Psychology Statistics for Dummies

The quick, easy way to master all the statistics you'll ever need The bad news first: if you want a psychology degree you'll need to know statistics. Now for the good news: Psychology Statistics For Dummies. Featuring jargon-free explanations, step-by-step instructions and dozens of real-life examples, Psychology Statistics For Dummies makes the knotty world of statistics a lot less baffling. Rather than padding the text with concepts and procedures irrelevant to the task, the authors focus only on the statistics psychology students need to know. As an alternative to typical, lead-heavy statistics texts or supplements to assigned course reading, this is one book psychology students won't want to be without. Ease into statistics – start out with an introduction to how statistics are used by psychologists, including the types of variables they use and how they measure them Get your feet wet – quickly learn the basics of descriptive statistics, such as central tendency and measures of dispersion, along with common ways of graphically depicting information Meet your new best friend – learn the ins and outs of SPSS, the most popular statistics software package among psychology students, including how to input, manipulate and analyse data Analyse this – get up to speed on statistical analysis core concepts, such as probability and inference, hypothesis testing, distributions, Z-scores and effect sizes Correlate that – get the lowdown on common procedures for defining relationships between variables, including linear regressions, associations between categorical data and more Analyse by inference – master key methods in inferential statistics, including techniques for analysing independent groups designs and repeated-measures research designs Open the book and find: Ways to describe statistical data How to use SPSS statistical software Probability theory and statistical inference Descriptive statistics basics How to test hypotheses Correlations and other relationships between variables Core concepts in statistical analysis for psychology Analysing research designs Learn to: Use SPSS to analyse data Master statistical methods and procedures using psychology-based explanations and examples Create better reports Identify key concepts and pass your course

The Impact of Shame on the Therapeutic Alliance and Intimate Relationships

Objectives


This study examined the role of shame coping styles and state shame in predicting the therapeutic alliance and intimate relationship functioning in individuals with mental health problems.


Method


A sample of 50 treatment-receiving adults aged 21 to 67 years with a mix of common mental health difficulties was recruited from a clinical psychology service. Participants were given questionnaire measures of shame states, shame coping styles, intimate relationship functioning, and the therapeutic alliance.


Results


Regression analyses indicated that the shame coping strategy of physical and psychological withdrawal was the primary risk factor for development of a less effective therapeutic alliance. Both withdrawal and attack self coping styles were significant predictors of impaired intimate relationship functioning.


Conclusions


These findings have implications for the theoretical role of shame in mental health presentations as well as the potential for internalizing shame coping styles (i.e., withdrawal, attack self) to act as a barrier to successful therapy and interpersonal relationships. The inclusion of shame-focused assessments and interventions in the initial stages of treatment with clients exhibiting these strategies could improve prognosis.

Burnout as a predictor of all-cause mortality among industrial employees: A 10-year prospective register-linkage study

Objective: Burnout, a psychological consequence of prolonged work stress, has been shown to coexist with physical and mental disorders. The aim of this study was to investigate whether burnout is related to all-cause mortality among employees. Methods: In 1996, of 15,466 Finnish forest industry employees, 9705 participated in the 'Still Working' study and 8371 were subsequently identified from the National Population Register. Those who had been treated in a hospital for the most common causes of death prior to the assessment of burnout were excluded on the basis of the Hospital Discharge Register, resulting in a final study population of 7396 people. Burnout was measured using the Maslach Burnout Inventory-General Survey. Dates of death from 1996 to 2006 were extracted from the National Mortality Register. Mortality was predicted with Cox hazard regression models, controlling for baseline sociodemographic factors and register-based health status according to entitled medical reimbursement and prescribed medication for mental health problems, cardiac risk factors, and pain problems. Results: During the 10-year 10-month follow-up, a total of 199 employees had died. The risk of mortality per one-unit increase in burnout was 35% higher (95% CI 1.07-1.71) for total score and 26% higher (0.99-1.60) for exhaustion, 29% higher for cynicism (1.03-1.62), and 22% higher for diminished professional efficacy (0.96-1.55) in participants who had been under 45 at baseline. After adjustments, only the associations regarding burnout and exhaustion were statistically significant. Burnout was not related to mortality among the older employees. Conclusion: Burnout, especially work-related exhaustion, may be a risk for overall survival. (C) 2010 Elsevier Inc. All rights reserved.

The Role of Work Group in Individual Sickness Absence Behavior

The purpose of our two-year follow-up study was to examine the effect of the social components of the work group, such as group absence norms and cohesion, on sickness absence behavior among individuals with varying attitudes toward work attendance. The social components were measured using a questionnaire survey, and data on sickness absence behavior were collected from the employers' records. The study population consisted of 19,306 Finnish municipal employees working in 1,847 groups (78% women). Multilevel Poisson regression modeling was applied. The direct effects of work group characteristics on sickness absence were mostly insignificant. In contrast, both of the social components of a work group had an indirect impact: The more tolerant the group absence norms (at both individual- and cross-level) and the lower the group cohesion (at the individual level), the more the absence behavior of an individual was influenced by his or her attitude toward work attendance. We conclude that work group moderates the extent to which individuals with a liberal attitude toward work attendance actually engage in sickness absence behavior.

