Conducting a Study: A Practical Checklist for Life Science Researchers

Planning and running a life science study involves many moving parts. A practical checklist helps you move from a rough idea to a completed project without losing track of design, ethics, recruitment, data collection, and reporting. This article gives you a step-by-step framework you can adapt to your own research, whether you work in a university lab, a clinical setting, or an applied field station.

Defining Your Research Question and Scope

The first step in any study is deciding what you actually want to know. A vague interest in a topic is not enough to guide data collection or analysis. You need a focused research question that can be answered with the resources you have.

Start by writing down your general area of interest. Then narrow it to a specific problem that has practical importance. For example, instead of studying "water quality in agricultural runoff," you might ask "Does buffer strip width affect nitrate levels in streams adjacent to corn fields?" This kind of question gives you a clear target for measurement and comparison.

A quantitative research study typically follows a sequence that begins with focusing on your interests and finalizing the research topic, then moves to framing research questions, conducting a thorough literature review, choosing an appropriate framework, designing the research, selecting the research site and participants, collecting data, analyzing the data, documenting findings, and publishing results [20]. This sequence works for many life science projects, from field ecology to laboratory experiments.

Your research question should be feasible. Ask yourself whether you can realistically recruit enough participants or collect enough samples within your timeline and budget. Feasibility also depends on your access to equipment, expertise, and institutional support. If you cannot answer the question with available resources, you need to revise the question or change the approach.

Conducting a Literature Review Before You Start

A literature review is not a formality. It tells you what is already known, what methods have been tried, and where the gaps are. Skipping this step leads to duplicated effort and weak justification for your study.

Use established literature databases to search for relevant studies. The National Center for Biotechnology Information provides access to a wide range of biomedical and life science literature [4]. PubMed, maintained by the National Library of Medicine, indexes millions of research articles and is a primary tool for finding peer-reviewed studies in the health and life sciences [5]. Search with combinations of keywords related to your topic, and track which search terms give you the most useful results.

As you read, keep notes on study designs, sample sizes, measurement methods, and reported limitations. This information will help you design your own study and justify your choices. If you find that a particular method has been criticized in the literature, you can either avoid it or address the criticism in your methods section.

The literature review also helps you identify reporting guidelines that apply to your study type. Reporting guidelines are checklists that tell you what information to include in your final report so that others can judge the trustworthiness and applicability of your findings. The EQUATOR Network is an international initiative that collects and disseminates reporting guidelines for health research [2]. Checking the EQUATOR Network early in your planning helps you know what information you will need to document as you go.

Choosing a Study Design That Fits Your Question

Your research question determines which study design is appropriate. The main categories are experimental, observational, and qualitative. Each has strengths and limitations.

Experimental designs involve manipulating a variable and measuring the effect. Randomized controlled trials are the gold standard for testing interventions because randomization helps balance known and unknown confounders between groups. However, randomized trials are not always feasible or ethical. When randomized trials are unavailable or not feasible, observational studies can be used to answer causal questions about the effects of interventions by attempting to emulate a hypothetical randomized trial [9]. This approach, called target trial emulation, requires careful specification of the causal question and the reasons for using observational data.

Observational designs include cohort studies, case-control studies, and cross-sectional surveys. These designs are common in life science research because they can be conducted without assigning participants to interventions. The reporting of observational studies is often of insufficient quality, which hampers assessment of strengths and weaknesses and limits generalizability [10]. The STROBE recommendations provide a checklist of 22 items covering title, abstract, introduction, methods, results, and discussion sections for observational studies [10].

Qualitative designs are appropriate when you want to understand experiences, perceptions, or processes in depth. Grounded theory is one qualitative approach that builds theory from data through iterative collection and analysis. In applied healthcare contexts, grounded theory requires explicit paradigmatic positioning, recognition of the researcher's interpretive role, and continuity between data collection and analysis [15]. Practical issues such as organizing episodes, ongoing memoing, data management, and the time-intensive nature of analytic consolidation are often underreported but critical to success [15].

