A two-person effort: On the role of the agent in EDA-DMILS experiments.
For over two decades, parapsychologists have accumulated empirical evidence suggesting a so-called Direct Mental Interaction With Living Systems (DMILS). This unorthodox form of interaction involves changes in one person's autonomic nervous system covarying with a second, distant person's intentions (see Schlitz & Braud, 1997). From the numerous parameters of the autonomic nervous system, electrodermal activity (EDA) is by far the most favored indicator for the DMILS effect: Being largely affected by unconscious processes (Boucsein, 1995; Edelberg, 1972; Roy, Sequeira, & Delerm, 1993), inferences drawn from EDA allow a more reliable interpretation than, for instance, inferences drawn from physiological signals, which are more susceptible to arbitrary (intentional) control (e.g., heart rate).
To date, there is no commonly accepted model of how this distant mental interaction operates. There seems to be a consensus, however, that specific favorable states of the two systems (agent and receiver) are conducive to the effect (see Braud, l980a, 1980b). At the beginning of experimental DMILS work, Braud postulated that two systems best "fit" or "conform" when one, the target system, is relatively labile and the other, the influencing system, is relatively stabile. In line with this view, Braud and Schlitz (1983) found lability, as operationalized by more FDA at rest, to be a potential prerequisite for the agent's calming effort. Unfortunately, there are no systematic follow-up studies on the significance of such state variables. In a recently conducted series of DMILS experiments, electrodermal lability was not shown to be an important variable for the DMILS effect (Schneider, in press).
However, the DMILS effect is usually regarded as the result of a joint endeavor (Braud & Schlitz, 1991), and the experimental setting is sometimes referred to as a healing analogue (Schlitz & Braud, 1985, 1997). Hence, there have been various attempts to identify important factors on behalf of both agent and receiver. Among these are, for instance, the participants' relatedness (Delanoy, Morris, Brady, & Roe, 1999), experimenter effects (Delanoy & Morris, 1999), and blocking or cooperating strategies (Braud, Schlitz, Collins, & Klitch, 1984; Watt, Ravenscroft, & McDermott, 1999). Unfortunately, the search for moderating variables has not been very successful in explaining how the effect is brought about. As a consequence, the process-oriented approach to DMILS rather resembles the figurative search for the needle in the haystack: No firm conclusions can be drawn as to what variables are to be considered for a successful DMILS study.
So far, only little attention has been devoted to the actual necessity of an agent and, therefore, the role of the agent is underresearched. In the DMILS paradigm, no studies have addressed this topic. A remote staring study (an experimental setting very similar to DMILS) by Braud, Shafer, and Andrews (1993) found that an experimental control condition ("sham"), in which the data were recorded without any starer present, produced no significant differences in the starees' EDA.
Results from other parapsychological paradigms involving two interacting individuals have not produced any significant conclusions either. For example, surveys of the ganzfeld literature by Palmer (1978) yielded rather heterogeneous results. From the few studies applying a systematic comparison between the presence or absence of an agent and the experimental outcome, some attributed only little importance to the agent's presence (e.g., Carpenter, 1977). Other studies yielded better results with an agent present (Raburn & Manning, 1977). Still others found no differences between different sending conditions (Morris, Dalton, Delanoy, & Watt, 1995; Williams, Roe, Upchurch, & Lawrence, 1994).
From a theoretical point of view, there are numerous ways how the DMILS effect might occur without any agent being present at all (Stokes, 1987). For example, one could conceive of the effect as the consequence of the receiver's precognition. Thus, a person would "foresee" the sequence of influencing epochs (activating and calming) and adjust his or her physiological arousal accordingly. Obviously, this line of reasoning would not regard the agent as a necessary prerequisite (although he or she might have a relevant psychological impact). However, if an intentionally active agent is crucial for the DMILS effect, it might be worthwhile to explore his or her role in more detail.
