Regression ranks among the most popular statistical analysis methods across many research areas, including psychology. Typically, regression coefficients are displayed in tables. While this mode of presentation is information-dense, extensive tables can be cumbersome to read and difficult to interpret. Here, we introduce three novel visualizations for reporting regression results. Our methods allow researchers to arrange large numbers of regression models in a single plot. Using regression results from real-world as well as simulated data, we demonstrate the transformations which are necessary to produce the required data structure and how to subsequently plot the results. The proposed methods provide visually appealing ways to report regression results efficiently and intuitively. Potential applications range from visual screening in the model selection stage to formal reporting in research papers. The procedure is fully reproducible using the provided code and can be executed via free-of-charge, open-source software routines in R.

Statistical analysis is error prone. A best practice for researchers using statistics would therefore be to share data among co-authors, allowing double-checking of executed tasks just as co-pilots do in aviation. To document the extent to which this ‘co-piloting’ currently occurs in psychology, we surveyed the authors of 697 articles published in six top psychology journals and asked them whether they had collaborated on four aspects of analyzing data and reporting results, and whether the described data had been shared between the authors. We acquired responses for 49.6% of the articles and found that co-piloting on statistical analysis and reporting results is quite uncommon among psychologists, while data sharing among co-authors seems reasonably but not completely standard. We then used an automated procedure to study the prevalence of statistical reporting errors in the articles in our sample and examined the relationship between reporting errors and co-piloting. Overall, 63% of the articles contained at least one p-value that was inconsistent with the reported test statistic and the accompanying degrees of freedom, and 20% of the articles contained at least one p-value that was inconsistent to such a degree that it may have affected decisions about statistical significance. Overall, the probability that a given p-value was inconsistent was over 10%. Co-piloting was not found to be associated with reporting errors.

RaviSheel04/Psychology-Data dataset hosted on Hugging Face and contributed by the HF Datasets community

This data set contains the replication data and supplements for the article "Knowing, Doing, and Feeling: A three-year, mixed-methods study of undergraduates’ information literacy development." The survey data is from two samples: - cross-sectional sample (different students at the same point in time) - longitudinal sample (the same students and different points in time)Surveys were distributed via Qualtrics during the students' first and sixth semesters. Quantitative and qualitative data were collected and used to describe students' IL development over 3 years. Statistics from the quantitative data were analyzed in SPSS. The qualitative data was coded and analyzed thematically in NVivo. The qualitative, textual data is from semi-structured interviews with sixth-semester students in psychology at UiT, both focus groups and individual interviews. All data were collected as part of the contact author's PhD research on information literacy (IL) at UiT. The following files are included in this data set: 1. A README file which explains the quantitative data files. (2 file formats: .txt, .pdf)2. The consent form for participants (in Norwegian). (2 file formats: .txt, .pdf)3. Six data files with survey results from UiT psychology undergraduate students for the cross-sectional (n=209) and longitudinal (n=56) samples, in 3 formats (.dat, .csv, .sav). The data was collected in Qualtrics from fall 2019 to fall 2022. 4. Interview guide for 3 focus group interviews. File format: .txt5. Interview guides for 7 individual interviews - first round (n=4) and second round (n=3). File format: .txt 6. The 21-item IL test (Tromsø Information Literacy Test = TILT), in English and Norwegian. TILT is used for assessing students' knowledge of three aspects of IL: evaluating sources, using sources, and seeking information. The test is multiple choice, with four alternative answers for each item. This test is a "KNOW-measure," intended to measure what students know about information literacy. (2 file formats: .txt, .pdf)7. Survey questions related to interest - specifically students' interest in being or becoming information literate - in 3 parts (all in English and Norwegian): a) information and questions about the 4 phases of interest; b) interest questionnaire with 26 items in 7 subscales (Tromsø Interest Questionnaire - TRIQ); c) Survey questions about IL and interest, need, and intent. (2 file formats: .txt, .pdf)8. Information about the assignment-based measures used to measure what students do in practice when evaluating and using sources. Students were evaluated with these measures in their first and sixth semesters. (2 file formats: .txt, .pdf)9. The Norwegain Centre for Research Data's (NSD) 2019 assessment of the notification form for personal data for the PhD research project. In Norwegian. (Format: .pdf)

