texto introducción a los métodos de investigación

# Métodos de investigación para Odontología

Los profesionales de la salud toman decisiones cruciales acerca de sus pacientes. Si bien podrían confiar en la intuición o experiencia, estas han mostrado ser poco precisas y reproducibles. Es aquí donde el método científico ofrece ventajas con respecto a otros tipos de conocimientos, disminuyendo la incerteza y aumentando la reproducibilidad de los resultados.

Además, un profesional de la salud no solo debe saber hacer, sino que debe saber porqué lo hace y que cabe esperar. Cómo se explica el estado de salud de un paciente y que podemos esperar en asuencia de tratamiento, o con alguno de los ttos disponibles son preguntas que la ciencia nos ayuda a responder.

Ver It's a claim! https://www.nature.com/articles/d41586-019-02407-9?utm_source=twt_nnc&utm_medium=social&utm_campaign=naturenews&sf217399180=1

## Introducción

### Science achieves results

• Science relies upon objective and measurable goals and outcomes
• Science requires results be replicated
• Science is self-regulating, promotes critical thinking, and encourages revision and improvements in understanding
• Science is a systematic approach

ver en https://www.winginstitute.org/evidence-based-education-science

### Science guards against flaws in other approaches:

People are susceptible to many influences that result in faulty decision-making. Most techniques that result in faulty decisions are well intentioned while other are employed deliberately.

People are susceptible to many influences that result in faulty decision-making. Most techniques that result in faulty decisions are well intentioned while other are employed deliberately.

• Mechanical or autonomic decision-making: Under particular circumstances, people tend to respond in similar patterns as they have in the past. Unfortunately, in many instances the unreasoned response results lead to making poor choices.
• Common Errors in Logical Thinking: Often arguments used in defense of an education intervention employ unsystematic and unintentional techniques that result in sloppy or unsound logical reasoning.
• Commonly Used Techniques Employed in Propaganda: Propaganda is a systematic and intentional set of persuasion techniques designed to manipulate people into adopting a position, ideology, or value.
• Identification of Pseudo-science: A pseudo-science is purported to be scientific or supported by science but fails to follow the scientific

## Estructura propuesta

1. Introducción a los métodos de investigación en ciencia médicas
2. Research means a systematic investigation, including research development, testing, and evaluation, designed to develop or contribute to generalized knowledge.
3. Razonamiento científico: lógica, falacias, sesgos
4. Ética en la investigación científica
5. Búsqueda de la información biomédica
6. Tecnologías de la información para la investigación médica
7. Diseño de estudios cuantitativos
8. Estudios observacionales de prevalencia
9. Estudios observacionales analíticos longitudinales
10. Estudios observacionales analíticos de corte transversal
11. Estudios clínicos experimentales
12. Estudios in-vitro, in-situ, animales
13. Estudios integrativos
14. El protocolo de investigación
15. Introducción al análisis de datos
16. Como recoger datos
17. Como validar un instrumento de medición
18. Como describir los datos
19. Como inferir información de los datos
20. Como dar a conocer los hallazgos
21. Presentaciones, posters y congresos
22. El manuscrito científico

## Estructura clase

1. Título clase
2. Objetivos
3. Conceptos claves
4. Contenidos
5. Lecturas obligatorias

“There is no other species on the Earth that does science. It is, so far, entirely a human invention, evolved by natural selection in the cerebral cortex for one simple reason: it works. It is not perfect. It can be misused. It is only a tool…..But it is by far the best tool we have, self-correcting, ongoing, applicable to everything.” - Carl Sagan

If you want to build a ship, don't drum up people to collect wood and don't assign them tasks and work, but rather teach them to long for the endless immensity of the sea. Antoine de Saint-Exupery

Ver A practical guide for health researchers

trasladar todo desde [https://metodos.jottit.com/] y ver en Equator

Recursos varios en [https://es.padlet.com/sergiouribe/metodos]

Introducción

Introducción a los métodos de investigación en odontología

Ética en investigación clínica y epidemiológica

Sesgos cognitivos en el proceso de la investigación

Hitos en el proceso de la investigación

Población y muestra

Diseño de estudios

• Estudios in vitro, in situ, animales
• Estudios observacionales
• Estudios clínicos
• Estudios integrativos
• Estudios diagnósticos
• Diseños cualitativos
• Evaluaciones económicas

¿Porqué investigar en Odontología

¿Dónde está la información para la práctica clínica

¿Cómo se genera la información en odontología

¿Cómo puedo utilizar esta información para mi práctica clínica

¿Que elementos debo considerar para el diseño y planificación de una investigación en odontología

¿Cómo puedo financiar mi investigación

¿Cómo se difunde la información científica en Odontología

Manejo de datos de investigación

## ¿Porqué investigar en Odontología? Porque el conocimiento científico es replicable

Sung et al. 2003;289:1278-1287

## Ciclo de la ciencia médica

Fuente: https://t.co/81qyGzm5tD

## Introducción al método científico

### Tipos de investigaciones Pure basic research Experimental and theoretical work undertaken to acquire new knowledge without looking for long term benefits other than the advancement of knowledge. Strategic basic research Experimental and theoretical work undertaken to acquire new knowledge directed into specified broad areas in the expectation of useful discoveries. It provides the broad base of knowledge necessary for the solution of recognised practical problems. Applied research Original work that has been undertaken primarily to acquire new knowledge with a specific application in view. It is undertaken either to determine possible uses for the findings of basic research or to determine new ways of achieving some specific and predetermined objectives. Experimental development Systematic work, using existing knowledge gained from research or practical experience for the purpose of creating new or improved products/processes.

