what is the meaning of diagnostic research studies

What is Diagnostic Research?

The Diagnostic research Is a type of study whose main purpose is to analyze a given situation exhaustively.

This type of research seeks to identify which factors intervene in a given scenario, what are their characteristics and what their implications, in order to generate a global idea of the context of the study object, and thus allow decisions to be made based on that information collected and analyzed.

Researcher looking through microscope. You may be looking for a cure for a serious illness. This is one of the reasons for the importance of research.

That is, a diagnostic investigation focuses mainly on the analysis of situations and offers, after this analysis, the appropriate basis for decision making.

The most relevant characteristics of a diagnostic investigation

Raises a problem.

Like all investigative processes, diagnostic research emerges as a response to a problem or situation that warrants a solution.

This problem must be relevant; It is expected that, after identifying the characteristics of the scenario and determining the actions to be taken to find the resolution to that problem, many people will benefit.

Once the diagnostic investigation is done, the result will determine if there is indeed the problem, what factors are involved and to what extent there are injured actors, among other aspects.

Study the characteristics of a scenario

The main objective of the diagnostic investigation is to analyze a specific situation based on the observation of the scenario and its entire context.

In order to study a situation in depth, it is necessary to identify all its characteristics, to detail them and to discover their implications.

So, fundamental part of a diagnostic investigation is to observe the study problem as a complex phenomenon.

Diagnostic research identifies the specific characteristics of both the situation to be studied and its context, classifies them according to their implications and examines them in detail.

It is based on a delimited field

A diagnostic investigation should cover a specific area. Its scope must allow it to be possible to know fully all the aspects that have to do with that chosen scenario.

If the field chosen is very broad, it will be difficult to delve into the subject and get to know all the implications that exist.

It is important to remember that the most important thing in a diagnostic investigation is the opportunity it offers to understand a situation and its factors.

For this reason, the researcher must be careful in choosing the topic around which his research will be developed: the delimitation of the research is fundamental to obtain a good result.

Identifies the factors involved

When conducting a diagnostic investigation, it is very important to recognize the main elements, which have an impact on the problem.

Since the diagnostic investigation seeks to study a situation and its context in a comprehensive way, it becomes necessary to know all the factors that intervene in it.

And this includes both the protagonist elements and those that have less incidence, but which are still an important part of the circumstance under study.

Taking into account subjects, contexts and actions

In a diagnostic investigation, since this is a deep exploration, it is necessary to take into account not only the subjects that are part of the problem to study, but also their actions and their contexts.

The problems in general are complex and admit the participation of different factors. It is wrong to base a diagnostic investigation on the observation of a single element.

Situations are the product of different components, and diagnostic investigations seek to analyze all the factors involved, whether subjects, contexts or actions.

Analyze situations

The purpose of diagnostic research is to recognize a specific situation and to understand all aspects of the situation.

After identifying the main factors, the diagnostic investigation focuses on analyzing the relationship that exists between these components, what are the scope of the situation, who participate and other key elements.

It is the analysis of these factors that is the true goal of a diagnostic investigation.

Seek to generate changes

The person conducting a diagnostic investigation should ultimately seek to intervene positively in the context that is part of its subject matter.

The intention of a diagnostic investigation is to solve a problematic situation existing in a given context.

The role of researchers is to actively participate in the identification of the problem, and to lay the foundations on which they themselves, or other actors, can make decisions related to the data and conclusions obtained from the research.

Helps to make decisions

Before making decisions regarding a given situation, it is necessary to know all its implications.

The diagnostic investigation allows to generate a complete analysis on a problem and its context, and gives rise to the decision making.

For this reason, diagnostic research is considered the starting point for the application of solutions.

It is essential that the object of study is well understood so that it can then take appropriate action.

A diagnostic investigation offers the possibility to understand the situation as completely as possible, and favors the making of assertive decisions.

Helps detect problems

It is possible that, in the middle of a diagnostic investigation, conflicting situations are identified that were not initially evident.

It may even be that these problems arising in the midst of research are a fundamental part of the underlying conflict.

Since diagnostic research seeks to penetrate all aspects and peculiarities of a particular situation, it allows the problematic and its context to be characterized as the study is deepened.

A deep and objective look at a problematic situation allows us to discover the underlying difficulties that may be as important or even more relevant than the original problem considered in the research.

Prioritize issues

Once the most relevant aspects of the study object are identified, the difficulties that are presented and the fundamental problems that need to be solved, the diagnostic investigation allows to categorize these opportunities and to order them according to their importance.

Knowing the problems that exist in a given context, and analyzing them objectively, rationally, empirically and profoundly, it is possible to identify the relevance of each factor and to recognize which ones need faster responses, or particular treatments with actors who can participate in Efficiently.

