NOTE: Extended to 2/28/2015 per NSSC information (Ed., 8/5/14)

In the third year of our project, we completed our bed rest analog study of journals kept by participants. Not only did this study produce substantial data validating several of our automated analysis techniques, it also provided data documenting novel findings about the affect and attitudes of bed rest participants, both in general and under various exercise and treatment protocols. We have shown the flexibility and rapid reconfigurability of our tools by being able to conduct novel investigations using the backlogged journal entries to answer practical questions of relevance to the bed rest study administrators and other PIs using the bed rest facility.

Also in the third year, we developed techniques for studying interpersonal task communications in the HI-SEAS (Hawaii Space Exploration Analog & Simulation) and HERA (Human Exploration Research Analog) habitat analogs. We were involved in 4 HERA missions (each 1 week in duration) and one 4-month HI-SEAS study. In all cases, we have collected journal and survey data, in conjunction with crew to ground email texts. For HERA, in addition, we have developed techniques for capturing and then transcribing crew-to-crew and crew-to-ground audio speech.

During the initial portion of a fourth year, we were engaged in data collection for portions of an 8-month HI-SEAS study and we completed processing and analysis of all data from both HERA and HI-SEAS studies, as well as cross-analog studies comparing the effectiveness of our techniques in different missions and analog environments. The results of these analyses have shown that our techniques for automatically reading and scoring elements of crew speech and/or textual communications and journals correlate significantly and reliably (over multiple missions and environments) with participant's own survey responses. This was particularly true for participant affect as measured against the Positive and Negative Affect Schedule (PANAS), a common survey instrument used to assess affect and variations in it over time. In addition, our many analyses conducted throughout this effort, are examples of the increased versatility of automated verbal processing, relative to survey instruments, as a means of assessing elements of crew affect, emotion, attitudes, and performance.

These results provide support for our general claim that non-intrusive, automated processing of text and speech could be used to replace or augment many surveys with payoffs in terms of accuracy, robustness, sensitivity and astronaut workload.

In this last program year, we have been in conversations with a large, corporate consulting firm which provides employee attitude survey data about performing automated analysis of “free text” responses within their survey instruments. We conducted a large internal research project demonstrating that tools like we have been using for NASA could be applied to their survey data to provide results that both correlate with, and greatly extend, their scalar survey questions. This demonstration is leading to a paid analysis service which we are beginning for them as of this writing.

The overall objective of the AD ASTRA project (Automated Detection of Attitudes and States through Transaction Recordings Analysis, NRA grant #NNX12AB40G) was to identify suitable combinations of automated text processing techniques (which we call “Non-Intrusive Psycho-Social State Assessors” or NIPSSAs) and data streams for assessing psycho-social states of interest to NASA and to validate our overall hypothesis that NIPSSA measures could replace survey data for assessing selected psychosocial states. It had long been known that astronauts’ journals, diaries, and blogs were a rich source of material about their experiences and attitudes toward those experiences, and interpersonal communications are, after all, one of the best methods humans have of assessing changes in attitudes and states. We reasoned that if we could automate assessments of such data streams—many of which are already being captured and, to some extent, monitored during space missions—we would greatly expand the set of data which NASA team dynamics researchers have available which would help to close multiple Team and B-Med gaps and potentially improve the psychosocial health of future astronauts. Better, we could do so while concurrently improving astronauts’ daily lives and productivity by reducing the volume of surveys they are asked to complete.

The first year of our project surveyed the available techniques and data streams, arrived at the prioritization of textual analysis of journal/log entries and of interactive task discourse (in email, chat, and transcribed speech), and then went on to demonstrate promising sensitivity in the tools via analysis of pre-existing, historical data sources. While we showed individual and temporal variations with anecdotal correspondence to events, no independent data about the writers’ emotional states existed for validation of our text analysis techniques. The second year was targeted at transitioning the promising NIPSSA techniques we found with the first year’s work on historical data to validation studies with newly collected “live” data from ongoing experiments in analog environments (particularly the FARU Bed Rest Study Campaign 11 conducted at the Flight Analog Research Unit at University of Texas Medical Branch (UTMB)).

The third project year (which ended in August, 2014) was devoted to completing the bed rest analog journal study we began in Year 2, continuing to participate in a 4-month crew habitat study in the HI-SEAS (Hawaii Space Exploration Analog & Simulation) analog and beginning participation in an 8-month HI-SEAS study collecting both journal and crew-ground textual interaction messages (with corresponding survey data), and finally, developing techniques for audio data collection and then transcription in the HERA (Human Exploration Research Analog) analog, in which we obtained and analyzed journal, survey, text and speech interaction data from four separate week-long missions.