For studies evaluating the effects of health interventions where randomization is not possible, quasi-experimental designs offer a middle ground. A taxonomy without labels has been proposed to help classify these designs based on their structural features instead of relying on inconsistent terminology [27]. Understanding the classification of your design helps you report it accurately and interpret the strength of causal claims appropriately.

Using Reporting Guidelines to Plan Your Methods

Reporting guidelines are beyond for writing the final paper. They are useful planning tools that tell you what information you need to collect and document throughout the study. Using a checklist according to your study design improves the quality of manuscript reporting [26].

For intervention studies, the Template for Intervention Description and Replication (TIDieR) checklist covers 12 items: brief name, why, what materials, what procedure, who provided, how, where, when and how much, tailoring, modifications, how well planned, and how well actual [8]. Without a complete description of interventions, clinicians and patients cannot reliably implement interventions that are shown to be useful, and other researchers cannot replicate or build on findings [8]. The quality of intervention descriptions in publications is often poor, so planning for complete description from the start is essential [8].

For diagnostic accuracy studies, the STARD 2015 statement contains a list of essential items that authors, reviewers, and readers can use as a checklist [6]. Diagnostic accuracy studies are at risk of bias due to shortcomings in design and conduct, and results may not apply to other patient groups and settings [6]. Readers need sufficient detail about study design and conduct to judge trustworthiness and applicability [6].

For knowledge, attitude, and practice surveys, the ChecKAP checklist provides 46 items across 8 fields: title, abstract, keywords, introduction, method, findings, discussion, and conclusion [7]. KAP surveys gauge a population's current level of knowledge about a specific health issue, and rigorous evaluation is essential for ensuring validity and reliability [7]. The checklist serves as a quality assessment tool for reviewers and a guideline for authors [7].

For observational studies emulating target trials, the TARGET checklist includes 21 items organized into 6 sections: abstract, introduction, methods, results, discussion, and other information [9]. Key recommendations include identifying the study as an observational emulation of a target trial and summarizing the causal question and reason for emulation [9].

For studies involving patient and public involvement, the GRIPP2 checklists provide guidance for reporting involvement activities. GRIPP2-LF includes 34 items and is suitable for studies where patient and public involvement is the main focus, while GRIPP2-SF includes 5 items for studies where involvement is a secondary focus [12]. These checklists were developed through international consensus and represent the first evidence-based guidance for reporting patient and public involvement in research [12].

For discrete choice experiments in health, the DIRECT checklist details minimum standards for reporting methods [13]. This checklist can be used by authors to ensure sufficient detail is reported, providing reviewers and readers with the information they need to assess study quality [13].

For observational and qualitative study protocols, the ObsQual checklists were developed and validated through analysis of 333 study protocols submitted for ethical review [11]. These checklists include educational components and examples intended to assist novice researchers [11].

At a Glance: Study Planning Checklist

The table below summarizes the key planning steps and the questions you should answer before collecting data.

Designing Your Study Protocol

A study protocol is a detailed written plan that describes every aspect of the study before you start. It serves as your roadmap and as a record of your intentions. If you need to deviate from the protocol, you document the deviation and the reason.

The protocol should include the research question, background and rationale, study design, participant or sample selection criteria, data collection procedures, data analysis plan, and ethical considerations. For observational and qualitative studies, protocol reporting checklists can help you structure this document [11]. These checklists were developed to enhance the quality of research protocols and include educational components for novice researchers [11].

For experimental studies, consider using the Experimental Design Assistant from the NC3Rs [3]. This free online tool helps you design experiments and provides feedback on potential design flaws. It is particularly useful for animal studies because it encourages randomization, blinding, and appropriate sample size calculation [3].

Your protocol should also address data management. The National Institute of Standards and Technology supports a Research Data Framework that helps researchers plan for data storage, documentation, and sharing [1]. Planning for data management at the start of your study prevents problems later when you need to analyze or share your data.

