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Scientific Methodology and Biostatistics

Code: 106104
Credits: 6
2026/2027
Degree programme Type Course
Nursing FB 1

Contact lecturer

Name :
Maria Feijoo Cid
Email :
maria.feijoo@uab.cat

Teaching staff

Albert Navarro Gine

Group languages

You can consult this information at the end of the document.

Prerequisites

none

Objectives

This subject contains the basic training in scientific methodology and biostatistics of the degree. Nurses, whenpracticing their profession, face a set of situations-problems that put their abilities to the test (selection ofinformation, organization of reasoning, distinction between the fundamental and the accessory, statisticalinterpretation of health problems, etc.)

The purpose is to structure a critical and thoughtful thinking that allows the critical reading of research in healthsciences and the analysis of health problems using statistics to promote a practice nurse of excellence.

The subject raises the basic knowledge and skills to apply in the accomplishment of the degree's final project.

Learning outcomes

  • SM01 (Use scientific evidence in professional practice.) Use scientific evidence in professional practice.
  • SM10 (Use information and communication systems to diagnose and deliver quality care based on scientific evidence.) Use information and communication systems to diagnose and deliver quality care based on scientific evidence.

Contents

Below is a brief description of the subject:


  1. Bases of scientific knowledge: Sources and types of human knowledge. The scientific method. the scientific method's characteristics and limitations.
  2. Quantitative and qualitative methodologies: Introduction and differences between both.
  3. Research process: Relationships between the scientific method, the research process and a scientific article.
  4. Research problem and hypothesis formulation.
  5. Review and bibliographic search.
  6. Study design.
  7. Sample and Population.
  8. Methods of data collection.
  9. Evaluation of scientific articles: internal validity and external validity.
  10. Evidence Based Nursing.
  11. Gender-sensitive research
  12. General concepts of statistics: basic terminology of research and statistics. Principles of the measure
  13. Recollection, tabulation and graphic presentation of results. Basic principles of descriptive inferential statistics.
  14. Handling of statistical data files.
  15. Presentation and interpretation of results in scientific articles

Learning activities and methodology

Title Hours ECTS Learning outcomes
THEORY 28 1.12 SM01, SM10
LABORATORY PRACTICES 13 0.52 SM01, SM10
TUTORIALS 1 0.04 SM01, SM10
CLASSROOM PRACTICES 10 0.4 SM01, SM10
Self study 76 3.04 SM01, SM10
SEMINARS 14 0.56 SM01, SM10

The learning methodologies are the backbone for the achievement of both theoretical content and skills involved in reflective-critical thinking when solving nursing problems based on the scientific method. The following is a brief description of each learning methodology


In Theory, necessary theoretical contents of the Scientific Methodology Module and the Biostatistics Module will be taught.


In the seminars (SEM) -belonging to both modules- the students will work in small groups. They will be introduced to the critical and reflective reading of original articles in the field of nursing and/or health sciences. As an example look at the Impacto en la salud del programa de intervención comunitaria «Educación para la salud en la adolescencia». These seminars will help to identify and discuss about real examples (original/scientific articles) the theory previously done. The original articles reflect the results of some of the nursing interventions. The critical reading of those articles will guide the nursing decision making based on the scientific method.


The laboratory practices (Plab) belong to the two blocks: on the biostatistics block quantitative data will be analyzed with analysis software, their interpretation will be performed and it will be shown how to present the results in the scientific environment. On the scientific methods' block, searches for information in scientific databases will be carried out prior planning. The two four-hour PLABs that belong to the biostatistics block are mandatory. Non-attendance at one of these PLAB sessions without valid justification, provided that the student has attended the other one, will result in a deduction from the mark obtained equivalent to one third of the maximum total mark for the Biostatistics assignment; that is, 3.33 points out of 10 in the assignment mark, which corresponds to 0.5 points in the overall course mark.

Non-attendance at both specified PLAB sessions will result in: a) a mark of 0 if neither of the two absences is validly justified; b) the requirement to complete a similar assignment, autonomously and individually, in accordance with the instructions provided by the teaching staff, if one or both absences have been duly justified. If one of the two absences has not been justified, 3.33 points out of 10 will be deducted from the mark for the individually completed assignment. Students may consult the valid and non-valid grounds for justifying absences in the UDCMB guide on the rescheduling of assessments: https://www.uab.cat/doc/DOC_Guia_Reprogramacio.

The classroom practices (PAUL) will work on concepts associated with both scientific methodology and biostatistics.