This apparent lack of consistent empirical evidence led us to design a study in which the agent's role in the DMILS setting was systematically explored. We compared sessions with and without an agent being intentionally active (i.e., attempting to activate or calm the receiver). Because there are various ways to assess EDA (Boucsein, 1992) and because little is known about the functional significance of various EDA parameters (which parameter best indicates an effect?), this study was also designed to explore these issues in more detail. This topic is vital for the DMILS paradigm because the majority of the published DMILS studies do not use standard psychophysiological methodology (Schmidt & Walach, 2000) and, therefore, the size of the true DMILS effect is unknown (Schneider, Binder, & Walach, 2000). Hence, it is questionable whether the reported effect by Schlitz and Braud (1997) is subject to artificial biases. For example, in a recently conducted EDA-DMILS pilot study by Schmidt, Schneider, Binder, Burkl e, and Walach (2001), various EDA parameters yielded comparable effect sizes clearly larger than the one reported in Schlitz and Braud's meta-analysis (ES= .4 to .46 vs. ES= .25; with ES representing Rosenthal's r). Yet, in another four DMILS studies (Schneider, in press), only one EDA parameter (number of nonspecific skin conductance responses [NS.SCR freq]) turned out to be a functional indicator with significant effect sizes of -.49 (Experiment 3) and .52 (Experiment 4). Hence, it is unclear which EDA parameters should be included to best reflect a DMILS effect.
To further explore the role of the agent, we assessed the participants' and the experimenters' estimation of various features of the experimental setting. Specifically, we were interested in whether the experimental outcome (i.e., the difference in EDA during remote calming and activating) was linked with perceived interconnectedness, sympathy, interest, and enthusiasm.
In accordance with various other DMILS studies (e.g., Braud & Schlitz, 1983; Braud et al., 1984; Radin, Taylor, & Braud, 1995), we confounded the roles of the experimenter and the agent. It should be noted, however, that there are both advantages and disadvantages to this approach. On the one hand, it may be psychologically relevant to include pairs of acquainted participants who are emotionally related to each other. Emotional relatedness should foster potentially relevant variables such as trust and reduce psychological resistance to "influence" or "to be influenced." On the other hand, having the experimenters act as agents is an economic way of running the same number of sessions with only half as many participants, and the power of any given study can considerably be increased. In line with the fact that most DMILS studies are underpowered, this point is of major importance. Because we were primarily interested in exploring the difference between a present, intentionally active agent and an absent, inten tionally inactive one, the experimental protocol seemed to be best met by confounding the roles of agent and experimenter. Furthermore, this approach reduced the number of potential systems involved in the DMILS effect (investigator, experimenter, and agent). However, to check for the quality of the rapport between agent and receiver, both had to complete postexperimental self-rating forms.
Each session encompassed two phases: one with and one without an agent being intentionally active. It consisted of 12 activating and 12 calming epochs of 1-min length interspersed by 15-s pause epochs. Each session started with a pause epoch. After half of the influencing epochs were over, there was a 1-min break to allow the experimenter to either enter or leave the agent's cabin depending on when the randomly generated schedule assigned the influencing phase. The experimenter was informed about this schedule by a written instruction immediately after starting the recording period. The influencing schedule itself was generated by an algorithm 2 weeks before the first session was run. The receivers were kept unaware of the influencing schedule.
Some participants did not show any skin conductance responses (SCRs; nonresponding), and therefore the number of valid recordings of the SCR and skin conductance level (SCL) differed considerably In Condition 1, there were 37 sessions with the agent active in the first half of the session. In Condition 2, there were 33 sessions with the agent active in the second half of the session. The number of valid SCL recordings consisted of 40 sessions with the agent influencing in the first half (Condition 1), and 41 sessions with the agent influencing in the second half (Condition 2). To avoid artifacts (e.g., a match between EDA drift and calming epochs), the sequence of influencing epochs of each half equally used an algorithm that randomly determined the schedule. Each session lasted approximately 32 min.
The decision to split each session in two halves, one with and one without an agent, was based on various considerations. First, it allowed us to reduce receivers' expectations as to exactly when they were to be activated or calmed. Second, the experimenters' involvement as agents for only half of the time helped to sustain their focus on the receivers. Third, balancing the time when the experimenters acted as agent (first half vs. second half) allowed us to check for possible sequential effects.
We initially planned to complete 80 data sets with valid SCR recordings. However, because of a relatively high number of nonresponsive participants, the total N of the SCR records was reduced to 70. The sample with complete SCL measurements consisted of 52 female and 29 male participants between 16 and 68 years of age (mean age = 34 years, SD = 13). The sample with complete SCR measures comprised 42 female and 28 male participants between 16 and 57 years of age (mean age = 34 years, SD = 12).