Noriega, C."Diagnostic evaluation in introduction to research"(2006) at the University of Palermo. Retrieved on 4 August 2017 from University of Palermo: palermo.edu
"Methods of research"at the National Autonomous University of Mexico. Retrieved on 4 August 2017 from Universidad Nacional Autónoma de Mexico: unam.mx
Marí, R., Sánchez, P. and Gastaldo, I."Approach to the model of pedagogical diagnosis"at Universitat de Valencia. Retrieved on 4 August 2017 from Universitat de Valencia: uv.es
Farooq, U."Types of Research Design"(6 October 2013) in Study Lecture Notes. Retrieved on 4 August 2017 from Study Lecture Notes: studylecturenotes.com.

StatPearls [Internet].

Diagnostic testing accuracy: sensitivity, specificity, predictive values and likelihood ratios.

Jacob Shreffler ; Martin R. Huecker .

Affiliations

Last Update: March 6, 2023 .

Definition/Introduction

To make clinical decisions and guide patient care, providers must comprehend the likelihood of a patient having a disease, combining an understanding of pretest probability and diagnostic assessments. [1] Diagnostic tools are routinely utilized in healthcare settings to determine treatment methods; however, many of these tools are subject to error.

Issues of Concern

Benefits of Diagnostic Testing

The utilization of diagnostic tests in patient care settings must be guided by evidence. Unfortunately, many order tests without considering the evidence to support them. [1] Sensitivity and specificity are essential indicators of test accuracy and allow healthcare providers to determine the appropriateness of the diagnostic tool. [2] Providers should utilize diagnostic tests with the proper level of confidence in the results derived from known sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), positive likelihood ratios, and negative likelihood ratios. [2]

The presentation of diagnostic exam results is often in 2x2 tables. The values within this table can help to determine sensitivity, specificity, predictive values, and likelihood ratios. A diagnostic test’s validity, or its ability to measure what it is intended to, is determined by sensitivity and specificity. [3] See Table. Diagnostic Testing Accuracy Table.

Sensitivity

Sensitivity is the proportion of true positives tests out of all patients with a condition. [4] In other words, it is the ability of a test or instrument to yield a positive result for a subject that has that disease. [2] The ability to correctly classify a test is essential, and the equation for sensitivity is the following:

Sensitivity=(True Positives (A))/(True Positives (A)+False Negatives (C))

Sensitivity does not allow providers to understand individuals who tested positive but did not have the disease. [5] False positives are a consideration through measurements of specificity and PPV.

Specificity

Specificity is the percentage of true negatives out of all subjects who do not have a disease or condition [4] . In other words, it is the ability of the test or instrument to obtain normal range or negative results for a person who does not have a disease. [2] The formula to determine specificity is the following:

Specificity=(True Negatives (D))/(True Negatives (D)+False Positives (B))

Sensitivity and specificity are inversely related: as sensitivity increases, specificity tends to decrease , and vice versa. [3] [6] Highly sensitive tests will lead to positive findings for patients with a disease, whereas highly specific tests will show patients without a finding having no disease. [6] Sensitivity and specificity should always merit consideration together to provide a holistic picture of a diagnostic test. [7] Next, it is important to understand PPVs and NPVs.

PPV and NPV

PPVs determine, out of all of the positive findings, how many are true positives; NPVs determine, out of all of the negative findings, how many are true negatives. As the value increases toward 100, it approaches a ‘gold standard.’ [3] The formulas for PPV and NPV are below.

Positive Predictive Value=(True Positives (A))/(True Positives (A)+False Positives (B))

Negative Predictive Value=(True Negatives (D))/(True Negatives (D)+False Negatives(C))

Disease prevalence in a population affects PPV and NPV. When a disease is highly prevalent, the test is better at ‘ruling in' the disease and worse at ‘ruling it out.’ [1] Therefore, disease prevalence should also merit consideration when providers examine their diagnostic test metrics or interpret these values from other providers or researchers. Providers should consider the sample when reviewing research that presents these values and understand that the values within their population may differ. [5] Considering all of the diagnostic test outputs, issues with results (e.g., very low specificity) may make clinicians reconsider clinical acceptability, and alternative diagnostic methods or tests should be considered. [8]

Likelihood Ratios

Likelihood ratios (LRs) represent another statistical tool to understand diagnostic tests. LRs allow providers to determine how much the utilization of a particular test will alter the probability. [4] A positive likelihood ratio, or LR+, is the “probability that a positive test would be expected in a patient divided by the probability that a positive test would be expected in a patient without a disease.”. [4] In other words, an LR+ is the true positivity rate divided by the false positivity rate [3] . A negative likelihood ratio or LR-, is “the probability of a patient testing negative who has a disease divided by the probability of a patient testing negative who does not have a disease.”. [4] Unlike predictive values, and similar to sensitivity and specificity, likelihood ratios are not impacted by disease prevalence. [9] The formulas for the likelihood ratios are below.