Participant Recruitment and Sample Selection

Recruiting participants or selecting samples is often the most challenging part of a study. Your recruitment plan should be realistic about who you can reach and how long recruitment will take.

Define your inclusion and exclusion criteria clearly. These criteria determine who is eligible to participate and directly affect the generalizability of your findings. If your criteria are too narrow, you may struggle to recruit enough participants. If they are too broad, your sample may be too heterogeneous to detect meaningful effects.

Consider the factors that influence research participation in your specific population. In a study of pediatric epilepsy patients undergoing stereo-electroencephalography, 89 percent of patients approached for consent agreed to participate [16]. Despite high rates of comorbidities including neurocognitive disorder, language delay, global developmental delay, mood disorders, ADHD, autism spectrum disorder, and other cognitive or intellectual disabilities, all participants engaged in at least one task [16]. However, global developmental delay was associated with a significant reduction in time spent on active tasks [16]. This finding suggests that while many comorbidities do not prevent participation, some conditions may affect the amount of data you can collect from individual participants [16].

For survey-based research, recruitment often relies on community organizations or professional networks. A study of Pacific women in Aotearoa New Zealand recruited participants through a nationwide non-governmental organization and used principles of Pacific co-design [19]. All 94 participants identified with at least one Pacific group and reflected the demographics of the Pacific population in Aotearoa [19]. This approach shows how partnering with community organizations can support recruitment of specific populations.

When recruiting, be transparent about what participation involves. Explain the time commitment, any procedures or measurements, and how data will be used. Participants need this information to give informed consent.

Ethical Considerations and Approvals

Ethical conduct is a non-negotiable part of life science research. You must obtain approval from the appropriate institutional review board or ethics committee before starting data collection. This applies to research involving human participants, animals, or sensitive data.

Your ethics application should describe the study purpose, procedures, risks and benefits, consent process, and data handling plans. The committee will assess whether the study is ethically acceptable and whether participants are adequately protected.

For research involving patient and public involvement, the GRIPP2 checklists provide guidance on reporting how patients and the public were involved in the research [12]. Involving patients as research partners at all stages of development is a key principle of these guidelines [12].

Ethical considerations also extend to how you conduct interviews or surveys. For cognitive debriefing interviews with pediatric populations, best practices include developing the interview guide, evaluating the characteristics of the instrument to be debriefed, and considering interview conduct [18]. These practices were developed through a scoping review and a two-round modified Delphi process with experts in patient-reported outcome instrument development [18].

Data Collection Procedures

Data collection should follow your protocol precisely. Consistency in data collection is essential for the validity of your findings. If different team members collect data differently, your results may be biased.

For quantitative studies, data is often collected through online polls, questionnaires, surveys, and direct measurements [20]. The choice of data collection method depends on your research question and the nature of the data you need.

For qualitative studies, data collection typically involves interviews, focus groups, or observations. In grounded theory studies, data collection and analysis are continuous and iterative [15]. You collect data, analyze it, and use the analysis to guide further data collection. This approach requires careful organization of episodes and ongoing memoing to capture your analytic thinking [15].

For studies involving specialized equipment, such as nanopore sensing or neuroimaging, data collection procedures must be documented in detail. A study of conducting polymers at the single-molecule level used nanopore resistive pulse sensing combined with molecular docking simulations [17]. The methods required stable aqueous supramolecular dispersions and specific interactions with biological nanopores [17]. Such technical studies demand rigorous documentation of equipment settings, calibration, and data quality checks.

Recording and Managing Your Data

Good data management is the foundation of trustworthy research. You need a system for recording, storing, and organizing your data that allows you to find and verify information later.

The Research Data Framework from the National Institute of Standards and Technology provides guidance on managing research data throughout its lifecycle [1]. This framework helps researchers plan for data storage, documentation, and sharing in ways that support reproducibility and long-term access.