None of the participants had previously taken part in a DMILS experiment. They were recruited by means of newspaper advertisement and remunerated with DM 20 each (approx. $45). The newspaper advertisement addressed a general public interested in parapsychological phenomena. Whereas the participants acted as receivers, five female experimenters whose ages were between 24 and 36 years acted as agents. From the 70 sessions, Experimenter B ran 16, Experimenter J ran 17, Experimenter L ran 15, Experimenter S ran 14, and Experimenter R ran 8. The experimenters were trained by the second author in an intensive role-play-like fashion. Additionally, they learned about DMILS findings as reported in the parapsychological literature.
Skin conductance was recorded on the nondominant hand by applying a constant voltage of 500 mV. The signal was taken with two Ag/AgCl electrodes (8 mm in diameter) filled with a 0.5% NaCl electrolyte paste in a neutral base (TDE-246, brand name EC-33). The electrodes were attached to the thenar and hypothenar eminences by means of double-sided adhesive collars at least 15 min before the start of data collection. To avoid strain on the electrodes, we attached the wires to the skin of the participant's inner forearm. The skin sites were pretreated with methyl alcohol (70%). To obtain the different EDA parameters, we coupled the signal with an on-line coupler (F. Schafer, University of Wuppertal, Germany). The phasic signal component was obtained by treating the signal with a time constant of 10s (high-pass filtering). The maximal resolution was .0048 MicroSiemens for the phasic component (nonspecific SCRs) and .048 MicroSiemens for the tonic component (SCL). (1)
The EDA signal was taken with a 16-Hz sampling rate and fed forward to a multichannel bioamplifier. (I-410 BCS by J. & J. Engineering, Inc., Poulsboro, WA, USA), which converted the analogue signals into 12-bit digital signals. The data were stored in three channels (SCL, SCR, and respiration) with the experimental condition coded in a fourth channel. The collected data were stored on the hard drive of the recording PC and backed up on a zip-drive.
All physiological data were filtered with a 0.5-Hz low pass. The EDA signals were parameterized by the software EDR_PARA by Schafer (1999). This interactive program detects electrodermal responses (EDRs) and performs a parameterization. Values from the SCL were parameterized by averaging 960 bit values (60 s x 16 Hz) from one influencing epoch. The overall SCL value was obtained for each experimental condition by averaging six activate and six calm epochs. In accordance with the results from a pilot study (Schmidt et al., 2001), all EDRs exceeding .015 MicroSiemens were considered. For each experimental condition, values from the SCR channel were counted and summed up to obtain the number of nonspecific skin conductance responses (NS.SCR freq). Because an EDA-DMILS effect might also affect the strength of the electrodermal responses (Schmidt et al., 2001), their amplitudes were summed to obtain the sum of their weights (Sum NS. SCR amp).
Before parameterization, data were visually inspected by the second author, during which the sequence of epochs (activate and calm) remained blinded. Data sets were excluded from further evaluation when one of the following criteria was met:
1. The mean SCL was smaller than 0.5 MicroSiemens.
2. The data set consisted of less than 10 NS.SCRs exceeding 0.015 MicroSiemens. The rationale behind this reasoning was that a sufficient number of nonspecific responses was needed to statistically evaluate a DMILS effect.
3. Electrodes were detached during the recording process.
4. Incorrect data recording (e.g., incomplete data saving).
The physiological measures were taken at an ambient average temperature of 26[degrees]C and SD = 1.7[degrees]C and an average humidity of 49% (SD = 4.7%).
To assess the participants' and the experimenters' experiences during the DMILS session, we applied postexperimental self-rating forms. They consisted of a visual analogue scale with two labeled anchors:
PARTICIPANTS' RATING ITEMS Score 0 100 It was hard to work with someone It was not hard to work with unknown to me. someone unknown to me. I did not feel connected to the I felt connected to the experimeter. experimenter. I felt at ease here. I did not feel at ease here. I found the experimenter's I did not find the experimenter's introduction pleasant. introduction pleasant. EXPERIMENTERS' RATING ITEMS Score 0 100 Did you feel like easily No Yes cooperating with the participant? During the talk, was the Confident Not confident participant: Interested Uninterested Enthusiastic Sceptical How do you estimate your connection Low High with the receiver? Was the participant: Sympathetic Not sympathetic
To assess the extent to which the participant and the experimenter felt connected to each other, we applied the following interconnectedness score (2)
(Item 5Experimenter + Item 2Participant) --\Item 5Experimenter -- Item 2Participant\.
