Some recent papers by P. Lush and colleagues have argued that the rubber hand illusion (RHI), where participants can feel a rubber hand as their own under appropriate multisensory stimulation, may be caused mainly by hypnotic suggestibility and expectations (demand characteristics). These papers rely primarily on a study with 353 participants who took part in a RHI experiment carried out in a classical way with brush stroking. Participants experienced a synchronous condition where the rubber hand was seen to be touched in synchrony with touch felt on their corresponding hidden real hand, or the touches were applied asynchronously as a control. Each participant had a related measure of their hypnotisability on a scale known as the Sussex-Waterloo Scale of Hypnotisability (SWASH). The authors found a correlation between the questionnaire ratings of the RHI in the synchronous condition and the SWASH score. From this, they concluded that the RHI is largely driven by suggestibility and further proposed that suggestibility and expectations may even entirely explain the RHI. Here we examine their claims in a series of extensive new analyses of their data. We find that at every level of SWASH, the synchronous stimulation results in greater levels of the illusion than the asynchronous condition; moreover, proprioceptive drift is greater in the synchronous case at every level of SWASH. Thus, while the level of hypnotisability does modestly influence the subjective reports (higher SWASH is associated with somewhat higher illusion ratings), the major difference between the synchronous and asynchronous stimulation is always present. Furthermore, by including in the model the participants’ expectancy ratings of how strongly they initially believed they would experience the RHI in the two conditions, we show that expectations had a very small effect on the illusion ratings; model comparisons further demonstrate that the multisensory condition is two-to-three-times as dominant as the other factors, with hypnotisability contributing modestly and expectations negligibly. Thus, although the results indicate that trait suggestibility may modulate the RHI, presumably through intersubject variations in top-down factors, the findings also suggest that the primary explanation for the RHI is as a multisensory bodily illusion. The rubber hand illusion (RHI)  arises fThe initial findings of Botvinick and Cohen have stimulated a vast amount of research; according to Google Scholar, the study has had more than 4,400 citations at the time of writing. Part of the reason for the RHI’s popularity is that it is relatively robust, easy to replicate, and flexible to adapt to various experimental settings. It also works well in laboratory exercises for psychology undergraduates, for public demonstrations in popular science events, and in experiments with neurological or neurosurgical patients. Our own experience of public events is that members of the public who are completely naïve to the illusion, typically visibly show their surprise at the moment that the illusion of ownership over the rubber hand occurs. The subjective illusion is often quantified with questionnaires and rating scales  in line In addition to questionnaire rating scales and perceptual judgements, several indirect behavioural and physiological measures for the RHI have been developed. The point of these measures is to provide more objective evidence that the illusion is associated with changes in multisensory body representation, as one would expect from a perceptual bodily illusion. One commonly used such test is the “proprioceptive drift” that registers a change in hand position sense towards the location of the rubber hand during the illusion . The levAnother objective measure is based on the cross-modal congruence task , which pAn indirect physiological index of the RHI is to register changes in autonomic arousal that occur when a sharp or crushing object  is seen threatening the rubber hand; this is called the threat-evoked skin conductance response (SCR) . CriticaIn addition to these three classic tests, many other behavioural and physiological tests have been proposed in the literature . For exaAn equivalent to the RHI has been shown to operate with a virtual hand in virtual reality , and manFinally, the rubber hand illusion is supported by neuroscience. In functional magnetic resonance imaging (fMRI) experiments, the RHI has been associated with increased blood oxygenation level-dependent (BOLD) contrast signals in the premotor cortex and posterior parietal and subcortical regions associated with multisensory integration of body-related sensory signals . MoreoveThe theoretical understanding of the RHI has concentrated on the multisensory integration of visual, tactile, and proprioceptive information . CentralHowever, as with any psychological or perceptual phenomenon, there will still be individual differences between people. Not everyone experiences the RHI, and although this is not unique for a perceptual illusion, the response variables tend to be relatively varied across individuals. In line with the multisensory account, individual differences in the sensitivity in arm position sensing  or in thMoreover, individual differences at the cognitive level might also influence the illusion experiences of participants through top-down mechanisms and modulate multisensory integration and the evaluation of this experience at a post perceptual metacognitive level. Such individual differences have been previously studied; for example, R2 = 0.09) in the synchronous condition and a weaker relationship with proprioceptive drift (R2 = 0.02). Similar relationships were observed between hypnotic suggestibility and the illusion ratings in the asynchronous condition (R2 = 0.09). Lush and colleagues did not simply conclude that trait hypnotic suggestibility may modulate the RHI in line with previous studies but went much further and suggested that the RHI may be entirely explained by hypnotic suggestibility, expectations, and demand characteristics; they also suggested that multisensory mechanisms may only play a minor role, if any. A commentary : 114 received instructions that the RHI effect would be stronger in the synchronous condition, 115 were told that the effect would be strongest in the asynchronous condition, and 124 were given no instruction about which of the two conditions should elicit the illusion. The participants then had to rate their expectancies of whether they thought they would experience the rubber hand as their own in each of the two conditions (see further below). Lush and colleagues’ hypothesis was that the RHI expectancy ratings would differ across conditions depending on the type of instruction, a result that was not supported by the data; therefore, all the data were pooled and analysed as a single sample. These data (n = 353) were used in the current analyses.Next, the participants received pre-recorded information about the RHI via headphones. The participants were explicitly told how the RHI illusion works and that ‘‘the combination of information from touch and vision induces an illusory experience of ownership over the rubber hand.’’The participants were then tested on the RHI using their right hand and a rubber right hand. They each experienced both the synchronous and asynchronous conditions of the rubber hand experiment in counterbalanced order. The participants sat in front of a table, and one of 16 different experimenters sat on the opposite side. The rubber hand was placed in front of the participant inside a box, and the participant could see the fake hand through a square window on top of the box. The participant’s real hand was kept still inside the box in a visually occluded location 20 cm to the right of the rubber hand. The experimenter used a paintbrush to stroke the rubber hand’s middle finger at approximately 1 Hz for 60 s while simultaneously stroking the middle finger of the participant’s real hand with an identical brush either synchronously or asynchronously.The RHI was measured following usual practice with a questionnaire and a proprioceptive drift test. There were three crucial questionnaire statements scored on a Likert scale ranging from –3 (strongly disagree) to 3 (strongly disagree):s1: It seemed as if I were feeling the touch of the paintbrush in the location where I saw the rubber hand touched.s2: It seemed as though the touch I felt was caused by the paintbrush touching the rubber hand.s3: I felt as if the rubber hand was my hand.These questions were administered after each of the synchronous and asynchronous exposures. The three question scores were combined into their average to obtain an “RHI score”; hence, there were two variables as follows:ss = (s1 + s2 + s3)/3 (synchronous)sa = (s1 + s2 + s3)/3 (asynchronous)s4), but we did not use the ratings from this statement in the current analyses since the illusion statements are more informative for the current research questions and only this single control statement was included .The study also included a fourth control statement (dpdsync for the synchronous condition (difference in proprioceptive drift for the synchronous condition) and dpdasync for the asynchronous condition.In addition, participants were asked to point without visual feedback towards where they felt their  right hand to be both before and after the rubber hand procedure. The window on top of the box was closed so that the participants could no longer see the rubber hand, and a ruler was placed on top of the box. The participants were asked to indicate the point on the ruler where they thought the index finger of their right hand was located inside the box, and the position was noted by the researcher. The proprioceptive drift is the difference between this indicated real right index finger location after the illusion induction and the location before. We denote these differences by mean(ss) is high  for the synchronous condition, while mean(sa) is significantly lower  for the asynchronous condition. Critically, mean(dpdsync) > mean(dpdsync) is taken as proprioceptive drift evidence of a successful RHI induction.The typical RHI findings are that swash and the RHI response variables and not the regression line intercepts, a critical aspect of the results was missing from the original article. Next, we present the data descriptively and show through a graphical analysis that the distributions of the questionnaire scores differ substantially between the asynchronous and synchronous conditions independently of the swash scores. Following this, we continue with a descriptive analysis of the proprioceptive drift results and again show a difference between the asynchronous and synchronous conditions independently of swash. In these descriptive analyses, we are only reporting the actual data and not attempting statistical inference. Where significance values are presented, these are only to illustrate the strength of a correlation or difference for purely descriptive purposes.In the Section “Results,” we first conduct a normal linear regression in line with the correlational analysis by swash. We use this model to generate new pseudorandom data and compare these with the original data, showing that the model predicts the results well. Whether we use normal linear regression, descriptive analysis or