NLP Mental Health Conversations

Stimulating AI-Driven Mental Health Guidance

By Huggingface Hub [source]

About this dataset

This dataset contains conversations between users and experienced psychologists related to mental health topics. Carefully collected and anonymized, the data can be used to further the development of Natural Language Processing (NLP) models which focus on providing mental health advice and guidance. It consists of a variety of questions which will help train NLP models to provide users with appropriate advice in response to their queries. Whether you're an AI developer interested in building the next wave of mental health applications or a therapist looking for insights into how technology is helping people connect; this dataset provides invaluable support for advancing our understanding of human relationships through Artificial Intelligence

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For more datasets, click here.

Featured Notebooks

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How to use the dataset

This guide will provide you with the necessary knowledge to effectively use this dataset for Natural Language Processing (NLP)-based applications.

• Download and install the dataset: To begin using the dataset, download it from Kaggle onto your system. Once downloaded, unzip and extract the .csv file into a directory of your choice.

• Familiarize yourself with the columns: Before working with the data, it’s important to familiarize yourself with all of its components. This dataset contains two columns - Context and Response - which are intentionally structured to produce conversations between users and psychologists related to mental health topics for NLP models dedicated to providing mental health advice and guidance.

• Analyze data entries: If possible or desired, take time now to analyze what is included in each entry; this may help you better untangle any challenges that come up during subsequent processes yet won't be required for most steps going forward if you prefer not too jump ahead of yourself at this juncture of your work process just yet! Examine questions asked by users as well as answers provided by experts in order glean an overall picture of what types of conversations are taking place within this pool of data that can help guide further work on NLP models for AI-driven mental health guidance purposes later on down the road!

• Cleanse any information not applicable to NLP decisioning relevant application goals: It's important that only meaningful items related towards achieving AI-driven results remain within a clean copy of this Dataset going forward; consider removing all extra many verbatim entries or other pieces uneeded while also otherwise making sure all included content adheres closely enough one particular decisions purpose expected from an end goal perspective before proceeding onwards now until an ultimate end result has been successfully achieved eventually afterwards later on next afterward soon afterwards too following conveniently satisfyingly after accordingly shortly near therefore meaningfully likewise conclusively thoroughly properly productively purposely then eventually effectively finally indeed desirably plus concludingly enjoyably popularly splendidly attractively satisfactorally propitiously outstandingly fluently promisingly opportunely in conclusion efficiently hopefully progressively breathtaking deliciousness ideally genius mayhem invented unique impossibility everlastingly intense qualitative cohesiveness behaviorally affectionately fixed voraciously like alive supportively choicest decisively luckily chaotically co-creatively introducing ageless intricacy voicing auspicious promise enterprisingly preferred mathematically godly happening humorous respective achieve ultra favorability fundamentals essentials speciality grandiose selectively perfectly

Research Ideas

• Creating sentence-matching algorithms for natural language processing to accurately match given questions with appropriate advice and guidance.
• Analyzing the psychological conversations to gain insights into topics such as stress, anxiety, and depression.
• Developing personalized natural language processing models tailored to provide users with appropriate advice based on their queries and based on their individual state of mental health

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

**License: [CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication](https://creativec...

The purpose of this dataset is to share the positive psychology intervention of university students. The results obtained from this dataset, the descriptive analysis and the statistical analyses performed on this data were developed using SPSS and give rise to a scientific article (currently under review).

The NeuroNSGA-MHED (Personalized Mental Health Education Dataset) is a simulated dataset designed to support research and development in the field of personalized mental health education. It reflects real-world, multi-dimensional data that can be used to understand user behavior, mental wellness indicators, and engagement with educational content.

