Web-Based, Interactive, Interest-Based Negotiation Training for Managing Conflict in Isolated Environments: Opportunistic Study With an e-Survey
Notice bibliographique
Résumé
BACKGROUND: Effective negotiation in relationships is critical for successful long-duration space missions; inadequate conflict resolution has shown serious consequences. Less desirable forms of negotiation, including positional bargaining (eg, negotiating prices), can exacerbate conflicts. Traditional positional bargaining may work for simple, low-stakes transactions but does not prioritize ongoing relationships. High-stakes situations warrant interest-based negotiation, where parties with competing interests or goals collaborate in a mutually beneficial agreement. This is learnable but must be practiced. Refresher training during conflicts is important to prevent out-of-practice crew members from using less effective negotiation techniques. Training should be self-directed and not involve others because, on a space mission, the only other people available may be part of the conflict. OBJECTIVE: We aimed to develop and test an interactive module teaching principles and skills of interest-based negotiation in a way that users find acceptable, valuable for learning, and enjoyable. METHODS: Using a web-based, interactive-media approach, we scripted, filmed, and programmed an interest-based negotiation interactive training module. In the module, the program mentor introduces users to "The Circle of Value" approach to negotiation and highlights its key concepts through interactive scenarios requiring users to make selections at specific decision points. Each selection prompts feedback designed to reinforce a teaching point or highlight a particular negotiation technique. To evaluate the module, we sought populations experiencing isolation and confinement (an opportunistic design). This included 9 participants in isolated, confined environments in the Australian Antarctic Program and the Hawai'i Space Exploration Analog and Simulation Mars simulation, as well as a subset of people who self-identified as being isolated and confined during the COVID-19 pandemic. Feedback was collected from participants (n=54) through free-response answers and questionnaires with numerical scaling (0=strongly disagree to 4=strongly agree) at the end of the module. RESULTS: In total, 51 of 54 (94%) participants found the activity valuable for learning about conflict management (identified by those who selected either "somewhat agree" or "strongly agree"), including 100% of participants in the isolated and confined environment subset (mode=3). In total, 79% (128/162) of participant responses indicated that the module was realistic (mode=3), including 85% (23/27) of responses from participants in isolated and confined environments (mode=3). Most participants felt that this would be particularly valuable for new team members in an isolated, confined environment (46/54, 85% of all participants, mode 4; 7/9, 78% of the isolated and confined environment subset, mode 3) as well as veterans. CONCLUSIONS: This module offers a self-directed, consistent approach to interest-based negotiation training, which is well received by users. Although the data are limited due to the opportunistic study design, the module could be useful for individuals in isolated and confined environments and for anyone involved in high-stakes negotiations where sustaining relationships is essential.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».