinePlus

Graphical representation of WLGS data.a: Graphical representation of the time spent together based on data from the six crew sensors on mission days 197 (upper left), and 204 (upper right). These graphs are similar to Moreno’s classical sociogram. The thickness of lines represents the time spent together separately for each measurement day. b: Two graphical representations of subjects latent position and interaction size for one and the same mission day (15) using R statnet including a statistical comparison of two agency groups (“hosts”, “guests”) with extremely opposite significance estimations. For anonymity new subject identifier were randomly assigned (V1-V6).
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pone.0134814.g002: Graphical representation of WLGS data.a: Graphical representation of the time spent together based on data from the six crew sensors on mission days 197 (upper left), and 204 (upper right). These graphs are similar to Moreno’s classical sociogram. The thickness of lines represents the time spent together separately for each measurement day. b: Two graphical representations of subjects latent position and interaction size for one and the same mission day (15) using R statnet including a statistical comparison of two agency groups (“hosts”, “guests”) with extremely opposite significance estimations. For anonymity new subject identifier were randomly assigned (V1-V6).

Mentions: WLGS data were obtained twice a week starting with mission day 15. Out of 132 expected data sets 130 (98.5%) were obtained. However, only 89 (67.4%) were complete during day time for the analysis. The remaining 42 data sets were missing primarily due to insufficient battery recharging. The WLGS data matrix can be found in the S1 Data. Graphs similar to Moreno’s sociogram were generated based on the WLGS data including the crew members only. This kind of classical sociogram illustrates immediately the change of time relationships among the crewmembers. Fig 2A shows some examples of single day assessment. It can be seen that some of the relationships (e.g. A-D, C-D) remain relatively dominant while others (e.g. D-E, B-C) remain relatively weak. In Fig 2B the latent positions of crewmembers were calculated twice for one and the same day (day 15) using the ergmm procedure of the R-package latentnet (statnet). The reference distribution was chosen as recommended by Krivitsky in a short e-mail communication. All crew members were assigned to an “agency”, the “hosts” or the “guests”. The structures look similar but the estimate of the covariate coefficient of the agency effect provided opposite significance results for the F-value (MCMC sample size = 4000): highly significant (p < 2.2e-16) vs. not significant (p = .405). The lower Bayesian Information Criterion (BIC) 187.8 vs. 210.7 supports the model with the high significant differences. The averaged time spent together with other crew members is more formally illustrated in Fig 3.


Wireless Monitoring of Changes in Crew Relations during Long-Duration Mission Simulation.

Johannes B, Sitev AS, Vinokhodova AG, Salnitski VP, Savchenko EG, Artyukhova AE, Bubeev YA, Morukov BV, Tafforin C, Basner M, Dinges DF, Rittweger J - PLoS ONE (2015)

Graphical representation of WLGS data.a: Graphical representation of the time spent together based on data from the six crew sensors on mission days 197 (upper left), and 204 (upper right). These graphs are similar to Moreno’s classical sociogram. The thickness of lines represents the time spent together separately for each measurement day. b: Two graphical representations of subjects latent position and interaction size for one and the same mission day (15) using R statnet including a statistical comparison of two agency groups (“hosts”, “guests”) with extremely opposite significance estimations. For anonymity new subject identifier were randomly assigned (V1-V6).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4529101&req=5

pone.0134814.g002: Graphical representation of WLGS data.a: Graphical representation of the time spent together based on data from the six crew sensors on mission days 197 (upper left), and 204 (upper right). These graphs are similar to Moreno’s classical sociogram. The thickness of lines represents the time spent together separately for each measurement day. b: Two graphical representations of subjects latent position and interaction size for one and the same mission day (15) using R statnet including a statistical comparison of two agency groups (“hosts”, “guests”) with extremely opposite significance estimations. For anonymity new subject identifier were randomly assigned (V1-V6).
Mentions: WLGS data were obtained twice a week starting with mission day 15. Out of 132 expected data sets 130 (98.5%) were obtained. However, only 89 (67.4%) were complete during day time for the analysis. The remaining 42 data sets were missing primarily due to insufficient battery recharging. The WLGS data matrix can be found in the S1 Data. Graphs similar to Moreno’s sociogram were generated based on the WLGS data including the crew members only. This kind of classical sociogram illustrates immediately the change of time relationships among the crewmembers. Fig 2A shows some examples of single day assessment. It can be seen that some of the relationships (e.g. A-D, C-D) remain relatively dominant while others (e.g. D-E, B-C) remain relatively weak. In Fig 2B the latent positions of crewmembers were calculated twice for one and the same day (day 15) using the ergmm procedure of the R-package latentnet (statnet). The reference distribution was chosen as recommended by Krivitsky in a short e-mail communication. All crew members were assigned to an “agency”, the “hosts” or the “guests”. The structures look similar but the estimate of the covariate coefficient of the agency effect provided opposite significance results for the F-value (MCMC sample size = 4000): highly significant (p < 2.2e-16) vs. not significant (p = .405). The lower Bayesian Information Criterion (BIC) 187.8 vs. 210.7 supports the model with the high significant differences. The averaged time spent together with other crew members is more formally illustrated in Fig 3.

Bottom Line: A correspondence of 95.7% with the survey video on day 475 confirmed external reliability.Correlation analyses of a sociometric questionnaire (r = .35-.55, p< .05) and an ethological group approach (r = .45-.66, p < 05) provided initial evidence of the method's validity as a measure of cohesion when taking behavioral and activity patterns into account (e.g. only including activity phases in the afternoon).This confirms our assumption that the registered amount of time spent together during free time is associated with the intensity of personal relationships.

View Article: PubMed Central - PubMed

Affiliation: Division of Space Physiology, Institute of Aerospace Medicine, German Aerospace Center (DLR), Cologne, Germany.

ABSTRACT
Group structure and cohesion along with their changes over time play an important role in the success of missions where crew members spend prolonged periods of time under conditions of isolation and confinement. Therefore, an objective system for unobtrusive monitoring of crew cohesion and possible individual stress reactions is of high interest. For this purpose, an experimental wireless group structure (WLGS) monitoring system integrated into a mobile psychophysiological system was developed. In the presented study the WLGS module was evaluated separately in six male subjects (27-38 years old) participating in a 520-day simulated mission to Mars. Two days per week, each crew member wore a small sensor that registered the presence and distance of the sensors either worn by the other subjects or strategically placed throughout the isolation facility. The registration between two sensors was on average 91.0% in accordance. A correspondence of 95.7% with the survey video on day 475 confirmed external reliability. An integrated score of the "crew relation time index" was calculated and analyzed over time. Correlation analyses of a sociometric questionnaire (r = .35-.55, p< .05) and an ethological group approach (r = .45-.66, p < 05) provided initial evidence of the method's validity as a measure of cohesion when taking behavioral and activity patterns into account (e.g. only including activity phases in the afternoon). This confirms our assumption that the registered amount of time spent together during free time is associated with the intensity of personal relationships.

No MeSH data available.


Related in: MedlinePlus