Yearly citation counts for the publication titled "Statistical Inference for Causal Effects in Clinical Psychology".

Relative frequency of application of Bayesian inferential statistics by journal and year.

This dataset contains data from 30 participants who completed the same questionnaire on meat consumption 12 times. The participant’s opinion was perturbed on each of the 11 items and measured to what extent this changed the participant’s scores on the questionnaire. It is a unique dataset that can be used for several purposes. The questionnaire data can aid research that aims to infer causal relations between variables.

Task: The dataset can be used to study causal discovery.

Summary:

• Size of dataset: 360 x 11
• Task: Causal Discovery
• Data Type: Discrete
• Dataset Scope: Standalone
• Ground Truth: Known
• Temporal Structure: Static
• License: TBD
• Missing Values: No

Missingness Statement: There are no missing values.

Features: Each measurement is a a six-level factor with levels 1 (completely disagree) to 6 (completely agree)

• moral: Eating meat is morally wrong
• nutr: Meat contains important nutrients for your body
• envir: The production of meat if harmful for the environment
• infer: Animals are inferior to people
• suff: By consuming meat you contribute to animal suffering
• tax: There should be a tax on meat
• taste: I like the taste of meat
• death: Meat reminds me of death and suffering of animals
• sad: If I had to stop eating meat I would feel sad
• guilty: If I eat meat I feel guilty
• disg: If I eat meat I feel disgust

The "Ground Truth" was obtained by the conditional invariant prediction method applied to the data on attitudes of meat consumption.

Bayesian reasoning - the optimal process of updating a hypothesis or belief with new information - is a critical aspect of both everyday decision-making and statistics education, but strategies for effectively teaching the topic in the classroom remain elusive. This study leverages the findings of prior research on facilitating Bayesian reasoning by utilizing a visualization, called the bar display, as a method for teaching Bayes theorem and its underlying probability concepts. Data were collected from a college-level statistics-in-psychology course, wherein students were taught and tested on Bayesian reasoning either with or without the bar display. In addition to testing the immediate efficacy of the bar display, data were also collected to test long-term retention and the potential differential benefits for low numeracy and high anxiety students. Results indicated engagement with the bar display as a method for visually approximating answers to Bayesian questions, with students trained with the bar display providing more accurate answers to Bayesian reasoning questions before training and at long-term assessment. Additionally, students with self-reported low numeracy and high math anxiety performed better on Bayesian reasoning questions when learning with the bar display. Recommendations for future implementations are discussed.

Network of 41 papers and 65 citation links related to "Statistical Inference for Causal Effects in Clinical Psychology".

These are replication data for Czarna, A.Z., Leifeld, P., Smieja, M., Dufner, M., & Salovey, P. (2016). Do Narcissism and Emotional Intelligence Win Us Friends? Modeling Dynamics of Peer Popularity Using Inferential Network Analysis. Personality and Social Psychology Bulletin.

In our everyday lives, we are required to make decisions based upon our statistical intuitions. Often, these involve the comparison of two groups, such as luxury versus family cars and their suitability. Research has shown that the mean difference affects judgements where two sets of data are compared, but the variability of the data has only a minor influence, if any at all. However, prior research has tended to present raw data as simple lists of values. Here, we investigated whether displaying data visually, in the form of parallel dot plots, would lead viewers to incorporate variability information. In Experiment 1, we asked a large sample of people to compare two fictional groups (children who drank ‘Brain Juice’ versus water) in a one-shot design, where only a single comparison was made. Our results confirmed that only the mean difference between the groups predicted subsequent judgements of how much they differed, in line with previous work using lists of numbers. In Experiment 2, we asked each participant to make multiple comparisons, with both the mean difference and the pooled standard deviation varying across data sets they were shown. Here, we found that both sources of information were correctly incorporated when making responses. Taken together, we suggest that increasing the salience of variability information, through manipulating this factor across items seen, encourages viewers to consider this in their judgements. Such findings may have useful applications for best practices when teaching difficult concepts like sampling variation.

Determining model posteriors. (PDF)

The pilottiming.mat file contains timing data for the 22 pilots conducted for the Beach task in November 2020.

The file is a 3D matlab variable, with the structure (participant, trial, frame index) and excludes practice trials. Values indicate seconds elapsed from start of trial.

