Define a question that can be answered
Separate the broad area of interest from the specific question. State the population, setting, material or corpus where appropriate, identify the outcome or phenomenon, and explain why the answer matters. The literature should establish the problem rather than become a list of loosely related studies.
Align objectives and methods
For each objective, identify the information needed, how it will be obtained and how it will be interpreted. A design that cannot answer an objective should be revised before data collection. We can flag mismatches among sampling, instruments, interview plans, variables and the intended analysis.
- Create an objective-to-method table.
- Identify access, recruitment, equipment or archive constraints.
- Explain the analysis plan before promising results.
- List assumptions that require pilot work or supervisor approval.
Build a feasible schedule
Work backwards from the submission milestone and allow time for approvals, access, recruitment, transcription, analysis and revision. Distinguish tasks under your control from external decisions. A contingency plan should explain what changes if recruitment, data access or an experiment is delayed.
Prepare the review version
Use the exact institutional headings, word limits and declaration requirements supplied by you. Typical outputs include an annotated draft, a structure plan and a list of questions for the supervisor or ethics committee. Approval belongs to the relevant institution; a polished proposal does not guarantee it.
Scope, files and delivery
Start with a short project brief. We assess the work, discuss the expertise required and confirm the deliverables, fee, schedule and included revisions in writing. Share the current version and the instructions that govern it. Additional data, a new target journal or a substantially changed brief may require a revised scope. You review the proposed changes and retain responsibility for the research.