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

Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Exercise and Cardiovascular Response01:20

Exercise and Cardiovascular Response

Exercise significantly impacts cardiovascular response, which is crucial for understanding patient health and designing effective treatment plans.
Light to moderate physical activity initiates a series of interconnected responses in the body. The heart rate modestly increases in anticipation of the workout, followed by widespread vasodilation as oxygen consumption by skeletal muscles increases. This results in decreased peripheral resistance, increased capillary blood flow, and accelerated...

You might also read

Related Articles

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

Sort by
Same author

A personal reflection on co-creation in public health: a dream partly realised.

Public health research & practice·2022
Same author

Effectiveness and costs of strategies to recruit Australian adults with type 2 diabetes into a text message intervention (DTEXT) study.

Public health research & practice·2022
Same author

Improving community-based first response to out of hospital cardiac arrest (FirstCPR): protocol for a cluster randomised controlled trial.

BMJ open·2022
Same author

Measuring change in adolescent physical activity: Responsiveness of a single item.

PloS one·2022
Same author

The impact of different intensities and domains of physical activity on analgesic use and activity limitation in people with low back pain: A prospective cohort study with a one-year followup.

European journal of pain (London, England)·2022
Same author

Historical Context of Cardiac Rehabilitation: Learning From the Past to Move to the Future.

Frontiers in cardiovascular medicine·2022

Related Experiment Video

Updated: Jun 18, 2026

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
05:59

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

Non-response bias in physical activity trend estimates.

Cora L Craig1, Christine Cameron, Joe Griffiths

  • 1Canadian Fitness and Lifestyle Research Institute, Ottawa, Canada. ccraig@cflri.ca

BMC Public Health
|November 26, 2009
PubMed
Summary

This study found that changes in survey response rates did not significantly impact physical activity (PA) trends in Canadian adults. Understanding potential biases is crucial for accurate health policy decisions regarding energy balance.

More Related Videos

Physical Activity Measurement in Children Accepting Table Tennis Training
06:51

Physical Activity Measurement in Children Accepting Table Tennis Training

Published on: July 27, 2022

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption
08:45

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption

Published on: June 20, 2025

Related Experiment Videos

Last Updated: Jun 18, 2026

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
05:59

Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity

Published on: March 7, 2019

Physical Activity Measurement in Children Accepting Table Tennis Training
06:51

Physical Activity Measurement in Children Accepting Table Tennis Training

Published on: July 27, 2022

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption
08:45

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption

Published on: June 20, 2025

Area of Science:

  • Public Health
  • Epidemiology
  • Behavioral Science

Background:

  • Reported increases in leisure time physical activity (PA) and obesity present a paradox.
  • Differential bias in PA estimates over time is a potential explanation for these trends.

Purpose of the Study:

  • To investigate the impact of changing response rates on PA prevalence estimates in Canadian adults.
  • To assess potential biases in PA data collection methods.

Main Methods:

  • Analysis of national telephone surveys on PA conducted between 1995 and 2007.
  • Comparison of PA prevalence between survey participants and hard-to-reach individuals using adjusted t tests.

Main Results:

  • An increase in the number of calls needed to reach households and initial refusal rates was observed.
  • Higher PA prevalence was noted with more contact attempts, but this finding lacked statistical significance after adjustments.

Conclusions:

  • Differential non-response rates did not significantly alter physical activity trend estimates.
  • Awareness of potential biases is vital for health policymakers analyzing energy balance trends.