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Protocol
In research, protocol refers to the written procedures or guidelines that provide the blueprint for the research study, as well as good and ethical practices that should be observed when conducting research, such as good etiquette when dealing with participants, adherence to ethical principles and guidelines to protect participants, compliance with institutional review board requirements, not engaging in academic dishonesty, and so on. Good protocol is a critical component of high-quality research. A well-written research protocol is particularly important for obtaining institutional review board clearance for the research, as well as for seeking funding opportunities. In addition, the written research protocol serves as a manual to guide the entire research effort, and it can also be used as a monitoring and evaluation tool to monitor progress throughout the research and to evaluate success at the completion of the research. This entry describes the structure of the written proposal and discusses other types of protocols.
Structure of the Written Research Protocol
The written research protocol is a detailed descriptive text of how the research will be conducted, and its length and complexity are affected by the nature and scope of the research. The principal investigator generally has some flexibility in determining the comprehensiveness and layout of a particular protocol; however, each research protocol must comply with the requirements (i.e., structure, context, format, length, etc.) for the institutional review board that will grant its approval. A well-written research protocol can contribute greatly to making a research effort high quality. Comprehensive information provides not only guidance and clarity on how to conduct each and every aspect of the research, but also advice on what should be done (e.g., whom to contact) if an unusual situation occurs that was unforeseen. The aforementioned structure and details are fundamental to good research protocols.
Cover Page and Title
The cover page should include the full title of the study, as well as the version number, and version date (e.g., Version 1.0 dated May 1, 2010). The document should also indicate if the protocol is a “draft” or “final” document (e.g., Draft Protocol). The title should be short and concise, and also include key words such as the proposed research design, population to be investigated, and location of data collection. For example, a study on juvenile delinquency might be titled “Study of Juvenile Delinquency in Country A Using Convenience Sampling.” These key words are important to facilitate classification/indexing of the project. A short title should also be specified for use throughout the document. The short title should be first abbreviated in the project summary. The cover page should also include the names, roles, and contact information for the primary authors/investigators/advisors, as well as any major sponsors. If this information is too much to place on the cover page, it should be placed on a separate page after the cover page.
Signature Page
This page should include the signatures of the individuals listed on the cover page.
Contents Page
This page details the various sections and appendixes contained in the protocol, along with corresponding page numbers.
Acronym/Abbreviation Page
This page provides a list of all acronyms and/or abbreviations used in the protocol, along with a definition for each one.
Summary or Abstract
The summary is the most important section of most documents/reports—the research protocol is no exception. It provides a succinct sketch (i.e., a snapshot) of the entire protocol. It is located at the front of the document but is generally prepared after the entire protocol is written. It summarizes the research objectives; presents the main research question or hypothesis; provides a brief description of the methods and procedures that will be used to conduct the research (e.g., research design, study population, place, timing of interventions); discusses the anticipated study outcomes; and provides the dates for important milestones as well as the estimated time frame and budgeted cost for the research.
Background
The background describes existing knowledge and research in the area of study. It is supported by a comprehensive literature review of both published and unpublished work that should highlight any deficiencies or gaps in existing knowledge. The justification for the study, as well as a clear articulation of the research questions or hypotheses, and a detailed discussion of the study objectives (general and specific) are also generally included in this section. Some protocols, however, may use separate sections to discuss one or more of the aforementioned issues. For example, objectives may be discussed under a section titled “Specific Aims of the Study,” research questions may be discussed under “Problem Statement,” and so on. Alternatively, some protocols use a section called “Introduction” instead of “Background.”
The justification should clearly outline the nature of the problem, its size, and its effect; the raison d'ětre for the study; the feasibility of the study; the potential benefits or outcomes that are expected to be derived from the study (categorized into participant, short-term/long-term, population, knowledge base, etc.); how the results might be used (e.g., national policy, organizational policy, community level, future research); how the study might help to correct the deficiency; how the study will add to the existing body of knowledge, and so on. The objectives should follow from the research questions or hypotheses—they should be smart, measurable, achievable, relevant, and time based (SMART).
Methodology
The methodology provides a detailed description of the methods and procedures that will be used to conduct the study. It includes a description of the following, but may not necessarily be discussed under the separate subheads outlined below.
- Study Design. This subsection describes the proposed study design (e.g., experimental, cohort, case-control) and provides justification for the choice. The selection of a particular study design is linked to the particular study objectives, as well as ethical considerations and availability of resources. Where an intervention is part of the research design, the protocol must discuss the intervention and note the following: frequency and intensity of intervention, venue, and entity or person in charge of the intervention.
