| Study | Effect expected | N | Trials | M | SD | Hits (%) | t | p | ES | Var | BF | Direction | Year | Lab/Online |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Erotic Images 2 | ✔ | 678 | 50 | 25.13 | 3.52 | 50.26 | 0.95 | 0.34 | 0.04 | 0 | 0.64 | greater | 2017 | 🌍 |
Erotic Images 2
Hypothesis
The study aimed to explore the potential micro-psychokinetic effects of viewing erotic images, specifically whether individuals can subconsciously influence the number of erotic images they see, deviating from what would be expected by chance. Six hypotheses were developed to test this phenomenon, comparing the number of erotic images seen by different participant groups against random chance using Bayesian one-sample t-tests.
Hypothesis 1 predicted that individuals who frequently consume pornography and have a positive, healthy relationship with it would see more erotic images than expected by chance, as their subconscious desire would influence the outcome.
Hypotheses 2 and 3 focused on singles: satisfied singles were expected to see more erotic images due to their contentment, while dissatisfied singles were predicted to see fewer images because of their perceived lack or deprivation, drawing on findings from a similar study involving nicotine-dependent smokers.
Hypotheses 4 and 5 mirrored this logic for people in relationships: satisfied individuals were expected to see more erotic images, while dissatisfied individuals were predicted to see fewer, again due to perceived lack.
Hypothesis 6 extended this reasoning to individuals addicted to internet pornography, suggesting that they would see fewer erotic images due to their addiction, which creates a constant sense of deprivation. This hypothesis was particularly influenced by the concept of a self-fulfilling prophecy, where the subconscious state of deprivation leads to fewer instances of the desired outcome, as seen in similar studies on addiction.
Participants
| Characteristic | Count/Statistic |
|---|---|
| N | 678 |
| Female | 34.66% |
| Male | 64.31% |
| Mean Age | 26.06 years |
| SD Age | 7.77 years |
Materials
The study aimed to investigate whether people’s attitudes toward pornography could influence the number of erotic images they see, deviating from what a random generator would determine. To achieve this, an online questionnaire was used to collect demographic data and assess participants’ attitudes toward pornography, including their gender, age, sexual orientation, marital status, and satisfaction with their relationship. Participants were also asked about their pornography consumption habits, including type, duration, and frequency.
To assess pornography addiction, the Cyber Pornography Use Inventory (CPUI) was used. The CPUI consists of 31 items divided into three subscales, but only the addictive patterns subscale, which has strong internal consistency, was relevant for this study. The study was conducted in German, with a majority of participants being native German speakers.
Erotic images were used to test for micro-psychokinetic effects, with four sets of stimuli created. These included neutral images and erotic images tailored to different sexual orientations: heterosexual, lesbian, and gay. The neutral and heterosexual erotic images were sourced from the International Affective Picture System (IAPS), while the lesbian and gay erotic images were obtained from license-free websites and validated by individuals of each sexual orientation to ensure appropriateness and normative quality.muli, examining how the priming affected the likelihood of selecting positive or negative target images.
Procedure
The study was conducted online to reach a broad range of participants and to encourage more honest responses on sensitive topics like sexuality and pornography consumption by minimizing social desirability bias. The sample included adults aged 18 and older, recruited through various channels such as social media platforms like Facebook, WhatsApp, and university contacts. The link to the study was shared in diverse groups, including those focused on psychological topics, as well as groups related to different sexual orientations.
Participants first answered demographic questions and completed part of the Cyber Pornography Use Inventory (CPUI) to assess their addiction to internet pornography. They also responded to questions about their pornography consumption habits and general attitudes toward pornography. Following this, participants were shown 50 images that matched their sexual orientation, which included either erotic content or neutral stimuli like everyday objects. After viewing the images, participants answered post-task questions to assess how seriously they had taken the study and the truthfulness of their responses. These answers were used to exclude any participants who might have provided dishonest or inattentive responses, ensuring the validity of the study’s findings. Finally, two questions related to self-efficacy were included, although they were not central to the research question and were intended for use in a different study.
Sample Size and Data Analysis
The study used Bayesian one-sample t-tests to evaluate the hypotheses. The test value—the expected number of erotic images seen by chance—was set at 25, assuming a 50:50 chance of viewing erotic versus neutral images out of 50 total images. A low Cauchy prior level of .1 was chosen for the Bayesian analysis, reflecting the expectation of weak effect sizes in micro-psychokinetic studies, where subtle, unconscious influences are at play. This decision was based on prior research indicating that such effects tend to be minimal.
The sample size was determined by practical restrictions, since this study was conducted as a student project with limited resources.
Data