In our fourth and final, partial year (through February, 2015), we completed analyses of our HERA transcription data, and performed some cross-analog analyses illustrating the robustness of our techniques, and produced our Final Report. We were asked to take a 6 month no-cost extension by NASA personnel (through August, 2015) in which we provided a final outbriefing to NASA, prepared and submitted our data, and produced several articles. In all three analogs, we collected participant journals and daily surveys to cross validate our automated assessment techniques. In the HERA study, we also collected more than 160,000 minutes of captured audio recordings across four mission and transcribed large portions of this to enable examination of automated processing of interactive speech data.

The results have shown that automated textual analysis of subjects’ free form journals can reliably replace at least some forms of attitude and emotion surveys since our automated journal analyses regularly correlated significantly with subjects’ own survey ratings of their emotional positivity/negativity, and their focus on past/present/future across all three of our analog studies. Correlations between their attitudes about the study and about their physical well-being, as well as their focus on themselves vs. others, were also repeatedly significant. Furthermore, there is evidence that automated evaluation of journal entries may do a better job of assessing participant attitudes than do daily observers: a comparative analysis between our automated assessments and subjects’ own survey responses vs. the survey assessments of the subject by a nurse showed that automated analyses did a better job at predicting subjects’ survey responses.

We also demonstrated the speed and flexibility of our approaches by rapidly producing multiple after-the-fact analyses of elements of participants’ attitudes and emotions throughout the study including analyses of the effects of exercise and of testosterone treatments on subjects’ emotions and attitudes about sleep and food. Further, by examining the correlates of positive or negative mentions of a word group (e.g., food, eating, specific food items) we can provide suggestive evidence about how a specific individual or group thinks about that topic—e.g., that food is comforting and tied to nostalgia and social contacts or that it is a source of concern about body image and health. This flexibility to perform post hoc and deep, individualistic analyses (frequently in support of other researchers) proved to be a particularly useful capability and a strong distinguisher from survey questions.

In addition to journals, we developed techniques for examining interactive dialogue during tasks and daily activities. This form of communication is more immediate and less pre-meditated than journal entries and, therefore, is expected to be a less guarded but more transitory source of attitudes and emotions. We have detected significant differences in the overall emotional valence of the different crews, of valence for differing tasks among the different crews, and of varying (and differing) drivers for those emotional sentiments among the crew members.

During debriefs with insightful analog participants and operations personnel and throughout the 3.5 years of this program, we have identified a number of recommendations for the use of the developed techniques that are particularly relevant to long duration missions. Among these are an intervention or advisory tool for crewmembers themselves (reflecting exhibited changes in mood or attitude), a “power level” and “team comfort/routine” indicator for tracking intra-crew dynamics, and an aid for ground researchers to glean attitude and topic focus information from mission and training debriefing sessions. As recognized by the Behavioral Health & Performance (BHP) element, it will be crucial to provide accurate and low cost detection methods to detect measures relevant to BHP’s Team, BMed, and Sleep and Fatigue risks. We present data supporting the validity of ADASTRA techniques as one such approach.

SEPTEMBER 2014 REPORT: The overall objective for the project is to identify suitable combinations of processing techniques (which we call “Non-Intrusive Psycho-Social State Assessors” or NIPSSAs) and data streams for assessing psycho-social states of interest to NASA. The second year of our project was targeted at transitioning the promising NIPSSA techniques we found with the first year’s work on historical data to validation studies with newly collected “live” data from ongoing experiments in analog environments. The third project year has been devoted to completing the bed rest analog journal study we began in Year 2, continuing to participate in a 4 month long crew habitat study in the HI-SEAS analog collecting both journal and crew-ground textual interaction messages (with corresponding survey data), developing techniques for audio data collection and then transcription in the HERA analog, and then obtaining and analyzing journal, survey, text, and speech interaction data from HERA missions. In further testimony to the ease, speed, and flexibility with which data can be analyzed using our tools, we have been able to conduct novel analyses examining topics not planned for initial surveys using the bed rest journal data, and we have been among the first researchers to provide analyses of HERA crew data after each mission.