- Sample Size, Selection, and Location. The protocol should provide details on the sample size and the justification for the sample size (including chosen levels of significance and power), explain how the sample was selected (e.g., probability—random selection or nonprobability—nonrandom selection), explain how the locations and sites were selected, provide a clear listing of the inclusion and exclusion criteria for participant selection, and so on. Where informants and/or focus groups are being used, the selection criteria, number of persons participating, and so on will also need to be discussed.
- Unit of Analysis. The unit of analysis—individual or group—must be discussed.
- Sampling Frame. The protocol should discuss and justify the sampling frame selected for the study.
- Operationalization of the Variables. All variables being investigated should be defined and operationalized.
- Measurement of Variables. The protocol should specify how the variables will be measured.
- Incentives for Participation. Any incentives that are being offered for participation, as well as the time and mode of delivery, should be outlined clearly.
- Data Collection Procedures. Both primary and secondary data collection procedures (e.g., surveys—face-to-face/telephone/mail, focus groups, nonparticipant observation, content analysis) must be outlined and justified. In the case of secondary data sources, the source, content, and quality will also need to be discussed. Instruments being used, including interview guides, registration forms, and so on, must be appended to the protocol.
- Quality Control Procedures. The protocol should clearly outline the strategies that will be used to safeguard data integrity, and thus by extension enhance overall (a) reliability (e.g., to ensure high interrater reliability, raters will be properly trained and monitored, and a code manual will be prepared to ensure that the coding process is consistent); (b) validity (e.g., face and content validity will be established by having an expert panel review the instrument); and (c) data quality (e.g., all interviewers will receive 12 hours of training that will include several demonstration exercises, the interview guide and the questionnaire will be discussed in-depth, and a pilot study will be conducted). The discussion on quality control may be incorporated under specific subheads.
- Data Management. The procedures for data storage and data security should be discussed. This discussion should identify where the data will be stored or located, as well as the duration of retention (e.g., federal regulations in the United States require data retention for at least 3 years), who will have access to the data, the level of access, and so on. The procedures for data collection, coding, and validation should also be discussed.
- Project Management. The procedures for managing the study should be outlined. Issues to be discussed will include staff requirements, staff training, supervision of personnel, responsibility matrix, the project schedule and work breakdown structure (generally prepared using Microsoft Project), and the project budget. If only an overview is provided of the project schedule and budget, then the detailed schedule and budget should be appended to the report.
- Data Analysis. The software packages that will be used for data analysis should be described, as well as the types of analyses that will be performed (e.g., statistical, nonstatistical, analytical). In addition, other issues such as the handling of missing data, outliers, and so on should be discussed.
- Ethical Issues. Ethical issues are central to research protocol. Any potential risks (e.g., physical, psychological, social, economic) to participants should be fully discussed. Measures to protect participants from possible risks or discomforts should also be fully disclosed. The manner in which informed consent is to be obtained should also be addressed. For example, in research involving certain groups (children, mentally challenged, elderly), informed consent must be obtained from a third party. In such cases, the protocol must explain how the third party will be contacted, and so on. Participants' rights to withdraw any time without risk of prejudice, penalty, or otherwise, as well as their rights to refuse to answer particular questions, should also be outlined clearly. The protocol should also outline who will provide debriefing and indemnity if participants are harmed through negligence or otherwise while participating in the study.
- Anonymity and Confidentiality. Procedures for keeping the data anonymous and confidential should be outlined, as well as the procedure that will be used to assure participants that this will be done (e.g., official letter backed up by verbal assurance stating that all data will be aggregated and no individual-level data will be revealed). This is particularly important when sensitive data are involved. This discussion should be linked to data management. The data coding procedures for participant identification should also be discussed.
Limitations of the Study
The limitations of the study should be clearly outlined so that the users of the information can make informed judgments in light of the limitations.
Dissemination or Publication of Results
This section should discuss the stakeholder groups that will have access to the research findings and how the results will be communicated (e.g., written report, presentation, town hall meeting, journal article, news media). It should also discuss who will have publication rights.
References
A list of all references quoted in the preparation of the protocol should be listed in sequential order.
Appendixes
Research instruments, consent and assent forms, letter to participants assuring anonymity and confidentiality, interview guides, detailed schedules and budgets, and so on, should be appended to the protocol. The curriculum vitae of each principal and secondary investigator should also be appended. If advertising is done in order to recruit participants, all recruitment materials, such as press releases and radio, television, and newspaper advertisements, should also be appended to the protocol that is being submitted for institutional review board approval.
Other Types of Protocol
In addition to the written protocol that is important for institutional review board purposes, written protocols for interview guides and schedules may also be prepared to guide the research effort in its quest for high-quality data. In addition, other types of protocol, such as appropriate behavior when dealing with participants (e.g., greeting, listening attentively to participants, keeping an appropriate distance from the participants, etc.) and dress protocol, are usually discussed in training sessions.