Your data management plan should address:

• File naming conventions that are consistent and descriptive
• Folder structures that organize data by study phase or participant
• Version control for documents and analysis scripts
• Backup procedures to prevent data loss
• Documentation of data collection procedures and any deviations from the protocol
• Data sharing plans that comply with funder and institutional requirements

For qualitative research, data management includes organizing interview transcripts, field notes, and memos. The limits of automation should be recognized, and the time-intensive nature of analytic consolidation should be planned for [15].

Analyzing Your Data

Data analysis should be planned in advance and described in your protocol. The analysis plan should specify the statistical methods or qualitative analytic approach you will use and the criteria for interpreting results.

For quantitative data, you will need to clean the data before analysis. This involves checking for errors, missing values, and outliers. Document any decisions you make about handling missing data or excluding observations.

For qualitative data, analysis typically involves coding, categorizing, and identifying themes. In grounded theory, the researcher plays a central interpretive role, and continuity between data collection and analysis is essential [15]. Memo writing throughout the analysis process helps capture your thinking and supports the development of theory.

For bibliometric analysis, the main steps include data collection from relevant databases, data cleaning and refining, and subjecting data to various bibliometric methods to generate meaningful information [22]. This approach is used to identify patterns, trends, and impact within a field [22].

Documenting Findings and Reporting

The final step of your study is documenting and reporting your findings. The quality of your report determines whether others can understand, evaluate, and build on your work.

Use the reporting guideline that matches your study design. The EQUATOR Network provides access to a comprehensive collection of reporting guidelines [2]. Selecting the appropriate guideline before you write helps you structure your report and ensure you include all necessary information.

For observational studies, the STROBE checklist covers 22 items across the title, abstract, introduction, methods, results, and discussion sections [10]. Eighteen items are common to cohort studies, case-control studies, and cross-sectional studies, and four are specific to each design [10].

For intervention studies, the TIDieR checklist ensures complete description of the intervention [8]. The 12 items cover the brief name, rationale, materials, procedure, who provided the intervention, how it was delivered, where, when and how much, tailoring, modifications, and how well the intervention was delivered as planned [8].

For diagnostic accuracy studies, the STARD 2015 checklist includes 30 items [6]. The explanation and elaboration document clarifies the rationale for each item and describes what is expected from authors [6].

For knowledge, attitude, and practice studies, the ChecKAP checklist includes 46 items across 8 fields [7]. It acts as a quality assessment tool for reviewers and a guideline for authors [7].

Common Failure Patterns in Study Conduct

Many studies fail not because of poor ideas but because of avoidable errors in planning and execution. Recognizing common failure patterns helps you avoid them.

One common failure is inadequate preparation of the research question. Researchers who start data collection without a clear question often collect data that cannot answer the question they eventually settle on. This wastes time and resources.

Another failure pattern is poor documentation of methods. If you do not document your procedures as you go, you will struggle to write a complete methods section later. Reviewers and readers will not be able to judge the trustworthiness of your findings.

Recruitment problems are also common. Researchers often underestimate the time and effort required to recruit participants. If your recruitment plan is unrealistic, you may end up with a sample that is too small or not representative of your target population.

Data management failures include lost files, inconsistent naming conventions, and inadequate backup procedures. These problems can compromise the integrity of your data and prevent analysis.

Ethical failures include starting data collection before receiving ethics approval, failing to obtain proper informed consent, and mishandling confidential data. These failures can have serious consequences for participants and for your research career.

Limitations and Feasibility Considerations

Every study has limitations. Acknowledging limitations is not a sign of weakness but a mark of scientific rigor. Your report should describe the limitations of your study and their potential impact on your findings.

Feasibility is a key consideration throughout the study planning process. A study that is not feasible cannot be completed, regardless of its scientific merit. Feasibility depends on time, budget, expertise, equipment, and access to participants or samples.