Significant accomplishments from the bed rest analog include:

1. Continued work in the bed rest analog allowed us validate several of our general techniques against survey data. These include: a. Significant correlations between our scoring of use of positive and negative emotional terms and the corresponding survey scores on the PANAS (Positive and Negative Affect Schedule) instrument. b. Significant correlations between the use of past, present, and future verb tenses in journal entries and a self-report of focus on past, present, and future. c. Significant positive correlation between mentions of a category of terms pertinent to the bed rest study in journal entries and ratings of attitude toward the survey. d. Significant negative correlation of use of terms in a category corresponding to physical state and the survey ratings of the participant’s own physical state.

2. We developed novel techniques and extensions for assessing the “drivers” of attitude on an individual by combining word category use with sentiment analysis. This let us draw conclusions, for example, that one individual’s use of food terms in journal entries with negative affect correlates with his use of body, physical, and health terms—which we interpret as likely indicating concerns about what the hospital diet is doing to his physique—while another uses food terms with positive affect in entries where he also uses past tense verbs and terms for social activities and family—which we interpret as likely indicating that he associates food with nostalgia for social gatherings and events. This type of insight could greatly help ground support in understanding how a psychological intervention or incentive might be interpreted by various crew members.

3. We identified an overall “positivity metric” with a potential “red line” threshold for adverse positivity expressions in journal entries, based on the work of Losada (Losada and Fredrickson, 2005), which suggests that a ratio of positive to negative utterances around 3:1 is indicative of a “thriving” individual or relationship. While this work is controversial, even discredited to some extent, and should be treated with caution, results did seem promising in our data, see below.

4. In addition to our planned analyses, we illustrated the speed and flexibility of applying our techniques (as well as the richness of journal entries as opposed to survey questions) by performing multiple auxiliary analyses which had not been anticipated in our initial experimental plan—such as on the psychological effects of exercise and testosterone treatments. These analyses were typically done in a 1-3 days of person time given our prior data set.

In addition to these validation analyses, we also were able to draw some substantive conclusions about the psychological states and the use of journals in long duration confinement conditions (for which the bed rest conditions serve as an analog). These include:

1. Although there are large individual differences, including some which countered this trend, word count of journal entries declines significantly over time.

2. Within that general trend, the proportional use of positive emotion terms, affect terms in general, perceptual terms (indicative of things being noticed or sensed in the environment), and cognitive mechanism terms (expressions of thought and reasoning) all decline significantly over time. Future tense verb use, though, increased significantly over time.

3. The analysis of positivity ratios described above showed that these ratios were correlated with trait anxiety surveys in our study and were also correlated positively with the use of terms in achievement and work categories in journal entries, and negatively correlated with use of terms indicative of health, physical state, anxiety, anger, frustration, and discouragement. Furthermore, the one subject whose ratio was below that 3:1 threshold in our sample was one who dropped out of the study.

4. Our analysis of the journals of exercisers vs. non-exercisers vs. exercisers also treated with testosterone showed:

a. The overall affect in journal entries (as measured by LSA valence) is higher for exercisers (in both groups) than non-exercisers. Exercisers rate (on surveys) their physical state as higher and they use physical and body terms more frequently, and with higher valence. Their valence for terms having to do with exercise is also higher.

b. When we discriminated between exercisers and exercisers with testosterone, however, we saw that exercise with or without testosterone clearly has substantial benefits on attitude. There was, however, no obvious added benefit from testosterone use on these fronts, over exercise alone. On the other hand, exercisers who did not have testosterone gave more positive survey responses (as opposed to our automated inferences from their journals) on explicit questions about several attitudes or behaviors than did exercisers with testosterone (who did not differ significantly from controls). Of somewhat more concern, testosterone subjects had twice the level of anxiety term usages in their journal entries as did either exercisers without testosterone or controls.

5. We did a comparative analysis between our automated assessment of subject journals and subjects’ own survey responses vs. the survey assessments of the subject by a nurse who interacted with him throughout the day. These results showed that our automated analyses did a much better job at predicting subjects’ survey responses than did the nurses’ survey answers.