Further Readings
- Descriptive Statistics
- Distributions
- Graphical Displays of Data
- Hypothesis Testing
- p Value
- Alternative Hypotheses
- Beta
- Critical Value
- Decision Rule
- Hypothesis
- Nondirectional Hypotheses
- Nonsignificance
- Null Hypothesis
- One-Tailed Test
- Power
- Power Analysis
- Significance Level, Concept of
- Significance Level, Interpretation and Construction
- Significance, Statistical
- Two-Tailed Test
- Type I Error
- Type II Error
- Type III Error
- Important Publications
- “Coefficient Alpha and the Internal Structure of Tests”
- “Convergent and Discriminant Validation by the Multitrait–Multimethod Matrix”
- “Meta-Analysis of Psychotherapy Outcome Studies”
- “On the Theory of Scales of Measurement”
- “Probable Error of a Mean, The”
- “Psychometric Experiments”
- “Sequential Tests of Statistical Hypotheses”
- “Technique for the Measurement of Attitudes, A”
- “Validity”
- Aptitudes and Instructional Methods
- Doctrine of Chances, The
- Logic of Scientific Discovery, The
- Nonparametric Statistics for the Behavioral Sciences
- Probabilistic Models for Some Intelligence and Attainment Tests
- Statistical Power Analysis for the Behavioral Sciences
- Teoria Statistica Delle Classi e Calcolo Delle Probabilità
- Inferential Statistics
- Q-Statistic
- R2
- Association, Measures of
- Coefficient of Concordance
- Coefficient of Variation
- Coefficients of Correlation, Alienation, and Determination
- Confidence Intervals
- Margin of Error
- Nonparametric Statistics
- Odds Ratio
- Parameters
- Parametric Statistics
- Partial Correlation
- Pearson Product-Moment Correlation Coefficient
- Polychoric Correlation Coefficient
- Randomization Tests
- Regression Coefficient
- Semipartial Correlation Coefficient
- Spearman Rank Order Correlation
- Standard Error of Estimate
- Standard Error of the Mean
- Student's t Test
- Unbiased Estimator
- Weights
- Item Response Theory
- Mathematical Concepts
- Measurement Concepts
- Organizations
- Publishing
- Qualitative Research
- Reliability of Scores
- Research Design Concepts
- Aptitude-Treatment Interaction
- Cause and Effect
- Concomitant Variable
- Confounding
- Control Group
- Interaction
- Internet-Based Research Method
- Intervention
- Matching
- Natural Experiments
- Network Analysis
- Placebo
- Replication
- Research
- Research Design Principles
- Treatment(s)
- Triangulation
- Unit of Analysis
- Yoked Control Procedure
- Research Designs
- A Priori Monte Carlo Simulation
- Action Research
- Adaptive Designs in Clinical Trials
- Applied Research
- Behavior Analysis Design
- Block Design
- Case-Only Design
- Causal-Comparative Design
- Cohort Design
- Completely Randomized Design
- Crossover Design
- Cross-Sectional Design
- Double-Blind Procedure
- Ex Post Facto Study
- Experimental Design
- Factorial Design
- Field Study
- Group-Sequential Designs in Clinical Trials
- Laboratory Experiments
- Latin Square Design
- Longitudinal Design
- Meta-Analysis
- Mixed Methods Design
- Mixed Model Design
- Monte Carlo Simulation
- Nested Factor Design
- Nonexperimental Design
- Observational Research
- Panel Design
- Partially Randomized Preference Trial Design
- Pilot Study
- Pragmatic Study
- Pre-Experimental Designs
- Pretest–Posttest Design
- Prospective Study
- Quantitative Research
- Quasi-Experimental Design
- Randomized Block Design
- Repeated Measures Design
- Response Surface Design
- Retrospective Study
- Sequential Design
- Single-Blind Study
- Single-Subject Design
- Split-Plot Factorial Design
- Thought Experiments
- Time Studies
- Time-Lag Study
- Time-Series Study
- Triple-Blind Study
- True Experimental Design
- Wennberg Design
- Within-Subjects Design
- Zelen's Randomized Consent Design
- Research Ethics
- Research Process
- Clinical Significance
- Clinical Trial
- Cross-Validation
- Data Cleaning
- Delphi Technique
- Evidence-Based Decision Making
- Exploratory Data Analysis
- Follow-Up
- Inference: Deductive and Inductive
- Last Observation Carried Forward
- Planning Research
- Primary Data Source
- Protocol
- Q Methodology
- Research Hypothesis
- Research Question
- Scientific Method
- Secondary Data Source
- Standardization
- Statistical Control
- Type III Error
