Assessing Significance, Novelty and Feasibility

Overview

A researchable question is not automatically worth pursuing. Before a protocol is developed in detail, the team should assess whether the proposed study is significant, sufficiently novel, ethical and feasible. This appraisal protects participants and resources from projects that cannot answer their question or are unlikely to add useful knowledge.

The widely used FINER criteria describe a good research question as Feasible, Interesting, Novel, Ethical and Relevant [1,2]. These criteria are not a scoring formula, but they provide a practical structure for refinement. A question may be important yet infeasible in its current form, or feasible yet too trivial to justify the effort.

Significance concerns why the answer matters. Novelty concerns what the study adds to existing knowledge. Feasibility concerns whether the proposed team, population, data, methods, time and resources can deliver a credible answer. These dimensions interact and should be assessed together.

Why this matters

Health research consumes participant time, sensitive information, staff effort, laboratory materials and funding. A study that recruits too slowly, relies on unavailable records, measures an unimportant outcome or repeats known work without justification may produce little value. Avoidable weaknesses contribute to research waste [3].

Early appraisal also improves success. It encourages investigators to verify the evidence gap, consult stakeholders, check data availability, estimate eligible numbers, test instruments and identify governance requirements before promising an unrealistic project.

Significance: why does the answer matter?

Significance is not established by describing a disease as common. The proposal should explain the pathway from the evidence gap to a meaningful decision or contribution.

Health and patient importance

Does the problem affect mortality, morbidity, quality of life, treatment burden, safety or patient-valued outcomes? Are particular groups disproportionately affected?

Clinical or service decision

Will the answer inform diagnosis, treatment, follow-up, resource allocation, implementation or quality improvement? Identify the decision-maker and decision.

Public-health and policy relevance

Could the study clarify burden, inequity, intervention reach, policy effects or system performance? Local policy relevance should be specific rather than rhetorical.

Scientific contribution

Will the study test a theory, resolve conflicting evidence, improve measurement, establish temporal information, evaluate transportability or provide a foundation for subsequent work?

Consequence of continued uncertainty

What happens if the gap remains? Unnecessary treatment, missed disease, inefficient services, inequitable access or inability to plan may establish significance.

Novelty: what does the study add?

Novelty does not mean that no similar study has ever existed. Valuable research can:

• confirm an important finding with stronger methods;
• refute a result that may be biased or inconsistent;
• extend evidence to a neglected population, outcome, setting or time horizon;
• explain a mechanism or contextual variation;
• improve measurement, design or analysis;
• evaluate implementation or real-world performance;
• replicate a consequential claim; or
• synthesise a fragmented body of evidence.

A first study in one hospital is novel only when local context could meaningfully affect the answer or when the data support a decision that external evidence cannot resolve.

Verifying novelty

Novelty requires a purposeful literature search, not memory or a single database query. Search reviews, primary studies, trial registries, protocols, theses and relevant policy or surveillance sources. Record the search date and refine the question when closely related work is found.

Replication should not be dismissed as unoriginal. A rigorous replication can be highly valuable when a finding is influential, uncertain or context dependent. Conversely, a superficial change of location or questionnaire may add little.

Feasibility: can the study deliver a credible answer?

Feasibility should be tested against the exact protocol rather than a general impression.

Participants and recruitment

• How many people meet eligibility criteria each month?
• What proportion is likely to be approached, consent and remain in follow-up?
• Are important subgroups sufficiently represented?
• Does recruitment depend on busy clinicians or rare events?

Data and measurement

• Do required records exist and can they be linked?
• Are definitions consistent across sites?
• Is the instrument valid in the language and population?
• Can outcomes be measured at the required time?
• How much missing or delayed data is expected?

Design and sample-size requirements

• Is the accessible sample compatible with the desired precision or effect size?
• Are the number of clusters, events or outcome cases adequate?
• Does the project include more objectives than the sample can support?