While we have completed the bed rest study of subject journals during this program year, we have also been participating in two additional studies the HI-SEAS (Hawaii Space Exploration Analog & Simulation) and HERA (Human Exploration Research Analog) habitat analogs. In neither case are analyses from these studies complete, but we have been able to develop and extend our techniques in methodological ways to enable data capture. These include:

• In the HI-SEAS study, we have collected four months of both journal and interactive email-like exchanges between crew and ground. We developed extended survey techniques to obtain data to validate analyses of inter-crew and crew-ground “familiarity” or social distance, the degree of routine vs. unusualness of a day, etc. We have also now adapted our interpersonal communications analysis techniques for power and team comfort/routine to be able to handle the data from the BaseStation software used by the HI-SEAS team to collect and sequence crew-ground communications. We have now completed an initial run of our analytic software on both journal and crew-ground interactions, but have not yet completed analysis of the results.

• We extended those survey and data collection techniques for use in the data and communications environment of the week long studies in the HERA analog. More extensively, we researched, worked with HERA facility personnel, tested, developed, and eventually deployed an approach to capturing spoken interactions between crew and from crew to ground in the analog. This approach has now been used in the first four HERA missions.

• We also developed techniques for transcribing the captured audio from HERA missions in a cost-effective fashion. This represents a substantial effort in the past 6 months as we have explored automated, semi-automated, and human transcription setups, then consulted with and evaluated multiple transcription services, and ultimately identified a specific service provider and developed a process for selecting portions of the ~40,000 minutes of audio recording produced per HERA mission which were both needed by us and the other researchers in the HERA studies, and then transcribed, formatted, and shipped those portions.

The results achieved during this program year now demonstrate both the viability and the validity of one class of non-intrusive psycho-social state detectors to streamline, speed and in some cases, enable, the collection of data to effectively monitor and measure team and individual health and performance fluctuations during autonomous, long duration exploration missions. For journal data, we have been successful at applying NIPSSA techniques to a variety of “live” analog settings and have shown that they correlate with traditional survey measures. We have also shown that such data is far more flexible and rich than traditional survey measures—enabling rapid, later analysis for questions not articulated or of interest during initial study development. Finally, somewhat beyond initial expectations, we are supplying data relevant to retiring BHP gaps using these NIPSSA techniques. We have designed techniques and are collecting and analyzing data from additional analog studies where we are collecting interpersonal task communications data in text and speech to enable further detailed analyses of team dynamics using similar and alternate NIPSSA techniques.

Reference: Fredrickson BL, Losada MF (2005). "Positive affect and the complex dynamics of human flourishing." Am Psychol 60 (7): 678–86.

During the last program year, we identified three potential analog studies and were attempting to prioritize and select among them. To date, in partial testimony to the ease and speed with which data can be analyzed using our tools, we have participated to some extent in all three, and are examining data from a fourth as well.

1. A bed rest analog allowed us develop our general techniques and to collect long-duration journal data for evaluating NIPSAA techniques for individual psychological state data under controlled and monitored conditions which included some of the physical duress and isolation that astronauts suffer. Data has been collected on 11 subjects to date and analyzed.

2. The UCF/gOE team roles experiment is allowing us to extend our techniques to collect interactive communications from a team involved in tasks analogous to ship mission operations and generate novel team task- or function-based NIPSAA’s. Data collection is beginning this month.

3. HI-SEAS team habitat analog offered the best analog to true astronaut living and working conditions and allowed the capture of crew-to-ground communications, as well as individual journals. The study is complete but to date we have only received journal and survey data (no crew-ground communications) and have begun analysis of this.

4. AMO is an ongoing study of simulated crew-mission operations under varying time lag conditions. We have recently begun examining transcribed speech data from this study to both validate our NIPSSA techniques and seek effects of time lag on social interaction behaviors.

Due to timing of the studies most findings from this year come from the bed rest analog journal data, with some additions from HI-SEAS.A summary of our findings follows:

• Correlations between our assessments of subjects’ psychological states and attitudes using NIPSSA techniques from free-form journal entries are proving to be regularly correlated with subjects’ own survey responses in the bed rest and, to a lesser degree, HI SEAS studies. This serves to validate our general approach, at least to the extent that it can glean information that more intrusive surveys or more time-intensive human reading and processing of journal entries might. It also serves to focus us on which kinds of NIPSSA analyzers for maximal reliability. States which we can assess through automated journal analysis validated with subject survey data include negative emotion and anxiety, past vs. present focus, focus and positive/negative affect about the (bed rest) study and their participation in it, focus on and sentiment about their own physical state, and focus on self vs. others.

• Latent Semantic Analysis techniques are enabling us to assess the valence of subjects’ writing about specific topics, and to determine some of the associations that drive those feelings. We demonstrate this with regards to the topics of food and ingestion, identifying subjects for whom food is a more central focus of attention and writing, but also those for whom it is a generally positive vs. generally negative topic, as well as specific time periods of more or less focus and affect about it.