the Bayesian model, we find that the synchronous condition results in stronger illusion scores than the asynchronous condition for the questionnaires and that the proprioceptive drift is greater for synchronous than asynchronous conditions. Although swash is positively correlated with the RHI questionnaire score, the synchronous scores are greater overall than the asynchronous scores, indicating the major role of multisensory integration, with hypnotisability as a secondary modulating individual difference factor. Finally, we compare different models and examine the relative importance of hypnotisability and expectations  and show that the contribution of the multisensory conditions dominates.For statistical inference, we present a Bayesian statistical model that brings all the analyses together and demonstrates major differences between the asynchronous and synchronous responses independently of stata.com) for the descriptive analysis and rstan,2 the R interface to Stan (see below) for the Bayesian analysis. For convenience, the details of the different analyses and their rationale are described in the respective Section “Results” below.The statistical software used in our analysis was Stata 16  and in the case of sa on swash R2 = 0.09 (P < 0.0005).3 Based on their interpretation of these results, As described above, using the pooled ss and sa) on swash. For ss, we found that the slope is 0.58 , and for sa, we found that the slope is 0.68 , and these slopes were emphasised by Lush and colleagues. This leads to the conclusion that ss and sa are positively associated with swash, as reported by ss, we find that the intercept is 0.33 . For sa it is –1.47 . From this, we can conclude that even though there may be a positive association between the RHI questionnaire score and swash, this corresponds to two almost parallel lines with a positive slope, but the line for ss is above that of sa . What this means is that even though swash has an effect, as reported by swash, the synchronous score is greater than the asynchronous score.However, P < 0.0003).However, there are some important considerations to be taken into account with this type of analysis. The first is that the normality assumption is violated. The residual errors of a regression fit should be approximately normally distributed. Second, there are several influential points that may influence the regression line, which is an important consideration in linear regression analyses. This can be shown by standard leverage against normalised squared residual error plots . Technicss and sa scores are bound between –3 and 3, yet there is nothing in the model that takes into account these constraints; this means that it might be possible for fitted values to be outside of this range . In fact, the ranges of fitted values are squashed compared to the ranges of ss and sa, which are both from –3 to 3. The fitted values for ss range from 0.33 to 2.50, and the range for sa is from –1.47 to 1.08. Especially in the case of ss, there is quite a difference between the range of observed and fitted values.Third, the statistical model is not appropriate to the range of values of the response variables. The swash; i.e., they are the residual errors of the regression. We note that after eliminating the linear influence of swash, there remains an observable difference between the two distributions. The weight of the synchronous distribution is clearly shifted towards higher affirmative scores  the distributions of ss and sa would be similar since the multisensory integration aspect (whether the stimulation were synchronous or asynchronous) would have little effect; more importantly, we would expect that (ii) for greater values of swash, the effect of multisensory integration should be overridden by the hypnotisability effect. The 70th and 90th percentiles of swash are 2.00 and 2.64, respectively. ss and sa across all n = 353 participants. swash > 2.00 (n = 103). swash > 2.64 (n = 36).A correlation is a single statistic that summarises the degree of linear relationship between two variables, yet it may not well represent the full relationship between them, especially when underlying distributions are not considered. In this section, just by examining the raw data, a quite different picture emerges compared to only considering correlations. If there was a dominating effect of ss, and this hardly varies for increasing levels of swash. For the asynchronous cases, the distributions are essentially uniform. In case of interest, the Kolmogorov–Smirnov test rejects the null hypotheses that the asynchronous and synchronous samples are from the same distribution in each case .As can be seen in swash on the questionnaire scores, we plotted the proportions of relatively high scores  and high scores  for each value of swash from 0 to 2.5 in steps of 0.1 (It is not possible to go much higher than 2.5 because n decreases too much). Let propsa ≥ 1(sw) be the proportion of observations with sa ≥ 1 conditional on swash > sw, and similarly for propss ≥ 1(sw) for the synchronous case . Similarly, for propsa ≥ 2(sw), propss ≥ 2(sw) for scores ≥ 2. We computed the pairs resulting in 26 coordinates:To further examine the possible impact of sa, ss ≥ 1. It is clear that in these data, there is a very strong and essentially constant relationship, with the synchronous case being substantially greater independent of the level of swash. Similarly, sa, ss ≥ 2. Of course, in this case, the proportions are lower, but the same relationship holds; at every level, the synchronous proportions are higher than the asynchronous proportions in these data. Although the level of hypnotisability increases the likelihood of higher illusion scores (in line with the reported correlations and previous work), the dominant factor in these data is whether the stimulation is synchronous or asynchronous. In other words, participants who are more hypnotisable are somewhat more likely to give higher scores, but multisensory integration maintains a difference between the asynchronous and synchronous conditions. We have presented these results as they are in the underlying data without any statistical inference. We turn to that in Section “A Statistical Model for the Questionnaire Data.”dpdsync for synchronous drift and dpdasync for asynchronous drift. For dpdsync (proprioceptive drift in the synchronous condition), we observed R2 = 0.02 (P = 0.011) and for dpdasyncR2 = 0.00 (P = 0.45), which again replicates Lush and colleagues’ findings. Moreover, since the regression indicates that the slope for the synchronous case is positive  but the slope for the asynchronous case is not , and the intercepts are not significantly different from 0 in both cases, again this means that for every level of swash, the regression lines indicate that the drift for the synchronous case is greater than that for the asynchronous case.Recall that for proprioceptive drift, there are two response variables: Here, we present a statistical model that overcomes the three problems mentioned in Section “Normal Linear Regression for the Questionnaire Scores,” namely, (i) the distributions of the response variables do not fit the underlying assumption of normality, (ii) there are influential points, and (iii) the questionnaire response variables are bound to the interval , which was not taken into account in the analysis.ss and sa, these are linearly transformed into the range  . We call these transformed response variables for ss and sa, pss, pas ∈ , respectively. Instead of the assumption of a normal distribution, we use the Beta distribution as a model for these new bounded response variables, conditional on the parameters. As seen from Instead of using Beta distribution, which has mean The Beta distribution has two parameters, α > 0 and β > 0, referred to as the y is a response variable (pss or pas) and x is a covariate (swash). Then, the likelihood  is:Suppose that which ensures that the mean is μ. The parameter ϕ > 0 is not of any interest here.0 + β1x , so that no matter what the value of this expression, μ is in the correct interval. Typical choices are the “inverse logit” function or the cumulative distribution function of the standard normal distribution. We use the first . Hence,Since μ has to be constrained to be in the interval , we need a “link function” that relates μ to the linear expression in the covariate, η = βThe prior distributions chosen are “weakly informative” :0, β1 are –20 to 20 and for ϕ 2.4 to 55.7. Hence, the prior distributions have very wide support, but in any case, because the dataset is large, these priors will be overwhelmed by the data.This means that the prior distributions are proper probability distributions but with wide variance. Note that the prior  95% credible intervals for βpas, these parameters are denoted βpas,0, βpas,1, ϕpas, and for pss, βpss,0, βpss,1, ϕpss.For the response variable n = 353 observations , i = 1, 2, n. We use the Stan probabilistic programming language (4 through the rstan interface (see text footnote 2) to derive posterior distributions for the parameters; i.e., the distributions are updated based on the data. Note that this is one overall model for both pas and pss simultaneously and not two separate models.We have language 4 throughStan was executed with 2000 iterations using 4 chains. All Rhat = 1, indicating that the 4 chains mixed and converged without problems. The Stan programs that accompany this paper are available and can be executed online–see pss,1 and βpas,1 are in the positive region, indicating the positive association between pas and swash and between pss and swash. Moreover, from the means of these distributions and the credible intervals, it can be seen that the slopes for pss and pas are similar. However, considering the intercepts, the probability that βpss,0 > 0 is 0.916, whereas the probability that βpas,0 < 0 is 1.000. Hence, the results show that the relationship between the response variables and swash follows two almost parallel curves, but the asynchronous curve is considerably lower than the synchronous curve at every level of swash. This corresponds to the findings of Section “Normal Linear Regression for the Questionnaire Scores.”pas, pss for any level of swash, simply as the posterior distribution of μ using η = β0 + β1swash. swash = 0, 1, …, 5. It is apparent that the asynchronous and synchronous RHI scores increase with increasing values of swash, as would be expected from the correlations reported in swash, with the mean synchronous scores always greater than the mean asynchronous scores with high probability. swash. Note that in these data, the median level of swash is 1.6, and the mean is 1.62. Obtaining a sample of people with very high SWASH scores, such as 4 and 5  in swash was 3.75, with the 95th percentile 2.88. Nevertheless, our model allows for such extrapolations to be done, and the results indicate that even in such groups with very high SWASH scores a clear effect of multisensory integration is present.Using the statistical model , we can find the posterior distributions of the mean questionnaire scores (μ) for each of pss and pas.The Stan program supports the generation of new simulated data based on the posterior distributions. Pseudorandom observations are drawn from the posterior distributions of the parameters, and Eqs 2, 3 are used