https://www.cdu.edu.au/research/ori/rd-activity-types

### Sesgos Common Data Mistakes to Avoid | Geckoboard [WWW Document], s. f. URL https://www.geckoboard.com/learn/data-literacy/statistical-fallacies/ (accedido 2.20.19). https://paperpile.com/app/p/7664e426-9b6a-05d6-96b9-7e291b24e045 o ## Ética e investigación

Ética e investigación

## ¿Dónde está la información para la práctica clínica? Actualmente está en bases de datos disponibles para los profesionales y público en general. El desafío del profesional está en distinguir aquellas fuentes válidas y fiables del resto.

Tecnologías de la información para la investigación biomédica

## ¿Cómo se genera la información en odontología? De distintas maneras según la pregunta de estudio. Las preguntas relevantes clínicamente se responden mediante métodos y diseños clínicos-epidemiológicos que permiten evaluar el estado de salud de poblaciones, identificar factores de riesgo y evaluar la eficacia, efectividad y eficiencia de las intervenciones.

## Preguntas y diseños de investigación

● novel ● creative ● uncertain ● systematic ● transferable and/or reproducible.

OECD, 2015. The Measurement of Scientific, Technological and Innovation Activities Frascati Manual 2015 Guidelines for Collecting and Reporting Data on Research and Experimental Development: Guidelines for Collecting and Reporting Data on Research and Experimental Development. OECD Publishing.

### Observational study design measures of disease, measures of risk, and temporality

n ### ¿Quien está enfermo? ### ¿Porqué enferman las personas No se puede demostrar causalidad en medicina.

#### Resumen de medidas epidemiologicas

Ver an_overview_of_measurements_in_epidemiology.pdf

#### Criterios de Hill Decimos que un factor se puede considerar de riesgo o asociado a una enfermedad si cumple varios de estos criterios Hill, A.B., 1965. The enviroment and disease: association or causation? Proc. R. Soc. Med. 58, 295–300.

1. Fuerza de la asociación: estadística
2. Consistencia
3. Especificidad
4. TEMPORALIDAD: factor (est cohorte), vs indicador o marcador (est retrospectivos o transversales)
5. Gradiente biológico
6. Plausibilidad biológica
7. Coherencia
8. Analogia
9. Experimental

#### Causalidad Causas suficientes y necesarias

#### Modelos de causalidad ##### Triada Funciona bien para enfermedades infecciosas ##### Red de causalidad

##### Torta de causalidad Rothman Permite explicar enfermedades crónicas no transmisibles Permite identificar factores de riesgo común

#### Estudios observacionales

Etiological studies examine the association of exposures with diseases or health-related outcomes. Exposures potentially causing diseases are also called risk factors and may take many forms; they can be fixed states (e.g., sex, genetic factors) or vary over time, for example metabolic risk factors (e.g., hypercholesterolemia, insulin resistance, hypertension), lifestyle habits (e.g., smoking, diet), or environmental factors (e.g., air pollution, heat waves). Conceptually, these exposures differ from interventions, which explicitly aim to influence health outcomes and have a clear starting point in time [2]. Observational studies are important to study exposures that are difficult or impossible to study in randomised controlled trials (RCTs), such as air pollution or smoking. Also, observational studies are important to study causes with long latency time, such as carcinogenic effects of environmental exposures or drugs.

The epidemiological study of risk factors typically relies on comparisons (exposed versus unexposed); such comparisons can be made in cohort studies in which exposed and unexposed people are followed over time [3]. Other approaches such as self-controlled studies, case-control studies, cross-sectional studies, ecological studies, instrumental variable analyses, and mendelian randomisation also rely on comparisons. Box 1 presents an overview of observational study designs used to study etiology.

Box 1. Observational designs and approaches for studying etiology Cohort study

Cohort studies follow a study population over time. Researchers can study the occurrence of different outcomes. In etiological research, an exposed and an unexposed group are compared regarding the risk of the outcome. Different levels of exposure and exposures that vary over time can be studied. Instrumental variable methods and self-controlled case series studies are types of cohort studies (see below).

Example

In a large population-based cohort study, the occurrence of infectious complications was compared between patients with and patients without Cushing disease [4].

Instrumental variable methods/mendelian randomisation

Instrumental variable (IV) analyses use an external factor that determines the exposure of interest but is (ideally) not associated with the outcome other than through its effect on the exposure. In other words, the instrument is not associated with the factors that may confound the association between exposure and outcome. The instrument can be calendar time, geographical area, or treatment preferences [5,6]. Mendelian randomisation studies are examples of IV analyses using genetic factors as instruments.

Example

A Mendelian randomisation study investigated whether more years spent in education increase the risk of myopia or whether myopia leads to more years spent in education [7].