In a longitudinal study of physicians specializing in care for older adults, 41 of 78 invited residents participated, a participation rate of 53 percent [14]. The study found that residents who started before the pandemic, nonnative Dutch residents, and those with more research experience had more favorable attitudes toward conducting research [14]. Changes in intrinsic motivation were noted in the initial phases, including when developing a research question, while attitudes mostly returned to initial levels in later phases [14]. This study illustrates how feasibility factors such as timing, experience, and external events can affect research participation and motivation [14].

For studies involving specialized populations, feasibility may depend on the willingness of participants to engage despite comorbidities or other challenges. The pediatric epilepsy study found that despite high prevalence of neuropsychological comorbidities, participants contributed meaningfully to studies investigating important developmental questions [16]. This finding supports the inclusion of participants with comorbidities instead of excluding them [16].

Safety and Welfare Considerations

Safety and welfare considerations apply to both human participants and animals involved in research. Your study design should minimize risks and maximize benefits for all involved.

For human participants, this means ensuring that procedures are safe, that participants understand what they are consenting to, and that their data is protected. For vulnerable populations, such as children or people with cognitive impairments, additional safeguards may be required.

For animal studies, the NC3Rs Experimental Design Assistant helps researchers design experiments that minimize animal use and suffering while maximizing the scientific value of the data [3]. The tool encourages randomization, blinding, and appropriate sample size calculation, all of which support the principles of replacement, reduction, and refinement.

For studies involving patient-reported outcome instruments with pediatric populations, cognitive debriefing interviews require careful attention to the developmental level of participants [18]. Best practices include developing the interview guide with age-appropriate language and considering the characteristics of the instrument being debriefed [18].

Professional Escalation Criteria

Some problems during a study require escalation to a supervisor, ethics committee, or other authority. Knowing when to escalate is important for protecting participants and maintaining research integrity.

Escalate to your supervisor or principal investigator if you encounter:

• Unexpected adverse events or safety concerns
• Protocol deviations that could affect participant safety or data integrity
• Evidence of data fabrication or falsification
• Conflicts of interest that could affect the conduct or reporting of the study
• Inability to recruit participants that threatens the feasibility of the study

Escalate to the ethics committee if you need to make significant changes to your protocol that affect participant risk or the consent process. Do not implement such changes without approval.

Escalate to institutional authorities if you suspect research misconduct or violations of regulations. Reporting concerns is a professional responsibility.

Frequently Asked Questions

What is the first step in conducting a study?

The first step is defining your research question and assessing its feasibility. Write down what you want to know and whether you can answer the question with available resources. A quantitative research study typically begins with focusing on your interests and finalizing the research topic, then moves to framing research questions [20]. Conduct a literature review to understand what is already known and to identify gaps your study can address.

How do I choose the right study design?

Your research question determines the appropriate design. Experimental designs are suitable for testing interventions, observational designs are useful when randomization is not feasible, and qualitative designs help understand experiences and processes. Reporting guidelines from the EQUATOR Network can help you understand the requirements for different study types [2]. Consider whether a randomized trial is feasible or whether you need to emulate a target trial using observational data [9].

What is a reporting guideline and why should I use one?

A reporting guideline is a checklist that tells you what information to include in your study report so that others can judge the trustworthiness and applicability of your findings. The EQUATOR Network collects and disseminates reporting guidelines for health research [2]. Using a reporting guideline from the planning stage helps you document the right information throughout your study.

How do I determine how many participants or samples I need?

Sample size determination depends on your study design, the expected effect size, and the statistical power you want to achieve. Your protocol should specify the sample size and the assumptions behind it. For animal studies, the NC3Rs Experimental Design Assistant can help you design experiments with appropriate sample sizes [3]. If you are unsure about sample size calculations, consult a statistician before starting data collection.

What should I include in a study protocol?

A study protocol should include the research question, background and rationale, study design, participant or sample selection criteria, data collection procedures, data analysis plan, and ethical considerations. For observational and qualitative studies, protocol reporting checklists can help you structure the document [11]. The protocol serves as your roadmap and as a record of your intentions.

How do I handle missing data?