  • PAUL of scientific methodology will be used to perform in situ a literature review to decide the best nursing intervention to solve a health problem. This literature review will be delivered in one of the research dissemination formats. A PAUL methodology will guide the writing and development of each of the corresponding parts of a literature review. The research problem will be previously defined from the coordination of the subject and will be the same for all first year students. A PAUL of methodology will be worked in the same small groups that previously have been made to the seminars. These PAUL are not mandatory but, in the case of problems to the group work the person/s who do not comply with the tasks assigned by the group will do individually the literature review.
  • The biostatistics PAUL will be dedicated to the formalization of the biostatistics work and is mandatory. Failure to attend this PAUL without valid justification (see valid and invalid concepts in the guide on the rescheduling of tests to the UDCMB: https://www.uab.cat/doc/doc_guia_reprogramacio), will result in the loss of one third of the maximum total grade of the Biostatistics paper (i.e. 3.33 points out of 10 in the assignment mark, which corresponds to 0.5 points on the total grade of the subject).


Annotation: within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Assessment

Continuous assessment activities

Title Weight Hours ECTS Learning outcomes
Objective written test evaluations (Scientific methodology) 35% 3 0.12 SM01, SM10
Evaluation by submitting written works 30% 2 0.08 SM01, SM10
Objective written test evaluations (Biostatistics) 35% 3 0.12 SM01, SM10

ONGOING EVALUATION


All the evaluation activities are compulsory, in case of not presenting it will be graded as Not Evaluable (NA) and will be quantified as zero (0). The evaluation of the subject is structured as follows:

  1. (OE1) Objective test (scientific methodology exam): multiple-choice test: 35%.
  2. (OE2) Objective test (Biostatistics exam): multiple-choice test: 35%.
  3. (OE3) Submission of literature review (Scientfic methodology): 15%.
  4. (OE4) Submission of written works_data analysis (Biostatistics): 15%.


The final mark of the course is the weighting of the 4 ongoing assessment tests. In order to pass the course a minimum of 5.0 in the final grade is required. If the ongoing assessment is failed, the student may sit the retake exam. It must be taken into account that, according to general regulations, in order to take part in the final exam, students must have been previously assessed in a set of activities whose weight is equivalent to a minimum of two thirds of the total grade of the subject. This retake exam will include the entire syllabus of the failed assessment test.


Use of IA:

The use of Artificial Intelligence technologies (IA) for this subject is allowed exclusively in support tasks such as proofreading or translations or audiovisual support. The use of IA in support tasks such as bibliographic or information search or any other knowledge generation task is prohibited. The student will have to clearly identify which parts have been generated with this technology, specify the tools used, include a critical reflection on how these have influenced the process and the final result of the activity and reference them (as specified in Bibliography). The non-transparency of the use of IA in this evaluable activity will be considered academic dishonesty and may result in a total penalty in the grade of the activity, or higher penalties in serious cases.


The performance of any irregularity in an evaluation act (academic fraud, plagiarism or improper use of AI, unless this use is expressly authorized by the teaching guide), which may lead to a significant variation in the grade, assumes that this act will be graded with a 0. In the event that the teaching guide foresees that in order to pass the subject it is an essential requirement to have obtained a minimum grade in this evaluation act or that there are several irregularities in the evaluation acts of the same subject, the final grade of this subject is 0. Apart from this, a disciplinary process may be instructed to the student that incurs any of these irregularities.


Retake:

  1. Any student who has taken at least two thirds of the total grade of the subject is entitled to retake the exam.
  2. The final mark will be the result of the weighting of the retake tests with the continuous assessment tests passed.
  3. In order to pass the course having taken a recovery test, it is necessary to obtain a minimum of 5.0 in the final mark.


Definition of NOT ASSESSABLE (NA): it will be understood as Not Assessable (NA) that situation in which the student does NOT present 50% or more of the evaluation activities.


Test Review: all students have the right to review the evaluation tests by appointment with the corresponding teacher. Thereview will consist of an individual tutoring session in which students will receive feedback regarding their evaluation.


The treatment of particular cases will be made from a teaching committee (formed by the subject coordinator,and 2 of the teachers of the same, 1 from each department involved) where the particular situation of each student will be evaluated and the mostappropriate decisions will be taken.


ONE-TIME EVALUATION:


Students who wish to add to the single evaluation must do so following the deadlines established by academic management. The same day of the single evaluation will be evaluated the whole course with its corresponding evaluation activities. One-time evaluation will be a multiple-choice test with the following content:


The final mark of the single evaluation is the mark of the multiple-choice test.. In order to pass the subject with One-time evaluation it is necessary to obtain a minimum of 5.0 in the final grade.


Definition of NOT ASSESSABLE (NA): Not Assessable shall be understood as the situation in which the student does NOT sit for the single evaluation exam.


The retake ofthe one-time evaluation takes place on the same day as the retake of the ongoing evaluation. In the retake exam, the student is assessed on the failedtest/s. The number of exams and structure will be the same asfor the one-time evaluation. The calculation of the final mark for the subject follows the same criteria.