Self-controlled designs

In self-controlled case series, the occurrence of the outcome is compared between time windows during which individuals are exposed to a risk factor and time windows not exposed. In contrast to standard cohort designs, the comparison is within individuals. The design is used to study transient exposures for which exact timings are available, such as infections, vaccinations, drug treatments, climatic exposures, or disease exacerbations [8].

Example

A self-controlled study examined the effect of cold spells and heat waves on admissions for coronary heart disease, stroke, or heart failure in Catalonia [9].

Case-control study

In case-control studies, exposures are compared between people with the outcome of interest (cases) and people without (controls) [3]. The design is especially efficient for rare outcomes.

Example

A multicentre case-control study examined the association between mobile phone use and primary central nervous system tumours (gliomas and meningiomas) in adults [10].

Cross-sectional studies

In cross-sectional studies, study participants are assessed at the same point in time to examine the prevalence of exposures, risk factors, or disease. The prevalence of disease is then compared between exposure groups like in a cohort study, or the odds of exposure are compared between groups with and without disease, like in a case-control study [3]. The temporal relationship between exposure and outcome can often not be determined in cross-sectional studies.

Example

A cross-sectional analysis of the United Kingdom Biobank study examined whether neighbourhood exposure to fast-food outlets and physical activity facilities was associated with adiposity [11].

Ecological studies In ecological studies, the association between an exposure and an outcome is studied and compared between populations that differ geographically or in calendar time. Limitations include the ecological fallacy, in which associations observed at the aggregate level do not hold at the individual level and confounding, which is often difficult to control.

Example

An ecological study of male circumcision practices in different regions of sub-Saharan Africa and HIV infection found that HIV prevalence was lower in areas where male circumcision was practiced than in areas where it was not [12]. The protective effect of male circumcision was later confirmed in randomised trials [13].

Considering confounding and bias Confounding is a crucial threat to the validity of observational studies. Confounding occurs when comparison groups differ with respect to their risk of the outcome beyond the exposure(s) of interest due to a common cause of exposure and outcome.

Other threads to the validity of the effect estimation are measurement (misclassification) bias or selection bias. Misclassification is a crucial bias in environmental and occupational epidemiology, particularly for long-term exposures [26].

#### Ejemplo de análisis de un estudio de casos y controles OSWEGO http://rpubs.com/sergiouribe/510574

? ### ¿Cuál es la efectividad de las intervenciones

#### Preguntas que hay que hacerse antes de comenzar un estudio clínico en humanos:

• Are the patients to be included in a study sufficiently representative of the population for whom the medicine is intended?
• Are the planned measures to assess the benefits of a medicine valid and relevant?
• Is the proposed plan to analyse results appropriate?
• Does the study last long enough and include enough patients to provide the necessary data for the benefit-risk assessment?
• Is the medicine being compared with an appropriate alternative?
• Are the plans to follow the long-term safety of the product appropriately designed?

ver más en https://www.ema.europa.eu/en/human-regulatory/research-development/scientific-advice-protocol-assistance#types-of-questions-addressed-section

ver como hackear un RCT https://twitter.com/adamcifu/status/1092424281038954497?s=09

#### Tipos de estudios clinicos

• Clasificación por fase
• Clasificación por hipótesis

? ### Estudios que utilizan otros estudios: revisiones sistemáticas Systematic reviews, scoping reviews, umbrella reviews

Ver https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-018-0611-x

#### Systematic reviews Systematic reviews can be broadly defined as a type of research synthesis that are conducted by review groups with specialized skills, who set out to identify and retrieve international evidence that is relevant to a particular question or questions and to appraise and synthesize the results of this search to inform practice, policy and in some cases, further research [11, 12, 13]. According to the Cochrane handbook, a systematic review ‘uses explicit, systematic methods that are selected with a view to minimizing bias, thus providing more reliable findings from which conclusions can be drawn and decisions made.’ [14] Systematic reviews follow a structured and pre-defined process that requires rigorous methods to ensure that the results are both reliable and meaningful to end users. These reviews may be considered the pillar of evidence-based healthcare [15] and are widely used to inform the development of trustworthy clinical guidelines [11, 16, 17].

A systematic review may be undertaken to confirm or refute whether or not current practice is based on relevant evidence, to establish the quality of that evidence, and to address any uncertainty or variation in practice that may be occurring. Such variations in practice may be due to conflicting evidence and undertaking a systematic review should (hopefully) resolve such conflicts. Conducting a systematic review may also identify gaps, deficiencies, and trends in the current evidence and can help underpin and inform future research in the area. Systematic reviews can be used to produce statements to guide clinical decision-making, the delivery of care, as well as policy development [12].

Broadly, indications for systematic reviews are as follows [4]:

1. Uncover the international evidence
2. Confirm current practice/ address any variation/ identify new practices
3. Identify and inform areas for future research
4. Identify and investigate conflicting results
5. Produce statements to guide decision-making

#### Scoping reviews True to their name, scoping reviews are an ideal tool to determine the scope or coverage of a body of literature on a given topic and give clear indication of the volume of literature and studies available as well as an overview (broad or detailed) of its focus. Scoping reviews are useful for examining emerging evidence when it is still unclear what other, more specific questions can be posed and valuably addressed by a more precise systematic review [21]. They can report on the types of evidence that address and inform practice in the field and the way the research has been conducted.