to generate new sets of observations on the response variables. This results in what are termed the “predicted posterior distributions” of the response variables. These predicted posterior distributions can be compared with the original data. If the model is adequate, then the predicted posterior distributions should be similar to the observed distributions of pss is 0.71 ± 0.25, and the corresponding values for the predicted posterior are 0.68 ± 0.26. For pas, these values are 0.44 ± 0.27 and 0.44 ± 0.28. pas and pss and the corresponding predicted posterior distributions. In contrast, sa and ss scores, and the fit is poor  and an independent exponentially distributed random variable . Then, x + y has this distribution. The distribution has three parameters , where μ and σ are the mean and standard deviation of x, and λ is the rate of y (the mean of y is 1/λ). Therefore, setting z = x + y, the mean of the random variable z is μ+1/λ.As mentioned above, dpdsync and dpdasync. If z represents either one of those, then the model is:The proprioceptive drift responses are z is μ. We relate μ to the linear predictor as follows:Hence, the mean of 0, β1 and σ as above and We use the same non-informative priors for βpds,0, βpds,1, σpds, λpds, and μexp, pds for synchronous proprioceptive drift (dpdsync) and βpda,0, βpda,1, σpda, λpda, and μexp, pda for asynchronous drift (dpdasync). This model is included as an extension of that presented above for the subjective scores; i.e., there is one overall model that incorporates both the subjective and proprioceptive drift scores. The two sets of parameters are βswash . In the asynchronous case, there is little evidence of an association between the drift and swash, the probability of the slope being positive is only 0.635, and the credible interval well includes 0; in fact, the mean of the distribution is almost 0 with a much larger standard deviation (0.18).dpdsync) has mean ±SD of 1.06 ±2.98, and the corresponding observed values are 1.05 ±3.02. For the asynchronous case (dpdasync), the predicted posterior distribution values are 0.51 ±2.67, and the corresponding observed values are 0.49 ± 2.73. exp, pds and μexp, pda showing greater probabilities for higher values for the synchronous case. For example, the posterior probability,The predictive posterior distribution for synchronous proprioceptive drift  method , which ldpdasync. Unlike the case of the original normal distribution regression where there were a large number of influential points, in this analysis, there were none. Moreover, no overfitting is indicated, and all estimates of the numbers of parameters are close to the actual number. Overall, the model has good predictive capability.For each response variable and all data points except one, the Pareto k estimates are less than 0.5, with one between 0.5 and 0.7 for swash in their impact on the questionnaire results. This gives rise to a simple mixed effects model. We use the following notation, for i = 1, 2, …, N (= 2×n), n = 353, the number of participants, where:In the above, we followed the analysis conducted by psi is the normalised questionnaire score in the  range as above.condi = 0 for the asynchronous condition and 1 for the synchronous condition.swashi is the corresponding swash score.idi is the identifier number for the corresponding participant, where idi is in the range 1, 2, …, n for the n participants.Then, the linear predictor is:The inverse link function is given by Eq. 3and the likelihood is, following Eq. 2:i is the mean.where μuiid in Eq. 5 expresses the random effects part of the model, which takes into account the fact that there are a pair of observations for each participant and uiid will be the same for that pair, also allowing for individual differences. The remaining part of Eq. 5 is for the fixed effects and allows for the questionnaire scores to be influenced by condition, swash, and the interaction between them.The term j are normal, giving prior 95% credible intervals in the range ± 20. The prior distribution for ϕ is Gamma and therefore the prior 95% credible interval is 2.4 to 55.7, as used earlier. Convergence of the model was achieved with prior distributions for The prior distributions of βThe model was fit with Stan using 4000 iterations and 4 chains, and convergence was achieved with all Rhat = 1, indicating that the chains had properly mixed. More iterations were used here because of the greater number of parameters. The summaries of the posterior distributions of the parameters are shown in swash. There is no useful contribution of the interaction term, which will not be considered further. The size of the coefficients (the “Mean” column) shows that condition has a greater impact than swash (the coefficient is 2.63 times larger for cond), and the 95% credible intervals do not overlap. However, the different impacts of cond and swash can be more clearly seen by considering the posterior predicted distribution of ps.swash are 1.6 and 2.64, respectively. ps for swash > 1.6 , and based on this, together with another paper (expectancy_sync) and the same question for asynchronous with the only difference that words “are in synchrony” had been replaced with “are not in synchrony” (expectancy_async). These were scored as –3 (strongly disagree) to 3 (certain). We consider the difference, expect = expectancy_sync-expectancy_async, as an overall measure of expectation in favour of experiencing the RHI in the synchronous as opposed to the asynchronous condition .er paper , that weThe model in Eq. 5 can be extended to include the new variable:expect and its interaction with cond. Checks of a model that included interactions of swash with cond and expect with swash show that these do not contribute to the model fit and can be excluded. No interaction between swash and expectation is itself noteworthy since it does not seem to fit with Lush and colleagues’ assumption that expectations and trait hypnotisability interact.Here, we have included a main effect for cond and swash, the results are qualitatively the same as in expect (the main effect corresponds to the asynchronous condition), but the interaction with cond is important. What this shows is that in the synchronous condition only, the greater the value of expect, the greater the illusion. This is not surprising and shows an overall consistency of the model: the more that participants believed that they would experience the RHI based on the instructions they received before the experiment, the more likely they would be to report this. However, this does not mean that “demand characteristics” are the cause of the illusion or that expectations play a significant role. Note that there was no effect of expectation in the asynchronous condition, suggesting that elimination of the RHI by the temporally incongruent visual and tactile signals was so decisive that it overrode any prior expectations regarding the illusion.expect in principle ranges between –6 (when expectancysync = −3 and expectancysync = 3 and expectancyasync = −3). There are only 39 cases with expect > 2 but 128 cases with expect > 1. ps for expect > 1 under asynchronous and synchronous conditions. Again, the evidence is strong that it is the multisensory condition that dominates the results; the probability of higher scores is much greater in the synchronous than in asynchronous conditions, even at this relatively high level of expect. The same shaped distributions are obtained even for greater levels with expect > 2, expect > 3, andexpect > 4 .The variable Although we have seen that both hypnotisability and expectations may contribute to the subjective RHI scores, is it worth including these in the statistical model, i.e., how much do they contribute in comparison to the multisensory factor? To address this issue, we use the ELPD statistic introduced earlier. ELPD is a pointwise predictive log density for a new dataset . It is aexpect (Model 2) leads to hardly any change in the ELPD, the change being –0.5 with a comparatively large standard error of 2.0. Therefore, the more parsimonious Model 2 is preferred to the more complex Model 1. If we drop swash from Model 2 to obtain Model 3, then there is a noticeable drop in the ELPD , indicating that Model 2 is preferred. However, if we drop cond from Model 2 to arrive at Model 4, then there is a much larger decrease in the ELPD . This discussion emphasises what we have found earlier: both cond and swash contribute to the illusion scores, but cond is notably the most important factor, and expect only makes a negligible contribution. Models 5 and 6 are included for completeness and show that without the inclusion of cond, the ELPD is very much smaller.Overall, as shown in this section, it is clear that the dominant factor in the illusion scores is the multisensory one. Hypnotisability contributes to some extent, while expectations contribute negligibly.A series of recent papers has challenged the traditional explanation of the RHI being a perceptual bodily illusion based on multisensory integration and instead proposed an explanation mainly around hypnotic suggestibility, expectations, and demand characteristics, all of which are primarily based on the same underlying data that we have discussed . For exaswash). Second, eliminating the linear effect of swash from the subjective response variables shows a substantial difference in the distributions of the synchronous and asynchronous scores  in explaining the RHI, even though, of course, we know that correlation does not imply cause. Our analysis shows that this approach ignores the major contribution of multisensory integration. Since multisensory integration was the only factor that was manipulated in the experiment (barring the expectation induction that had no effect), this must be a causal factor. Causality, in this case, is further supported by the facts that the specific pattern of multisensory information that triggers the illusion precedes the onset of the subjective illusion and that there is a strong hypothesis regarding the underlying mechanism, both at the computational and neural implementation levels . That is, this difference is present in both the least and the most hypnotisable individuals in the sample, which is interesting, as it suggests that hypnotisability is not a necessary factor for experiencing the RHI and that even in the most hypnotisable individuals studied, there is a major effect of multisensory integration. Notably, even though the level of illusion is affected by SWASH, the level of illusion is influenced by the multisensory condition independent of SWASH, and as our model comparisons show, the contribution of multisensory integration is always greater than the hypnotisability factor, even at the highest levels of the SWASH scale.The fact that the relationship in illusion ratings between the synchronous and asynchronous conditions is stable across SWASH is interesting in several ways, beyond the points that have already been discussed. First, this stability suggests that the relationship between expectations/demand characteristics and hypnotic suggestibility may not be as tight as Lush and colleagues theorised. If the idea is that the participants produce experiences and behaviour to meet task expectancies, then, if you are not suggestible, you should not respond very differently to