This statistic depicts the proportion of women among active psychologists working in the U.S. from 2007 to 2019. According to the data, the share of women psychologists has increased from 57 percent in 2007 to 69 percent in 2021.

In 2023 a total of 29,896 registered general psychologists in Australia were female, compared to 7,168 registered general male psychologists. With regard to provisional psychologists, women also outnumbered men.

The number of female psychologists in Sweden was more than double as high as the number of male psychologists during the whole period from 2013 to 2023. In 2023, there were around 12.6 thousand female psychologists in Sweden, and around 5.1 thousand male psychologists.

In 2023, around 31.6 percent of women and 20 percent of men in Germany were especially interested in information about social interactions and psychology. This data is based on a survey conducted in Germany that year. The Allensbach Market and Advertising Media Analysis (Allensbacher Markt- und Werbeträgeranalyse or AWA in German) determines attitudes, consumer habits and media usage of the population in Germany on a broad statistical basis.

R code and data for:

Del Giudice, M. (in press). The S-index: Summarizing patterns of sex differences at the distribution extremes. Personality and Individual Differences.

Distribution of gender identity/sexual orientation score.

aAlmost invariably this is in addition to farming.bNon-responders were included in calculation of percentage as 'untested'.cOnly those who reported being sexually active were included in the calculation.

Dataset for Rasch analyses of the brief Critical Thinking Scale (CTh) and assessment of change

Data from the study reported in ” Exploring first semester changes in domain-specific critical thinking”.

Data are from Danish Psychology students, and consists of three data sets containing the variables described below.

Baseline data set (n = 336)

Gender: 1 = female, 2 = male

Agegroup (median split): 1 = 21 years and younger, 2 = 22 years and older

Math (perception of own mathematical knowledge as adequate): 1 = inadequate, 2 = adequate

Statfuture (expectation to need statistics in future employment): 1 = yes, 2 = maybe, 3 = no

CTh1, CTh2, CTh5 are items of the CTh scale with response scale (item statements included in the article): 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always

RescaledWML (rescaled person parameter estimates at baseline)

Matched longitunial data set dataset (n = 165)

Gender, Agegroup, Math and Statfuture were collected at baseline

Gender: 1 = female, 2 = male

Agegroup (median split): 1 = 21 years and younger, 2 = 22 years and older

Math (perception of own mathematical knowledge as adequate): 1 = inadequate, 2 = adequate

Statfuture (expectation to need statistics in future employment): 1 = yes, 2 = maybe, 3 = no

CTh1b, CTh2b, CTh5b are items of the CTh scale at baseline with response scale (item statements included in the article): 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always

CTh1f, CTh2f, CTh5f are items of the CTh scale at follow-up with response scale (item statements included in the article): 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always

RescaledWMLf (rescaled person parameter estimates at follow-up)

This dataset provided data for the study: "Does Neuroticism Increase Discrimination Perceptivity and Vulnerability to its Adverse Effects? Implication for Psychological Adaptation: A case study of Anglophone African Immigrants in Russia", which aims to determine whether neuroticism is negatively associated with psychological adaptation (PA) of immigrants/minorities, which is partially mediated by perceived discrimination (PD), as well as whether the negative relationship between perceived discrimination and psychological adaptation is strengthened by neuroticism. In other words, the study tested the following hypotheses: 1. PD is negatively associated with PA 2. Neuroticism is negatively associated with PA, partially mediated by PD. 3. The negative relationship between PD and PA is strengthened by neuroticism.

Data was collected and analyzed from a sample of 157 Anglophone African Immigrants. The dataset contains data on PD (mean computed with 4 items); the big-5 personality traits (extraversion-4 items, agreeableness-2 items, conscientiousness-5 items, openness-4 items, neuroticism-5 items); PA (4 items); socio-demographics (age, gender, level of education); & length of time spent in Russia.

The results from a multiple regression analysis predicting PA (predictors: age, length of time in Russia, PD, the big-5 traits), showed that PD is negatively associated with PA. Data for visualizing the scatterplot of the regression model is amongst the dataset.

The result from mediation analysis indicated that neuroticism was negatively associated with PA, partially mediated by PD.

The result from moderation analysis indicated that neuroticism strengthened the negative association between PD and PA. Data for visualizing the interaction between PD and neuroticism, predicting PA is also available in this dataset.