The general purpose for conducting scoping reviews is to identify and map the available evidence [5, 22]. Arskey and O’Malley, authors of the seminal paper describing a framework for scoping reviews, provided four specific reasons why a scoping review may be conducted [5, 6, 7, 22]. Soon after, Levac, Colquhoun and O’Brien further clarified and extended this original framework [7]. These authors acknowledged that at the time, there was no universally recognized definition of scoping reviews nor a commonly acknowledged purpose or indication for conducting them. In 2015, a methodological working group of the JBI produced formal guidance for conducting scoping reviews [6]. However, we have not previously addressed and expanded upon the indications for scoping reviews. Below, we build upon previously described indications and suggest the following purposes for conducting a scoping review:

1. To identify the types of available evidence in a given field
2. To clarify key concepts/ definitions in the literature
3. To examine how research is conducted on a certain topic or field
4. To identify key characteristics or factors related to a concept
5. As a precursor to a systematic review
6. To identify and analyse knowledge gaps

## ¿Cómo puedo utilizar esta información para mi práctica clínica? La manera óptima es mediante un enfoque sistemático denominado Odontología basada en la Evidencia. Esto implica plantear una pregunta clínica, búsqueda, selección y análisis crítico de la evidencia, la aplicación de la evidencia y la evaluación de los resultados.

### La práctica basada en la evidencia

### La pregunta con formato clínico

### La búsqueda de la información

### La selección de la información

### El análisis crítico de la evidencia

#### ¿Es válida esta evidencia?

#### ¿Es importante esta evidencia válida?

## ¿Es aplicable esta evidencia válida e importante?

## ¿Que elementos debo considerar para el diseño y planificación de una investigación en odontología?

El diseño y planificación requieren de un documento que detalle el objetivo de la investigación, el diseño del estudio, de qué manera se recopilarán y analizarán los datos y estrategias de diseminación de los resultados. Asimismo, contiene información que permite evaluar la pertinencia ética de la investigación, los recursos en tiempo, dinero y personal necesarios y las fechas estimadas de cada una de las etapas. Toda esta información queda disponible en el protocolo de investigación.

### El diseño del estudio

ver pautas de Equator Network

### Good clinical practice

Good Clinical Practice = Ethics + Quality Data

Ver International Council for Harmonisation, s. f. Efficacy Guidelines : ICH [WWW Document]. International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). URL https://www.ich.org/products/guidelines/efficacy/article/efficacy-guidelines.html (accedido 9.10.19).

Ver https://www.fda.gov/media/77415/download

What are the foundations for the ethical conduct of clinical research? The Nuremberg Code (1947) - Voluntary participation - Informed Consent - Minimization of risk The Declaration of Helsinki (1964) - Well-being of subject takes precedence - Respect for persons - Protection of subjects health and rights - Special protection for vulnerable populations The Belmont Report (1979) - Respect for Persons - Informed consent - Protection of vulnerable populations - Beneficence - Non-malfeasance - Justice - Fairness International Conference on Harmonisation (ICH-GCP) International Standards Organization 14155 Code of Federal Regulations The Nuremberg Code (1947) The Declaration of Helsinki (1964) The Belmont Report (1979)

International Conference on Harmonisation (ICH-GCP) Ethics: 1. Ethical conduct of clinical trials 2. Benefits justify risks 3. Rights, safety, and well-being of subjects prevail z Protocol and science: 4. Nonclinical and clinical information supports the trial 5. Compliance with a scientifically sound, detailed protocol Responsibilities: 6. IRB/IEC approval prior to initiation 7. Medical care/decisions by qualified physician 8. Each individual is qualified (education, training, experience) to perform his/her tasks z Informed Consent: 9. Freely given from every subject prior to participation Data quality and integrity: 10. Accurate reporting, interpretation, and verification 11. Protects confidentiality of records z Investigational Products 12. Conform to GMP’s and used per protocol z Quality Control/Quality Assurance 13. Systems with procedures to ensure quality of every aspect of the trial

z International Standards Organization 14155 z Code of Federal Regulations

#### What constitutes Good Clinical Practice in device research?

z IRB-approved protocol z Valid Informed Consent z Monitoring Plan z Adverse Device Effect Reporting [Adverse Event (AE) or Serious Adverse Event (SAE)] z Proper documentation z Valid data collection/reporting procedures

### Factibilidad del protocolo de investigación

Population

+ Do you have access to the right patient population? + Will you need to recruit patients from external sources? If so, will sponsor provide funding? + Is the proposed enrollment goal realistic? + Is the proposed enrollment period realistic? + Will enrollment compete with other studies seeking the same patients? + Are inclusion/exclusion criteria overly restrictive? (Consider the likely screen failure ratio and the number of screen failures) + Do you expect a significant number of adverse events? (How ill is this population?)

2. Protocol

+ Is the protocol well designed? + Is the protocol ethical? Will the IRB have problems with it? + Is the study question important? + Will the subjects benefit from participating in the study? + Is the sponsor willing to consider suggestions or modifications if you do not think the protocol is feasible as written? (In case of sponsored study) + Can other services (e.g., lab, radiology) meet the protocol requirements? + Is necessary equipment available? + Are patient compliance problems likely? If so, will it be necessary to monitor subjects' compliance with time-consuming phone calls or postcards? + Are case report forms complex? + Are drug or device storage/accountability requirements complicated? + Will the drug be available for patients at the end of the study? (This can impact patient satisfaction.)

