Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Expected Value01:15

Expected Value

7.8K
The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
7.8K
Determination of Expected Frequency01:08

Determination of Expected Frequency

2.6K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.6K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

8.7K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
8.7K
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

11.4K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
11.4K
Mechanical Ventilation II: Invasive Ventilation01:23

Mechanical Ventilation II: Invasive Ventilation

773
Ventilators are essential medical equipment used to aid patients with respiratory difficulties. Their primary function is to assist or replace spontaneous breathing by providing mechanical ventilation. There are two general classes of mechanical ventilators: negative-pressure and positive-pressure ventilators.
Negative-Pressure Ventilators
Negative-pressure ventilators create a vacuum around the chest or body to draw air into the lungs, simulating breathing. This method does not require an...
773
Blind Procedures02:07

Blind Procedures

13.5K
Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
13.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The Role of L4-L5 Facet Joint and Disc-Related Anatomy in Lumbar Spondylolisthesis: An Imaging Study.

Spine·2026
Same author

Balancing Act: Infection Risks of Nonoperative Treatments Before Lumbar Fusion: Commentary on an article by Sahyun Sung, MD, et al.: "Effect of Preoperative Acupuncture and Epidural Steroid Injection on Early Postoperative Infection After Lumbar Spinal Fusion".

The Journal of bone and joint surgery. American volume·2026
Same author

The relationship between distal lumbar lordosis correction and early postoperative L1-pelvic angle changes in adult spinal deformity surgery.

Spine deformity·2026
Same author

Quantitative Swept-Source Optical Coherence Tomography Angiography Indicators of Neurovascular Dysfunction in Alzheimer Disease.

JAMA ophthalmology·2026
Same author

Response to letter to the editor regarding "preoperative frailty and muscle composition are associated with postoperative satisfaction and decisional regret after adult spinal deformity surgery".

Spine deformity·2026
Same author

Anterior Cervical Approach to Vertebral Artery Exposure: A Step-By-Step Surgical Technique Guide By the Cervical Spine Research Society.

Clinical spine surgery·2026

Related Experiment Video

Updated: Feb 6, 2026

Optimizing Minimally Invasive Spine Surgery: A Fully 3D CT O-Arm Navigated Workflow in MIS TLIF
08:34

Optimizing Minimally Invasive Spine Surgery: A Fully 3D CT O-Arm Navigated Workflow in MIS TLIF

Published on: October 17, 2025

558

Expectation Versus Reality: Exploring Decisional Regret in Minimally Invasive Lumbar Spine Surgery.

Michael Jeffko1, Aiyush Bansal2, Kenneth T Nguyen2,3

  • 1School of Medicine, University of Washington, Seattle, Washington, USA.

Neurosurgery
|February 4, 2026
PubMed
Summary

Patient expectations significantly impact satisfaction after minimally invasive lumbar decompression. Mismatched expectations, especially regarding pain relief, strongly correlate with decisional regret (DR).

Keywords:
Decisional regretDecompressionLumbar spine surgeryMODEMSMinimally invasive surgeryPatient satisfactionPatient-centered care

More Related Videos

A Mouse Model of Lumbar Spine Instability
05:28

A Mouse Model of Lumbar Spine Instability

Published on: April 23, 2021

9.1K
Clinical Application of Microscope-Assisted Minimally Invasive Anterior Lumbar Interbody Fusion
04:42

Clinical Application of Microscope-Assisted Minimally Invasive Anterior Lumbar Interbody Fusion

Published on: June 16, 2023

1.2K

Related Experiment Videos

Last Updated: Feb 6, 2026

Optimizing Minimally Invasive Spine Surgery: A Fully 3D CT O-Arm Navigated Workflow in MIS TLIF
08:34

Optimizing Minimally Invasive Spine Surgery: A Fully 3D CT O-Arm Navigated Workflow in MIS TLIF

Published on: October 17, 2025

558
A Mouse Model of Lumbar Spine Instability
05:28

A Mouse Model of Lumbar Spine Instability

Published on: April 23, 2021

9.1K
Clinical Application of Microscope-Assisted Minimally Invasive Anterior Lumbar Interbody Fusion
04:42

Clinical Application of Microscope-Assisted Minimally Invasive Anterior Lumbar Interbody Fusion

Published on: June 16, 2023

1.2K

Area of Science:

  • Spine Surgery Outcomes
  • Patient-Reported Outcomes
  • Shared Decision-Making

Background:

  • Unmet patient expectations can decrease satisfaction and increase decisional regret (DR) in elective spine care.
  • Minimally invasive lumbar decompression (MILR) requires understanding patient expectations for optimal outcomes.
  • This study investigates the link between expectation-actuality differences and DR in MILR patients.

Purpose of the Study:

  • To evaluate the correlation between patient expectation-actuality differences and DR after MILR.
  • To identify other patient-reported outcomes associated with DR in this population.
  • To inform preoperative counseling strategies for improved patient satisfaction.

Main Methods:

  • Prospective cohort study of adults undergoing elective MILR.
  • Patients completed preoperative and postoperative surveys (MODEMS) assessing expectations and outcomes.
  • Decisional Regret Scale (DRS) and expectation-outcome mismatch were analyzed using univariate linear regression.

Main Results:

  • DR was strongly associated with greater expectation-outcome mismatch across all domains.
  • Mismatch in pain relief, daily activity, exercise, sleep, return-to-work, and disability prevention predicted higher regret.
  • Demographic and clinical factors were not associated with regret; MODEMS mismatch was the most consistent predictor.

Conclusions:

  • Decisional regret after MILR is significantly linked to expectation-actuality differences.
  • Pain relief, activity levels, and exercise are key drivers of unmet expectations and subsequent regret.
  • Refining expectation assessment tools is crucial for reducing regret and enhancing patient-reported outcomes.