Journal of the Society for Psychical Research, (2008) 72, 98-106
by Rupert Sheldrake


Most people have had the experience of turning round with the feeling that someone is looking at them from behind, finding that this is the case. Most people have also found that they can sometimes make people turn around just by looking at them (Sheldrake, 1994, 2003a; Cottrell, Winer & Smith, 1996).

The sense of being stared at (or scopaesthesia: Carpenter, 2005) can be investigated experimentally with people working in pairs, with the looker sitting behind the subject. In a randomized series of trials, the looker either looks at the back of the subjects neck, or looks away and thinks of something else. The looker signals to the subject when the trial begins by means of a mechanically produced sound. After about 10 seconds the subject guesses out loud whether he or she is being looked at or not, and the starer records whether the guess is right or wrong (Sheldrake, 1999). By chance, 50% of the guesses would be correct.

Experiments of this kind are so simple that students can do them in classroom experiments or as projects. Many thousands of trials of this kind have been carried out in schools and colleges, with highly significant positive results. I have organized many of these trials myself, both with children and with adults, and they have been replicated independently by dozens of other investigators in several different countries (Sheldrake, 1998. 1999, 2003a, 2005).

The results usually showed a distinctive pattern: in the 'looking' trials, scores were above the chance level, usually around 60%, while in the 'not looking' trials they were close to the chance level of 50%, with overall success rates around 55% (Sheldrake, 1999, 2003a). The patterns of results was similar whether or not the subjects were blindfolded or received trial-by-trial feedback (Sheldrake, 2001), and when they were looked at through closed windows (Sheldrake, 2000) or through a one-way mirror (Colwell, Schröder & Sladen, 2001: experiment 1).

However, not all studies have given similar results. After obtaining highly significant positive results in their first experiment for trials in which feedback was provided (the no feedback condition was at chance), Colwell et al. (2001) conducted a second experiment in which they changed two conditions: a different person served as starer and they used a different randomization procedure. The results were close to the chance level. They concluded that the difference from their first experiment must be due to the randomization method rather than the change of starer. But their assumption that the difference in outcome could not be due to a change in starer may well be invalid: in a study using a different technique, in which starees were looked at through a closed circuit television (CCTV), Wiseman and Schlitz (1997) found a striking experimenter effect whereby the results were non-significant when Wiseman, a sceptic, was the starer, while with Schlitz as starer, the results were positive and statistically significant.

Marks & Colwell (2001) argued that the positive result in Colwell et al.s (2001) first experiment might be an artifact that arose because of a particular set of randomized score-sheets that I used in some of my experiments, and that Colwell et al. used in theirs. The randomizations involved counterbalanced sequences, and Marks & Colwell showed these particular sequences contained more alternations than would be expected in structureless randomizations. They argued that when starees were given trial-by-trial feedback, they could have learned implicitly there were patterns in the randomizations, and somehow used this information to score at above-chance levels. This hypothesis implies that scores should increase towards the end of tests because there has been more opportunity for implicit learning to occur.

Lobach & Bierman (2004) carried out two staring experiments with student participants in which starers and starees were separated by a one-way mirror. (They also carried out a study using CCTV.) In the first experiment, there was a significant positive result only with starers who were sceptics, and not with starers who were believers. In the second experiment there was no significant effect. They discussed several reasons for the weakness or absence of effects in their studies, including a possible inhibitory effect of the formal laboratory setting and the fact that starees were not blindfolded but had their eyes open and had to respond by making their guesses through a computer. Like Marks & Colwell (2001), they also explored the possibility that in some of my own tests, starees given trial-by trial feedback could have obtained hit rates above chance artifactually, through a combination of two effects. First, with randomization sequences that had too frequent alternations between looking and not-looking trials, starees could have elevated their hit rates by alternating their guesses. Second, if the total number of looking and not-looking trials was equal, or nearly equal, and if subjects remembered the number of looking and not-looking trials, then towards the end of the test it should become increasingly possible to predict whether a looking or not-looking trial would come next. Scores should therefore improve towards the end of the test. They carried out computer simulations that showed that such guessing strategies could indeed produce artifactual positive results. Moreover, by adding in a response bias in favour of saying "looking", their simulations reproduced a similar pattern of results to those found in many previous staring tests, with hit rates in 'looking' trials close to 60% and in 'not-looking' trials about 50%.