This dataset combines diverse data sources, including behavioral, psychological, academic, and interaction-related attributes, offering a rich context for studying personalized learning paths and mental health literacy.

🧠 Key Features User Demographics: Includes age, gender, education level, occupation, and geographic region.

Behavioral and Lifestyle Data: Tracks sleep duration, physical activity, screen time, and stress levels.

Social Media Metrics: Sentiment indicators, keyword mentions, and word frequency analysis.

Academic and Productivity Information: Daily study/work hours, task completion rates, and attendance.

Psychological Assessments: Simulated scores for mental health screening tools and resilience levels.

User Interaction Logs: Engagement with educational content, feedback ratings, and quiz performance.

Personalization Labels:

recommended_content_type: Suggests type of content suited to each user.

recommended_duration: Indicates optimal content length.

learning_outcome_score: Reflects the effectiveness of educational interactions.

🔍 Use Cases Designing personalized mental health learning applications

Exploring relationships between lifestyle, psychological traits, and learning outcomes

Evaluating user satisfaction and engagement in digital education platforms

Supporting educational psychology and well-being studies with contextual data

In this article, we explore the use of two published datasets for teaching a wide range of students about regression models, with a particular focus on interaction terms. The two datasets come from recent psychology studies on beliefs about poverty and welfare, and about the dynamics of groups projects. Both datasets (and their original research papers) are accessible to students, and because of their context, students can learn about data collection, measurement, and the use of statistics when studying complex social topics, while using the data to learn about regression analysis. We have used these data for a range of in-class activities, journal paper discussions, exams, and extended projects, at the undergraduate, master’s, and doctoral levels. Supplementary materials for this article are available online.

This dataset contains several files related to our research paper titled "Attention Allocation to Projection Level Alleviates Overconfidence in Situation Awareness". These files are intended to provide a comprehensive overview of the data analysis process and the presentation of results. Below is a list of the files included and a brief description of each:

R Scripts: These are scripts written in the R programming language for data processing and analysis. The scripts detail the steps for data cleaning, transformation, statistical analysis, and the visualization of results. To replicate the study findings or to conduct further analyses on the dataset, users should run these scripts.

R Markdown File: Offers a dynamic document that combines R code with rich text elements such as paragraphs, headings, and lists. This file is designed to explain the logic and steps of the analysis in detail, embedding R code chunks and the outcomes of code execution. It serves as a comprehensive guide to understanding the analytical process behind the study.

HTML File: Generated from the R Markdown file, this file provides an interactive report of the results that can be viewed in any standard web browser. For those interested in browsing the study's findings without delving into the specifics of the analysis, this HTML file is the most convenient option. It presents the final analysis outcomes in an intuitive and easily understandable manner. For optimal viewing, we recommend opening the HTML file with the latest version of Google Chrome or any other modern web browser. This approach ensures that all interactive functionalities are fully operational.

Together, these files form a complete framework for the research analysis, aimed at enhancing the transparency and reproducibility of the study.

Health professionals are expected to consistently perform to a high standard during a variety of challenging clinical situations, which can provoke stress and impair their performance. There is increasing interest in applying sport psychology training using performance mental skills (PMS) immediately before and during performance. A systematic review of the main relevant databases was conducted with the aim to identify how PMS training (PMST) has been applied in health professions education and its outcomes. The 20 selected studies noted the potential for PMST to improve performance, especially for simulated situations. The key implementation components were a multimodal approach that targeted several PMS in combination and delivered face-to-face delivery in a group by a trainer with expertise in PMS. The average number of sessions was 5 and of 57 min duration, with structured learner guidance, an opportunity for practice of the PMS and a focus on application for transfer to another context. Future PMST can be informed by the key implementation components identified in the review but further design and development research is essential to close the gap in current understanding of the effectiveness of PMST and its key implementation components, especially in real-life situations.