the synchronous and asynchronous conditions. However, if you are highly suggestible, you should respond very differently because you have a personality that will make you respond to task demands with the ability to generate “experiences” and the behaviour to do so convincingly. However, as the results from the current analyses show, there is no evidence for such an interaction between the multisensory condition and trait hypnotic suggestibility, which is also in line with −7, while the chance of the groups differing by at least 0.5 has a probability of 0.010  or to include a common control condition in the different groups and analyse group ×condition interactions. However, randomisation in the selection of groups would result in a very low probability that two groups might differ on their mean level of SWASH if drawn from the same population. Based on the current data, it is extremely unlikely that two randomly selected groups for a between-group study (drawn from a population with similar characteristics as the sample of 353) would have differences in SWASH that are so large that it would bias the results. For example, the chance that two groups of 30 participants would differ in their mean SWASH score by at least 1 is less than 2.7×10.010 see .post hoc exploratory analyses. However, in our view, the comparison of the illusion and control conditions was not sufficiently discussed and apparently not weighted in when formulating the overall conclusion.In All the previous findings and arguments notwithstanding, Lush and colleagues maintain that convincing evidence favouring the RHI as a multisensory illusion is lacking and that demand characteristics provide a more probable and straightforward explanation for the synchronous versus asynchronous differences . Demand Although it is difficult to completely rule out the theoretical possibility of demand characteristics in any experimental psychological study , the key issue is whether such effects can explain the main findings when control conditions and other aspects of the experimental design and task instructions are taken into account. In our view, it is extremely unlikely (most likely impossible) that demand characteristics can constitute the main explanation for the large and replicable RHI effects found across a wide range of paradigms, procedures, and measures in the previous literature. The total number of studies, types of experimental designs and control conditions, and specific findings are simply too numerous to be explained away by demand characteristics, and the literature is too vast to review here; an interested reader is directed to the many previous review articles on this topic .That said, let us briefly consider a few examples of where it is particularly difficult for the participants to determine the underlying hypothesis see . SimilarNevertheless, in our reanalysis of the Alternatively, trait hypnotisability could act postperceptually on metacognition. This could, for example, be accomplished through affecting the internal decision criterion that participants use when they fill out the questionnaire ratings scales and have to judge whether or not they felt the illusion and how certain they are about this judgement (how strongly they agree or disagree with the statements). It is possible that individuals with low scores on SWASH might be more conservative, i.e., that they require a stronger illusion before they will affirm it, and at the same time be more confident when they reject the illusion in the asynchronous condition (being more likely to give very low ratings). Conversely, participants with high SWASH scores may be more liberal when rating the illusion and more willing to give higher scores. Links between trait hypnotisability and alterations in metacognition have been reported in agency tasks , therebyP = 5.2×10−10, R2 = 0.10, n×352 due to 1 missing value) and in the asynchronous condition   hand, in terms of shape, skin tone, freckles or some other visual feature” (S4), which is observed both in the synchronous condition ( = 0.12) . Notably = 0.12) . This in = 0.12) . Future However, Lush et al.’s interpretation is that S4 reflects “visual hallucinations”  and thatSD = 0.7) on a scale from 0 to 5 (This brings us to perhaps the most fascinating idea in Lush and colleagues’ “phenomenological control” theory, namely, that many healthy individuals can hallucinate, i.e., see, hear, feel and sense things that are not there, as vividly as real perception. The idea that people can “control their own phenomenology” in this way is inspired by the hypnosis literature and findings from experiments on highly hypnotisable individuals who are actively induced into a hypnotic state or exposed to hypnotic suggestions . Howeverm 0 to 5 , which mm 0 to 5 . In addim 0 to 5 . Thus, dIn conclusion, none of the current findings of our reanalysis rule out the effect of trait hypnotisability on RHI reports, as has been shown before . HoweverThe original contributions presented in the study are included in the article/Approval for the study on which this article is based was received from the University of Sussex ethics committee and participants gave informed consent for the study.MS conceived the study, performed all statistical analyses, and wrote the first draft. HE contributed to the writing of the manuscript, in particular to the Sections “Introduction” and “Discussion.” Both authors developed the additional analyses involving expectancy ratings and model comparisons and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This study aims to analyse the inter-rail modal shift behaviour of suburban rail passengers to examine ridership for the proposed metro extension corridor in Chennai, India. This investigation was conducted in 2019 as part of a feasibility study for the extension of the metro line spanning between Chennai Airport and Kilambakkam, a southern suburb of Chennai. The same origin–destination pair is also served by the suburban rail system. It is an extension of the operating line from Washermenpet to the airport of the Phase I metro project. For this inter-rail competition study, a sample of 272 suburban rail passengers covering work, education and other trip purposes were interviewed using a stated preference questionnaire. Six stated scenarios were considered for analyses which included travel time saving by using the metro along with the fare difference between metro and bus. The study revealed that suburban rail passengers were less concerned about travel time saving and gave priority to fare difference irrespective of trip purpose. This shows the unique metro choice behaviour of suburban rail travellers in the Indian context. Modal shift studies aim to assess passenger willingness to shift from one mode to another mode of travel, chiefly in urban regions. Cities in India are introducing metro rail systems to resolve traffic congestion problems. Delhi was the pioneer in construction/operation of metro systems in India, beginning 20 years ago. In later years metro operation was started in Chennai (India) and is under phase-by-phase expansion.Metro system is one of the attractive urban modes with air-conditioned coaches, and hence a noteworthy shift of passengers is expected from the existing public transport modes such as sub-urban rail. Analysis of modal shift behaviour of different mode users is effectively carried out by developing mathematical models.In general, modelling studies are conducted in developing countries to understand the shift in behaviour of private mode users –6, para-Since both are rail-based public transport modes and running parallel to each other, the study is useful for both the operators for framing policies to achieve a balanced ridership.From the above table, it is evident that travel cost played a major role in determining shift in all studies. However, none of the studies investigated the shift from one rail mode to another, whereas the present study focuses on understanding the shift behaviour of suburban rail users to the proposed metro extension corridor (suburban rail-to-metro rail shift) in Chennai, India. unique metro choice behaviour of suburban rail users.The study was conducted as part of a feasibility report for the proposed metro rail corridor. To achieve the above objective, a stated preference (SP) questionnaire was prepared consisting of six different proposed scenarios, and the survey was conducted among suburban rail users by a face-to-face interview method. Using the SP data, two modal shift models were developed, one for the entire data and the other for the data pertaining to work trip travellers using the binary logit technique, and probabilities of shift were estimated for both models. The study reveals that the predicted probabilities demonstrate a Chennai, a well-known metropolitan city in India, has an urban population of 4.65 million according to the 2011 Census of India . City tr The suburban rail system is the oldest and serves commuter needs in three different directions, north, west and south. MRTS is an elevated rail line constructed along Buckingham Canal. Suburban rail and MRTS are operated by the same zonal railways under Indian Railways known as Southern Railways. Both MRTS and suburban rail systems run on broad gauge 1.676 m) and with non-air-conditioned coaches. Metro rail is managed by Chennai Metro Rail Limited (CMRL), the sole authority formed by the Government of Tamil Nadu. Metro started operation with two corridors, one along Anna Salai  and the other line passing through Poonamallee High Road and Jawaharlal Nehru Road. It runs on standard gauge (1.435 m) and all the coaches are air-conditioned, with large glass windows for a panoramic view. It has partly underground and partly elevated tracks. The present study focuses on the metro corridor along Anna Salai (red line) which runs between Washermenpet and the airport and is under phase II extension .Low ground space occupation—2 m width is sufficient for elevated rail.Rapid—reduces travel time by 50% to 75%.Metro trains have doors that close before the train starts moving. This should prevent people from hanging outside the trains. Platform screen doors should prevent people from accidentally being pushed onto the tracks while waiting for the trains .Metro rail has entered a new era in the transport system in Chennai, with the added advantages compared to the suburban rail system as follows :Metro racheaper than bus fare in Chennai.However, the metro fare is higher than the suburban rail fare. For instance, metro fare is INR 40 for 10 km, whereas suburban rail fare is only INR 5 for the same distance. This means that a passenger has to pay eight times the fare to travel in the metro. In fact, suburban rail fare is In accord with the feasibility study (FS) report, the 15.3 km elevated metro line from Chennai Airport to Kilambakkam via Tambaram consists of 13 stations. The proposed corridor is fully elevated, so construction will be easier/cheaper than for underground metro construction. As it is very close to IT hubs, Anna Zoological Park and the proposed Kilambakkam bus stand, the stretch is expected to attract many commuters to the Chennai metro  to Urappakkam, runs parallel to the proposed metro extension corridor, leading to competition between the two.Studies relevant to the present study are