The Faculty of Health Studies, University of Rijeka, is one of Croatia’s key higher education institutions for health studies, nursing, physiotherapy, midwifery, radiologic technology, laboratory diagnostics, public health and other applied health disciplines. In the F5 SEO cluster, this article represents a core topic for health studies in Rijeka, especially for papers based on clinical-practical data, questionnaires, Likert scales, assessments, rehabilitation outcomes, patient satisfaction, quality of life and public health indicators.
Students, doctoral candidates and researchers at the Faculty of Health Studies in Rijeka often work with data on pain, functional status, mobility, quality of life, health behavior, knowledge and attitudes of health professionals, patient satisfaction, nursing care, physiotherapy interventions, midwifery practice, radiology protocols and public health risks. Because of this broad thematic range, statistical data analysis plays a key role in final papers, graduate papers, professional papers and scientific work.
Statistical data analysis for the Faculty of Health Studies, University of Rijeka
The Faculty of Health Studies, University of Rijeka, is an important institution for education of health professionals and development of applied research in health care. In SEO context, it is often searched as Faculty of Health Studies Rijeka, FZS Rijeka, health studies Rijeka, statistics for health studies Rijeka, SPSS nursing Rijeka, SPSS physiotherapy Rijeka, public health Rijeka and data analysis in health papers. In the F5 cluster, this article should be one of the main articles for health studies, public health and applied health statistics in Croatia.
Unlike classical medical faculties, where papers often focus on clinical outcomes, diagnostic tests and biomedical parameters, papers at the Faculty of Health Studies in Rijeka strongly belong to applied health practice. Research often starts from real problems in nursing, physiotherapy, radiologic technology, midwifery, public health, laboratory diagnostics, health education, prevention and rehabilitation.
Statistical data analysis in such papers must be clear enough for students to understand the results, but also methodologically precise enough for the paper to be academically convincing. It is not enough to show only absolute numbers and percentages. Hypotheses, sample, variables, statistical tests, tables and interpretation must be clearly structured.
Statistical support includes dataset structuring, method selection, SPSS analysis, tables and interpretation. I prepare statistical results and suggest how to present them in the academic paper. The author remains responsible for the final text and interpretation.
Specific characteristics of the Faculty of Health Studies Rijeka
The Faculty of Health Studies Rijeka is especially important for SEO because it covers several health fields in which students regularly need help with statistical data analysis. Commonly analyzed topics include surveys, Likert scales, assessments, clinical-practical indicators, rehabilitation outcomes, quality of life, patient satisfaction, pain, function, knowledge, attitudes, workload, burnout, communication and patient safety.
Many papers have an applied character. Research questions relate to concrete practice problems: how satisfied patients are with care, whether pain is associated with quality of life, whether attitudes differ by work experience, whether a rehabilitation program affects functional status, whether knowledge differs between groups or how reliable a specific questionnaire is.
This article should therefore cover a broad range of SEO terms: statistics FZS Rijeka, SPSS Faculty of Health Studies Rijeka, statistical data analysis nursing, statistics physiotherapy, health questionnaire analysis, Likert scale health, public health SPSS, rehabilitation outcomes statistics, quality of life statistics and questionnaire validation in health studies.
Data types in health studies
Papers may include demographic data, clinical-practical data, survey data, Likert scales, pain scores, quality of life, functional status, patient satisfaction, health habits, physical activity, work ability, stress, burnout, knowledge and attitudes of health professionals, risk perception, therapy adherence and intervention effectiveness.
In nursing, common topics include patient satisfaction, quality of care, workload of nurses and technicians, burnout, communication, patient safety, patient education, prevention of complications, assessment of patient needs and attitudes toward professional practice. In physiotherapy, research often analyzes pain, range of motion, functional tests, rehabilitation outcomes, balance, mobility, strength, disability and quality of life.
In midwifery, topics may include education of pregnant women, experiences of mothers, satisfaction with care, breastfeeding, perceived support, information and attitudes toward perinatal care. Radiologic technology may include protocols, radiation dose, safety, image quality, knowledge and attitudes. Public health may include health behavior, prevention, epidemiological indicators, risk factors and population attitudes toward health.
Research design
Cross-sectional studies
Cross-sectional studies are very common in final and graduate papers in health studies. They analyze a situation at one time point, such as knowledge, attitudes, satisfaction, quality of life, pain, functional status or health behavior. Population, sample, instruments, variables and hypotheses must be clearly defined.
Group comparisons
A very common design compares groups by sex, age, work experience, education level, diagnosis, therapy, department, type of intervention, workplace or level of functional limitation. Depending on variable type, t-test, Mann-Whitney U test, ANOVA, Kruskal-Wallis test, chi-square test and Fisher’s exact test can be used.
Correlational studies
Correlational studies examine associations between variables: pain and quality of life, stress and burnout, physical activity and function, knowledge and health behavior, patient satisfaction and communication, or workload and psychological stress.
Intervention and evaluation studies
Some papers examine the effect of education, rehabilitation programs, preventive interventions, protocol changes or therapeutic procedures. It is important to define pre- and post-measurement, control group if available, primary outcome and an appropriate test for change.