• Staff ratings for bed rest participant’s mental states were reasonable predictors of subject’s own ratings, but they sometimes differed significantly (especially about self-reported emotional state), while journals processed using our NIPSSA techniques were frequently better correlated.

• We illustrated multiple, powerful capabilities to process individual subject’s journal entries without a detailed human reading and report topics of interest, subject’s feelings about and associations with those topics, what drives positive or negative valence in an entry (either in general or about a specific topic), etc. These capabilities provide a detailed insight into each unique individual’s thought processes without a substantial investment in specialists’ time.

• We have used these techniques, and both the journal and survey data collected this year to begin identifying general trends across subjects—data that may serve to directly assist in retiring BHP gaps. Chief among these is the findings that (a) although word count for journal entries differed significantly across subjects, it did not regularly differ over time, indicating that there is no a priori reason to expect the effectiveness of journaling to diminish over time, (b) positive affect, the use of positive emotion terms, perception terms and affect terms in general diminish over the 100 day period of bed rest, but negative emotions do not necessarily increase and (c) mentions of physical state tend to correlate with negative feelings about physical state, but mentions decline over time, and (d) in open-topic journals such as these, crews tend to write more on abnormal days and days with good crew-ground interactions which implies that such writing may serve as an indicator of good interactions, but also that examination of bad interactions is not done as deeply.

• Finally, we note that our NIPSSAs are delivering on their promise of rapid assessment of non-intrusive data. We were able to process 2 months of journal and survey data from 5 HI SEAS participants in less than 1 week. Human coding (not to mention reading) of such results could not begin to match that pace. Similarly, upon recently receiving interactive task communication data from the Autonomous Mission Operations study, we were able to process it with our existing power/leadership and team comfort NIPSSAs in under 2 hours, though those data have yet to be reviewed.

Additional progress includes the creation of tool for visualizing the resulting bed rest data to aid in understanding the change of psycho-social measures over time. We also continued NIPSSA development this year, including the definition of multiple recognition categories relevant to the analyses of bed rest and HI SEAS and the initial development of a novel type of interactive task communication NIPSSA which, if validated, will not require speech-to-text transcription. Finally, we are currently involved in planning for a series of team analog studies to be performed in the new Human Exploration Research Analog (HERA) facility during our next program year. HERA will provide unique tests to our techniques as it is planned to yield crew-crew communications (in speech recordings to be transcribed to text), videos, as well as structured variations in workload, tempo and potentially crew-ground interactions.

The results achieved during this program year now demonstrate the viability of one class of non-intrusive psycho-social state detectors to streamline, speed and in some cases, enable, the collection of data to effectively monitor and measure team and individual health and performance fluctuations during autonomous, long duration exploration missions. For journal data, we have been successful at applying NIPSSA techniques to a variety of “live” analog settings to both validate them and learn more about what can be derived from them and, somewhat beyond initial expectations, we are already beginning to supply data relevant to retiring BHP gaps using these NIPSSA techniques. We have designed, identified and are beginning to collect and analyze data from additional analog studies pertinent to other classes of NIPSSAs.

Task progress during this year includes the extension of a prior literature review of available NIPSSA techniques culminating in the development of a table indexing candidate NIPSSA methods and the types of psycho-social states they are capable of identifying. This table currently consists of 165 entries spanning 12 primary categories. After reviewing possible data sources, and prioritizing NIPSSA method maturity vs. desired state assessment vs. data availability, we settled on a parallel focus on two broad data x detection method x psychosocial state combinations. These were selected as having a high likelihood of concurrently (a) being present in future space operations, (b) being assessable by non-intrusive methods, (c) providing data about psychosocial states of interest to NASA, and (d) doing so via automated methods. They are:

Approach #1—Individual Psychological State from Individualized Reflective Log Data (as included in an individual’s journal, diary or more recently, in blogs and tweets).

Approach #2-- Relationships and Team States from Interactive Task Communication Data – that is, data generated during team interactions primarily in working environment.

Due to the challenge of obtaining suitable historical data for testing initial NIPSSA approaches on these two data types and our specialized needs of representative data together with concurrent validation data (assessing the same psychosocial state via other, validated techniques that we could use for correlation analysis with our new, non-intrusive approaches), we were unable to obtain a data set that met all requirements for our first year. This forced a focus on diverse data sets together with creativity in identifying validation data or conditions in our initial experiments this year. It also makes a core goal in Year 2 the production of such paired interaction data with validation data in across a series of analog experiments.