Expertise and operational capacity

• Does the team have clinical, methodological, statistical, qualitative, laboratory, informatics and project-management expertise as needed?
• Are intervention training, blinding, follow-up and quality-control procedures realistic?

Time and cost

• Do approvals, contracts, instrument adaptation, recruitment, follow-up and analysis fit the available period?
• Are laboratory tests, software, personnel, travel, transcription and data storage budgeted?

Ethics, governance and access

• Is the risk–benefit balance acceptable?
• Can consent be obtained appropriately?
• Are data custodians willing and legally able to provide access?
• Are privacy, security and cross-institutional agreements achievable?

PROTOCOL CHECKLIST

Complete a feasibility evidence file

• Count potentially eligible participants from recent records.
• Map every recruitment and follow-up step with the responsible person.
• Obtain written confirmation of data, laboratory and site access.
• Test key variable availability and missingness on a small permitted sample.
• Confirm instrument language, licensing and administration requirements.
• Prepare a realistic timeline including approvals and follow-up.
• Build a costed budget and identify unfunded dependencies.
• Record required expertise and named collaborators.
• Identify stop, modify or proceed criteria for unresolved feasibility questions.

Interesting, ethical and relevant

“Interesting” means that the question can sustain the investigator, team and stakeholders through the work. Personal interest is valuable but insufficient; patient, community and service perspectives may reveal priorities or burdens the team has overlooked.

“Ethical” includes scientific validity, fair participant selection, reasonable burden, privacy and social value. A study that cannot recruit enough participants or measure its outcome adequately may be ethically unacceptable because participant contributions are unlikely to generate useful knowledge.

“Relevant” concerns the contribution to science, clinical care, policy, public health or future research. The intended users should be identifiable.

A structured prioritisation matrix

When several ideas compete, a transparent matrix can support discussion. Scores should not replace judgement, and criteria may require different weights.

Illustrative project-prioritisation matrix

illustrative

Criterion	National app trial	Local knowledge survey	Linked-record and interview study
Consequence of evidence gap	High	Moderate	High
Novel contribution	Moderate	Low	High
Recruitment feasibility	Low	High	Moderate to high
Data and measurement feasibility	Low	High	Moderate
Fit with available time and expertise	Low	High	High
Clear next decision	Moderate	Low	High

Note: Ratings are illustrative and require evidence. A low score may indicate redesign rather than abandonment.

The first idea could become feasible through multicentre collaboration and staged intervention development. The second could become more meaningful if linked to a validated implementation question. The third may be the strongest immediate study.

Pilot and feasibility studies

A feasibility study asks whether and how a future definitive study can be conducted. It may assess recruitment, retention, adherence, data completeness, acceptability, intervention delivery or randomisation procedures. A pilot study is a type of feasibility study in which part or all of the future study is conducted on a smaller scale [4].

A small study should not be called a pilot merely because the sample is limited. Feasibility objectives and progression criteria should be explicit. Clinical-effect estimates from a small pilot are usually too imprecise to determine effectiveness and should not be used as the main success criterion. Current NIH peer-review criteria similarly bring research importance together with rigour, feasibility, expertise and resources, although local project appraisal need not reproduce a funding-agency scoring system [5].

Progression criteriaMMed extension

Feasibility studies can pre-specify green, amber and red thresholds for key uncertainties such as recruitment, retention or intervention fidelity. These thresholds should be justified and interpreted with uncertainty and context rather than applied mechanically. The decision may be proceed, proceed with modification or do not proceed.

Worked example

WORKED EXAMPLE

Applying FINER to the postpartum study

Feasible: Recent records indicate approximately 35 eligible deliveries per month. Laboratory linkage is technically possible for hospital and public primary-care systems. Twelve months of recruitment provides a plausible sample, although private testing capture requires additional work.

Interesting: Obstetric, primary-care and patient representatives identify the transition of care as a persistent concern. The findings would guide the design of a follow-up intervention.