Most psychologists are likely to have at least some clients bring a dream into therapy. In the few studies looking at the use of dreams in therapy, therapists report that they do not feel confident or competent to adequately respond to their clients' introduction of dream material in therapy. The possible consequences of this include a negative impact on the therapeutic alliance and misinterpretation of the therapist's rejection of a dream narrative as a disinterest in the client's inner life. This research project seeks to identify psychologists' and psychology clients' understanding of their experiences of the use of dream material in therapy and their understanding of the role of dreams in contemporary psychological practice. While there have been some surveys about the use of dreams in therapy, relatively little is known about this topic, so a phenomenological, qualitative approach will be used. This research will be broken into two studies. The first study will use semi-structured interviews to interview psychologists and the second study will use semi-structured interviews to interview psychology clients. A hermeneutic phenomenological analysis of the interview transcripts will be completed with the aid of Dedoose software.

Raw data for participants that answered the Statistical Anxiety Test. A sample of 681 undergraduate Spanish students (80% women) of a Grade in Psychology, aged 18-60 years (M = 20.5, SD = 4.9), completed the computer version of the test. Raw responses and the time to response each item were recorded. The test included a scale to assess social desirability In addition, the examination mark in a test about statistic was recorded for a set or participants (N=430). Total scores were computed as an addition to item responses. ORION factor score estimates in the scales of the test were obtained using factor analysis (ULS extraction, Robust Promin, and ORION scores estimates). The software used to compute the factor analysis was FACTOR. The information provided is: sample descriptives, participants' responses, item response times, and participants' scores in test scales.

Project Overview Psychological research concerning disability has failed to consistently recognize people with disabilities as a relevant marginalized group or to advance a fuller understanding of their experiences in an ableist society. This project seeks to emphasize the importance of social psychological research that celebrates difference, and that works with and for the disabled community. In doing so, it calls attention to the value of including people with disabilities in broader conversations about diversity, normalcy, and social change. This qualitative study focuses on the perspectives of people with disabilities regarding their disability identity, disability culture, allyship, and needed social change with the aim of informing preliminary directions for future research connecting social psychology and disability studies. Data were collected from 31 individuals with disabilities through an online survey and analyzed using an integrated framework of disability models and prominent social psychological theories. The findings highlight substantial heterogeneity in the experiences and views of people with disabilities, underscoring the depth and breadth of future research needed to better understand the disabled experience and the meaning of empowerment within the disabled community. Data and Data Collection Overview Data collection ran from March 2023 to May 2023. A link to the survey was posted on various online platforms and at physical locations via flyer on a university campus in the western United States. The link was also distributed among personal and family contacts of the researcher. Online, the survey was initially posted on the messaging platform Slack and a personal social media account. In subsequent weeks, the survey was posted to six online forum pages dedicated to disability discussion and/or research participation, as well as a university-affiliated social media account. The survey was closed after a period of three weeks when no new responses were submitted despite continued data collection efforts. Data were gathered via a qualitative Google Forms survey with nine open-ended questions. The survey was completely anonymous to reduce the risk of social desirability bias. Respondents were informed at the beginning of the survey of the researcher’s own disability status (non-disabled), the anonymity of all answers, and the survey’s purpose as part of research on the connection between disability studies and social psychology; they were also encouraged to share only information which they were comfortable sharing. The survey questions were developed to ask about common social psychological topics (e.g., identity, interpersonal relationships) with specific application to disability. Allyship was also a key concept explored. A self-selected sample of 31 respondents participated, representing 36 disabilities in total. Eleven participants identified as multiply disabled. The most common self-reported disabilities included autism and neurodivergence, C-PTSD/PTSD, postural orthostatic tachycardia syndrome (POTS), Ehlers-Danlos syndrome (EDS), attention-deficit/hyperactivity disorder (ADHD), and d/Deaf or hard of hearing (HOH). The remaining 29 disabilities encompassed a wide range of physical, mental health, cognitive, chronic health, and intellectual conditions, such as anxiety, bipolar disorder, chronic migraine, and Tourette syndrome. Responses reflect language used verbatim by participants, even where it includes outdated and / or reclaimed phrasing. Selection and Organization of Shared Data The data files shared here consist of the survey responses in the form of a spreadsheet. The documentation files shared consist of the questionnaire, the codebook used to analyze the data, this Data Narrative, and an administrative README file.