Missing data is a common challenge in life science research. Your analysis plan should specify how you will handle missing data, whether through complete case analysis, imputation, or other methods. Document any decisions you make about missing data and the reasons for those decisions. The reporting guidelines for your study type may have specific requirements for describing missing data.

What should I do if I need to change my protocol after starting?

If you need to change your protocol, document the deviation and the reason. For changes that affect participant safety or the consent process, obtain approval from the ethics committee before implementing the change. For other changes, document them in your study records and describe them in your final report.

How do I know when to escalate a problem to my supervisor?

Escalate to your supervisor if you encounter unexpected adverse events, protocol deviations that could affect safety or data integrity, evidence of research misconduct, conflicts of interest, or recruitment problems that threaten the feasibility of the study. Escalate to the ethics committee for significant protocol changes that affect participant risk or consent. Escalate to institutional authorities if you suspect research misconduct or regulatory violations.

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References and Further Reading

• Research Data Framework. National Institute of Standards and Technology.
• EQUATOR Network. EQUATOR Network.
• Experimental Design Assistant. NC3Rs.
• NCBI Literature Resources. National Center for Biotechnology Information.
• PubMed. National Library of Medicine.
• STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration.. BMJ open, 2016.
• ChecKAP: A Checklist for Reporting a Knowledge, Attitude, and Practice (KAP) Study.. Asian Pacific journal of cancer prevention : APJCP, 2024.
• Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide.. BMJ (Clinical research ed.), 2014.
• Transparent Reporting of Observational Studies Emulating a Target Trial-The TARGET Statement.. JAMA, 2025.
• Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration.. International journal of surgery (London, England), 2014.
• Development and validation of observational and qualitative study protocol reporting checklists for novice researchers (ObsQual checklist).. Evaluation and program planning, 2024.
• GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research.. BMJ (Clinical research ed.), 2017.
• A Reporting Checklist for Discrete Choice Experiments in Health: The DIRECT Checklist.. PharmacoEconomics, 2024.
• Attitudes to Conduct Research in Physicians Specializing in Care for Older Adults: A Longitudinal Study.. 2026.
• Conducting grounded theories in midwifery research: Practical insights.. 2026.
• Perspectives in conducting task-based research in pediatric surgical epilepsy patients. 2026.
• Supramolecular strategy for probing conducting polymers at single molecule level.. 2026.
• "Reading level is just one component": best practices for cognitive debriefing patient-reported outcome instruments with pediatric populations.. 2026.
• Knowledge and perceptions of gynaecological cancers of Pacific women in Aotearoa New Zealand.. 2026.
• Conducting Quantitative Research Study: A Step-by-Step Process. Journal of Engineering Education Transformations, 2023.
• The Steps of User-Centered Design in Health Information Technology Development: Recommendations from a PhD Research Study. 2016 International Conference on Computational Science and Computational Intelligence (CSCI), 2016.
• Bibliometric Analysis: The Main Steps. Encyclopedia, 2024.
• Steps Involved in Text Recognition and Recent Research in OCR, A Study. 2019.
• The relationship between syntactic complexity and rhetorical move-steps in research article introductions: Variation among four social science and engineering disciplines. Journal of English for Academic Purposes, 2021.
• Applying epidemiological principles to ergonomics: A checklist for incorporating sound design and interpretation of studies. Applied Ergonomics, 1997.
• Recommendations for using checklists according to the type of study design used. A way to improve the quality of manuscript reporting. Revista De Cirugia, 2026.
• Quasi-experimental study designs series-paper 5: a checklist for classifying studies evaluating the effects on health interventions-a taxonomy without labels. Journal of Clinical Epidemiology, 2017.
• Developing a checklist for assessing urban design qualities of residential complexes in new peripheral parts of Iranian cities: A case study of Kerman, Iran. Sustainable Cities and Society, 2020.

This article is educational and does not replace institutional policy, professional advice, or applicable safety and regulatory requirements.