The Association of Distress and Sleeping Problems With Physicians' Intentions To Change Profession: The Moderating Effect of Job Control

The present study examined whether job control moderated the association between stress indicators (distress and sleeping problems) and intentions to change profession among 2,650 Finnish physicians. Ordinal logistic regression analysis was applied. The authors found that high levels of distress and sleeping problems were associated with higher levels of intentions to change profession, whereas high job control was associated with lower levels of intentions to change profession even after adjusting for the effects of gender, age, and employment sector. In addition, high job control was able to mitigate the positive association that distress and sleeping problems had with intentions to change profession. Our findings highlight the importance of offering more job control to physicians to prevent unnecessary physician turnover.

Association of impulsivity with sleep duration and insomnia in an employee population

Clinical studies have linked impulsivity and insomnia in patients, but little is known about this association in non-clinical settings. This study examined whether impulsive temperament is associated with sleep duration and insomnia complaints in a large cohort of hospital employees (535 men and 4014 women). Linear regression models were related to prospective data from two surveys conducted in 1998 and 2000. Adjustments were made for age, marital status, education, shift work, smoking, alcohol consumption, body mass index, physical activity, minor psychiatric morbidity, social support, somatic disease, depression and other psychiatric disease in 1998. In men, higher impulsivity predicted shorter sleep duration and waking up several times per night independent of baseline characteristics. In women, higher impulsivity predicted having difficulty falling asleep and waking up feeling tired after the usual amount of sleep after adjustment for most of covariates. However, these associations turned out to be non-significant after adjustment for somatic and psychiatric disease. These results support the hypothesis that impulsive temperament could be a risk factor for insomnia in men. (c) 2007 Elsevier Ltd. All rights reserved.

Impulsivity as a predictor of newly diagnosed depression

Depression is a severe mental disorder, whose onset has been related to environmental, genetic and personality factors. This study examined the association between impulsivity and incidence of depression. Logistic regression models were related to prospective data from two surveys (2-year time lag) conducted in a large cohort of hospital employees (N = 4,505). Only respondents with no history of depression at baseline were included. Impulsivity was predictive of the onset of depression (OR = 1.95, CI 95% = 1.28-2.97) after adjustment for age, sex and education. This association remained statistically significant after additional adjustment for a variety of baseline characteristics, such as smoking, alcohol consumption, and size of social network. A measure of mental distress (GHQ-12 responses), which may serve as a proxy measure for undiagnosed depression, was also associated with impulsivity. Impulsivity appears to be a distinct personality factor that may contribute to the onset of depressive illness in adults.

Relationship between work stress and body mass index among 45,810 female and male employees

Objective: The proportion of overweight and obese people has grown rapidly, and obesity has now been widely recognized as an important public health problem. At the came time, stress has increased in working life. The 2 problems could be connected if work stress promotes unhealthy eating habits and sedentary behavior and thereby contributes to weight gain. This study explored the association between work stress and body mass index (BMI; kg/m(2)). Methods: We used cross-sectional questionnaire data obtained from 45,810 female and male employees participating in the ongoing Finnish Public Sector Cohort Study. We constructed individual-level scores, as well as occupational- and organizational-level aggregated scores for work stress, as indicated by the demand/control model and the effort-reward imbalance model. Linear regression analyses were stratified by sex and socioeconomic status (SES) and adjusted for age, marital status, job contract, smoking, alcohol consumption, physical activity, and negative affectivity. Results: The results with the aggregated scores showed that lower job control, higher job strain, and higher effort-reward imbalance were associated with a higher BMI. In men, lower job demands were also associated with a higher BMI. These associations were not accounted for by SES, although an additional adjustment for SES attenuated the associations. The results obtained with the individual-level scores were in the same direction, but the relationships were weaker than those obtained with the aggregated scores. Conclusions: This study shows a weak association between work stress and BMI.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

Increasing the accuracy of Nitrogen Dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics.

Nitrogen Dioxide (NO2) is known to act as an environmental trigger for many respiratory illnesses. As a pollutant it is difficult to map accurately, as concentrations can vary greatly over small distances. In this study three geostatistical techniques were compared, producing maps of NO2 concentrations in the United Kingdom (UK). The primary data source for each technique was NO2 point data, generated from background automatic monitoring and background diffusion tubes, which are analysed by different laboratories on behalf of local councils and authorities in the UK. The techniques used were simple kriging (SK), ordinary kriging (OK) and simple kriging with a locally varying mean (SKlm). SK and OK make use of the primary variable only. SKlm differs in that it utilises additional data to inform prediction, and hence potentially reduces uncertainty. The secondary data source was Oxides of Nitrogen (NOx) derived from dispersion modelling outputs, at 1km x 1km resolution for the UK. These data were used to define the locally varying mean in SKlm, using two regression approaches: (i) global regression (GR) and (ii) geographically weighted regression (GWR). Based upon summary statistics and cross-validation prediction errors, SKlm using GWR derived local means produced the most accurate predictions. Therefore, using GWR to inform SKlm was beneficial in this study.