reviewed, and the key observations are given below:Factors influencing the desires of single-occupant commuters to shift to buses and car pools were studied and policies were recommended to inspire the use of high-occupancy vehicles . The stuAn investigation was conducted in Malaysia to identify factors which had led to an enormous shifting of car riders to the public transport (PT) system . For thiA modal shift arises when one mode assumes comparative leverage in a travel market over another. The relative advantage can take different forms such as cost, capacity, time, flexibility or reliability. The category of passengers travelling and their circumstances  broadly affect the proportionate importance of each of these factors .The effects of the addition of an exclusive bus lane on auto-rickshaw (three-wheeled motorized para-transit vehicle) users in Chennai was studied using a binary logit model . For thiThe challenges and opportunities in implementing a modal shift from private mode to PT in the UK were analysed in detail . In the A study was carried out to understand the shift behaviour of private transport users and PT users to the existing and proposed metro corridors in Mumbai . For thit-test). The two best models were used to estimate the value of time in Egyptian pounds (LE), with results of 11.30/h and LE 14.50/h, with associated inaccuracy of +3.7% and +33.0%.The value of time (VoT) of Alexandria city was estimated by developing a disaggregate linear-in parameter utility-based binary logit mode choice model . The modNewly introduced metro rail in Chennai has led to growing competition among PT modes . To studThe possibility of shift from the PT system toward private modes such as cars in India due to the unexpected outbreak of COVID-19 was studied . For thiSelected studies from the period 1979–2021 pertaining to modal shift were reviewed. It was found that most of the models were developed using a binary logit method. None of the Indian literature studied the impact of metro on suburban rail. The present study considers both travel time and cost saving in an Indian context and tries to predict the probability of shift from suburban rail to metro (rail-to-rail shift). Also, a binary logit model was developed to better understand the modal shift behaviour.Hypothetical, “stated” preferences in controlled experiment set-upAbility to predict reaction to future, not currently existing optionsLower costAccurately specified choice setNumerous answers from each respondentDifferent choice formats Ability to analyse trade-offs among qualitative characteristicsA disaggregate method was used in the present study. Behavioural disaggregate models have various benefits: minimal data are required for model calibration, and the model is easily transferable and easily understood . From thHence, in the present exercise, an SP approach was used for model calibration. Since the modes considered were suburban rail and metro (binary situation), a binary choice model was selected. The interpretation of variables was easier in a logit model than a probit model, and hence the logit model was used for the study. Figure Socio-economic characteristics: gender; age of the commuters; monthly family income in Indian rupees (INR: 1 euro ≈ 81 INR); vehicle ownership; place of work; frequency of travel; educational level; employment sectorDetails on current trip: purpose of trip; mode and stages of travel; trip lengthStated hypothetical scenarios: (six scenarios as given below)Scenario (1): travel time saving is 25%: 2 times the MTC bus fareScenario (2): travel time saving is 25%: 3 times the MTC bus fareScenario (3): travel time saving is 25%: 4 times the MTC bus fareScenario (4): travel time saving is 50%: 2 times the MTC bus fareScenario (5): travel time saving is 50%: 3 times the MTC bus fareScenario (6): travel time saving is 50%: 4 times the MTC bus fareStated preference methods try to determine people's willingness to pay by directly asking them how much they value certain environmental goods or services through an appropriately designed survey questionnaire . SP survPshift is the probability of shift from suburban rail to metro, X1, X2, X3 ... are factors influencing change behaviour (factors include socio-economic and travel characteristics of suburban rail passengers), and a0, a1, a2 ... are model attributes to be calibrated using the model development exercise.The model developed is a binary logit model. Binary models serve a number of functions. First, the ease of binary choice settings makes it possible to develop a range of practical models which gives greater flexibility in more complicated choice situations. Second, there are many basic theoretical problems that are simple to illustrate in the context of binary choice. Since our aim is to study the shift behaviour of suburban rail travellers to proposed metro rail, only two modes were considered . The structure of the model is as follows:xi, yi = variable value, x, y = mean valuesIn statistics, correlation is a way of establishing the relationship/association between two variables . In other words, the correlation coefficient formula helps in calculating the correlation coefficient which measures the dependence of one variable on the other variable. Correlation is measured numerically using the following formula:X1, X2, X3 ...) and the dependent variable (Pshift). Table Before beginning the modelling exercise, it is necessary to identify the significant influencing variables in explaining the shift behaviour. For this, the correlation coefficient can be used as a tool in ranking the variables. A correlation matrix is developed which includes all the independent variables X1, X2, X ... and Code indications:From the correlation matrix, the following variables are chosen for model development based on the ranking of correlation coefficients from maximum to minimum. Variables have a correlation coefficient value with the probability of shift (dependent variable) equal to or greater than ±0.05 and are selected and listed in Table Once again a correlation matrix is developed from the previous correlation matrix consisting of only ten selected variables (including the dependent variable) to determine whether any inter-correlation exists among the selected variables. If inter-correlation exists, such a pair of variables can be isolated and any one among them selected based on the correlation with the dependent variable. Thus the developed inter-correlation matrix is presented in Table Daily trip makers were highly correlated with occasional trip makers (1.0). The correlation with the dependent variable was also equal with opposite signs. However, if the sample percentage was considered, daily trip makers were significant in the survey output (84.5%). Hence, the variable daily trip maker was included in the model.Similar to the above case, three age ranges influenced the probability of shift. If the correlation coefficient was considered, all three variables were intercorrelated, and passengers with age range of 41–60 influenced the dependent variable in a better way compared to the other two. However, if the sample percentage was considered, passengers with age range of 21–40 were significant in the survey output (66.9%). Hence, the variable passenger age range 21–40 was included in the model.Considering income ranges, two income ranges 15,001–20,000 and 30,001–40,000 influenced the dependent variable. Comparing both variables in terms of correlation value and sample size, the income range 15,001–20,000 (0.06 and 19.1%) was included in the model development.From the above discussion, five variables were finally chosen for model development: (a) fare difference, (b) gender, (c) daily trip makers, (d) passengers with age range 21–40 and (e) passenger income range 15,001–20,000.Step 1:Model type: For estimating the probability of shift from suburban rail to the proposed metro line, a binary logit model is developed using SP data. The collected SP data are coded in Microsoft Excel using binary codes .Step 2:Model development: The model is developed considering only the chosen variables based on the correlation coefficient values (r). The total number of suburban rail passengers interviewed is 272 (sample size) and opinions are collected for six different fare difference in combination with travel time saving scenarios. Hence, the total number of data points used in the model is 1672 (i.e. 272×6).Step 3:Model validation: Among 1672 data points, 1331 are used for model development. The remaining 301 data points are kept as the hold-out sample for model validation purposes. The result of model development using 1331 data points is given in Table Full model development is done step-by-step as discussed below:Step 4:Recalibration of model: The model is recalibrated once again with 1632 data points for model application and the developed model is presented in Table Thus the developed model is applied to the hold-out sample of 301 data points and the log-likelihood (LL) values are calculated by applying the above model on the hold-out sample and compared with the software-estimated LL as shown in Table Positive observation: From the recalibrated model, it can be observed that suburban rail travellers falling in the age group of 21–40 (with estimated coefficient = +0.317) and monthly income of 15,001–20,000 (with estimated coefficient = +0.413) are more willing to use metro once it started operation in the study corridor.Using the recalibrated model, the probability of shift from suburban rail to metro is estimated for the proposed fare and travel time saving scenarios and is presented in Table From the above table, it is evident that the travel time saving does not have a significant impact on the shift of passengers from suburban rail to metro rail. The reason may be that suburban rail travellers feel that the metro does not save travel time when compared to their current mode of travel.It is also observed that when the metro fare is just two times the bus fare, then 85.4% of suburban passengers show interest in the proposed metro, whereas if the fare is three and four times the bus fare, then the shift is only 38.8% and 6.4%, respectively. This means that the suburban travellers are sensitive to fare changes.Most urban travel demand analysis models were structured for different trip purposes separately. In other words, it was usually assumed that the demand for different activities, such as work, recreation and so forth, were independent . Hence tNegative observation: From the above work trip model, it can be observed that suburban male passengers (with estimated coefficient = −0.403) and daily trip makers  (with estimated coefficient = −1.201) are not willing to use the proposed metro.r), it is clear that suburban rail travellers falling into the age groups of less than 20 (r = +0.03) and 21–40 (r = +0.05) are willing to shift to metro in the study. This means that the younger group of travellers shows more interest in metro than older people. It is true from the model output that suburban rail passengers falling in the age group of 21–40 (+0.317/ t stat: +2.14), with monthly income 15,001–20,000 (+0.413/ t stat: +2.34) are more willing to use metro, while daily travellers are reluctant to use metro (−0.744/ t stat: −3.94).From the correlation value (r = +0.19). Since the metro fare is comparatively higher than the suburban rail fare, senior people are not willing to shift to metro. Table From the correlation value, it is observed that the suburban travellers with age greater than 60 fall in the income range of INR 10,000–15,000 ((3)r = −0.65) plays a significant role in determining shift behaviour of suburban rail travellers.Fare difference ((4)r = −0.16). This indicates that in order to reduce travel cost, travellers use different modes in a single trip.The correlation between number of stages and travel cost is significantly high, with a negative sign ((5)r = −0.06), occasional travellers (r = +0.06) are more likely to use the metro service.Compared to daily travellers ((6)r = +0.82), as expected.Travel time and travel distance are highly positively correlated ((7)t stat: −4.45).Compared to female travellers, male travellers are less willing to use metro (−0.788/ (8)Similar behaviour to the above is observed for work trip travellers.