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Suzanne Bell

Publications and source records attributed to Suzanne Bell.

24 records · Page 2
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Behavioral Health Benefits of the ISS Pick-and-Eat Crop Growth System

Summary: We summarize findings related to assessing the pick-and-eat salad-crop productivity and acceptability of the ISS food system as a countermeasure to maintain behavioral health in long-duration spaceflight. BACKGROUND Plants are a potential countermeasure for the stresses of living in space. Caring for plants and eating fresh food have been shown to serve as a psychological benefit for previous astronauts and for others in analogous environments such as Antarctica [1,2]. Gardening can be therapeutic in terrestrial settings [3]. These effects may carry over or be more pronounced in austere environments such as spaceflight. It can reduce stress and increase sensory stimulation and enjoyment [2]. Growing crops may offer astronauts meaningful and engaging work as they care for living things in an austere environment away from Earth’s nature and as they provide sustenance for their crew. We examined the extent to which interacting with plants (e.g., tending to, consuming) was related to behavioral health outcomes in long-duration space missions. METHOD Participants were 27 astronauts that interacted with the plant system VEG-04, VEG-05, and HRF-VEG (VEG-03 I-L, PH-04). In total, there were 106 in-flight observations. Participants completed monthly measures of mood and well-being, enjoyment and time spent performing specific crop growth and consuming the plants, meaningfulness, performance, connections with others and the Earth, desire to work with and eat plants, and experiences with struggling or dying plants. Higher ends of the 7-point Likert scale indicated more positive outcomes, lower ends of the scale were anchored with more negative outcomes, and the scale midpoints indicated neutral positions. Participants selected a specific survey version based on whether they interacted with the plant system(s) or not, and we included only the scores from the crewmembers that participated in any given activity. RESULTS & DISCUSSION Results indicated that participants generally rated tasks related to the plants and crop growth as enjoyable. Consuming the harvested plants and voluntary viewing were the most enjoyable activities. Tending to the plants was reported as moderately enjoyable, indicating BHP benefits from this work task. The BHP impacts of whether the task was engaging, meaningful, supported well-being, or was demanding for a crewmember were generally positive and increased over time. As shown in the Figure, working with plants was reported as more engaging, meaningful, and beneficial to well-being over time, while the demand from the task was moderate to low and consistent over time. Engaging, meaningful, and supporting well-being were strongly, positively correlated with each other, which is consistent with research that suggests engaging and meaningful work can support well-being. Plant activities such as voluntary viewing, watering, harvesting, and consuming, were positively related to task engagement and meaning, and enjoyment and well-being. Findings suggest that working with plants and consuming them can be a behavioral health countermeasure for long-duration spaceflight. REFERENCES [1] Schlacht I, et al. (2020) Impact of plants in isolation: The EDEN-ISS…in Antarctica. In Advances in Human Factors of Transportation, Washington DC. [2] Vessel E, Russo S (2015) Effects of reduced sensory stimulation and…countermeasures…. NASA/TM-2015-218576. [3] Odeh R, Guy C (2017) Gardening for therapeutic people-plant interactions during LDSM. Open Agriculture, 2(1), 1-13. ACKNOWLEDGEMENTS This research was supported by the Human Health and Performance Contract NNJ15HK11B, and NASA grant MTL #1075 (PI G.D. Massa).

countermeasure↗
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Predicting Team Functioning in Long Term Space Missions Using Acoustic and Linguistic Measures

Maintaining optimal team functioning is critical for long-duration space exploration missions, yet traditional monitoring methods, such as self-reports and wearable sensors, often impose operational burdens or suffer from bias. This paper investigates a non-intrusive speech-based artificial intelligence (AI) framework to predict degradations in team functioning using data from the Human Exploration Research Analog (HERA) of the U.S. National Aeronautics and Space Administration (NASA). Using acoustic features, linguistic descriptors, and semantic embeddings, we evaluate static non-linear and temporal machine learning models to predict both objective (task accuracy) and subjective (self-reported efficacy and cohesion) team functioning outcomes. Results indicate that temporal models outperform static approaches, with prediction of objective task accuracy in Team Interaction Battery (TIB) improving from near chance to 71%. Self-reported outcomes, including team efficacy and cohesion, are predicted more reliably than task performance, achieving balanced accuracies of up to 85.56% and 78.12%, respectively, and are found to be most strongly associated with acoustic features. In a second interdependent task, the MMSEV–EVA, accuracies of up to 78% are achieved using temporal models with acoustic features. Furthermore, incorporating just 1–2 days of team-specific historical data systematically improved performance, and acoustic markers from informal pre-task interactions provided modest predictive gains. Finally, while automated preprocessing yielded viable accuracy, humancorrected data provided moderate performance gains, though transcription error rates did not significantly correlate with model performance. These findings highlight the potential of speech as a passive, high-fidelity monitoring tool for autonomous habitats.

Temporal modeling↗