Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.

Review of Economics and Statistics: Forthcoming. Replication data for the simulation and empirical application in the paper "Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data", which consists of a subset of the Job Corps experimental study.

A combination of discrete and daily-aligned groundwater levels for the Mississippi River Valley alluvial aquifer clipped to the Mississippi Alluvial Plain, as defined by Painter and Westerman (2018), with corresponding metadata are based on processing of U.S. Geological Survey National Water Information System (NWIS) (U.S. Geological Survey, 2020) data. The processing was made after retrieval using aggregation and filtering through the infoGW2visGWDB software (Asquith and Seanor, 2019). The nomenclature GWmaster mimics that of the output from infoGW2visGWDB. Two separate data retrievals for NWIS were made. First, the discrete data were retrieved, and second, continuous records from recorder sites with daily-mean or other daily statistics codes were retrieved. Each dataset was separately passed through the infoGW2visGWDB software to create a "GWmaster discrete" and "GWmaster continuous" and these tables were combined and then sorted on the site identifier and date to form the data products described herein. A sweep through the combined dataset (the "database") was made to isolate duplicate observations, or observations for the same well and on the same day. If a discrete value was present, it was retained as authoritative for the day and in descending order of priority daily-mean, daily-maximum, and daily minimum. Therefore, only a single record for a well and day are present in the dataset. The duplicate search removed 876 records and 31 wells were involved; in total, this is about 0.3 percent of the database. References: Asquith, W.H., Seanor, R.C., 2019, infoGW2visGWDB—An R groundwater data-processing utility for manipulating, checking the veracity, and converting an "infoGW" object to the "GWmaster" object for the visGWDB software with demonstration for the Mississippi River Valley alluvial aquifer: U.S. Geological Survey software release, Reston, Va., https://doi.org/10.5066/P9MK0B6L. Painter, J.A., and Westerman, D.A., 2018. Mississippi Alluvial Plain extent, November 2017: U.S. Geological Survey data release, https://doi.org/10.5066/F70R9NMJ. U.S. Geological Survey, 2020, USGS water data for the Nation: U.S. Geological Survey National Water Information System database, accessed April 2, 2020, at https://doi.org/10.5066/F7P55KJN.

This study is a cross-sectional, hospital-based observational study conducted from July 2019 to March 2020 at Kasturba Hospital of Kasturba Medical College, Manipal, a tertiary care centre in Udupi district of Karnataka state in India. The sample consisted of medical practitioners working in various clinical branches of medicine of Kasturba Hospital, Manipal, with a minimum of one year of experience. Convenience sampling was used. Written informed consent was obtained from all participants. The sample size was calculated using the formula for statistically significant correlation coefficient and it was calculated as185. Participants’ age, gender and work experience details were documented in a proforma. Psychological flexibility was measured using Acceptance and action questionnaire-II (AAQ-II; Bond et al, 2011). Professional Quality of Life Scale Version 5 (ProQol 5; Stamm, 2010) was used to measure compassion satisfaction (CS), burnout (BO) and secondary traumatic stress (STS) among participants. The collected data was analyzed using IBM Statistical Package for Social Sciences (SPSS) statistics for Windows, Version 25 (IBM Corp, Armonk, NY, USA). Descriptive statistics were used to summarize the data. Mean and standard deviation (SD) were used for continuous data. Group differences across gender for continuous variables were examined using an independent t-test and P values less than 0.05 were considered significant. To establish the relationship between the variables Pearson’s’ correlation test was used.

The research hypothesis stated was that there would be no relationship between psychological flexibility and 1) compassion satisfaction, 2) burnout and 3) secondary traumatic stress among medical practitioners.

Out of the 185 that could complete the study, it included 70 females and 115 males. Mean age of the sample was 37.31 years. In terms of years of work experience, 149 doctors had less than 20 years of experience and 36 had more than 20 years of experience.

Mean scores of acceptance and action questionnaire-II and professional quality of life scale version 5 were analysed. Compassion Satisfaction had a mean score of 35.89, Burnout has a mean score of 24.97, Secondary Traumatic Stress had a mean score of 20.43 and Psychological Inflexibility had a mean score of 15.69.

The result of Pearson’s correlation showed the relationship between compassion satisfaction and psychological inflexibility was not significantly correlated. The relationship between burnout and psychological inflexibility is significantly and strongly positively correlated. The relationship between secondary traumatic stress and psychological inflexibility is significantly and strongly positively correlated. Using a t-test, it was shown that compassion satisfaction was relatively higher for females and burnout was relatively higher in males.