Thus both the Marks & Colwell hypothesis and the Lobach & Bierman hypothesis would predict that scores should improve towards the end of tests in which feedback was given.

By contrast, in a small-scale study with trial-by-trial feedback, Radin (2004) found the opposite: scores were highest in the first few trials and fell off toward the end of the session.

For all these reasons, it is of interest to know whether there is a general tendency for scores to increase or decline during tests on the sense of being stared at. I therefore re-examined the data from more than 19,000 trials conducted by myself and by other investigators to see if scores increased or decreased as the sessions went on. I did this by comparing the results from the first and second halves of the sessions, which usually consisted of 20 trials altogether. I analyzed results from tests conducted with and without feedback, and from tests using different randomization procedures: counterbalanced randomization sequences, structureless randomizations given by coin-tossing and computerized randomizations.

These comparisons enabled several different hypotheses to be tested:

  1. If the positive results in staring trials depend on the Lobach & Bierman (2004) strategy or the implicit learning hypothesis of Marks & Colwell (2001), results should increase significantly in the second half of the tests. This improvement should only be apparent in experiments with trial-by-trial feedback, and with counterbalanced randomization sequences. Both these hypotheses would predict that in experiments with no feedback and with 'structureless' randomization, results should be at chance levels throughout.
  2. If the positive results in these trials are a result of artifacts arising from subtle sensory cues that are learned as a result of feedback, then scores should be higher in the second half of trials with feedback than in the first half, and should remain at chance levels in trials without feedback. A similar pattern of results should be obtained whatever the randomization system.
  3. If the decline effect observed by Radin (2004) is of general occurrence, then scores should be lower in the second halves of the sessions.

In order to test these predictions, I have compared the results from the first and second halves of the test sessions.


I used data from my own tests and from those conducted by other investigators, details of which have already been described in previous publications. I retrieved the original score sheets for all these tests, and examined these score sheets to find out how many guesses were correct in the first and second halves of the test session for each subject. These 'first' and 'second' scores were then tabulated.

Both the Marks & Colwell and Lobach & Bierman hypotheses applied specifically to a particular set of counterbalanced randomized sequences that I used in some of my own experiments, and which were also used in tests conducted in schools in Connecticut by schoolteachers. Also their hypotheses apply only to tests in which trial-by-trial feedback was given. For this analysis I selected experiments that included these particular sequences, and compared them with other experiments in which different randomization methods were used and/or there was no feedback. In particular, I compared experiments in Connecticut schools with the counterbalanced randomized sheets and with coin tossing as the means of randomization. I compared experiments in a London school using counterbalanced randomization sheets with and without feedback. I also included an experiment I conducted with adult participants with coin-tossing randomization and feedback.

I also included data from an experiment conducted with automated instructions online in which the randomization was provided by an automatic randomization system, as described by Sheldrake (JSPR, under review). As in the coin-tossing method, the number of looking and not-looking trials in each test varied at random, although on average there were roughly equal numbers of each. In these tests with automated instructions, some starees received feedback and others did not. As described by Sheldrake (JSPR, under review) data from high-scoring participants (those with more than 17 hits out of 20) were not included in the analysis because of the possibility that they might have been cheating.