3. Procedures

+ Are procedures frequent? + Are procedures difficult, e.g., elderly patients asked to swallow pills? + Are procedures painful? + Is the dosing schedule complex? 4. Staff + Are qualified staff available? + If needed, is training available? + Does the PI have adequate time to devote to the protocol? + Are additional specialists needed? + Are study visits complex, presenting possible scheduling difficulties, e.g., how many different study staff will subjects encounter in a given visit?

5. Budgets

+ Does preliminary budget appear adequate?( Sponsors or investigator generated) + If the study is canceled prior to enrollment, will the sponsor pay for pre-study activities, e.g., IRB submission, meetings, chart reviews? + Will sponsor pay for an adequate number of screen failures (especially important for difficult protocols)? + Will the proposed payment schedule allow you to keep afloat, e.g., adequate up-front payment; payments paced according to work required by protocol? + Any other protocol required equipments or procedure etc

6. Other

+ Is adequate space available? + Will electronic or remote data retrieval systems be used? If so, will sponsor provide training? + Does the sponsor/PI expect this study to be audited by the + regulatory bodies?

7. Results

+ son los resultados relevantes en caso de cualquier resultado, positivo o negativo?

### La pregunta de investigación: el paso crucial de toda investigación

Ver en http://www.erm.ecs.soton.ac.uk/theme4/aims_and_objectives.html https://eclass.uoa.gr/modules/document/file.php/NURS239/%CE%A0%CE%95%CE%A4%CE%A1%CE%9F%CE%A3%20%CE%93%CE%91%CE%9B%CE%91%CE%9D%CE%97%CE%A3/%CE%91%CE%A1%CE%98%CE%A1%CE%91/research.pdf https://www.dummies.com/education/science/biology/identifying-aims-objectives-hypotheses-and-variables-for-a-clinical-study/ http://www.biosciencewriters.com/NIH-Grant-Applications-The-Anatomy-of-a-Specific-Aims-Page.aspx

#### Buena pregunta de investigación

• F
• I
• N
• E
• R

### Hipótesis y objetivos

#### Hipotesis A hypothesis is a statement, not a question. … The hypothesis is an educated, testable prediction about what will happen. “If _[I do this] _, then _[this]_ will happen.”

Ver en https://www.sciencedirect.com/science/article/pii/S0306987704005638?via%3Dihub

#### Objetivos Primario y secundarios Primario: que se va hacer Secundario como se va hacer, cuáles son los hitos

1. Specific
2. Measurable
3. Achievable
4. Realistic
5. Time-related

Como escribir los objectives, descargar artículo aquí llc_-_aims_template_r_locke_v111117.docx Como escribir los objetivos, segunda versión llc_-_specific-aims-help-sheet.doc

### Estudios piloto Fuente: Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L., Robson, R., Thabane, M., Giangregorio, L., Goldsmith, C., 2010. A tutorial on pilot studies: the what, why and how. BMC Med. Res. Methodol. 10.

Más información Moore, C.G., Carter, R.E., Nietert, P.J., Stewart, P.W., 2011. Recommendations for planning pilot studies in clinical and translational research. Clin. Transl. Sci. 4, 332–337.

Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L., Robson, R., Thabane, M., Giangregorio, L., Goldsmith, C., 2010. A tutorial on pilot studies: the what, why and how. BMC Med. Res. Methodol. 10.

## Detalle protocolo de investigación Protocolo de investigación

### El protocolo de investigación

#### Elementos esenciales

Ver en http://biostat.mc.vanderbilt.edu/wiki/Main/BiostatGrants

##### Specific Aims

Always required One page is recommended

##### Research Strategy

###### a. Significance

1. Explain the importance of the problem or critical barrier to progress in the field that the proposal addresses
2. Explain how the proposed project will improve scientific knowledge, technical capability, and/or clinical practice in one or more braod fields
3. Describe how the concepts, methods, technologies…that drive this field will be changed if the proposal aims are achieved

###### b. Innovation

1. Explain how the application challenges and seeks to shift current reserach or clinical practice paradigms
2. Describe any novel theoretical concepts, approaches or methodologies…, and any advanage over existing methodologies…
3. Explain any refinements, improvements or new application of theoretical concepts, approaches or methodologies…

###### c. Approach

1. Describe the overall strategy, methodology, and analyses to be used to accomplish the specific aims of the project
2. Discuss potential problems, alternative strategies, and benchmarks for success anticipated to achieve the aims

#### Timeline Gantt Chart study_task_timeline_template_1.xlsx

## ¿Dónde medir? Población y muestra

Población y Muestra

## Antes de comenzar: consideraciones acerca de buenas prácticas de investigación https://kkulma.github.io/2018-03-18-Prime-Hints-for-Running-a-data-project-in-R/

https://library.stanford.edu/research/data-management-services/data-best-practices

https://peerj.com/preprints/3183/

### Criterios de autoria https://geocognitionresearchlaboratory.com/research-in-the-grl/authorship-agreements-training-students/

### Buenas prácticas para el manejo de datos

Data in spreadsheets Broman, K.W., Woo, K.H., 2017. Data organization in spreadsheets (No. e3183v1). PeerJ Preprints. doi:10.7287/peerj.preprints.3183v1

Ellis, S.E., Leek, J.T., 2017. How to share data for collaboration (No. e3139v5). PeerJ Preprints.

