How Smokers Change Their World and How the World Responds: Testing the Oscillatory
            Nature of Micro-Psychokinetic Observer Effects on Addiction-Related Stimuli

Dechamps, Moritz C.; Maier, Markus

doi:10.31275/2019/1513

Cited by 10 publications

(30 citation statements)

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“…The BF curve variation of human data across time seems to be more pronounced than those obtained from most simulated data sets. This fluctuation in the human data creates an anomaly that fits with von Lucadou et al’s [ 23 ] propositions and is in line with Dechamps and Maier’s predictions [ 37 ]. The data files including the simulation data and the original data from Maier et al (Exp.…”

Section: Resultssupporting

confidence: 86%

“…This additional assumption would help distinguish MPI dependent decline effects from simple regressions to the mean effects. They suggested that the temporal change of the effect across time might indeed follow a systematic oscillation pattern, whereas the overall mean score of replications should not statistically deviate from chance expectation (see also [ 37 ]). In this way, all assumptions of quantum mechanics, including the randomness postulate, would be fulfilled, and scientific evidence for such effects would be shifted from an analysis of the samples’ mean score against chance to systematic temporal oscillations.…”

Section: Resultsmentioning

confidence: 99%

“…To test the FFT results from the human data against chance occurrence, all 1164 amplitudes obtained from the FFT of the human data set were then added up creating a sum score of the amplitudes obtained from all tested frequencies of this set. In the same way for each of the 10,000 simulations the sum score of amplitudes was computed (Dechamps and Maier [ 37 ] used a similar but less elegant test). The distribution of the sum scores of amplitudes across all simulations served as the null distribution (see Fig 4C ).…”

Section: Resultsmentioning

confidence: 99%

“…In the third subsection, three exploratory analyses address the temporal variation of the sequential BF within the original Study 4 of [1] combined with the newly collected data in the study presented here. These analyses explored the temporal change in evidence for the effect across time (from the initial detection of the effect to the later replication attempt), as suggested by [35][36][37]; see also [23]. These analyses tested non-random fluctuations within the combined data sets against 10,000 simulated data sets.…”

Section: Resultsmentioning

confidence: 99%

“…In this way, all assumptions of quantum mechanics, including the randomness postulate, would be fulfilled, and scientific evidence for such effects would be shifted from an analysis of the samples' mean score against chance to systematic temporal oscillations. Dechamps and Maier [37] developed three analytical methods to test these assumed systematic oscillations against random fluctuations. The three methods were designed to test the oscillations of the effect for data that combined the initial effect detection and replication attempts across time.…”

Section: Plos Onementioning

confidence: 99%

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A preregistered multi-lab replication of Maier et al. (2014, Exp. 4) testing retroactive avoidance

et al. 2020

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The term “retroactive avoidance” refers to a special class of effects of future stimulus presentations on past behavioral responses. Specifically, it refers to the anticipatory avoidance of aversive stimuli that were unpredictable through random selection after the response. This phenomenon is supposed to challenge the common view of the arrow of time and the direction of causality. Preliminary evidence of “retroactive avoidance” has been published in mainstream psychological journals and started a heated debate about the robustness and the true existence of this effect. A series of seven experiments published in 2014 in the Journal of Consciousness Studies (Maier et al., 2014) tested the influence of randomly drawn future negative picture presentations on avoidance responses based on key presses preceding them. The final study in that series used a sophisticated quantum-based random stimulus selection procedure and implemented the most severe test of retroactive avoidance within this series. Evidence for the effect, though significant, was meager and anecdotal, Bayes factor (BF 10 ) = 2. The research presented here represents an attempt to exactly replicate the original effect with a high-power ( N = 2004) preregistered multi-lab study. The results indicate that the data favored the null effect (i.e., absence of retroactive avoidance) with a BF 01 = 4.38. Given the empirical strengths of the study, namely its preregistration, multi-lab approach, high power, and Bayesian analysis used, this failed replication questions the validity and robustness of the original findings. Not reaching a decisive level of Bayesian evidence and not including skeptical researchers may be considered limitations of this study. Exploratory analyses of the change in evidence for the effect across time, performed on a post-hoc basis, revealed several potentially interesting anomalies in the data that might guide future research in this area.

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Section: Resultssupporting

confidence: 86%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

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A preregistered multi-lab replication of Maier et al. (2014, Exp. 4) testing retroactive avoidance

et al. 2020

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Bioenergy Treatment for Improving Well-Being: A Meta-Analysis

Walach

Marmann²

2023

Complement Med Res

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Background: Bioenergy treatment devices have become popular and widely available for self-treatment to improve well-being. We meta-analyzed eight very similar studies of the Healy device to assess the joint effect size. Method: Eight studies with similar designs, some active controlled, some waitlist controlled, testing the Healy bioenergy device were meta-analyzed. They were conducted by the producer of the device. An additional search with appropriate keywords revealed no additional studies Result: The overall effect size across studies, combining all active arms and averaging outcome measures is Hedge’s g = 0.757 (random effects model, I2 = 85.8; z = 6.57; p < .0001). The stronger active intervention against control yields a heterogeneous g = 0.825 (random effects, I2 = 82.5; z = 7.77; p < .0001). Active treatments against each other result in a significant g = 0.29 (fixed effects, I2 = 0.0; z = 8.34; p < .0001). Discussion: The highest effect sizes are produced by a measure of coherence, followed by the WHO5 wellbeing questionnaire, the Perceived Stress Scale, with the Measure Your Own Medical Outcome Profile resulting in the smallest effect size. Heterogeneity can partially be explained by the type of control, with active control producing smaller, and wait-list controls larger outcomes. Another source of heterogeneity is the sequencing of studies: Effect sizes grow for three studies, which were similar and then fell and remained very similar for the rest of the studies. A limitation of this analysis is the fact that the studies were all done by the R&D-Department of the producer of the device, and an independent confirmation would be desirable. Conclusion: The Healy device is an effective bioenergy device for self-treatment to improve general well-being in healthy individuals.

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Temporal Change of Observer Effects on Quantum Randomness: Testing the Oscillatory Nature of Micro-psychokinetic Effects on Addiction-related Stimuli

Dechamps,

Maier

2022

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How Smokers Change Their World and How the World Responds: Testing the Oscillatory Nature of Micro-Psychokinetic Observer Effects on Addiction-Related Stimuli

Cited by 10 publications

References 0 publications

A preregistered multi-lab replication of Maier et al. (2014, Exp. 4) testing retroactive avoidance

A preregistered multi-lab replication of Maier et al. (2014, Exp. 4) testing retroactive avoidance

Bioenergy Treatment for Improving Well-Being: A Meta-Analysis

Temporal Change of Observer Effects on Quantum Randomness: Testing the Oscillatory Nature of Micro-psychokinetic Effects on Addiction-related Stimuli

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