Data sets associated with the manuscript The Basel Version of the Awareness of Social Inference Test - Theory of Mind (BASIT-ToM): Preliminary Validation Analyses in Healthy Adultsdata_BASIT-ToM_test scenes_analyses of questions:SubID=Participants' identification numberQuestion code consists of a letter (i.e., message type, H=honesty, pS=paradoxical sarcasm, sS=simple sarcasm), a scene number (i.e., scene 1-4), the portrayed intensity (i.e., l=low, m=medium, h=high), a questions' identification letter [i.e., a-d= Theory of Mind (ToM) questions, e=hypermentalisation question], abbreviations of type (i.e., cogn=cognitive ToM, aff=affective ToM, hyper=hypermentalisation) and order (i.e., 1=first-orderToM, 2=second-order ToM) of ToMdata_BASIT-ToM_practice scene_analyses of questions:SubID=Participants' identification numberQuestion code consists of a word (i.e. Practice=practice scene), the portrayed intensity (i.e., l=low, m=medium, h=high),a questions' identification letter [i.e., a-d= Theory of Mind (ToM) questions, e=hypermentalisation question], abbreviations of type (i.e., cogn=cognitive ToM, aff=affective ToM, hyper=hypermentalisation) and order (i.e., 1=first-orderToM, 2=second-order ToM) of ToMdata_BASIT-ToM_number of times scenes were watchedSubID=Participants' identification numberScene code consists of a letter (i.e., message type, H=honesty, pS=paradoxical sarcasm, sS=simple sarcasm or Practice=Practice scene), a scene number (i.e., scene1-4), and the portrayed intensity (i.e., l=low, m=medium, h=high)

In 2015, the Open Science Collaboration repeated a series of 100 psychological experiments. Since a considerable part of these replications could not confirm the original effects and some of them pointed in the opposite direction, psychological research is said to lack reproducibility. Several general criticisms can explain this finding, such as the standardized use of undirected nil-null hypothesis tests, samples being too small and selective, lack of corrections for multiple testing, but also some widespread questionable research practices and incentives to publish positive results only. A selection of 57,909 articles from 12 renowned journals is processed with the JATSdecoder software to analyze the extent to which several empirical research practices in psychology have changed over the past 12 years. To identify journal- and time-specific changes, the relative use of statistics based on p-values, the number of reported p-values per paper, the relative use of confidence intervals, directed tests, power analysis, Bayesian procedures, non-standard α levels, correction procedures for multiple testing, and median sample sizes are analyzed for articles published between 2010 and 2015 and after 2015, and in more detail for every included journal and year of publication. In addition, the origin of authorships is analyzed over time. Compared to articles that were published in and before 2015, the median number of reported p-values per article has decreased from 14 to 12, whereas the median proportion of significant p-values per article remained constant at 69%. While reports of effect sizes and confidence intervals have increased, the α level is usually set to the default value of .05. The use of corrections for multiple testing has decreased. Although uncommon in each case (4% in total), directed testing is used less frequently, while Bayesian inference has become more common after 2015. The overall median estimated sample size has increased from 105 to 190.

ABSTRACT OBJECTIVE: To analyze the factors associated with the presence of depression symptoms in women after breast cancer. METHODS: Cross-sectional study with 181 women with breast cancer, aged 57.0 years (SD = 9.5), who were undergoing treatment or after treatment in the Oncology Research Center in Florianópolis, state of Santa Catarina, Brazil. The questionnaire comprised items addressing general and health information, economic level, anthropometric measures, depression symptoms (Beck Depression Inventory), self-esteem (Rosenberg Self-Esteem Scale), and body image (Body Image After Breast Cancer Questionnaire). Descriptive and inferential statistical analysis were performed by chi-square and Fisher's exact tests to verify association, Mann-Whitney U test to compare the groups and Poisson regression to identify the prevalence ratio of the factors associated with presence of depression symptoms (p < 0.05). RESULTS: We found an association between the presence of depression symptoms and the group of younger women (aged 40–60 years), those who had another disease besides cancer, those who had mastectomy surgery, those who suffered from lymphedema, and those who presented low–medium self-esteem. Less educated women presented more depressive symptoms, as did women with worse body image on the subscales of limitations, transparency, and arm concerns. CONCLUSIONS: Age, educational attainment, diagnosis of other diseases, type of surgery, lymphedema, self-esteem, and body image were factors associated with the presence of depression symptoms in Brazilian women after breast cancer. Health professionals should be aware of these relationships and try to detect depression symptoms earlier and improve the care they provide to these women.