Validation of questionnaires and scales
Health papers often use questionnaires and scales. If an instrument is translated, adapted or used on a new population, reliability, internal consistency, factor structure and relationships with relevant measures should be checked.
Important statistical methods
Descriptive statistics
Descriptive statistics describe the sample and results using frequencies, percentages, means, standard deviations, medians, interquartile ranges, minimum and maximum values. Presentation must match variable type and distribution.
Group comparison tests
Parametric and nonparametric tests are used. t-test and ANOVA are used when assumptions are met, Mann-Whitney U test and Kruskal-Wallis test for ordinal data, asymmetric distributions or smaller samples. Chi-square and Fisher’s exact test are used for categorical variables.
Correlation analysis
Correlations examine relationships between continuous or ordinal variables. Pearson correlation is used for approximately normally distributed continuous variables, while Spearman correlation is used for ordinal variables or when normality assumptions are not met. In health papers, Spearman correlation is often appropriate for Likert scales.
Regression analysis
Regression analysis evaluates predictors of outcomes. Linear regression is used for continuous outcomes, logistic regression for binary outcomes and ordinal regression for ordinal outcomes. Regression can identify predictors of quality of life, pain, function, satisfaction, burnout, risk behavior or therapy adherence.
Reliability analysis
Cronbach’s alpha is used to assess internal consistency of scales. In multi-item questionnaires, reliability shows whether items measure the same construct. Item correlations, alpha if item deleted and scale structure may also be reported.
Factor analysis
Exploratory factor analysis examines the structure of a questionnaire or scale. In health studies, it may be used for instruments measuring attitudes, satisfaction, quality of life, fear, stress, professional burden, perception of care or self-assessed competencies.
ROC analysis
ROC analysis can be useful when evaluating diagnostic or classification value of a test, scale or functional indicator. AUC, sensitivity, specificity and possible cut-off values are presented.
SPSS analysis and interpretation
SPSS is a common tool in health studies because it supports group comparisons, correlations, regression, reliability analysis, factor analysis and graphical presentation. Statistical analysis is not only about running tests. Results must be explained in the context of health practice.
Interpretation should show what results mean for nursing care, physiotherapy, rehabilitation, midwifery, radiologic practice, public health, health education or patient safety. A p-value shows statistical significance, but not automatically practical importance. Effect size, confidence intervals and direction of differences or associations are important.
Likert scales and questionnaires
Many papers in health studies use Likert scales. It is important to decide whether individual items, total scores or subscales are analyzed. Individual Likert items are often treated as ordinal variables, while summed scale scores with good reliability and enough items are often analyzed as continuous variables.
Questionnaires should be described with number of items, response range, scoring, direction of interpretation, reliability and meaning of higher values.
Sample size and statistical power
In health studies, samples often depend on available respondents, patients, departments or institutions. Still, a minimum number of participants should be planned according to hypotheses and methods. Too small a sample may fail to confirm real differences or associations.
Planning is especially important when comparing several groups, performing regression analysis, validating a questionnaire or evaluating an intervention. Expected effect size, number of predictors, number of groups and desired statistical power should be considered.
Typical topics for the Faculty of Health Studies Rijeka
Typical topics include nursing, physiotherapy, midwifery, public health, radiologic technology, laboratory diagnostics, quality of life, pain, functional status, rehabilitation outcomes, patient satisfaction, knowledge and attitudes of health professionals, disease prevention, health behavior, patient safety, burnout, stress, communication in health care, patient education and questionnaire validation.
SEO position: F5 cluster for health studies Rijeka
For SEO strategy, the Faculty of Health Studies Rijeka should be a core article for the F5 cluster in Rijeka and the Kvarner region. This article connects nursing, physiotherapy, midwifery, radiology, laboratory diagnostics and public health research. It is clearly distinct from F2 medical faculties, which cover clinical medicine, and from F6 educational-rehabilitation topics, which cover specific rehabilitation and assessment instruments.
Workflow
The workflow includes reviewing the topic and hypotheses, checking dataset structure, defining variables, selecting statistical methods, SPSS analysis, table preparation and interpretation. I prepare statistical results and suggest how to present them in the academic paper. The author remains responsible for the final text and interpretation.
FAQ
Can a nursing survey be analyzed?
Yes. Knowledge, attitudes, satisfaction, burnout, quality of care, communication, patient safety and other nursing indicators can be analyzed.
Can a physiotherapy paper be analyzed?
Yes. Pain, functional status, range of motion, rehabilitation outcomes, quality of life and therapy effects can be analyzed.
Can Likert scales be analyzed?
Yes. Individual items, total scores, subscales, reliability and factor structure can be analyzed.
Is SPSS sufficient for health studies?
For many final, graduate and professional papers, SPSS is sufficient. More complex longitudinal models may require additional tools or advanced models.
Keywords
statistics Faculty of Health Studies Rijeka, FZS Rijeka SPSS, health studies Rijeka statistics, nursing statistics Rijeka, physiotherapy statistics Rijeka, public health SPSS Rijeka, health survey analysis, Likert scale health, quality of life statistics, rehabilitation outcomes statistics
Metatext
Statistical data analysis for the Faculty of Health Studies, University of Rijeka: SPSS, health studies, nursing, physiotherapy, midwifery, public health, Likert scales, questionnaires and rehabilitation outcomes.