Data analysis pipeline Huebner, M., Vach, W., le Cessie, S., 2016. A systematic approach to initial data analysis is good research practice. J. Thorac. Cardiovasc. Surg. 151, 25–27.

## ¿Cómo recoger datos? Escalas de medición, cuestionarios, escalas, validación

### Psychometric properties definitions in the field of health-related assessment de https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4275948/

Properties Definitions

1. Content validity The ability of an instrument to reflect the domain of interest and the conceptual definition of a construct. In order to claim content validity, there is no formal statistical testing, but item generation process should include a review of published data and literature, interviews from targeted patients and an expert panel to approach item relevance [2].
2. Face validity The ability of an instrument to be understandable and relevant for the targeted population. It concerns the critical review of an instrument after it has been constructed and generally includes a pilot testing [2].
3. Construct validity The ability of an instrument to measure the construct that it was designed to measure. A hypothetical model has to be formed, the constructs to be assessed have to be described and their relationships have to be postulated. If the results confirm prior expectations about the constructs, the instrument may be valid [2].
4. Convergent validity Involves that items of a subscale correlate higher than a threshold with each other, or with the total sum-score of their own subscale [2].
5. Divergent validity Involves that items within any one subscale should not correlate too highly with external items or with the total sum-score of another subscale [2].
6. Known group validity The ability of an instrument to be sensitive to differences between groups of patients that may be anticipated to score differently in the predicted direction [2].
7. Criterion validity The assessment of an instrument against the true value, or a standard accepted as the true value. It can be divided into concurrent validity and predictive validity [2].
8. Concurrent validity The association of an instrument with accepted standards [2].
9. Predictive validity The ability of an instrument to predict future health status or test results. Future health status is considered as a better indicator than the true value or a standard [2].
10. Reliability Determining that a measurement yields reproducible and consistent results [2].
11. Internal consistency The ability of an instrument to have interrelated items [2].
12. Repeatability (Test-retest reliability) The ability of the scores of an instrument to be reproducible if it is used on the same patient while the patient’s condition has not changed (measurements repeated over time) [2]. Measurement error is the systematic and random error of a patient’s score that is not attributed to true changes in the construct to be measured [17].
13. Responsiveness The ability of an instrument to detect change when a patient’s health status improves or deteriorates [2].

## ¿Cómo medir? Medición y tabulación de datos

Tabulación de datos

ver https://www.camscanner.com/share/7nNnz/0/w105s11iqbodi

### Cuestionarios

## Origen de los datos: real world data Nabhan, C., Klink, A., Prasad, V., 2019. Real-world Evidence—What Does It Really Mean? JAMA Oncol. doi:10.1001/jamaoncol.2019.0450

## ¿Cómo analizar los datos? Análisis estadístico Ver en OSF

Reporte en Lederer et al., 2019. Control of Confounding and Reporting of Results in Causal Inference Studies. Guidance for Authors from Editors of Respiratory, Sleep, and Critical Care Journals. Ann. Am. Thorac. Soc. 16, 22–28. https://paperpile.com/app/p/55287432-b796-0b7c-b09d-56b81abc0f85

### Buenas prácticas para la planilla de datos

1. Separa el ingreso de datos de la planilla de datos
2. Nombra los archivos con nombres significativos, sin utilizar espacios, signos de puntuación o caracteres especiales. Buenos nombres son “analisis_datos_riesgo_caries.R”
3. Manten un solo archivo utilizando un sistema de control de versiones. Esto se puede lograr en una carpeta de Dropbox y copiando encima el archivo o con una plataforma para datos de investigación como osf.io
4. utiliza nombres que permitan su orden. Esto se logra con la fecha en formato AAAA-MM-DD-nombre_del_archivo.csv, por ejemplo “2018-02-18-datos_clinicos_panguipulli.csv”. No utilizar “archivo_final.csv” ni nada por el estilo.
5. Organiza en carpetas siguiendo una lógica, por ejemplo carpeta datos, carpeta resultados, carpeta material_accesorio, etc
6. utiliza un directorio para todo el proceso
7. dentro de la carpeta utiliza siempre nombres significativos, evitando nombres como “datos.csv” o “manuscrito.odt” pues corres el riesgo que en 10 años más cuando busques los archivos tengas lleno de archivos “investgacion.odt”
8. utiliza formatos abiertos, como csv, odt, txt, etc. Evita utilizar doc, docx, etc y cualquiera propietario. Hace años atrás la principal planilla era Visicalc con formato .vcs, que ahora no se puede leer. Hazle un favor al tu futuro.
9. Separa los datos originales de los derivados.
10. Guarda los datos originales como solo lectura.
11. Separa el código de los datos
12. Separa los resultados del código
13. Manten un diccionario con información

#### Buenas prácticas con excel / calc

### Recomendaciones para el análisis de datos

De http://www.nature.com/srep/publish/guidelines#statistical-guidelines

Every article that contains statistical testing should state the name of the statistical test, the n value for each statistical analysis, the comparisons of interest, a justification for the use of that test (including, for example, a discussion of the normality of the data when the test is appropriate only for normal data), the alpha level for all tests, whether the tests were one-tailed or two-tailed, and the actual P value for each test (not merely “significant” or “P < 0.05”). It should be clear what statistical test was used to generate every P value. Use of the word “significant” should always be accompanied by a P value; otherwise, use “substantial,” “considerable,” etc.