In this paper I describe the results of all these pre-selected data-sets there was no exclusion of data-sets after the analysis had been conducted. The details were as follows:

  1. Connecticut 1996 (CT-96): Experiments with feedback in five schools in Connecticut, USA, carried out by science teachers using coin-tossing randomization (Sheldrake, 1998, Table 2). In these tests the number of trials per session differed from school to school, and ranged from 20 to 40. There were always even numbers of trials. For the analysis reported here, the number of trials was divided into two equal halves. When there were 40 trials per session, for example, the first sample consisted of the first 20 and the second of the remaining 20 trials.
  2. Connecticut 1997 (CT-97): Experiments without feedback in seven schools in Connecticut using my score sheets with counterbalanced randomizations and 20 trials per session. In these and other tests using my counterbalanced randomizations there was a set of 24 different score sheets. These tests were carried out by science teachers in seven schools (Sheldrake, 1999, Table 3, excluding data from Sam Brown).
  3. University College School, London, winter 1997 (UCS-F): My own experiments with children given feedback, using score sheets with counterbalanced randomizations and 20 trials per session (Sheldrake, 2001, Table 1A).
  4. UCS Junior Branch, Spring 1997 (UCS-N): My own experiments with children without feedback, with starers and starees separated by closed windows, using score sheets with counterbalanced randomizations and 20 trials per session (Sheldrake 2000, Table 1).
  5. Holma College, Höör, Sweden, 2000 (Holma),: My own experiments with adults given feedback, using coin-tossing for randomization and 20 trials per session (Sheldrake, 2002).
  6. Data from the automated online test procedure accessed through my web site ( as described in Sheldrake (JSPR, under review).

The statistical significance of the hits rates was calculated using the binomial test, one-sided, with the null hypothesis that the hit rates would be at the chance level of 0.5. For a comparison of the hit rates in the first and second halves of each experiment, the 2x2 chi-squared test was used (Campbell, 1989).


Tests with feedback

In all the tests with feedback, the hit rates were above chance in both the first and the second halves. In the three conventional experiments, there was a slight increase in the hit rates in the second halves, but there was no such increase in the automated test online (Table 1A). None of these changes in hit rate was statistically significant.

Tests without feedback

In the experiments without feedback, the scores were above chance levels in both the first and the second halves (Table 1B). In all cases, the percentage of correct scores was slightly lower in the second halves of the tests, but the differences were not statistically significant.

Table 1

Comparison of hit rates in the first and second halves of test sessions with feedback (A) and without feedback (B). The total number of trials in each half is shown together with the numbers and percentages of hits in the first (1) and second (2) halves. There were three methods of randomization: by tossing coins (Coins), using counterbalanced randomization sheets (Sheets) and by an automatic computer-based randomization system (Auto). The column headed p diff contains p values from statistical tests for a difference between 1 and 2.

A: With Feedback

Test diff Randomization Trials 1. Hits p 2. Hits p 1. % 2. % p diff
CT-96 Coins 822 444 0.01 464 3x10-4 54.0 56.4 0.32
UCS-F Sheets 780 446 3x10-4 461 >10-1 57.2 59.1 0.44
Holma Coins 380 206 0.06 219 0.002 54.2 57.6 0.34
Online Auto 2880 1622 <1x10-6 1617 <1x10-6 56.3 56.2 0.89

B: Without Feedback

Test Randomization Trials 1. Hits p 2. Hits p 1. % 2. % p diff
CT-97 Sheets 940 522 4x10-3 517 0.001 55.5 55.0 0.81
UCS-N Sheets 1540 820 0.005 796 0.09 53.2 51.6 0.22
Online Auto 2530 1326 0.008 1319 0.02 52.4 52.1 0.84

Trialwise results

For the automated tests, the trial-by-trial results for tests with and without feedback are shown in Figure 1. The hit rates with feedback were generally higher than those without, but there was no obvious trend over time, nor was any significant trend revealed by linear regressions. The most striking feature was the data for the first trial, where starees who were about to receive feedback had an extraordinarily high hit rate of 67.7%, while those with no feedback were slightly below the chance level, with 47.8%. This difference was very significant statistically (chi-squared=21.9; p<< 1x10-6).

Figure 1. Trial by trial hit rates in the experiment with automated instructions online for tests with and without feedback.