Hence, the larger the interconnectedness score, the stronger the feeling of interconnectedness, and vice versa.
For each session, one pair of activate and calm values was obtained for every single physiological parameter (EDA). Because we were interested in recording periods with and without an agent, the 12 influencing epochs per session were split into 6 activate and 6 calm epochs (within measurement). Under the null hypothesis, no significant difference should be observed between the physiological arousal of the receivers between activation and calming when no agent was present. Under the alternative hypothesis, the receivers' physiological arousal between the agents' calming efforts and activating efforts should significantly differ. To test for this, we applied dependent t tests. (3) Because of the exploratory character of this study and the (so far) largely unknown intercorrelations of the physiological parameters in DMILS settings, no adjustments of the significance level were made (i.e., all tests were applied to the .05 significance level). In accordance with the DMILS tradition (Braud & Schlitz, 1991), effect sizes were calculated following the effect size measure
r = [square root of ([t.sup.2]/[t.sup.2]+df)]
We also tested for differences between the experimental conditions (agent vs. no agent; first condition vs. second condition). To do so, we performed analyses of variance (ANOVAs) with repeated measures on the within factor (first half vs. second half). To estimate the experimental success, we calculated a dependent variable according to the following formula: (4)
q = 1n A+1/2/C+1/2([square root of ((A+1/2)(C+1/2)/A+C+1)])
where A = activating epochs and C = calming epochs. According to this formula, the physiological values were standardized (M = 0, SD = 1) such that positive q values indicated greater physiological activity during remote activation than during calming attempts and vice versa. This index is called the q index.
The experiment was carried out at the Institut fur Grenzgebiete der Psychologie und Psychohygiene, Freiburg, Germany. The DMILS laboratory consists of two electromagnetically shielded and sound-attenuated cabins at approximately 10 m distance from each other. The electromagnetic attenuation of both rooms was between the range of 10 KHz to 1 GHz.
On arriving at the institute, the participant was welcomed and escorted to the lab. The participant signed an informed consent, and the electrodes were fixed. (5) Then the experimenter explained the experimental procedure. Specifically, the participant was told that the experimenter would try to activate or calm him or her in one half of the recording time. After an informal prechat addressing the participants' interest in the study as well as the experimental procedure, the participant was shown the agent's cabin and then guided into the receiver's room. The participant was instructed to remain in a passively alert state without deliberately trying to become aware of the experimenter's intentions. Rather, he or she should keep an open and receptive attitude. To do so, a pleasant screen saver program (Northern Light) was displayed on a monitor, which could be watched if wished. Then the experimenter closed the two doors of the cabin and checked the proper recording of the EDA. When starting the session, the e xperimenter was informed in which condition she had to act as agent. If the participant was to be influenced in the first half of the session, the experimenter went straight to the agent's cabin and followed the instructions (activate, calm, rest) displayed on a feedback monitor. A real-time trace of the receiver's actual phasic EDA served as feedback for the experimenter's influencing attempts. The end of the influencing period (i.e., after six activate and six calm epochs) was provided acoustically. The experimenter left the cabin and engaged in some distracting activity (e.g., reading a newspaper). In the second experimental condition, the experimenter engaged in some distracting activity during the first half of the experiment. The end of the first half was indicated by an acoustic signal. There was a 1-min time lag to allow the experimenter time to get seated in the agent's cabin without having to rush. When the session was over, the experimenter left her cabin, went to the receiver's room to accompany t he participant out of the room, and had him or her complete a short postexperimental form. Then, both experimenter and participant were given the opportunity to share their experiences of the experiment. After the participant had been remunerated and discharged, the experimenter completed her postexperimental form. All forms were collected in a sealed box that was only opened after the completion of the study.
Participants will produce a significant DMILS effect with an agent present, but not with no agent. This hypothesis was tested by
(a) comparing the DMILS scores with MCE separately for the agent and no-agent conditions and
(b) comparing the q index between the agent and no-agent conditions.