Data sets should be summarized with descriptive statistics, which should include the n value for each data set, a clearly labelled measure of centre (such as the mean or the median), and a clearly labelled measure of variability (such as standard deviation or range). Ranges are more appropriate than standard deviations or standard errors for small data sets. Graphs should include clearly labelled error bars. Authors must state whether a number that follows the ± sign is a standard error (s.e.m.) or a standard deviation (s.d.).

Authors must justify the use of a particular test and explain whether their data conform to the assumptions of the tests. Three errors are particularly common:

1. Multiple comparisons: When making multiple statistical comparisons on a single data set, authors should explain how they adjusted the alpha level to avoid an inflated Type I error rate, or they should select statistical tests appropriate for multiple groups (such as ANOVA rather than a series of t-tests).
2. Normal distribution: Many statistical tests require that the data be approximately normally distributed; when using these tests, authors should explain how they tested their data for normality. If the data do not meet the assumptions of the test, then a non-parametric alternative should be used instead.
3. Small sample size: When the sample size is small (less than about 10), authors should use tests appropriate to small samples or justify their use of large-sample tests.

### Statistical checklist

METHODS

1. Reported n at start of study and for each analysis
2. Provided sample size calculation or justification
3. Identified all statistical methods unambiguously
4. If statistical methods were described adequately, were any of them clearly inappropriate?
5. Provided alpha for all statistical tests
6. Specified whether tests were one-sided or two-sided
7. Stated whether the data met the assumptions of the test
8. Reported actual P values for primary analyses
9. Were the statistical measures (mean, standard error, standard deviation, etc.) reported, and were they clearly labeled?
10. Was the unit of analysis clearly stated in all comparisons?
11. Are mean and standard deviation used to describe data sets that may be non-normally distributed or when the sample size is very small?
12. Explanation of unusual or complex statistical methods
13. Explanation of data exclusions, if any
14. Explained reasons for any discrepancy between initial n and n for each analysis
15. Explained method of treatment assignment (randomization, if any)
16. Explained any data transformation
17. Discussed adjustments for multiple testing

For graphs

1. Were effect sizes distorted? (by truncation of y axis, etc.)
2. Were error bars unlabeled?
3. Were error bars absent?

### Manejo de datos Tradicional Moderno ## ¿Cómo se difunde la información científica en Odontología?

La difusión de los resultados de las investigaciones es tan importante como su generación. En la actualidad existen muchas maneras de difundir los hallazgos científicos, comenzando con la autodifusión en redes sociales, la presentación de los resultados en congresos científicos y la publicación de los resultados en revistas indizadas revisadas por pares. ### Redes sociales e investigación ### Presentaciones en congresos y conferencia

#### Presentaciones orales

#### Como hacer buenas diapositivas https://speakerdeck.com/mseckington/the-art-of-slide-design s ### El artículo científico

frases para articulo cientifico

Buscar MESH en https://meshb.nlm.nih.gov/MeSHonDemand

¿Cómo escribir de manera concisa y precisa? Es lo que oyes en tu cabeza, pero nunca es correcto a la primera. (Stephen King)

[Writing tips](https://grants.nih.gov/grants/how-to-apply-application-guide/format-and-write/write-your-application.htm#Important%20Writing%20Tips)

'Si quieres ser escritor, debes hacer dos cosa más que nadie: leer mucho y escribir mucho' (Stephen King)

'Escribe con la puerta cerrada y re-escribe con la puerta abierta' (Stephen King)

### Como escribir un articulo cientifico

[Como escribir un artículo científico](http://www.cienciaodontologica.com/search/label/escritura%20cientifica)

[Cómo escribir un artículo científico 2](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4260692/?report=reader)

[Reporte de resultados de test estadístico](https://www.amherst.edu/academiclife/departments/psychology/resources/SPSS/reportstats)

[Reviewer letter samples](http://www.calpoly.edu/~eli/iceb/SampleLetters.htm)

Razones del rechazo de un artículo científico

#### Consejos para escribir

#### ¿Quién o quiénes son los autores? https://ori.hhs.gov/education/products/niu_authorship/index.htm?platform=hootsuite

Ejemplos de autorías en https://www.epj.org/images/stories/faq/examples-of-author-contributions.pdf

#### Diferencias entre tesis y artículo

#### Preparación de figuras para un artículo científico

preparación de figuras para un artículo científico

#### Final list of informative statements to communicate results of systematic reviews Santesso, N., Glenton, C., Dahm, P., Garner, P., Akl, E., Alper, B., Brignardello-Petersen, R., Carrasco-Labra, A., De Beer, H., Hultcrantz, M., Kuijpers, T., Meerpohl, J., Morgan, R., Mustafa, R., Skoetz, N., Sultan, S., Wiysonge, C., Guyatt, G., Schünemann, H.J., GRADE Working Group, 2019. GRADE guidelines 26: Informative statements to communicate the findings of systematic reviews of interventions. J. Clin. Epidemiol. doi:10.1016/j.jclinepi.2019.10.014

### Recomendaciones para escribir un buen artículo científico

Keep your message clear Think about the message you want to give to readers. If that is not clear, misinterpretations may arise later.