- Wave
- Research Validity Issues
- Bias
- Critical Thinking
- Ecological Validity
- Experimenter Expectancy Effect
- External Validity
- File Drawer Problem
- Hawthorne Effect
- Heisenberg Effect
- Internal Validity
- John Henry Effect
- Mortality
- Multiple Treatment Interference
- Multivalued Treatment Effects
- Nonclassical Experimenter Effects
- Order Effects
- Placebo Effect
- Pretest Sensitization
- Random Assignment
- Reactive Arrangements
- Regression to the Mean
- Selection
- Sequence Effects
- Threats to Validity
- Validity of Research Conclusions
- Volunteer Bias
- White Noise
- Sampling
- Cluster Sampling
- Convenience Sampling
- Demographics
- Error
- Exclusion Criteria
- Experience Sampling Method
- Nonprobability Sampling
- Population
- Probability Sampling
- Proportional Sampling
- Quota Sampling
- Random Sampling
- Random Selection
- Sample
- Sample Size
- Sample Size Planning
- Sampling
- Sampling and Retention of Underrepresented Groups
- Sampling Error
- Stratified Sampling
- Systematic Sampling
- Scaling
- Software Applications
- Statistical Assumptions
- Statistical Concepts
- Autocorrelation
- Biased Estimator
- Cohen's Kappa
- Collinearity
- Correlation
- Criterion Problem
- Critical Difference
- Data Mining
- Data Snooping
- Degrees of Freedom
- Directional Hypothesis
- Disturbance Terms
- Error Rates
- Expected Value
- Fixed-Effects Model
- Inclusion Criteria
- Influence Statistics
- Influential Data Points
- Intraclass Correlation
- Latent Variable
- Likelihood Ratio Statistic
- Loglinear Models
- Main Effects
- Markov Chains
- Method Variance
- Mixed- and Random-Effects Models
- Models
- Multilevel Modeling
- Odds
- Omega Squared
- Orthogonal Comparisons
- Outlier
- Overfitting
- Pooled Variance
- Precision
- Quality Effects Model
- Random-Effects Models
- Regression Artifacts
- Regression Discontinuity
- Residuals
- Restriction of Range
- Robust
- Root Mean Square Error
- Rosenthal Effect
- Serial Correlation
- Shrinkage
- Simple Main Effects
- Simpson's Paradox
- Sums of Squares
- Statistical Procedures
- Accuracy in Parameter Estimation
- Analysis of Covariance (ANCOVA)
- Analysis of Variance (ANOVA)
- Barycentric Discriminant Analysis
- Bivariate Regression
- Bonferroni Procedure
- Bootstrapping
- Canonical Correlation Analysis
- Categorical Data Analysis
- Confirmatory Factor Analysis
- Contrast Analysis
- Descriptive Discriminant Analysis
- Discriminant Analysis
- Dummy Coding
- Effect Coding
- Estimation
- Exploratory Factor Analysis
- Greenhouse–Geisser Correction
- Hierarchical Linear Modeling
- Holm's Sequential Bonferroni Procedure
- Jackknife
- Latent Growth Modeling
- Least Squares, Methods of
- Logistic Regression
- Mean Comparisons
- Missing Data, Imputation of
- Multiple Regression
- Multivariate Analysis of Variance (MANOVA)
- Pairwise Comparisons
- Path Analysis
- Post Hoc Analysis
- Post Hoc Comparisons
- Principal Components Analysis
- Propensity Score Analysis
- Sequential Analysis
- Stepwise Regression
- Structural Equation Modeling
- Survival Analysis
- Trend Analysis
- Yates's Correction
- Statistical Tests
- F Test
- t Test, Independent Samples
- t Test, One Sample
- t Test, Paired Samples
- z Test
- Bartlett's Test
- Behrens–Fisher t′ Statistic
- Chi-Square Test
- Duncan's Multiple Range Test
- Dunnett's Test
- Fisher's Least Significant Difference Test
- Friedman Test
- Honestly Significant Difference (HSD) Test
- Kolmogorov-Smirnov Test
- Kruskal–Wallis Test
- Mann–Whitney U Test
- Mauchly Test
- McNemar's Test
- Multiple Comparison Tests
- Newman–Keuls Test and Tukey Test
- Omnibus Tests
- Scheffé Test
- Sign Test
- Tukey's Honestly Significant Difference (HSD)
- Welch's t Test
- Wilcoxon Rank Sum Test
- Theories, Laws, and Principles
- Bayes's Theorem
- Central Limit Theorem
- Classical Test Theory
- Correspondence Principle
- Critical Theory
- Falsifiability
- Game Theory
- Gauss–Markov Theorem
- Generalizability Theory
- Grounded Theory
- Item Response Theory
- Occam's Razor
- Paradigm
- Positivism
- Probability, Laws of
- Theory
- Theory of Attitude Measurement
- Weber–Fechner Law
- Types of Variables
- Validity of Scores
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