(9)From the probability of shift Table , it is cThe present study aimed to study the shifting behaviour of suburban rail passengers towards the newly proposed metro extension corridor in an Indian context. To accomplish this, an SP questionnaire survey was conducted among suburban rail travellers and a binary logit model (suburban rail and metro) was calibrated to estimate the probability of shift to metro. From the developed models, it is understood that suburban rail passengers assigned less importance to the travel time saving, while fare difference played a major role in the probability of shift, irrespective of trip purpose. This shows the unique propensity of urban rail travellers in the Indian context. The major findings of the study are as follows:The current study considered cost and travel time saving in stated scenarios. In future studies, other sustainable modes such as walking, cycling and cycle rickshaw as feeder service choice can be investigated for model development.One of the aspects of PT service is travel time reliability (TTR) . From thThe future work and suggestions are as follows.


P < 0.05), demonstrating the effectiveness of the BQA program. More than 80% of survey respondents who joined the BQA program stated they believed the BQA program improved animal health and welfare on their operation (n = 617). Among those who had not joined the BQA program, 40% believed BQA practices did not align with their ranching operation, while 38% had not heard of the BQA program (n = 256). The survey indicated that male ranchers, those with more years ranching, those with a larger percent of income coming from ranching, and ranches with larger total acres grazed were more likely to be BQA certified at any time (P < 0.05). Finally, ranchers who were BQA certified at any time were more likely to state that joining a rancher sustainability program would be beneficial to their operation. In conclusion, not only did the survey provide valuable insight into BQA program adoption but highlighted how BQA pedagogy and program structure may be a suitable framework for creating future rancher sustainability programs.Till date, with over 137,000 certified members, the most successful rancher educational program has been the Beef Quality Assurance (BQA) program. The BQA program was established in the mid-1990’s to improve animal health and welfare with a primary objective to reduce the incidence of injection site lesions by instructing producers to administer injections in the neck only. The present study investigated the drivers of this success to inform future rancher education programs around agricultural sustainability. An online multistate survey was administered to cattle ranchers in collaboration with state cattlemen’s associations to better understand rancher motivations for adopting new practices and to gain insight on current involvement in BQA. In total, the survey consisted of 45 questions and was divided into 3 sections: (1) rancher demographics, (2) BQA participation and current best management practice (BMP) application, and (3) willingness to join new rancher educational programs. Data from 842 respondents are including in this study. Of the survey participants, 70% were currently BQA certified or had been BQA certified at one time, and 30% had never been certified. Ranchers who were BQA certified at any time were less likely to administer injections in areas other than the neck compared to ranchers who were not certified ( To stay competitive in the sustainable foods movement, the beef industry has sought to improve sustainability within their own supply chains. However, before system sustainability can be achieved, sustainability practices must be adopted and implemented at the foundation of the system. With over 725,000 cow-calf producers in the United States , rancherWith a high degree of rancher involvement and BMP implementation, the BQA program serves as a model and case study for the development of future rancher educational and sustainability programs. However, the reasons ranchers volunteered to join this program have not been extensively investigated. In addition, other than the National Beef Quality Audit , there iAn online survey for ranchers was developed and administered using the platform Qualtrics . In total, the survey consisted of 45 questions divided into three sections including: (1) Rancher Demographics, (2) Beef Quality Assurance Participation and current BQA practice application, and (3) Willingness to join new rancher educational programs. Survey questions were derived from literature and discussions with collaborating ranchers. After questions were developed, the initial survey was pilot tested with California ranchers located in northern California. Once pilot testing was completed and minor adjustments were made, the final survey was administered online to ranchers across six of the seven National Cattlemen’s Beef Association regions including the Northwest, Southwest, Southeast Midwest, Northern Plains, and Southern Plains . To recrTo provide insights into the key factors shaping BQA membership and BMP practices, descriptive statistics were used to characterize key components adapted from the rangeland decision-making framework from n = 589), and 30% had never been certified (n = 253). Specifically, 24% of survey participants were currently certified and had enrolled in the BQA program within the last 3 years, 35% were previously certified and had recertified in the last 3 years, 24% had not participated in BQA, 11% had been certified at one time but never recertified (n = 100), and 7% had gone to a BQA program but never certified. For analysis, BQA participants were grouped into BQA certified (including certified at one time) and those who never certified and/or never participated.According to the BQA program guidelines, to be considered current in BQA certification participants needed to have completed the certification process within the last 3 years regardless of the previous certification. To become BQA certified producers must take an online or in-person course taught by a state BQA coordinator and/ or trainer. Among the survey participants, 70% were certified or had been BQA certified at one time . The frequency tables for variables in all models are summarized in For demographics regarding participants’ age, sex, location, and ranching operation characteristics, see n = 589), the most cited motivations for joining BQA were; (1) to improve animals’ health and welfare, (2) consumer perceptions/demands/concerns about animal welfare, and (3) reputation of their operation is greater when animals are a part of BQA . When BQA participants were asked if the BQA program had been beneficial to their ranching operation, 26% stated joining the BQA program had been extremely beneficial to their ranching operation, 32% stated very beneficial, 29% beneficial, 10% somewhat beneficial, and 3% stated BQA had not been beneficial (n = 617). Of the BQA participants surveyed when asked if there were any sections in the BQA guidelines that were not feasible or helpful only 20 producers listed program concerns. Of the BQA ranchers that had program feasibility issues over 80% of the issues were related to weaning or vaccination procedures. When all surveyed ranchers  were asked for their top three reasons for adopting a new practice, more than 63% stated profitability, followed by improved animal health (62%), and benefits outweigh effort of practice (41%). These results contrasted with the reasons for joining the BQA program, where profitability ranked 6th as a reason for BQA participation. Of the survey takers that were BQA certified, 73% stated joining the program was extremely or very beneficial, 28 stated beneficial, and only 14% stated somewhat beneficial or not beneficial (n = 560).We first sought to identify rancher motivations for becoming BQA certified. For those who had participated in the BQA program  in the neck only . The priP < 0.05). When examining the location of injections for antibiotics and vaccinations, BQA members were significantly less likely than non-BQA members to choose “neck and other” (P < 0.05) and “other only” (P < 0.05) locations over “neck only”. The multinomial logistic regression model also identified the percent of ranching income as a factor influencing injection site location choices: those receiving a larger proportion of income from their cattle business were less likely to give antibiotic and vaccination injections in “neck and other” (P < 0.05) and “other only” (P < 0.05) relative to “neck only”. Additionally, the model identified ranchers with a greater number of cattle and older ranchers less likely to administer antibiotic and vaccination injections in the “other only” relative to “neck only” .Multinomial logistic regression was used to determine whether there were statistical differences between the chosen site of injections  between BQA certified and non-BQA certified individuals . Being Bn = 842). Of the BQA certified ranchers, 57% stated they fence lined weaned their calves compared to 49% for non-BQA certified ranchers (P < 0.05). In terms of castration practices, 55% of BQA ranchers stated they castrated their calves prior to 3 months of age compared to 52% of non-BQA members (P > 0.05). In total, 51% of BQA members waited 45 days to ship weaned calves compared to only 25% of non-BQA members (P < 0.05). When it came to establishing a herd health plan with a veterinarian, 47% of BQA ranchers had established a veterinary plan while 31% of non-BQA certified ranchers had established a plan (P < 0.05). In terms of unsanctioned BQA practices, only 4.6% of BQA ranchers and 7.9% of non-BQA ranchers stated they performed darting on their cattle operations (P < 0.05).In addition to the BMP practice of injecting in the “neck only”, other BQA program BMPs included fence line weaning , castrating calves prior to three months of age, waiting 45 days after weaning to ship claves, and establishing a heard health plan with a veterinarian ; n = 842P < 0.05; P = 0.12), maintaining a succession plan (P = 0.34), and number of cattle owned (P = 0.42). No statistical relationship was identified between participation in a land assistance program  financial and technical assistance programs) and being a BQA member (P = 0.78). Although years of ranching increased the likelihood of