This statistic depicts the share of registered psychologists in Australia in 2018, by gender. That year, about 79.9 percent of registered psychologists in Australia were women.

Psychology Services - All staff survey: national Oracle database of NHSScotland psychology services workforce. Statistical information to describe the clinical workforce employed in NHSScotland Psychology services. Data includes NHS Board, professional group, target age of patients treated, area of work, tier of operation, band, gender and age. As from May 2010 these statistics can be designated as National Statistics products. This publication will be released quarterly from June 2011.

Source agency: ISD Scotland (part of NHS National Services Scotland)

Designation: National Statistics

Language: English

Alternative title: Workforce Planning for Psychology Services in NHSScotland

Distribution of gender attitudes, practices of gender relations, substance abuse and psychological measures by rape perpetration.

*adjusted for maternal age, educational level, smoking, pre-pregnancy body mass index, history of spontaneous abortion, late medical risk and neonate gender. For all analyses including ED at 30 weeks, the preterm group is limited to women delivering at 32+0–36+6 week's gestation.†emotional distress at 17 and 30 weeks are dichotomous variables, mean score ≥2 = 1.‡cases with covariates missing are excluded.§compared to no emotional distress at 30 weeks.

Descriptive statistics for preferences and actual choice of the partner relative height. For both variables mean height (±SD) of the male participants is reported.

This statistic depicts the gender distribution of massage therapists in Australia in 2016, by employment status. In this year, 20.77 percent of all massage therapists in Australia were female full time employees.

Psychometric performance of the Couples Gaslighting Scale in the Peruvian and Mexican population sample

This statistic shows the percentage of persons with serious psychological distress in the past 30 days among adults 18 years of age and over, in the U.S. from 1997 to 2016, by gender. In the period 2015-2016, 2.9 percent of all male adults in the United States had such problems.

General characteristics of the total study population, and by gender (N = 3181).

ODS / Goals and targets (from the 2030 Agenda for Sustainable Development) / Goal 5. Achieve gender equality and empower all women and girls / Target 5.2. Eliminate all forms of violence against all women and girls in the public and private spheres, including trafficking and sexual and other types of exploitation. / Indicator 5.2.1. Proportion of ever-partnered women and girls aged 15 years and older subjected to physical, sexual or psychological violence by a current or former intimate partner in the previous 12 months, by form of violence and by age

In the UK, national statistics show obesity and overweight rising in adults and children from 1993-2021 (NHS Digital, 2022). Obesity is defined as a Body Mass Index (BMI) score of ≥30.0, with overweight defined as BMI ≥ 25.0 and <30.0, and both conditions are associated with significant health risks (World Health Organization, 2021). Obesity is linked to weight gain caused by a positive energy balance, meaning that the calorific intake through consuming food and drink is greater than calorific expenditure through physical activity. Around 38% of UK adults are overweight and a further 26% obese, prompting government interventions to improve public health.

Calorie labelling on menus in large cafes, restaurants, and food outlets (over 250 employees) was introduced in England by the UK government in 2022 as part of a strategy to raise awareness about healthy eating and reduce obesity (Department of Health and Social Care, 2022). Menus must show food calorie content in kilocalories (kcal) and state the daily calorie needs of adults. The idea was to provide dietary information that would enable individuals to be more intentional about what they chose to eat, with the aim of reducing their calorific intake.

There is some evidence that calorie labelling on menus can reduce calorific intake. In their meta-analysis, Nikolaou et al. (2015) reviewed six studies that had investigated calorie labelling and calories consumed in US restaurants. In some studies, but not all, there was a small reduction in calories purchased (12.4-38.1 kcal reduction per person) linked to labelling. The UK government (Department of Health and Social Care, 2021) summarised a range of studies on calorie labelling and consumption, mainly drawn from the US, and arrived at a similar conclusion that labelling did not always affect consumer choices, but when it did, there was a small reduction in calorie intake.