Novel: Published studies report variable completion and barriers, but the local fragmented pathway and linkage problem have not been characterised. The contribution is not simply geographic; it identifies where documented follow-up is lost and integrates patient experience with service data.

Ethical: The record linkage has minimal physical risk but requires secure governance. Interview burden is modest. The study does not withhold recommended care.

Relevant: The service needs a defensible baseline and modifiable targets before introducing reminders or scheduling changes.

Refinement: The team limits the study to estimating completion and understanding barriers. Effectiveness testing is deferred until an intervention has been developed and feasibility established.

Appraising significance, novelty and feasibility

APPRAISAL CHECKLIST

Should this project proceed?

• Is the evidence gap clearly verified rather than assumed?
• Does the answer matter to patients, practice, policy or scientific understanding?
• Is the proposed contribution more than a new location or convenient dataset?
• Are potential users and decisions identified?
• Are eligible numbers and recruitment rates supported by real data?
• Are data access, measurement validity and follow-up pathways confirmed?
• Does the sample support the primary objective with acceptable precision?
• Are time, budget, skills and governance requirements realistic?
• Can the question be answered ethically without disproportionate burden?
• Would a feasibility study, collaboration or narrower first phase improve the project?

Suggested proposal wording

Common mistakes

Knowledge check

What does novelty mean under the FINER criteria?

Answer and reasoning

Novelty can include confirming, refuting or extending previous findings, studying a meaningful context, improving methods or providing needed replication. It does not require that no related study has ever been conducted.

Why is ‘first study in our hospital’ a weak significance argument?

Answer and reasoning

It describes location, not contribution. The proposal should explain how the local pathway, population, resources or policy create a decision that existing evidence cannot answer.

What evidence should support recruitment feasibility?

Answer and reasoning

Use recent counts from the actual source population, realistic eligibility and consent proportions, expected follow-up and the capacity of staff and sites. Investigator optimism alone is inadequate.

Why should a pilot study not be judged mainly by a statistically significant clinical effect?

Answer and reasoning

A pilot is usually too small for a precise effectiveness estimate. Its purpose is to resolve uncertainties about whether and how a future definitive study can be conducted, using pre-specified feasibility objectives and progression criteria.

Key take-home messages

SUMMARY

Key take-home messages

• Assess importance, novelty, ethics and feasibility before committing participants and resources.
• Significance links the evidence gap to a patient, service, policy or scientific decision.
• Novelty may confirm, refute, extend, replicate or improve existing evidence; geographic uniqueness alone is weak.
• Feasibility requires evidence about recruitment, data, measurement, design, expertise, time, cost and governance.
• FINER is a structured aid to judgement, not a mechanical score.
• A feasibility or pilot study should answer feasibility questions, not serve as a small inconclusive effectiveness trial.

References

1. Farrugia P, Petrisor BA, Farrokhyar F, Bhandari M. Research questions, hypotheses and objectives. Can J Surg. 2010;53(4):278–281.
2. Browner WS, Newman TB, Cummings SR, Grady DG, Huang AJ, Kanaya AM, et al. Designing clinical research. 5th ed. Philadelphia: Wolters Kluwer; 2022.
3. Chalmers I, Glasziou P. Avoidable waste in the production and reporting of research evidence. Obstet Gynecol. 2009;114(6):1341–1345. https://doi.org/10.1097/AOG.0b013e3181c3020d
4. Eldridge SM, Chan CL, Campbell MJ, Bond CM, Hopewell S, Thabane L, et al. CONSORT 2010 statement: extension to randomised pilot and feasibility trials. BMJ. 2016;355:i5239. https://doi.org/10.1136/bmj.i5239
5. National Institutes of Health. Simplified peer review framework. Bethesda: NIH; updated 28 April 2026. Accessed 4 August 2026. https://grants.nih.gov/policy-and-compliance/policy-topics/peer-review/simplifying-review/framework