participating in a BQA program, being either a first or multigenerational rancher had no effect on BQA membership (P = 0.34).Logistic regression was used to identify which factors increased the likelihood of ranchers joining the BQA program. Factors that increased the likelihood of becoming a BQA member were total grazing area, percent of income from ranching, region, years ranching, and gender . Upon further analysis, the number of head was determined to be weakly correlated with grazing acres . This low correlation between land space and head of cattle may be due to differences in regional stocking densities. For example, in the Western U.S., lower quality rangeland results in lower stocking densities compared to higher stocking densities in the Eastern U.S. where ranchers have increased access to more nutrient dense grazing.Previous studies have identified the scale of production , as an indicator for a new program or practice adoption . SpecifiTime Horizon variables  have been positively associated with the adoption of conservation programs . In the Type of land  used for ranching has been identified as an influencing factor for joining conservation programs. Previous studies have indicated that ranchers who owned greater amounts of private land (opposed to public land) were more likely to join conservation and education programs . Furthern = 65). In contrast, producers who reported being in the niche category’s “humanly raised, verified source and age, non-hormone treated cattle or Global Animal Partnership” resulted in a higher BQA certification of 60% (n = 165). The majority of cattle in the “humanly raised, verified source and age, nonhormone treated cattle or Global Animal Partnership” programs were most likely sold to feedlots who were either focused on overseas export or domestic niche production. Ranchers in these programs may have found BQA certification to add value in their operation, particularly when selling cattle at auction. However, ranchers in the “organic, grass-fed, and natural” niche programs may have retained ownership of their cattle throughout the animals’ lifecycles and most likely needed to adhere to additional animal welfare standards  than producers in other niche programs. Therefore, it was hypothesized that producers in these programs may not see added value from joining additional programs like BQA.The number of niche market operations in the United States has been increasing rapidly . DespiteWhen survey participants were asked where they administered antibiotics and vaccinations, 85% of those who were BQA certified administered antibiotics in the neck only compared to 66% of those not BQA certified . In addiIn terms of hormone injections, an informational disconnect was observed between BQA teachings and on-ranch practices. In contrast to vaccines and antibiotics, only 56% of BQA certified ranchers and 39% of noncertified BQA ranchers stated they administered hormone injections in the neck only. Although BQA certified ranchers were less likely to administer hormone shots in “other only” relative to “neck only” locations, both BQA certified and noncertified ranchers were likely to administer hormones in “neck and other” relative to “neck only” locations. However, the observed differences in injection practices between hormones and antibiotics/vaccinations may be due to variations in pharmaceutical approvals for specific purposes. Presently, some pharmaceuticals used for breeding purposes are approved for tail-head/rump administration. Therefore, future BQA programs need to address whether animals considered for breeding purposes can receive hormone injections outside the neck area.Compared to injection site BMPs, other BQA BMPs, such as fence line weaning, castration prior to three months of age, waiting 45 days to ship calves post weaning, and development of a heard health plan with a veterinarian, were implemented at lower rates among all survey takers . HoweverWith 80% of ranchers having a positive or neutral view of beef sustainability program participation, there appears to be a willingness for ranchers to engage in future sustainability programs . This inThe present survey was the first of its kind to directly ask ranchers across the U.S. about the adoption and efficacy of the Beef Quality Assurance certification program. First, the study found that although there were similar factors driving ranchers to join either the BQA program (become BQA certified) or the conservation program, the principal rancher BQA adoption driver was animal health and welfare. Second, the survey determined that BQA-certified ranchers were more likely to agree that joining a volunteer sustainability program would be beneficial to their operation than non-certified ranchers. The relationship between BQA and sustainability participation demonstrated how aspects of the BQA program may serve as a model for an industry wide sustainability program. Finally, although the BQA program has been highly successful at reducing injection site lesions the survey revealed information gaps and potential areas for improvement. Other BQA BMP including 45-day weaning, castrating prior to 3 months, and establishing a herd health program with a veterinarian were adopted at a much lower rates than the principal BMP of injecting in the neck only. In addition, factors that decreased the likelihood of becoming BQA certified were gender, years ranchers (newer ranchers), and ranchers who received less income from ranching. Therefore, additional resources and outreach efforts should be extended to ranchers in these demographics to increase BQA and BMP adoption. Overall, to further the understanding of ranching sustainability motivations, future work needs to investigate rancher land management practices  and determine how these management strategies relate to the willingness to join future sustainability practices.txac094_suppl_Supplementary_MaterialClick here for additional data file.


Mindfulness and self-care, practiced through a variety of methods like meditation and exercise, can improve overall sense of holistic well-being . Increasing mindfulness and self-care may lead to increased flourishing and job satisfaction among the nation-wide Cooperative Extension system delivery personnel (agents) through a theory-based online program and an extended experiential program.via statewide listservs. Participants were invited to attend sessions and complete competency checks and between-session assignments each week. The study was conducted using Zoom. Pre- and post- program surveys included validated scales for flourishing and physical activity status. Due to high demand for mindfulness programing during the onset of the COVID-19 pandemic, experiential “Mindful Meet-up” 30-minute sessions were held on Zoom. Dissemination and implementation of the two differing interventions  were examined.Cooperative Extension agents from two states were invited to participate in MUSCLE MUSCLE (more intensive program with assignments and competency checks) had lower reach, and did not show statistically increased flourishing or physical activity. Mindful Meet-ups had higher attendance and proportional reach during the beginning of the pandemic, but no practical measure of flourishing or physical activity behaviors. Unsolicited qualitative feedback was encouraging because the interventions were well-received and participants felt as though they were more mindful.While agents anecdotally reported personal improvements, capturing data on outcomes was challenging. Complementing outcome data with implementation and dissemination outcomes allowed for a richer picture to inform intervention decision-making . Physical, mental, and emotional health are all components of individual well-being, also called flourishing, and health status . FlourisOne workplace of interest is the Cooperative Extension system (herein: Extension). Extension is a nation-wide, federally funded system where educators work to engage with the community and provide education and programming to meet community needs –11. WithYoga is thought to reduce stress through utilizing breathing and movement patterns , 20. YogIn yoga, “mindfulness” can be an umbrella term to align with pratyahara , dharana (concentration), dhyana (meditation) and samadhi (absorption). In public health interventions, mindfulness has been defined as being fully aware and present in the moment. Examples of mindfulness interventions include breath and postural awareness practices , mindfulSelf-care has been defined as behaviors and processes that maintain overall health through health promoting practices and managing signs and symptoms , and it reach, effectiveness, adoption, implementation, and maintenance  Laboratory at Virginia Tech serves the Commonwealth of Virginia in two ways: (1) identifying Extension agent needs  and (2) matching evidence-based programming with county resident needs. PARCI lab members meet with agents representing each of the four districts of the state and, as a team, decide programming needs for the following year –36. In 2RE-AIM dimensions were operationalized as the following: The reach of an intervention or program is how well it connects with the intended audience . This alPhase I. In the spring of 2020, with the work from home orders due to the COVID-19 Pandemic, 30 minute “Mindful Meet-up” sessions were scheduled for Monday mornings on the video conferencing platform, Zoom see . These sPhase II. In the fall of 2020, with the continued pandemic, a 2-day mindfulness and self-care retreat titled “Mindfulness and Understanding of Self-Care for Leaders of Extension (MUSCLE)”, was planned to be online . Sessions included experiential physical activity opportunities such as yoga, tai chi, strength training, and interval training, as well as mindfulness opportunities such as sound bath healing, journaling, and self-compassion sessions. Other sessions were didactic and explored less typically acknowledged self-care and physical activity options like gardening tips, hiking, cooking sessions, and tips for working from home.Phase III. To meet the requests for more education on the topic and to follow-up from other programs on physical activity (described more below), a 9-week version of MUSCLE was conducted in the fall/winter of 2020. These sessions included covering the Physical Activity Guidelines for Americans, how yoga can fit into the guidelines, yoga myth busting, what mindfulness and self-care can encompass, mindfulness and breathing techniques, self-care techniques, and scope of practice and cueing techniques for personnel who might incorporate these practices into their own work. Since there was more time prior to the launch of this program, research questions were formulated and validated surveys were used during program registration (described below).via Zoom for nine consecutive Mondays. Each synchronous session included both didactic and experiential learning. Between sessions attendees were asked to complete asynchronous activities for mastery experiences related to techniques of mindfulness and self-care. These mastery experiences were included as practice as it has been shown that it promotes improved outcomes , as well as the activity to complete for the asynchronous portion of the week.To facilitate behavior change, group dynamics strategies  and indivia an