Academic stress, association (X2), academic program, sex (n = 1735).

Data demographics at T1 and T2, Health Students (n = 1735).

Learning modality, association (X2) academic program, sex (n = 1735).

Background: The Coronavirus disease (COVID-19) has emphasised the critical need to investigate the mental well-being of healthcare professionals working during the pandemic. It has been highlighted that healthcare professionals display a higher prevalence of mental distress and research has largely focused on frontline professions. Social restrictions were enforced during the pandemic that caused rapid changes to the working environment (both clinically and remotely). The present study aims to examine the mental health of a variety of healthcare professionals, comparing overall mental wellbeing in both frontline and non-frontline professionals and the effect of the working environment on mental health outcomes.

Method: A cross-sectional mixed methods design, conducted through an online questionnaire. Demographic information was optional but participants were required to complete: (a) Patient Health Questionnaire, (b) Generalised Anxiety Disorder, (c) Perceived Stress Scale, and (d) Copenhagen Burnout Inventory. The questionnaire included one open-ended question regarding challenges experienced working during the pandemic.

Procedure:
Upon ethical approval the online questionnaire was advertised for six weeks from 1st May 2021 to 12th June 2021 to maximise the total number of respondents able to partake. The survey was hosted on the survey platform “Online Surveys”. It was not possible to determine a response rate because identifying how many people had received the link was unattainable information. The advert for the study was placed on social media platforms (WhatsApp, Instagram, Facebook and Twitter) and shared through emails.

Participants were recruited through the researchers’ existing professional networks and they shared the advertisement and link to questionnaire with colleagues. The information page explained the purpose of the study, eligibility criteria, procedure, costs and benefits of partaking and data storage. Participants were made aware on the information page that completing and submitting the questionnaire indicated their informed consent. It was not possible to submit complete questionnaires unless blank responses were optional demographic data. Participants were informed that completed questionnaires could not be withdrawn due to anonymity.

The questionnaire consisted of four sections: demographic data, mental health information and the four psychometric tools, PHQ-9, GAD-7, PSS-10 and CBI. Due to the sensitive nature of this research, only the psychometric measures required an answer for each question, thus all demographic information was optional to encourage participant contentment. Once participants had completed the questionnaire and submitted, they were automatically taken to a debrief page. This revealed the hypothesis of the questionnaire and rationalised why it was necessary to conceal this prior to completion. Participants were signposted to mental health charities and a self-referral form for psychological support. Participants could contact the researcher via email to express an interest in the results. It was explained that findings would be analysed using descriptive statistics to investigate any correlations or patterns in the responses. Data collected was stored electronically, on a password protected laptop. It will be kept for three years and then destroyed.

Instruments: PHQ-9, GAD-7, PSS-10 and CBI.

Other questions included:

Thank you for considering taking part in the questionnaire! Please remember by completing and submitting the questionnaire you are giving your informed consent to participate in this study.

Demographic:

Gender: please select one of the following:

Male Female Non-binary Prefer not to answer

Age: what is your age?

Open question: Prefer not to answer

What is your current region in the UK?

South West, East of England, South East, East Midlands, Yorkshire and the Humber, North West, West Midlands, North East, London, Scotland, Wales, Northern Ireland Prefer not to answer

Ethnicity: please select one of the following:

White English, Welsh, Scottish, Northern Irish or British Irish Gypsy or Irish Traveller Any other White background Mixed or Multiple ethnic groups White and Black Caribbean White and Black African White and Asian Any other Mixed or Multiple ethnic background Asian or Asian British Indian Pakistani Bangladeshi Chinese Any other Asian background Black, African, Caribbean or Black British African Caribbean Any other Black, African or Caribbean background Other ethnic group Arab Option for other please specify Prefer not to answer

Employment/environment:

What was your employment status in 2020 prior to COVID-19 pandemic?

Please select the option that best applies. Employed Self-employed Unpaid work (homemaker/carer) Out of work and looking for work Out of work but not currently looking for work Student Volunteer Retired Unable to work Prefer not to answer Option for other please specify

What is your current employment status?

Please tick the option that best applies. Employed Self-employed Unpaid work (homemaker/carer) Out of work and looking for work Out of work but not currently looking for work Student Volunteer Retired Unable to work Prefer not to answer Option for other please specify

What is your healthcare profession/helping profession?

Please state your job title. Open question

How often did you work from home before the COVID-19 pandemic?

