We are very pleased to report that a manuscript for our collaborative research on Precognitive Remote Viewing has been published!
Here is the full citation:
Mossbridge, J., Cameron, K., & Boccuzzi, M. . (2024). State, Trait, and Target Parameters Associated with Accuracy in Two Online Tests of Precognitive Remote Viewing. Journal of Anomalous Experience and Cognition, 4(1), 88–121. https://doi.org/10.31156/jaex.24743
A PDF of the full paper can be downloaded HERE.
Abstract:
Objective. To better characterize the relations between accuracy on precognitive remote viewing (PRV) tasks and potentially relevant trait, state, and target parameters, we gathered PRV data in two online experiments and examined accuracy relative to: sex-at-birth, gender, age, anxiety, unconditional love, and target interestingness. Method. In experiment 1 we used a forced-choice, uncontrolled-time, self-judged PRV task for which 682 unpaid participants contributed a total of 5,432 trials. Experiment 2 used a free-response, controlled-time, independently judged PRV task for which 307 paid participants each contributed a single trial. In neither case were the participants pre-screened for precognition ability. Results. In experiment 1 (forced-choice PRV task), there was no significant target precognition and no effect of age on PRV performance, but we found a complex effect of sex-at-birth. We also found that targets most likely to be correctly predicted were also more likely to be judged as interesting compared to targets most likely to be incorrectly predicted; a pre-registered analysis confirmed this effect. In experiment 2 (free-response PRV task) we found significant target precognition, no effect of age on performance, and a weak and indirect effect of gender. Feelings of unconditional love and anxiety were both correlated with higher accuracy in experiment 2. Again, target interestingness was positively related to accuracy. Conclusion. These results suggest that accuracy on PRV tasks is related to the emotional state of participants and target interestingness, and that task characteristics mitigate overall performance. We provide recommendations for future research based on these observations.
Objective. To better characterize the relations between accuracy on precognitive remote viewing (PRV) tasks and potentially relevant trait, state, and target parameters, we gathered PRV data in two online experiments and examined accuracy relative to: sex-at-birth, gender, age, anxiety, unconditional love, and target interestingness. Method. In experiment 1 we used a forced-choice, uncontrolled-time, self-judged PRV task for which 682 unpaid participants contributed a total of 5,432 trials. Experiment 2 used a free-response, controlled-time, independently judged PRV task for which 307 paid participants each contributed a single trial. In neither case were the participants pre-screened for precognition ability. Results. In experiment 1 (forced-choice PRV task), there was no significant target precognition and no effect of age on PRV performance, but we found a complex effect of sex-at-birth. We also found that targets most likely to be correctly predicted were also more likely to be judged as interesting compared to targets most likely to be incorrectly predicted; a pre-registered analysis confirmed this effect. In experiment 2 (free-response PRV task) we found significant target precognition, no effect of age on performance, and a weak and indirect effect of gender. Feelings of unconditional love and anxiety were both correlated with higher accuracy in experiment 2. Again, target interestingness was positively related to accuracy. Conclusion. These results suggest that accuracy on PRV tasks is related to the emotional state of participants and target interestingness, and that task characteristics mitigate overall performance. We provide recommendations for future research based on these observations.
Acknowledgments:
The authors would like to thank the Bial Foundation for generously funding the first author during the course of this study (Bial grants 2014_260, 97_16, with 369/20 specifically covering the second analysis set). We are also grateful to Theresa Cheung, who funded the website for the book The Premonition Code, which allowed us to gather data for the first analysis set.
The authors would like to thank the Bial Foundation for generously funding the first author during the course of this study (Bial grants 2014_260, 97_16, with 369/20 specifically covering the second analysis set). We are also grateful to Theresa Cheung, who funded the website for the book The Premonition Code, which allowed us to gather data for the first analysis set.