Extension employee email listserv a few weeks after employees received work-from-home orders in response to COVID-19. Subsequent invites were sent out via email during each semester that the program was held. Most attendees were from the Family Nutrition Program or the Food and Consumer Science divisions of Extension. Any employee could attend from registering on Zoom, no data were collected (with the exception of the number of attendees) and no human subjects research was sought or approved.Phase I. Virginia Cooperative Extension employees were invited to attend Mindful Meet-ups via an Extension employee email listserv. Participants were able to attend some or all of the sessions based on their own interests and availability. Registration consisted of completing an interest survey for which sessions the employees wanted to attend, demographic characteristics, the L-CAT . However, with ongoing success within the reach dimension (Phase I), interest in more systematic evaluation was applied for Phase II (MUSCLE 2-day retreat) and Phase III (MUSCLE 9-week program). This included qualitative and quantitative data collection as outlined below. In addition, each phase was compared in terms of relative reach, effectiveness, adoption, implementation, and maintenance on a 5-point Likert scale  see Fig.Participants were asked to disclose their age and how many years they had worked with or been affiliated with Cooperative Extension during Phase II and III. The hypothesis was the years working with Cooperative Extensions would correlate positively with flourishing and confidence in delivering physical activity.MUSCLE participants were given pre- and post-program surveys to complete, whereas the Mindful Meet-up participants were given surveys at the beginning of the third iteration/semester of the program and post-program surveys at the end of the third semester.Flourishing is when all sectors of a person's life are good and there is a sense of well-being . To measThe yoga self-efficacy scale (YSES)  is a valTM Armbands   is a valArmbands  as compaArmbands . The L-CArmbands  and is tArmbands . StatemeArmbands .Separate questions were asked of the participants to determine the proportion of time during work hours the participants spent with Cooperative Extension participants conducting physical activity. The working hypothesis, based on the social cognitive theory for health promotion,  was thatvia Qualtrics software. The competency checks were de-identified, with participant IDs being their team name and a randomly chosen number that they were asked to decide upon in their first breakout room during the first Zoom session. Competency checks included information checks on the information covered during the synchronous sessions, as well as the asynchronous activities the participants were to complete throughout the week. By completing the competency checks, participants had another point of contact that encouraged them to complete their self- monitoring tools, action and coping plans, etc. Competency checks were evaluated based on completion, and not based on percent correct answers due to the subjective nature of some questions, i.e., “What is your favorite method of self-care?” This follows the projected model that increased MUSCLE participation will increase SFI and YSES, and results of increased PA will be seen on the follow-up L-CAT surveys.At the end of each week of the MUSCLE program, participants were asked to complete competency checks Adoption was assessed as the number of teams or leaders outside of the PARCI Lab that chose to lead sessions or expand the programs during Phase I, II, or III. Additionally, strategies to increase adoption by other systems within the university or Extension systems were employed. These strategies included meeting with other teams and leaders who aimed to start employee wellness programs, providing support, and having those leaders and teams lead sessions in the Phase I and II programs.Each program was implemented through online video conferencing software. Calendar invites for each program were sent to registered participants to encourage attendance post-registration. Hours of time team members worked to implement each program was specifically tracked for MUSCLE and more generally estimated for Mindful Meet-ups.Follow-up surveys were sent to each participant at the conclusion of the MUSCLE program and Mindful Meet-ups semester series, as well as 6 months after the conclusion of the MUSCLE program. Follow-up surveys included the same validated survey items from the pre-survey, including the SFI, the YSES, and the L-CAT.t-tests were used to evaluate physical activity and flourishing pre and post. As previously detailed, each program was evaluated through a pragmatic application of the RE-AIM framework . Paired work see  29, 31), 31t-tesPhase I: ~120 participants attended Mindful Meet-ups each week during the spring of 2020, declining to ~80 participants each week for the following semesters. The overall agent denominator of VCE is 220 for a proportion of 54.5% in the first semester and ongoing reach of 36.3% for the remaining two semesters. A majority (51%) of participants were from Family and Consumer Science and the Family Nutrition Program. Phase I was considered 4 for reach.Phase II: The MUSCLE 2-day retreat had 73 individuals registered, and an average attendance of 26 on the day 1 sessions and 19 on the day 2 sessions. The proportional reach of MUSCLE 2-day was based on two denominators: (1) all agents in VCE and (2) agents who attended Mindful Meet-ups, for 33.2 and 91.3%, respectively. Phase II was considered a 3 for reach.Phase III: Seventeen (13% of those eligible) participants completed the 9-week MUSCLE program. Phase III was considered a 1 for reach.via emails and administration for Meet-ups , delivered half of the sessions during semester 2 and 3.The 2-day MUSCLE retreat (Phase II) required ~60 h of work over 6 weeks, including the 8 h each day of the retreat itself. The MUSCLE 9-week program (Phase III) required ~55 h of work for the primary team member over 15 weeks, or ~3 h and 40 min per week. Mindful Meet-ups (Phase I) require only 30 minutes to 1 h per week to deliver, based on if there is a handout for the week or only experiential learning. Both the 9-week MUSCLE program and the 2-day MUSCLE retreat were more labor-intensive programs, as they required more effort from the leading team to implement (see The MUSCLE 9-week program (Phase III) and the 2-day MUSCLE retreat (Phase II) have not been repeated. However, there have been requests from both past participants and those who did not attend the MUSCLE program or retreat to have it held again. The Mindful Meet-ups (Phase I) had support for over 1.5 years from the administration of VCE FCS/FNP as well as Hokie Wellness, however did not receive any support or feedback from administration for a fourth semester. The program leaders for Mindful Meet-ups did receive a number of unsolicited emails from participants speaking about how much they enjoyed the program, how useful it was for them, and how they had grown in mindfulness. One notable email stated, “This was a great program. The program was very informative in helping me become more centered with all the new normals in effect.”Responses on the pre- and post-semester surveys for Mindful Meet-ups were highly limited, despite 58 people registering to attend the sessions and average attendance in the last semester being 13 (range 5–21). There were 9 pre-semester surveys completed and 6 post-semester surveys completed, with only 2 participants completing both the pre-and post- surveys. As Mindful Meet-ups had the longest maintenance of all three programs, it was scored as a 4.5 on maintenance, while both MUSCLE variations were scored as a 1, or “no maintenance” for maintenance. See Throughout the COVID-19 pandemic, needs for mindfulness, physical activity, and human connection evolved rapidly. While many others have explored the need for yoga and mindfulness offerings during the COVID-19 pandemic –48 thereExtension specific Mindful Meet-ups sprung from a desire to connect while working from home in the earliest weeks of the pandemic, and continued to serve throughout the following semesters. The MUSCLE programs, originally conceived prior to the pandemic, pivoted and flowed online and ended up reaching a larger proportion of the target audience than initially thought would be possible. Utilizing the APDER process , the proWhile the MUSCLE programs, in particular the 2-day retreat, were well attended, interest in conducting/attending them again has waned. This may be in part due to increased in-person activities, a proliferation of mindfulness and wellness based programming, or general disinterest in more mindfulness and physical activity content. When the last semester of Mindful Meet-ups came to a close, there was interest in continuing them from the participants, but due to shifting availability in the program leaders and wider availability of other, similar programs, Mindful Meet-ups was also discontinued. Participants from both the MUSCLE and Mindful Meet-ups who have expressed desire to attend more mindfulness and physical activity-based programming have been directed to other, on-going efforts that are not employee based and instead serve the general public. Some of these efforts include programs delivered by Hokie Wellness, who had partnered for the delivery of the Mindful Meet-ups program. Future research might examine the utilization of these public facing wellness programs as part of employee wellness opportunities and evaluate the effectiveness and need for employee-specific wellness programs.The RE-AIM and APDER cycles can be used before, during, and after implementation to evaluate programs and interventions for appropriateness, effectiveness, and necessity. These are especially helpful as guides when circumstances are changing rapidly, as in a pandemic. While employees expressed appreciation and personal commitment to attending mindfulness and physical activity-based programming throughout a variety of different programming iterations, there was no statistical improvement in flourishing or physical activity able to be discerned from the various programs described above. However, based on employee feedback on feeling valued and increasing their mindfulness practices, paired with the low cost and ease of implementation, employee wellness programs focusing on mindfulness are an important tool to consider when trying to increase employee satisfaction. Future studies may look at effectiveness of various styles of mindfulness programs and implementation and maintenance of those programs.adysart@vt.edu.The datasets presented in this article are not readily available because of limited participant approval. Requests to access the datasets should be directed to AD, The studies involving human participants were reviewed and approved by Virginia Tech Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.AD and SH contributed to the conceptualization and design of the study. AD wrote the first draft of the manuscript with SH providing editing. Both authors contributed to manuscript revision, read, and approved the submitted version.This work was supported by the Virginia Tech Open Access Subvention Fund.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.