Hence, the two alternative hypotheses read as follows:
(a) With agent present only, there should be greater physiological activation during activating than during calming epochs for at least one EDA parameter. This effect should occur independent of the actual half of influence. Thus, there should be an overall agent effect for the first condition, for the second condition, and for both conditions combined. No prediction was made as to which parameter(s) would indicate the DMILS effect.
(b) DMILS scores ("experimental success") will be significantly higher (more positive) in the agent condition than in the no-agent condition.
Irrespective of any DMJLS effect, we assumed significant within differences for the experimental success in both conditions but no differences between the two conditions. This would indicate if there was any superiority for pairs (agent and receiver) as opposed to individuals (receivers alone). Specifically, at least one of the q indices for the three EDA parameters was assumed to differ for the recording halves with and without agents.
We expected a significant positive correlation between the experimental outcome and the interconnectedness score both for the total sample and the samples of the two conditions. To do so, we chose the EDA parameter that yielded the largest effect size.
We expected a significant positive correlation between the experimental outcome and the experimenters' and the participants' ratings on the quality of the experimental setting.
Hence, there should be positive correlations between the q index of the EDA parameter with the largest effect size and the participants' perceived quality of the introduction, the degree of cooperation, and the feeling at ease. Likewise, there should be positive correlations between the q index and the experimenters' ratings on the participants' cooperation, interest, confidence, enthusiasm, and sympathy.
When testing Hypothesis 1, we found significant differences in the physiological activation of the receivers when they were remotely activated and calmed (see Table 1). From the three EDA parameters, this was true for the SCL and the Sum of NS.SCR amp. Thus, the receivers' activation during activating attempts showed both higher SCL and higher SCRs. For the recording period when no conscious influencing attempt was made, no such differences were found. As can been seen in Figure 1, the obtained effect sizes for the significant EDA parameters varied between .23 for the SCL and .31 for the Sum NS.SCR amp.
When we examined the time (half) when the receivers were influenced, the comparison of the receivers' EDA yielded significant differences for the EDA parameters SCL and Sum NS.SCR amp in the first condition. The respective effect sizes were .32 for the SCL and .28 for the Sum NS.SCR amp. In the second condition in which the receivers were remotely influenced in the second half of the session, only the EDA parameter Sum NS.SCR amp yielded a significant effect size of .33.
To test Hypothesis 2, we applied a between/within ANOVA, with condition (order of influence) as the between variable, agent/no-agent as the within variable, and the three q indices (NS.SCR freq, Sum NS.SCR amp, and SCL) as the dependent variable. Contrary to our expectation, none of the results indicated within differences of the agent factor: NS.SCR freq, F(1, 68) = 0.03, p = .995; Sum NS.SCR amp, F(1, 68) = 1.5, p = .225; and SCL, F(1, 79) = 0.78, p = .379. In accordance with the prediction, the results for the order factor were not significant: NS.SCR freq, F(1, 68) = 3.67, p = .065; Sum NS.SCR amp, F(1, 68) = 0.5, p .831; and SCL, F(1, 79) = 0.68, p = .411; nor was the interaction: NS.SCR freq, F(1, 68) = 3.51, p = .065; Sum NS.SCR amp, F(1, 68) = 0.4, p = .844; and SCL, F(1, 79) = .023, p = .88. Thus, the experimental success (i.e., the difference of the physiological activation between activation and calm epochs) did not differ between the half with and the half without senders in either condition.
To test Hypothesis 3, we correlated the interconnectedness score with the q index of the Sum NS.SCR amp, which yielded the strongest effect of the EDA parameters. Surprisingly, the correlation coefficient of r= -.039 (p = .373) was negligibly small, thereby not confirming our assumption. The pattern of results for the two condition samples confirmed this lack of relation (Condition 1: r=-.123, p=.234; Condition 2: r=.021, p=.453). Hence, Hypothesis 3 was not confirmed.
When testing Hypothesis 4, we found no significant correlations between the experimental success and the various psychological variables (see Table 2). Thus, Hypothesis 4 was not confirmed. Although the item means indicated that the participants felt at ease and were described by the experimenters as confident, interested, enthusiastic, and sympathetic, this did not have any impact on the experimental outcome. It is noteworthy, however, that both the experimenters and (especially) the participants found it difficult to work with someone unknown, as indicated by the low values.