The review of the final score (including that of the retake) follows the same procedureas for the ongoing evaluation.

Bibliography

Selected references:

  1. Albert Navarro Giné, Sergio Salas Nicás. Iniciación a la bioestadística para enfermería y otras profesiones sanitarias. Bellaterra: Universitat Autònoma de Barcelona, Servei de Publicacions, 2021.
  2. Grove, S. K., & Gray, J. R. Investigación En Enfermería: Desarrollo De La Práctica Enfermera Basada En La Evidencia (7th edition). Elsevier. 2019
  3. Argimon Pallás, JM; Jiménez Villa, J. Métodos de investigación clínica y epidemiológica. (5ª ed.) Barcelona: Elsevier, España, 2019.
  4. Bee, P.; Brooks, H.; Callaghan, P. and Lovell. K. A research handbook for patients an public involvement. Manchester, Manchester University Press, 2018.
  5. Denise F. Polit, Cheryl Tatano Beck. Essentials of nursing research: Appraising Evidence for Nursing Practice. Philadelphia : Wolters Kluwer/Lippincott/Williams & Wilkins Health. 8th ed. 2018
  6. Al Maqbali, M. Essential Research for Evidence-Based Practice in Nursing Care. Springer Nature Switzerland.1st ed. 2024 https://doi.org/10.1007/978-3-031-78298-52024


Referral bibliography:

  1. Nancy Burns, Susan K. Grove. Investigación en enfermería. Madrid. Elsevier 5a ed. 2016.
  2. Wayne W. Daniel. Bioestadística: base para el análisis de las ciencias de la salud. México: Limusa, 2002.
  3. Cobo, E; Muñoz, P; González, JA. Bioestadística para no estadísticos: principios para interpretar un estudio científico P, González JA. Barcelona: Elsevier Masson, 2007.


Citing AI use: Since some use of AI is allowed, AI must be cited. To know how to cite it see Citar y elaborar Bibliografías. Estilos bibliográficos: COMO CITAR INTELIGENCIA ARTIFICIAL (IA).

Reading Por qué ChatGPT no puede firmar artículos científicos. Javier Palanca.


Internet Sources

  1. http://www.easp.es/exploraevidencia/
  2. https://doaj.org/
  3. http://www.ncbi.nlm.nih.gov/pubmed
  4. http://www.scopus.com/home.url
  5. http://www.fisterra.com/

Software

The Jamovi statistics program is used in the biostatistics laboratory practices.

Course groups and languages

The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE

Type of teaching Group Language Semester Shift
(TE) Theory 101 Catalan second semester morning-mixed
(PAUL) Classroom practices 101 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 101 Catalan second semester morning-mixed
(SEM) Seminars 101 Catalan second semester morning-mixed
(TE) Theory 102 Catalan second semester morning-mixed
(PAUL) Classroom practices 102 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 102 Catalan second semester morning-mixed
(SEM) Seminars 102 Catalan second semester morning-mixed
(TE) Theory 103 Catalan second semester afternoon
(PAUL) Classroom practices 103 Catalan/Spanish second semester morning-mixed
(PLAB) Practical laboratories 103 Catalan second semester morning-mixed
(SEM) Seminars 103 Catalan second semester morning-mixed
(PAUL) Classroom practices 104 Catalan second semester morning-mixed
(PLAB) Practical laboratories 104 Catalan/Spanish second semester morning-mixed
(SEM) Seminars 104 Catalan second semester morning-mixed
(PAUL) Classroom practices 105 Catalan second semester afternoon
(PLAB) Practical laboratories 105 Catalan/Spanish second semester morning-mixed
(SEM) Seminars 105 Catalan second semester morning-mixed
(PAUL) Classroom practices 106 Catalan second semester afternoon
(PLAB) Practical laboratories 106 Catalan second semester morning-mixed
(SEM) Seminars 106 Catalan second semester morning-mixed
(PLAB) Practical laboratories 107 Catalan second semester morning-mixed
(SEM) Seminars 107 Spanish second semester morning-mixed
(PLAB) Practical laboratories 108 Catalan second semester morning-mixed
(SEM) Seminars 108 Spanish second semester morning-mixed
(PLAB) Practical laboratories 109 Catalan/Spanish second semester afternoon
(SEM) Seminars 109 Catalan second semester afternoon
(PLAB) Practical laboratories 110 Catalan/Spanish second semester afternoon
(SEM) Seminars 110 Spanish second semester afternoon
(PLAB) Practical laboratories 111 Catalan/Spanish second semester afternoon
(SEM) Seminars 111 Catalan second semester afternoon
(PLAB) Practical laboratories 112 Catalan second semester afternoon
(SEM) Seminars 112 Catalan second semester afternoon