Targeted literature searches are a fundamental part of writing clinical manuscripts that will meet the standards of high-quality journals and contribute meaningfully to evidence-based practice. When physicians write clinical manuscripts, utilizing a targeted literature search can identify high-quality, relevant, and current evidence. While a general literature review is useful, a targeted literature search is specific to the clinical question and should be completed through frameworks established, such as PICO (Population, Intervention, Comparator, Outcome) and PRISMA [1].
Planning Your Data Collection: Designing methods for effective research
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Planning Your Data Collection: Designing methods for effective research
1. What Is Data Collection?
Data collection refers to the process of systematically gathering and measuring information from the relevant sources to answer the research problem. Data collection is the basis of any research, as it aids in decision-making to build a foundation for developing strong conclusions. A data collection plan is essentially a roadmap on how to gather data for your research.[1]
2. Purpose of Data Collection
Data collection is something found in all research fields. Researchers must develop a data collection plan, because gathering data without a plan can yield inconclusive or invalid results. An effective data collection plan will help ensure that your research project is successful. [2]
Purpose of Data Collection.
• Decision Marketing
• Save time
• Design strategies
• Problems Identification
• Back up the Arguments
• Track the progress
3. Types of Data Collection Methods
The methods of data collection are accomplished in various forms. They’re classified into quantitative, qualitative, and mixed methods. It’s crucial to know the different methods and select the method that accurately meets your research needs. [3]
| Mixed | Quantitative | Qualitative |
|---|---|---|
| Combination of qualitative and quantitative data collection methods | Number-based | Behaviour-based |
| The planning and analysis phase takes time | Involves measuring and counting | Involves interviews and observation |
| Data is collected from both the methods | More time is consumed for planning as compared to the analysis phase | Less time is consumed for planning as compared to the analysis phase |
| Example: The final product after extraction was observed to be a white powder. The yield of this product was 78%. | Objective approach | Subjective approach |
| Data is collected from: 1. Surveys 2. Statistical experiments 3. Content analysis | Data is collected from: 1. Interviews 2. Case studies 3. Ethnography | |
| Example: The yield of the final product after extraction was 78%. | Example: The final product after extraction was a white powder. |
4. 9 Steps for Planning Your Data Collection
Planning for data collection is an essential part of achieving directionality in your research. A good plan allows you to streamline your data collection and organize it all in your mind. Following a series of steps will help you plan for data collection. The following steps reflect this activity, in order of progression. [4]
4.1. Define your research objectives
Before you begin data collection, it is critical to clearly articulate your research objectives. The research objectives will help you think about the types of data that are relevant to the goals. You should write the research questions and try to define them. This will implement a level of focus on the study.
4.2. Identify the data requirements
Once you define your research objectives, you must ascertain the precise data elements you require to appropriately answer the research questions. In addition, ascertain the available and accessible data, and determine its effectiveness. When considering available data, think both qualitatively and quantitatively – which could include surveys, interviews, observations, existing datasets, or experiment data studies. Equally, think about the level of detail for each data point and the most applicable data collection methods.
4.3. Select Appropriate Data Collection Methods
Identify data collection methods that suit your research purpose and data needs. Review the advantages and disadvantages of each method and select an appropriate method based on those considerations. There are many methods of data collection available to researchers including interviews, role-playing, focus groups, in-person surveys, online surveys, telephonic surveys, and observation. Evaluate the practicality of the method you select and identify the advantages and disadvantages of each type of research technique so that you make the best choice.
4.4. Create an Implementation Timeline
Develop a realistic timeline for the data collection stage of your study. This will help maintain organization of your study as well as provide a final date to reach a conclusion. But you need to consider the time needed to develop the method, conduct a pilot study, as well as time to interpret and analyze data. Also consider the resources and limits available to develop a reasonable timeline.