The results of this study indicate some interesting practical consequences. First, they support the view that the DMILS effect could be regarded as a two-person effort. As indicated by the separate analyses for the influencing halves, greater physiological activation of the receivers was only found when the experimenters were consciously focused on their counterparts (see Table 2). The effect sizes observed varied from .23 to .33 for the various EDA parameters. Although we deliberately chose not to correct for multiple testing because little is known about the various EDA parameters as DMILS indicators, we still obtained a significant effect for the parameter Sum NS.SCR amp when the significance level was adjusted to [alpha] = .017 (Bortz, 1993). However, the effect sizes obtained were smaller than the ones observed in Schmidt et al.'s (2001) pilot study. Because this study had a sufficient power of 1-[beta] > .9 when taking the average effect size of .4 from the pilot study as the power analytical basis (Coh en, 1988), it is conceivable that the true effect actually is smaller (compared with the one reported by Schlitz & Braud, 1997) even when standard psychophysiological requirements are fully met.
Interestingly, although a DMILS effect emerged when an agent was present, these DMILS scores were not significantly higher than the DMILS scores when there was no agent present. Hence, the two sets of results are contradictory with regard to the hypothesis and therefore only provide partial support of it, because the latter was confirmed by only one of the two sets of analyses. However, when taken together, this pattern of result could best be characterized as "weakly" supporting the hypothesis.
Obviously, we are far from providing a theoretical framework of how the effect is causally brought about. Nevertheless, these findings may have some important implications for future DMILS studies. Our results indicate that the quality of the rapport between the participant and the experimenters does not seem to be vital for the effect; nor does the feeling of interconnectedness. How do we reconcile this counterintuitive finding with our (fragmentary) conception of the effect? Should the idea "to influence" and "to be influenced" not be bound to psychological features of the quality of the relationship?
According to our view, psychological qualities such as ease and trust are of minor importance for the DMILS effect (as indicated by the low correlations with the experimental success). This view is in line with a recently conducted study (Schneider et al., 2000), which revealed effect sizes three times larger when the quality of the experimenter-participant interaction was neutral than when it was personal. Moreover, a lack of personal or intimate relationship between the participants does not reduce the possibility of the DMILS effect (as reflected by the low degree of easiness of cooperation in Table 2). In our view, this finding is especially interesting because it provides a strong argument against the objection of potentially confounded psychological factors such as social desirability. Therefore, there is no justification to assume that the validity of the assessment of the psychological variables was deteriorated (note that all postexperimental forms were anonymous and were not revealed before the end of the study).
A more important psychological aspect, however, seems to be the participants' knowledge about attempts at influence or interacting in the course of the physiological recording. Possibly, such knowledge reduces existing implicit or explicit resistance toward the occurrence of a DMILS effect. Future DMILS studies should explore this idea in more detail, for example, by varying the time of interaction between agent and receiver.
With regard to our second aim of this study, which was to explore the various physiological parameters, different (albeit linked) EDA parameters turned out to be sensitive indicators for the DMILS effect. Interestingly, the biggest effect sizes were found for the parameters that weights the reactions by their amplitudes (Sum NS.SCR amp): The participants showed larger psychophysiological reactions when they were remotely activated. However, significant effects were also observed for the tonic EDA parameter SCL (overall sample and sample of the first condition) that was exclusively used as the dependent variable in the last decade of EDA-DMILS research. Because the SCL is a comparatively slow-changing signal over time (Boucsein, 1992), the DMILS effect was therefore also found when one looks at the overall arousal. The finding that the SCL signal was marginally significant for recording periods when no agent was consciously focused on the receivers best fits with the view that a consciously focused agent might be a necessary yet not sufficient (exclusive) condition for the DMILS effect.
Nonetheless, the results indicate varied functional significances of the different EDA parameters. This is especially interesting in light of the fact that we found all three parameters to be highly intercorrelated for both the activate epochs and the calm epochs (r=.75 to r=.97). If our results are not due to mere chance (which would ultimately "cause" significances in single parameters), this still leaves the question of which parameter should be preferred to detect a DMILS effect. Until this question has sufficiently been answered, we recommend further systematic exploration of all three EDA parameters.