For Individualized Reflective Log Data and Analytic Methods we used a trove of publicly available astronaut journal, blog, and tweet data which NASA itself had collected and was making publicly available. These logs provided a conservative test for our approach due to the expectation that they would contain little evidence of emotional and attitudinal variations, especially of more negative emotions. Emotional content, past/present/future focus, group vs. individual focus and their correlations were identified from the journal entries utilizing James Pennebaker's Linguistic Inquiry and Word Count (LIWC) tool, along with analysis of novel topic categories we created such as references to “space” or a category of crew-related terms. As an example, findings implied nostalgia, melancholy, and perhaps loneliness in the journal entries of one astronaut, along with the tendency to move from a dominance of future tense usages (focusing on new and expected experiences) at the beginning of an ISS mission, to more present tense during the middle of the mission, followed by an increase in both future and past tense usage (perhaps indicative of a broader focus and reflection) toward the end of the mission. Correlations showed specific trends for individual astronauts including a positive correlation of crew terms and anxiety terms in one set of blog entries and a negative correlation of crew usages with both general and positive affect terms in another’s. Sentiment was assessed utilizing our previously pioneered techniques in Latent Semantic Analysis (LSA). Example findings include generally positive valence entries with fluctuations over time and between different astronauts. Additionally, fluctuations in attitudes about specific systems, equipment, procedures, and crew or ground support personnel were tracked in passages where those terms appeared.

For Interactive Task Communication Data and Analytic Methods we first utilized team interaction data in textual chat generated by student subjects interacting in a planetary exploration simulation with tasks explicitly emulating astronaut missions and work. Initial analyses utilized our previously created algorithms for deriving dynamic power relationships from politeness usages between individuals. We successfully showed variations in relationships between the group interaction styles. An independent variable within the experimental design allowed us a specific, validated test: Half of all trials included a “Mission Commander” (a confederate) and who directed explorations activities according to a schedule, while the other half were “autonomous” in that the teams negotiated their own schedule and activities among themselves. Our power detection NIPSSA was successful at identifying the power exerted by the mission controller in the team interaction data and consistently assigned him/her the highest power rating across all 7 team trials in that condition.

Given the similarity of textual communications in this planetary exploration simulation to radio communications in space flight, we have begun to analyze transcriptions of communications from the Apollo missions using the same NIPSSA approach. In one particularly interesting, initial finding, we have found that results of our processing of the Apollo 13 communication logs look radically different than those for other Apollo missions. CapCom (the “Capsule Communicator”—the primary communicant for all of Ground Control to the capsule) for Apollo 13 was communicating much more frequently with the astronauts and was assessed as exerting radically more power or authority than in other missions, or than he did prior to the O2 incident even within the Apollo 13 mission.

These initial successes in the team interaction data approach have led to ongoing follow on studies which are still in progress to 1) Rate the simulation data on team power relationships and determine inter-rater reliability of these ratings and provide a finer-grained correlate for our power assessment NIPSSA, 2) Applying the same algorithms to Apollo Radio Communications (an initial result is described above), 3) Constructing another NIPSSA, using the same core software techniques, to score "team comfort" (defined as conditions when the team is operating on a routine, well-understood task without undue pressure from work or social sources) to, ideally, provide a correlate for team performance, at least on routine tasks.

Our initial work shows promising tools and methods, and has identified some tantalizing, possible team and individual trends (such as the tendency for a powerful leader to increase team work focus to the point of reducing social interactions or the possible tendency for individuals to go through an “arc” of focus on the future and present in their reflections at the beginning of a mission, the present during the middle, and to shift focus to past and future toward the end); however, our NIPSSAs are far from fully validated, nor is the set complete. Much more work could and should be done. The lack of corresponding, independent validation data in almost all of the above analyses needs to be corrected in future studies. Also, through our analyses and discussions with other NASA performers this year, it is apparent that other NIPSSA tools, especially in the team interaction domain and based on team process and/or role behaviors, might provide more useful data. For both of these reasons, we are focusing on participating in several analog studies in the second year of our effort. This multi-faceted approach is designed both to continue the development and validation of our varied NIPSSA techniques and also to provide and distribute the assistance of our tools as broadly across as varied a set of data types and conditions as possible.