In a recent study with a large sample (N = 3,312) representing the US population, Jia et al. (2023) measured whether individuals noticed menu calorie labelling and, if they did, whether it affected their food choices. Twenty seven percent noticed and used labels to inform decisions about food, while 30% noticed labels but chose to ignore them. This implies that, while providing calorie labelling has utility for some individuals, others are not being reached through this approach. This suggests that US citizens have attitudes about the value they attribute to menu calorie labelling, and these views may mediate the effect of labelling information on calorific intake. In one of the very few studies in this area, Nikolaou et al. (2015) had also investigated menu calorie labelling preferences, but focused on young adults. In their US quantitative study (N = 1440), they found that 46% of participants welcomed calorie labelling, 30% did not want it, and 20% were undecided. The differences in findings between this study and that of Jia et al. (2023) could suggest an age effect, with younger people being more open to the benefits of menu calorie labelling. However, far more research is needed to state this with any conviction.

The research on psychological characteristics that predict calorie labelling preferences is very limited. There is some evidence that individuals’ sense of responsibility for their own health is associated with their menu calorie labelling preferences. In a South Korean study, Jeong & Ham (2018) collected survey data on health beliefs and menu labelling from 335 restaurant users. The survey questions assessed individuals’ use of labels in terms of the perceived health threats of non-use, health benefits of use, barriers to use (e.g., finding it difficult to understand the label), and cues to action (e.g., being encouraged by friends and family to use labels). Using structural equation modelling, Jeong & Ham found that perceived benefits strongly predicted label use (β = .66, p < .001), there were weak but significant relationships between label use and perceived barriers (β = -.19, p <.001) and perceived threats (β = .13, p < .01), and that cues to action predicted perceived threats (β = .37, p < .001) but not label use directly. Jeong & Ham’s study showed that health beliefs predict menu calorie label use in South Korea. However, this effect has not been demonstrated in other countries. Furthermore, the study’s focus was on the use of calorie labels rather than individuals’ views about them. The current study will investigate whether health-orientated beliefs influence menu calorie labelling preferences in the UK.

While it seems likely that individuals interested in optimising their health would value calorie labels as part of their personal health care, others may find labelling irritating or irrelevant, or even detrimental to health management. For example, calorie labelling may have a damaging effect on some individuals with eating disorders. Frances et al. (2023) conducted a qualitative survey of 399 individuals with an eating disorder history, using open-ended questions concerning calorie labelling and its impact on relationships and personal recovery. Following thematic analysis, the authors concluded that most participants considered calorie labelling hindered their recovery process, accentuated a sense of isolation, restricted their freedom, and increased their frustration and anger. Given that 20% of UK women are at risk of an eating disorder (NHS, 2020), Frances et al.’s work points to the potential negative impact of menu calorie labelling for an important segment of society. The full range of attitudes towards calorie labelling is worthy of research.

There is some evidence of a gender effect for the impact of menu calorie labelling on calorific intake. Roseman et al. (2017) conducted a field experiment in which 192 US university students were exposed to Burger King menus in one of four conditions, involving variations in calorie labelling information. The type of calorie information twinned with participants’ knowledge of nutrition significantly affected the intention to choose lower calorie foods, with a far greater impact on women than men. Nikolaou et al.’s (2015) study, described above, also found that young women reduced their calorific intake in response to menu calorie labelling significantly more than men did. In a survey-based study of 324 students in Croatia, Kresic et al. (2018) found that females appreciated the potential health benefits of calorie labelling significantly more than men did. These combined results suggested that women were more likely than men to be influenced by calorie labelling. However, the studies have not explored predictors of menu calorie labelling preferences.

One other variable of potential interest in menu calorie labelling is BMI, since it is often used as a screening method for weight category (e.g., underweight, healthy weight, overweight and obesity). A review of the literature indicates that the role of BMI in menu calorie labelling preference is largely unexplored. Indeed, Jia et al.’s (2023) study, described above, found that BMI had no effect on calorific intake linked to menu calorie labelling. This supports the idea that, at a population level, BMI is unlikely to predict menu calorie labelling preferences. An earlier study, Reale and Flint (2016), explored the impact of menu labelling on food choices in individuals with obesity. However, as they did not include a control of individuals with a lower BMI it is not possible to draw conclusions about the impact of BMI on menu labelling preferences. Further research is needed in this area, including whether the relationship between BMI and menu calorie labelling preferences are mediated by other variables, such as health-orientated beliefs and goals.

To the best of my knowledge, there has been no published study that combines health-orientated beliefs, gender, and calorie labelling preferences in the UK. The current study will aim to fill this gap.