This study was funded by the Institut fur Grenzgebiete der Psychologie und Psychohygiene, Freiburg, Germany. We appreciate the helpful comments on this article from Fiona Steinkamp and Stefan Schmidt. We are also grateful to Birgit, Leonie, Judith, Susanne, and Rebekka for their wonderful job as experimenters.
(1.) We also assessed respiration activity (thoracal and abdominal). Because of the results of another study (Schmidt et al., 2001) in which the EDA-DMILS effect partially dramatically dropped in size (up to 70%) when electrodermal reactions related to changes in respiration (e.g., deep inhalations) were discarded from statistical analysis, we did not treat respiratorily elicited EDRs as artifacts.
(2.) We thank Stefan Schmidt for this suggestion.
(3.) In accordance with the results from the above reported pilot study (Schmidt et al., 2001) we applied t tests for normally distributed EDA data to obtain the biggest effect sizes.
(4.) We thank Werner Ehm for this suggestion.
(5.) The time lag between electrode fixing and EDA recording did not fall below 15 min. This helped to avoid destabilizing effects due to differences between paste electrolyte and skin electrolyte concentration in the initial phase of application (Boucsein, 1992).
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[Figure 1 omitted]
TABLE 1 RESULTS FROM THE EDA RECORDINGS (SKIN CONDUCTANCE) Total sample Agent (b) t df p ES SD (a) SCL (d) 2.08 80 .021 .23 .1 NS.SCR freq (e) 0 69 .5 0 .1 Sum NS.SCR amn (d) 2.67 69 .005 .31 .1 Total sample No agent (c) t df p ES SD SCL (d) 1.88 80 .063 .21 .1 NS.SCR freq (e) 1.09 69 .281 .13 .1 Sum NS.SCR amn (d) 1.04 69 .15 .12 .1 Condition 1 1st half (agent) (c) t df p ES SD (a) SCL 2.11 39 .021 .32 .13 NS.SCR freq 0.93 36 .181 .15 .16 Sum NS.SCR amp 1.73 36 .046 .28 .14 Condition 1 2nd half (no agent) (b) t df p ES SD SCL 1.02 39 .312 .16 .15 NS.SCR freq 0.67 37 .491 .11 .16 Sum NS.SCR amp 1.24 37 .223 .20 .15 Condition 2 1st half (no agent) (c) t df p ES SD (a) SCL 1.68 40 .101 .26 .14 NS.SCR freq 0.84 32 .31 .15 .17 Sum NS.SCR amp -0.03 32 .98 -.01 .18 Condition 2 2nd half (agent) (b) t df p ES SD SCL 0.87 40 .196 .14 .15 NS.SCR freq -0.78 32 .22 -.14 .17 Sum NS.SCR amp 2.01 32 .027 .33 .15 Note. EDA = electrodermal activity; SCL = skin conductancel level; NS.SCR freq = number of nonspecific skin conductance responses; Sum S.SCR amp = sum of the amplitudes of the NS.SCR. (a)SD = [square root of (1 - [ES.sup.2]/N - 2)] (Rosenthal, 1994). (b)One-tailed tests. (c)Two-tailed tests. (d)Unit: MikroSiemens. (e)Unit: absolute number. TABLE 2 CORRELATIONS OF THE EXPERIMENTAL SUCCESS (Q-INDEX OF SUM NS.SCR AMP) AND THE POST-EXPERIMENTAL RATINGS OF PARTICIPANTS AND EXPERIMENTERS Participant Mean (a) r p Easiness of cooperation 10 .071 .282 Feeling at ease 85 (b) 052 335 Pleasantness of introduction 91 (b) 014 454 Experimenter Participant Mean (a) r p Easiness of cooperation 32 -.065 .207 Participant's confidence 76 (b) -.1 .206 Participant's interest 79 (b) -.022 .429 Participant's enthusiasm 67 (b) .029 .405 Sympathy for participant 72 (b) -.142 .122 Note. NS.SCR amp = sum of the amplitudes of the nonspecific skin conductance reactions. (a)Item range = 0-100. (b)Score reversed.
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|Title Annotation:||Direct Mental Interaction With Living Systems; electrodermal activity|
|Author:||Schneider, Rainer; Binder, Markus; Walach, Harald|
|Publication:||The Journal of Parapsychology|
|Article Type:||Statistical Data Included|
|Date:||Sep 1, 2001|
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