Create a logical framework It’s crucial to focus your paper on a single key message, which you communicate in the title. Everything in the paper should logically and structurally support that idea. It can be a delight to creatively bend the rules, but you need to know them first. You have to guide the naive reader to the point at which they are ready to absorb what you did. As a writer, you need to detail the problem. I won’t know why I should care about your experiment until you tell me why I should.

State your case with confidence Clarity is the sole obligation of the science writer, yet I find constantly that the ‘What’s new’ element is buried. Answering one central question — What did you do? — is the key to finding the structure of a piece. Every section of the manuscript needs to support that one fundamental idea. There is a German concept known as the ‘red thread’, which is the straight line that the audience follows from the introduction to the conclusion. In science, ‘What’s new and compelling?’ is the red thread. It’s the whole reason for writing the paper. Then, once that’s established, the paragraphs that follow become the units of logic that comprise the red thread.

Beware the curse of ‘zombie nouns’ Always think of your busy, tired reader when you write your paper — and try to deliver a paper that you would enjoy reading yourself.

Prune that purple prose Writers must be careful about ‘creativity’. It sounds good, but the purpose of a scientific paper is to convey information. That’s it. Flourishes can be distracting. Figurative language can also bamboozle a non-native English speaker. My advice is to make the writing only as complex as it needs to be.

Aim for a wide audience articles with clear, succinct, declarative titles are more likely to get picked up by social media or the popular press. Make your point clearly and concisely — if possible in non-specialist language, so that readers from other fields can quickly make sense of it.

Gewin, V., 2018. How to write a first-class paper. Nature 555, 129–130.

#### Tips para escribir un manuscrito científico

Delete connectives

This is another tip that will reduce the flow of the text but is effective in reducing word count. Rather than having longer sentences linked with “and” or “but”, just delete those connectives and have two separate sentences. This will reduce the word count.

Delete adverbs

Adverbs are usually very deletable in academic writing. At the very least, adverb-verb pairs can be converted into a better chosen verb on its own. For example, “dropped rapidly” could be replaced with “plummeted”.

Delete any auxiliary verbs from results

“could”, “may”, “might” and so on.

Tip: using ctrl + f to search through your document for “ly” is a quick way to find a lot of adverbs.

### Reporte de contribuciones al artículo Author Contributions

• Development of protocol:
• Laboratory investigations / Data recollection:
• Analysis and interpretation of data:
• Manuscript:

Ver detalle en http://www.pnas.org/content/115/11/2557

La siguiente es la lista de [Science](http://www.sciencemag.org/authors/science-journals-editorial-policies)

• Each author is expected to have made substantial contributions to the conception or design of the work;
• OR the acquisition, analysis, or interpretation of data;
• OR creation of new software used in the work;
• OR have drafted the work or substantially revised it;
• AND has approved the submitted version (and any substantially modified version that involves the author’s contribution to the study;
• AND agrees to be personally accountable for the author’s own contributions and for ensuring that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and documented in the literature.

Exclusion from authorship of individuals who have made author-level contributions is not permitted for papers published in Science Journals. Nor is guest or honorary authorship. Other individuals who have participated in generation of the research paper but who do not meet the criteria for authorship should be listed in the acknowledgments section with a brief indication of the nature of their contribution.

In addition, corresponding authors must:

• Ensure that all listed authors have received and approved the manuscript prior to submission.
• Receive all substantive correspondence with editors as well as full reviews.
• Verify that all data, materials (including reagents), and code, even those developed/provided by other authors, comply with the transparency and reproducibility standards of both the field and the journal.
• Ensure that original data/materials/code upon which the submission is based are preserved and retrievable for reanalysis.
• Confirm that the presentation in the paper of the data/materials/code accurately reflects the original sources.
• Foresee and minimize obstacles to the sharing of data/materials/code.
• Ensure the entire author group is fully aware of and in compliance with best practices.
• Be responsible for signing off on galleys and ensuring all authors complete the COI declaration and license forms.

## Glosario

Glosario de términos ## Iniciando una vida dedicada a la investigación

En caso que quieras proseguir estudios superiores como un Master o un Doctorado, entonces esta información te puede ser de utilidad

Writing a Research Statement

## Referencias Fathalla, M.F., Fathalla, M.M.F., World Health Organization, Regional Office for the Eastern Mediterranean, 2004. A practical guide for health researchers. World Health Organization, Regional Office for the Eastern Mediterranean, Cairo.

# Curso Quinto

## Clases

1. Introducción a los métodos de investigación en Odontología
2. Principios éticos de la investigación médica
3. Estructura general e hitos del proceso de investigación
4. Población y muestra
5. Preguntas y diseños de investigaciones
6. Búsqueda de la información biomédica
7. Estudios observacionales
8. Estudios analíticos
9. Estudios clinicos controlados
10. Revisiones sistemáticas
11. Otros estudios
12. El protocolo de investigación
13. El manuscrito de investigación
14. Diseminación de los resultados de una investigación
15. Recursos para investigación