In April 2011 a new set of clinical quality indicators was introduced to replace the previous four hour waiting time standard, and measure the quality of care delivered in A&E departments in England. Further details on the background and management of the quality indicators are available from the Department of Health (DH) website. This is the publication of data on the Accident and Emergency (A&E) clinical quality indicators, drawn from A&E data within provisional Hospital Episode Statistics (HES). These data relate to A&E attendances in March 2012 and draw on 1.53 million detailed records of attendances at major A&E departments, single speciality A&E departments (e.g. dental A&Es), minor injury units and walk-in centres in England. This report sets out data coverage, data quality and performance information for the following five A&E indicators: Left department before being seen for treatment rate Re-attendance rate Time to initial assessment Time to treatment Total time in A&E Publishing these data will help share information on the quality of care of A&E services to stimulate the discussion and debate between patients, clinicians, providers and commissioners, which is needed in a culture of continuous improvement. These A&E HES data are published as experimental statistics to note the shortfalls in the quality and coverage of records submitted via the A&E commissioning data set. The data used in these reports are sourced from Provisional A&E HES data, and as such these data may differ to information extracted directly from Secondary Uses Service (SUS) data, or data extracted directly from local patient administration systems. Provisional HES data may be revised throughout the year (for example, activity data for April 2011 may differ depending on whether they are extracted in August 2011, or later in the year). Indicator data published for earlier months have not been revised using updated HES data extracted in subsequent months. The data presented here represent the output of the existing A&E Commissioning Dataset (CDS V6 Type 010). It must be recognised that these data will not exactly match the data definitions for the A&E clinical quality indicators set out in the guidance document A&E clinical quality indicators: Implementation guidance and data definitions (external link). The DH is currently working with Information Standards Board to amend the existing CDS Type 10 Accident and Emergency to collect the data required to monitor the A&E indicators. A&E HES data are collected and published by the NHS Information Centre for Health and Social Care. The data in this report are secondary analyses of HES data produced by the Urgent & Emergency Care team, Department of Health. A&E HES data are published as experimental statistics to note the known shortfalls in the quality of some A&E HES data elements. The published information sets out where data quality for the indicators may be improved by, for example, reducing the number of unknown values (e.g. unknown times to initial assessment) and default values (e.g. the number of attendances that are automatically given a time to initial assessment of midnight 00:00). The quality and coverage of A&E HES data have considerably improved over the years, and the Department and the NHS Information Centre are working with NHS Performance and Information directors to further improve the data.

Based on Chinese General Social Survey data (CGSS 2021), binary logistic regression and stepwise regression were used to explore how Internet use improves the physical and mental health of elderly people and its influence mechanisms. The research found that Internet use has a positive and significant impact on the physical and mental health of the Chinese elderly, and the results are robust with variable replacement and model replacement tests. In its influence mechanism, it found that Internet use promotes the physical and mental health of elderly people through physical exercise, social interaction, and learning frequency, which have a partial mediating effect. The effectiveness of the Internet use in promoting physical and mental health of the Chinese elderly through learning frequency is higher than physical exercise and social interaction, highlighting the importance of continuous learning for the Chinese elderly in the digital age. At the same time, Internet use has an unequal influence on the physical and mental health of the Chinese elderly, and has a greater influence on the mental health of the elderly with higher socio-economic status. Therefore, the research proposes the following three suggestions. First, improve the popularity of Internet use among the Chinese elderly. Second, accelerate the development of Internet application products suitable for the Chinese elderly. Third, provide Internet education for different regions elderly groups, and implement targeted assistance for elderly people with poor socio-economic status.

Background characteristics of the study variables (N = 241).

Conflict management is rarely explored among physiotherapists though they often work in teams. Hence, this study explored attitudes, perceived competencies, beliefs, training experiences, and needs in conflict management among Italian physiotherapists. We conducted a cross-sectional online survey study between June and September 2023 among Italian physiotherapists. The survey instrument comprised four sections. Section 1: Socio-Demographic and Professional Data: Explored participant profiles and conflict frequency. Section 2: Attitudes and Competences: assess conflict-related behaviours and management styles (Likert Scale). Section 3: Training Experiences and Needs: Evaluated training importance and conflict-related issues with other professionals (Likert Scale). Section 4: Beliefs About Factors: Participants rated (0–10) factors influencing conflict management and its impact on care and well-being. Descriptive analyses were performed, presenting continuous data as mean (SD) and categorical data as frequencies/percentages. Likert scale responses were dichotomised (agreement/disagreement), and consensus was defined as ≥70% agreement. Median, quartiles, and box-and-whisker plots depicted responses were used for 0-to-10 scales. Physiotherapists (n = 203; mean age: 39±10.40) generally leaned towards a constructive communication style, characterised by compromise and collaboration, viewing conflict management as an opportunity to grow. There was a disparity between their exhibited behaviours and self-assessment of appropriateness in conflict resolution. Only 27.6% considered their conflict resolution skills as satisfactory. However, 85.7% acknowledged the significance of being trained in conflict management. Challenges were evident in conflicts within interprofessional relationships and communication with superiors. Both personal and organisational factors were identified as influencing conflict management, with participants recognising the detrimental impact of conflicts on their well-being and patient care. This study highlighted educational gaps in conflict management among Italian physiotherapists, showing areas of improvement in their training. Our results suggested that physiotherapists might need additional training in conflict management to enhance workplace well-being and the quality of care provided.

Statistics of one PDL’s length and precession over time.