The overall results were clear. In all experiments, the scores were very significantly above chance in both the first and the second halves of the tests.

In trials with feedback, there was a small increase in scores in the second halves of the sessions, but this was not statistically significant. In trials without feedback, there was a small but non-significant decrease in scores in the second halves (Table 1). These general conclusions were illustrated in more detail by the trialwise data from the test with automated instructions online (Figure 1).

These findings have the following implications for Hypotheses 1 to 3 outlined in the Introduction:

  1. The hypothesis of Marks & Colwell (2001) predicted that scores be above chance in the second halves, but only in trials with feedback and with counterbalanced randomizations. This was clearly not the case. The scores in the first halves were also above chance, and there was no significant increase in the second halves, even with feedback (Tables 1). Moreover, the results were very similar with counterbalanced randomizations and with structureless randomizations produced by coin tossing. Thus the data clearly go against the Marks & Colwell hypothesis, and also the Lobach & Bierman (2004) hypothesis, in so far as it predicts that scores should increase towards the end of the test. However, the Lobach & Bierman hypothesis would allow starees to obtain above-chance scores even in the first half by using an alternating guess strategy, but this would only be possible with the counterbalanced sequences and with feedback. The experiment that met these conditions was UCS-F (Table 1A), and if these data were taken in isolation, their hypothesis might seem plausible. But it is not plausible in view of the fact that that similar patterns of results were obtained with other randomization methods and in tests without feedback.
  2. The hypothesis that subjects learned through feedback to recognize subtle sensory clues likewise conflicts with the fact that the scores were positive both with and without feedback. Moreover, the scores were positive in the first halves of the sessions, before this hypothetical learning could plausibly have happened. Most remarkably of all, the highest hit rate occurred in the very first trial for starees in the feedback condition (Figure 1). But precisely because this was the first trial, when they made their guess they had not received any feedback at all! The large and very significant contrast between subjects in the feedback and no-feedback conditions cannot be explained in terms of feedback or its absence. Perhaps the most plausible explanation would be in terms of psychological differences caused by these different situations: starees knowing they are about to receive feedback may be more engaged with the testing process, and less nervous. By contrast, the lack of feedback may have an alienating effect on the starees and make them more self-conscious, inhibiting their ability to guess correctly. But whatever the explanation, it is clear that the higher hit rates with feedback than without are not because of any learning effect enabled by the feedback because feedback confers an advantage right from the outset, even before it has happened.
  3. The decline effect observed by Radin (2004) in tests with trial-by-trial feedback was not observed here and hence does not seem to be a general phenomenon in trials of this kind. Radins subjects were tested under formal laboratory conditions, and about half of them were teenagers unused to this kind of environment. Radin himself has suggested that they might have been intimidated by being tested in a laboratory known for investigating psychic phenomena, and may have experienced rising performance anxiety (Radin, personal communication, June 6, 2004). The subjects in the experiments described in this paper were tested under more informal conditions where their enthusiasm and curiosity probably sustained the interest of both starees and starers.

If the sense of being stared at is real, then it should be detectable from the outset of the session, and need not necessarily increase or decrease towards the end of the session. Thus the first and second halves should be more or less the same. With feedback, the scores might improve through a learning effect akin to biofeedback, and in fact there was a small and just-significant improvement (Table 3A). In trials without feedback, which are less interesting to take part in, there might be a tendency for subjects to get bored, or starers to concentrate less, leading to a decline. There was in fact a tendency for scores to decline, but it was not statistically significant (Table 3B).

In summary, the data from the first and second halves of these experimental sessions show a consistent pattern that goes against hypotheses that try to explain the results as artifacts. They support an interpretation in terms of the reality of the sense of being stared at.


This work was supported by the Lifebridge Foundation, New York, the Bial Foundation, Portugal, the Institute of Noetic Sciences, California, and the Perrott-Warrick Fund, administered by Trinity College, Cambridge.


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