Art therapy allows people to express feelings about any subject through creative work. It is beneficial for people who feel out of touch with their emotions. In Ghana, little is known about art therapy as a therapeutic tool. Herbal treatment, biomedical and faith healing practices are the most common treatment options for mental health. This research aimed to provide new insights into clinical psychologists on their knowledge and use of art therapy in treating clients and identified the enablers and barriers in this therapeutic intervention.Twenty-one clinical psychologists were sampled using the snowball sampling method. They were interviewed over the phone using a semi-structured interview guide which was developed based on the predefined study objectives. Thematic analysis was employed to analyze the data resulting in three central thematic areas.Twelve of the clinical psychologists were females and eight were male, with an age range between twenty-five to fifty years. The major themes identified were knowledge of art therapy, the use of art therapy and enablers and barriers in using art therapy. The study revealed that clinical psychologists had limited knowledge of art therapy mainly due to lack of training. With the use of art therapy, the participants revealed that they had used some form of art therapy before and they perceived art therapy to be effective on their clients however, they demonstrated low confidence in using it. Practitioner training and the availability of art therapy-related resources were identified as both facilitators and hindrances to the use of art therapy.Clinical Psychologists are cognizant of art therapy albeit they have limited knowledge. Therefore, training in how to use art therapy and the availability of resources to facilitate art therapy can be provided for Clinical Psychologists by the Ghana Mental Health Authority.

This statistic depicts the number of psychologists working in the U.S. from 2007 to 2021. The number of active psychologists in the United States had increased from ****** in 2007 to over ******* in 2021.

Comprehensive YouTube channel statistics for learning psychology, featuring 203,000 subscribers and 329,087 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Education category and is based in US. Track 208 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

The event type denotes whether an event is unfolding over a non-singular period of time like the (o)ngoing snow storm, if there is an incisive, temporally (s)ingular happening like the winning move in the golf event, or if there is (n)o particular event. Suffixes for ranges and time steps stand for (m)inute, (h)our, (d)ay, (y)ear. The fraction of messages posted in the peak hour, compared with hourly fractions 12 hours prior and afterwards, is denoted by and can be interpreted as the immediacy of the response to singular events. Exponents and measure the best least-squares fit slopes between and , and between and , respectively. The symbol denotes the imposed length limitation in the respective medium. Although the fraction of peak hour messages is highest for the golf event, correlation is stronger in the presidential election forum, possibly due to the length limitation in data set 1. All other correlations are consistent with the type of event, i.e. correlations are less strong when there is only an ongoing event. We checked for robustness of the parameters in Section S4 in File S1.

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

NEW VERSION - Descriptive data on group (and subgroup) level for the article mentioned in the title.

For decades, management accounting and control (MAC) researchers have employed a diverse set of source disciplines to predict and examine behavior, and psychology is among the most frequently drawn upon. Although the literature confirms that psychological theories are highly relevant to MAC research, the existing knowledge on this field remains fragmented. Given this background, we examine recent MAC research through a systematic review of the different subfields of psychology to investigate the development of this stream of research. To do so, we collect 125 relevant articles from nine leading accounting journals between 2000 and 2019 and analyze their contents. On this basis, we provide a detailed overview of the use of psychological theories in recent literature and identify links between specific theories and MAC topics. We find that the quantity and proportion of psychology-based MAC research and the diversity of psychology subfields all increase during our investigation period, especially between 2015 and the first half of 2019. Overall, most studies address performance measurement and evaluation topics, and social psychology concepts are the most frequently applied. However, we find considerable differences in the application of psychological theories across different MAC topics. Our review provides insights into the content of this research stream and, thus, serves as a valuable source for researchers seeking an overview of previous investigations drawing on different subfields of psychology.