Not at all, rarely, some, most, everyday Option for N/A

How often did you work from home during the first UK national lockdown for COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often did you work from home during the second UK national lockdown during COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often have you worked from home during the third UK national lockdown during COVID-19?

Not at all, rarely, some, most, everyday Option for N/A

How often are you currently working from home during the COVID-19 pandemic?

Not at all, rarely, some, most, everyday Option for N/A

Mental health:

How would you describe your mental health leading up to the COVID-19 pandemic?

Excellent, Very good, Good, Fair, Poor

How would you describe your mental health during the COVID-19 pandemic?

Excellent, Very good, Good, Fair, Poor

What have been the main challenges working as a healthcare professional/helping profession during COVID-19 pandemic? Open question

Data analysis: Firstly, any missing data was checked by the researcher and noted in the results section. The data was then analysed using a statistical software package called Statistical Package for the Social Sciences version 28 (SPSS-28). Descriptive statistics were collected to organise and summarise the data, and a correlation coefficient describes the strength and direction of the relationship between two variables. Inferential statistics were used to determine whether the effects were statistically significant. Responses to the open-ended question were coded and examined for key themes and patterns utilising the Braun and Clarke (2006) thematic analysis approach.

Ethical considerations: The study was approved by the Health Science, Engineering and Technology Ethical Committee with Delegated Authority at the University of Hertfordshire.

The potential benefits and risks of partaking in the research were contemplated and presented on the information page to promote informed consent. Precautions to prevent harm to participants included eligibility criteria, excluding those under eighteen years older or experiencing mental health distress. As the questionnaire was based around employment and the working environment, another exclusion involved experiencing a recent job change which caused upset.

An anonymous questionnaire and optional input of demographic data fostered the participants’ right to autonomy, privacy and respect. Specific employment and organisation or company information were not collected to protect confidentiality. Although participants were initially deceived regarding the hypotheses, they were provided with accurate information about the purpose of the study. Deceit was appropriate to collect unbiased information and participants were subsequently informed of the hypotheses on the debrief page.

Modification of academic activity, association (X 2). Academic program, sex (n = 1735).

Descriptive and inferential statistics for post hoc comparisons for low, medium, and high adherence to informal mindfulness practice.

Reproducibility package containing data, code and final plots of Figures 1 & 2 of this editorial in the European Journal of Neuroscience:A few simple steps to improve the description of group results in neuroscienceGuillaume A. Rousselet, John J. Foxe and J. Paul Bolamin pressFigure 1 was made in R, using a dataset created for the editorial.Figure 2 was made in Matlab, using a dataset and code that are part of a larger Matlab ERP tutorial available here:Rousselet, G. (2016). Introduction to robust estimation of ERP data. figshare.https://dx.doi.org/10.6084/m9.figshare.3501728See also related blog posts on data visualisation here:https://garstats.wordpress.com/

Social isolation is a relevant problem for veterans who are at risk for disengaging from others as a function of transition stress from military life to civilian life, and given high rates of exposure to trauma and psychological distress. Few researchers have examined social isolation in veterans over time, particularly during COVID-19 that led to significant barriers and restrictions on social interactions. The purpose of this longitudinal study was to assess veterans’ experience of social isolation and its mental health and social functioning correlates during a 6-month period of the COVID-19 pandemic. Participants were 188 United States veterans of the Iraq and Afghanistan wars. A total of four assessments were administered: one every two months for a total duration of six months. The average number of completed assessments across all participants was 3.70 (SD = 0.75) with 159 participants (84.13%) completing all four timepoints. Surveys included measures of global mental health and social functioning as indicated by perceived emotional support, quality of marriage, and couple satisfaction. Multilevel modeling was used to assess 1) growth models to determine whether social isolation changed over time and the trajectory of that change (i.e., linear or quadratic); and 2) whether social isolation was related to both concurrent and prospective indicators of mental health and social functioning. All analyses included person mean centered and grand mean centered isolation to assess for within-and between-person effects. Veterans reported a quadratic trajectory in social isolation that decreased slightly and stabilized over time. Findings indicate that higher social isolation, at both the within- and between-person level, was negatively associated with concurrent emotional support, mental health, quality of marriage, and couple satisfaction. However, all prospective effects were nonsignificant at the within-person level. Results suggest although isolation may decrease over time, veterans report worse mental health and social functioning during times when they report higher levels of social isolation compared to themselves and others. Future work is needed to determine if interventions can be applied during those times to prevent or target those negative associations.