4.5. Design the Method
Once you have determined how you will collect your data, concretize the method with the necessary tools or materials. For surveys, write clear, concise, and unbiased questions that will effectively elicit the information you want. Build structured interview protocols that facilitate thoughtful discussion about the key topics you want to address. Construct observation protocols that describe how the observations will be recorded for reliability and validity. Look for ways to collect the most useful data and put systems in place to specifically code and make sense of it. Finally, look for the ways you will measure the data you’ll be collecting.
4.6. Pilot Testing
Before you commence the data collection, pilot test the instruments and procedures you will be employing. Pilot testing can help you verify that your instruments work, and the small trial run is a good way to identify any ambiguity in the processes. You can also use the information collected from the pilot test to make the necessary changes and increase the dependability of your data.
4.7. Standardization
Develop a thorough standardized protocol guided by the types of data and what was learned from your pilot testing. Also, document the instruments and standard conditions that you want for the study. Standardization of your protocol will make any future work that replicates the study easier since two people are doing the same thing.
4.8. Develop Data-Collection Procedures
As with protocol development, you will want to provide detailed data-collection procedures. Include step-by-step procedures for data collection. You will want to document the procedures so that they are easy to follow and in the case of using surveys, interviews, or observation, you must state any ethical issues (if any). The researcher must receive sufficient training in the data-collection method and must document it clearly.
4.9. Plan for Data Analysis
While you are completing some aspects of your data-collection strategy, you need to think about planning and developing your data analysis. You need also to decide and develop your statistical approach that is related to your quantitative analysis, or if your data is qualitative, document the qualitative analysis you intend to apply to your collected data. You will want to operationalize the data when your variables can not be measured. You’ll need to also plan how the data will be represented.
5. Strengths and Weaknesses of Data Collection Methods
Identifying the strengths and weaknesses of the data collection method will help you to plan your data collection method appropriately. [5]
| Methods | Strengths | Weaknesses |
|---|---|---|
| Qualitative |
|
|
| Quantitative |
|
|
| Mixed |
|
|
6. Ethically Reporting the Data Collected Especially in the AI age
With the advancements and growth of technology, artificial intelligence (AI) is playing an increased role in the data collection and data analysis. Good data management practices and principles of data sharing have become increasingly important with AI now part of data management. AI has the potential for processing and analysing large data sets and can provide many valuable insights for researchers, but there are numerous issues using AI in data management. [6]
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Conclusion
A structured data collection plan is the backbone of successful research. Defining objectives and selecting the right methods ensure relevance and accuracy. Standardization and ethical practices safeguard reliability in an AI-driven era. Well-planned data collection leads to credible insights and stronger conclusions.
Planning Your Data Collection: Designing methods for effective research? Pubrica offers end-to-end research design, analysis, and reporting support
References
- Jain, P. (2021, May 13). What is data collection: Methods, types, tools. Retrieved September 3, 2025, from Simplilearn.com website: https://www.simplilearn.com/what-is-data-collection-article
- (N.d.). Retrieved September 3, 2025, from Savanta.com website: https://savanta.com/us/knowledge-centre/view/what-is-the-main-purpose-of-data-collection/
- Paradis, E., O’Brien, B., Nimmon, L., Bandiera, G., & Martimianakis, M. A. (2016). Design: Selection of Data Collection Methods. Journal of graduate medical education, 8(2), 263–264. https://doi.org/10.4300/JGME-D-16-00098.1
- Jessee, T. (2025, March 12). Data collection for strategy reporting: A step-by-step guide. Retrieved September 3, 2025, from Clearpointstrategy.com website: https://www.clearpointstrategy.com/blog/strategy-reporting-how-to-collect-data
- (N.d.). Retrieved September 3, 2025, from Studocu.com website: https://www.studocu.com/row/document/university-of-nairobi/introduction-to-statistics/8-strengths-and-weaknesses-of-data-collection-methods/72882384
- Chen, Z. (2023). Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities & Social Sciences Communications, 10(1), 1–12. https://doi.org/10.1057/s41599-023-02079-x