Positive Likelihood Ratio=Sensitivity/(1-Specificity)

Negative Likelihood Ratio=(1- Sensitivity)/Specificity

Now that these topics have been covered completely, the application exercise will calculate sensitivity, specificity, predictive values, and likelihood ratios.

Application Exercise

Example: A healthcare provider utilizes a blood test to determine whether or not patients will have a disease.

The results are the following:

A total of 1,000 individuals had their blood tested.
Four hundred twenty-seven individuals had positive findings, and 573 individuals had negative findings.
Out of the 427 individuals who had positive findings, 369 of them had the disease.
Out of the 573 individuals who had negative findings, 558 did not have the disease.

Let’s calculate the sensitivity, specificity, PPV, NPV, LR+, and LR-. We first can start with a 2X2 Table. The information above allows us to enter the values in the table below. Notice that values in blue cells were not provided, but we can get them based on the numbers above and the utilization of total cells. See Image. Diagnostic Testing Accuracy Table 2.

The provider found that a total of 384 individuals actually had the disease, but how accurate was the blood test?

Sensitivity=(369 (A))/(369(A)+15 (C))
Sensitivity=369/384
Sensitivity=0.961
Specificity=(True Negatives (D))/(True Negatives (D)+False Positives (B))
Specificity=(558 (D))/(558(D)+58 (B))
Specificity=558/616
Specificity=0.906

Positive Predictive Value

PPV =(True Positives (A))/(True Positives (A)+False Positives (B))
PPV =(369 (A))/(369 (A)+58(B))
PPV =369/427

Negative Predictive Value

NPV=(True Negatives (D))/(True Negatives (D)+False Negatives(C))
NPV=(558(D))/(558 (D)+15(C))
NPV=(558 )/573

Positive Likelihood Ratio

Positive Likelihood Ratio=Sensitivity/(1-Specificity)
Positive Likelihood Ratio=0.961/(1-0.906)
Positive Likelihood Ratio=0.961/0.094
Positive Likelihood Ratio=10.22
Negative Likelihood Ratio
Negative Likelihood Ratio=(1- Sensitivity)/Specificity
Negative Likelihood Ratio=(1- 0.961)/0.906
Negative Likelihood Ratio=0.039/0.906
Negative Likelihood Ratio=0.043

The results show a sensitivity of 96.1%, specificity of 90.6%, PPV of 86.4%, NPV of 97.4%, LR+ of 10.22, and LR- of 0.043.

Clinical Significance

Understanding that other diagnostic test data techniques do exist (e.g., receiver operating characteristic curves), the topics in this article represent essential starting points for healthcare providers. Diagnostic testing is a crucial component of evidence-based patient care. When determining whether or not to use a diagnostic test, providers should consider the benefits and risks of the test, as well as the diagnostic accuracy. [1] By having a foundational understanding of the interpretation of sensitivity, specificity, predictive values, and likelihood ratios, healthcare providers will understand outputs from current and new diagnostic assessments, aiding in decision-making and ultimately improving healthcare for patients.

Nursing, Allied Health, and Interprofessional Team Interventions

All interprofessional healthcare team members need to understand these values as applied to diagnostic testing, so they can better analyze a patient's condition based on testing results. Any lack of understanding in this area can lead to improper diagnostic interpretation leading to sub-optimal outcomes. Healthcare team members need to collaborate openly to facilitate proper diagnosis leading to properly targeted therapeutic interventions. [Level 5]

Review Questions
Access free multiple choice questions on this topic.
Comment on this article.

Diagnostic Testing Accuracy Table. Contributed by M Huecker, MD, and J Shreffler, PhD

Diagnostic Testing Accuracy Table 2 Contributed by M Huecker, MD, and J Shreffler, PhD

Disclosure: Jacob Shreffler declares no relevant financial relationships with ineligible companies.

Disclosure: Martin Huecker declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

Cite this Page Shreffler J, Huecker MR. Diagnostic Testing Accuracy: Sensitivity, Specificity, Predictive Values and Likelihood Ratios. [Updated 2023 Mar 6]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

In this Page

Bulk download.

Bulk download StatPearls data from FTP

Related information

PMC PubMed Central citations
PubMed Links to PubMed

Recent Activity

Diagnostic Testing Accuracy: Sensitivity, Specificity, Predictive Values and Lik... Diagnostic Testing Accuracy: Sensitivity, Specificity, Predictive Values and Likelihood Ratios - StatPearls

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers