What is health research?

Research begins with a question and is the process of answering those questions. In health research specifically, studies are created to answer questions that increase our understanding of people’s health and ways to improve health. For example, we might want to learn more about people's health-related experiences, dig deeper into why people have specific health habits, or determine whether a new medication or medical product can treat a health condition.  

What a study looks like depends on the types of question researchers want to answer. Different types of research can be used to answer different questions. 

Who manages health research studies? 

Many people are involved in making a research study happen because there is a lot that goes into  a successful study. For example, someone needs to decide:

• Who should be in the study
• How those people can learn about, sign up for, and get paid for the study
• What the study steps should look like
• What data should be collected
• How the data should be analyzed

Study teams can range from a small group of people working together to much larger groups where everyone has a very specific job. In general, the people in charge of leading health research studies are the study sponsor and a principal investigator (PI). They are supported by a variety of research staff.  

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When and Where do health research studies happen?

Health research takes place all year round, at many different places. The right place for a study often depends on the questions it wants to answer.  For example, some studies take place in person, at locations called “research sites”. Research sites can be a part of a hospital, private medical practice, or a university. Study volunteers go to research sites when the study involves in-person activities, like face-to-face interviews, lab tests or other clinical procedures, or the use of devices people do not have at home. 

Other studies are conducted completely virtually, often via smartphones or computers. These studies are sometimes called “decentralized” studies because participants do not have to go to a central study location or medical office and can participate remotely, from where they are. 

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What do health research studies look like?

Different types of research can be used to answer different questions. The diagram below explains some of the different kinds of research. We'll talk more about the specific types of studies we do at Evidation (formerly Achievement) Studies in a future Research 101 post.

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Who participates in health research studies?

The most important part of health research is the study participants. Study participants are volunteers who consent (in other words, give their permission) to be in a study. They provide data through surveys, labs, assessments, and other study activities, which help researchers answer their research questions. 

Study participants are crucial to the success of a study and the future of healthcare and medicine. Without study volunteers, there is no study. And with no studies, there are no improvements to healthcare.

Where can I learn more about how to participate?

The Evidation app is great for managing your health and for offering you opportunities to participate in research.

Clinicaltrials.gov is a registry of clinical trials that provides the public with information on past and current trials.

Thanks for taking the time to learn more about health research and how it can make a difference for you and the world around you. If you have any questions, feel free to contact us at study@evidation.com.

Doctors and scientists use a lot of language that can be hard for the average person to understand. This "jargon" helps them communicate effectively with one another, but it can make learning about research difficult.

When we talk about health research, we sometimes need to use these terms to be as specific and transparent as possible.

So, to help, we've put together this list of common research terms and their definitions.

Common Health Research Terms

You can refer back to this page anytime you need to, and we'll update it to reflect new topics we post about.

Aggregate data

Data from a group of individuals that is combined into a summary format, for example, in tables or graphs. When data is aggregated (combined), individuals cannot be identified by their data. 

Clinical Research

Clinical research is a type of health science which aims to produce knowledge that is valuable for understanding human disease, preventing and treating illness, and promoting health.  

Coded study data

Data from a study which does not contain personally identifiable information (PII), for example, name, address, date of birth, social security number, etc. The PII is replaced by a code (usually a string of random letters and numbers) so no one can know who the participant is just from looking at the dataset. The participant’s corresponding personal information is kept separate to protect their identity as much as possible.

Cohort

A group of individuals who share a common characteristic or group of characteristics who are observed in a study. For example, the feature they may have in common could be a health diagnosis or a treatment assignment.

Sometimes, this term can also be used to refer to a group that a study participant is assigned to, such as a “study branch”, "study group", or “study arm”. 

Examples:

• In a study on diabetes, researchers may observe a set of traits patients diagnosed with diabetes who are on insulin (cohort 1) and who are not on insulin (cohort 2)
• In a study on how social media affects people of different ages, researchers might  observe symptoms in people age 10-15 (cohort 1), 16-20 (cohort 2), and 21-25 (cohort 3)
  

Confidentiality

Confidentiality refers to how an individual’s personal data is protected by people or groups granted permission to process it. It refers to how a person’s information is treated once it has been shared. Maintaining confidentiality is an important way to protect privacy and build trust.

Control group

The control group in a randomized controlled trial does not receive an “experimental treatment”, or the treatment that is being tested. Instead, they may receive no treatment, or another treatment that gets compared to the treatment being tested. The purpose of the control group is to compare research results between the group that receives the treatment and the group that doesn’t. 

For example, in a study that wants to learn whether a pain medication is helpful, one group would get the pain medication and the other group wouldn’t. The group that does not receive the pain medication is known as the control group. The data from these two groups could then be compared to learn more about whether the pain medication (the treatment or drug) is helpful.

De-identification

A process used to remove any personally identifying information (or PII) from data collected during a study. This is used to protect the identity of participants in a research study.

De-identified data

Data that is not linked to any personally identifying information (or PII), which means that it cannot be linked back to a specific person. 

Decentralized trial

A research trial that is not conducted at a physical location or “site” (also referred to sometimes as a “siteless” trial). Instead of having participants come to a location to complete study activities, they are able to participate from where they are (i.e. online, using home care, telemedicine visits, etc.)

Eligibility criteria

Criteria for who can or cannot participate in a research study, as defined by the researchers. These criteria must be met by all participants. Eligibility criteria are put in place to make sure that the researchers are able to get meaningful data to answer the study’s research questions, and/or protect people who may experience negative effects from a study. Eligibility criteria are different for any study.

For example, a study researching a birth control pill in females may exclude males. That same study may exclude females with heart conditions for their safety, if the birth control being tested is known to cause heart problems.

Eligibility screening

Questions or activities used to determine (or “screen”) if a person is eligible to participate in a study. This often occurs in the form of a survey, but could include other activities such as interviews or medical assessments.

Enrollment

The process of entering into a research study or trial. This can include a variety of steps, including agreeing to participate in a study by signing the informed consent form.

Exclusion criteria

Any criteria that would make a person ineligible to participate in a study. Exclusion criteria are created by the researchers to make sure the study results are meaningful and to protect potential participants from study activities that could be harmful to them. 

For example, a study may exclude participants who take a blood pressure medication, if there is reason to believe that people taking that type of medication could be harmed by the study. 

Good Clinical Practice

Good Clinical Practice (GCP) is an international guide for how to conduct ethical and good quality research. GCP applies to every aspect of a study, from start to finish. The purpose of this guide is to protect the rights and safety of study participants, as well as ensure the integrity and quality of study data.

Health research

Research that aims to learn about human health. This type of research can help us learn about, prevent, and treat health conditions. Also sometimes referred to as clinical research. 

HIPAA

HIPAA stands for the Health Insurance Portability and Accountability Act of 1996. It is a U.S. federal law that created guidelines to protect patients' PHI (personal health information). For more details on how HIPAA applies to research, click here. 

Inclusion criteria

Criteria that a person must meet to be eligible to participate in a study. 

For example, a study that is researching a blood pressure medication may require individuals to have high blood pressure. 

Informed consent

A process by which a person voluntarily confirms that they are willing to participate in a particular study. During this process, the person is given detailed information about the study so that they can make an informed decision about whether they want to participate. If a person decides to participate in a study, their consent is documented on an Informed Consent Form.

Informed Consent Form (ICF)

A form used to explain and document a person’s willingness to participate in a specific study. The form provides any important information a person needs to be able to decide whether participating in the study is right for them. For example, the form will include information on the purpose of the study, who is conducting the study, and any risks.

Interventional Research

Studies which are designed to understand the effects of treatment or preventive measures on a condition. This can also be described as “experimental research.” 

For example, a researcher may want to understand if an anxiety medication can also be used to treat chronic pain. In such a study, the researcher may give the anxiety medication to individuals with chronic pain, to see if the medication affects them. 

Institutional Review Board (IRB)

A group which independently reviews any research involving people. This group is made up of at least five members with different scientific and non-scientific backgrounds (for example, researchers, doctors, nurses, scientists, psychologists, patients, etc.)  The role of the IRB is to ensure that participants' rights and welfare are protected and that studies are carried out in an ethical manner.

Observational Research

Studies which are designed to observe what happens to a group of participants. Unlike interventional research, observational research does not try to introduce a treatment or product, but instead observes how participants behave naturally.

For example, a researcher may want to observe how depression affects the average number of steps a person walks per day. 

Participant

A person who enrolls (or takes part) in a research study after signing an informed consent form and completing any other study-required enrollment activities.

Person-Generated Health Data

Health-related data that is created, recorded, or gathered by individuals (or by family members or caregivers). Sources of PGHD include wearable devices or phones, electronic surveys, apps, or any other interactions with technology that generate personal data about health. 

Personally identifiable information (PII)

Personally identifiable information (PII) is any form of sensitive data that can be used to identify a person (for example, name or social security number). A study that collects PII is required to protect that data.

Privacy

Privacy refers to a person’s right to limit access or processing of their personal information by other people or groups. This can include controlling what, how much, and when personal information is shared with others

Principal Investigator

The person(s) who leads and takes overall responsibility for a research study. Typically, this is a medical doctor or someone with a doctorate degree in a health field. The Principal Investigator (PI) makes sure that the research follows good scientific and ethical practices and that it can answer the research questions being asked (often, being asked by a study sponsor). The PI also oversees the research support staff.

Protected Health Information (PHI)

Protected Health Information (PHI) refers to personal health-related information that is shared between individuals or organizations who provide treatment, payment, and operations in healthcare. For example, this can include Medical Record Numbers, hospital bills, lab reports, etc. 

It’s important to note that PHI is different from PII. PII is an umbrella term for any information that can be traced to an individual’s identity, while PHI refers specifically to identifiable health information possessed by HIPAA covered entities. 

Protected group

Groups of people who are provided additional protections in health research based on federal regulations. In some cases, individuals in these groups may not be able to legally consent to participating in research by themselves and may require consent to be given by a caregiver or legally authorized representative. 

Examples of protected groups include children, pregnant women, and prisoners. 

Randomized Controlled Trial (RCT)

A study in which researchers randomly assign participants to different groups (also called arms or cohorts). The goal is to minimize bias and then compare the study results between the groups.

For example, a study may randomly assign participants to take either a new medication or a sugar tablet every day. The researchers will then use the data from participants to learn if the medication made a difference for the group that received it.

Real-world evidence

Clinical evidence that is generated from real-world data about the use, risks, and/or benefits of a medication, product, or treatment. 

Real-world data

Data about the use, risks, and/or benefits of a medication, product, or treatment that come from a variety of sources. For example, real-world data can come from clinical sources like electronic health records, claims and billing activities, product and disease registries. Or it can come from everyday sources like health apps and fitness trackers. 

Research

The process of using scientific methods to collect, analyze, and interpret data collected from studies to contribute to knowledge about a topic. 

Research site

A location where research is conducted. This can include hospitals, universities, private medical practices, research institutes, and more. 

Sponsor

A sponsor may be an individual or pharmaceutical company, governmental agency, academic institution, private organization, or other group that initiates, oversees, and/or is financially responsible for the research. 

For example, a pharmaceutical company may initiate research to learn if the drug they make works, and pay another independent organization to actually conduct the study. 

Study

Where research methods are used to collect, analyze, and interpret data collected from participants to contribute to knowledge about a topic. 

Study data

Information collected during a research study. It can include demographic information (race, age, education level), health information, descriptions of the participant’s progress, and other relevant information.

Withdrawal

The process of exiting a research study or trial. All research studies are voluntary, which means that participants are free to stop participating at any time for any reason.

COVID-19 continues to occupy our minds and affect our everyday lives. As vaccinations rolled out, questions emerged around what new directions the virus would take. For our third survey on COVID-19 Vaccination Perceptions and Behaviors (“Survey 3”), which was open between April and June 2021, we wanted to understand how people’s feelings and behaviors evolved as vaccination efforts continued in our communities.

We learned what percentage of members had gotten at least one vaccine, when they decided to get vaccinated, and what activities they felt comfortable resuming. The data also show interesting shifts in behaviors and mindsets compared to our previous surveys, and we’re excited to dive into some of the details with you below!

For an overview of the study objectives, methods, and results from the first perceptions and behaviors survey, please see our original blog post here. You can find the preliminary results from our second perceptions and behaviors survey here.

Background

74,740 people (“participants”) completed Survey 3. The average age of participants was 39.1, which is slightly higher than the previous surveys. Most participants identified as female (80.7%) and identified as white (79.6%).

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Vaccination Perceptions and Behaviors

The main focus for this survey was to examine people’s beliefs and preferences around COVID-19 vaccination now that access to the vaccine is more widespread.

72.6% of Survey 3 participants reported having received at least one COVID-19 vaccine.

This percentage represents a substantial increase compared to our last survey, in which only 11.4% of participants had received a vaccine. We expected to see an increase since more people were eligible for vaccination during Survey 3 than in Survey 2 (which launched in January 2021), but were surprised by the magnitude: for comparison, only about 63% of the US adult population had received at least one vaccine when the survey closed (see here for the CDC’s summary of COVID and US vaccination in early June).

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A majority of vaccinated participants received the Pfizer vaccine (53.8%), followed by Moderna (39.2%) and Johnson & Johnson (6.7%).

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Most vaccinated participants were eager to get the vaccine as soon as they became eligible. (63.3%).

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For many people, increasing access to COVID-19 vaccination was accompanied by a return to certain activities that had been put on hold. Between April and June, 47% of vaccinated participants started attending indoor events with others who are vaccinated, and 43.9% began eating in restaurants again. Meanwhile, 15.9% of participants reported that they had not yet resumed any activities.

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Changing Trends Over Time

We were happy to see a number of positive trends when we looked at evolving perceptions throughout the three surveys we’ve completed in the series so far. For example, Survey 3 participants tended to report lower hesitancy about COVID-19 vaccines compared to previous surveys.

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This decrease in hesitancy may be due to an increase in information: Survey 3 participants reported feeling even more informed about the vaccines than previous survey participants. 68.9% of people reported feeling “informed” or “very informed”, compared with 53.3% in Survey 2 and 27.1% in Survey 1.

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Participants also reported being increasingly likely to get their children vaccinated when they could. 37.2% of participants reported that they would vaccinate their children when they were able to, compared to 26.9% in Survey 2 and 19.2% in Survey 1.

We look forward to exploring more about decisions to vaccinate children in our next Perceptions and Behaviors survey.

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Next Steps

To understand how people’s perceptions and behaviors related to COVID-19 vaccination have continued to evolve as variants spread and vaccines became available to children, we will soon send an additional survey on Evidation Members’ perceptions and behaviors. Stay tuned for more!

If you’d like to get vaccinated, see this CDC page with resources to find appointments near you.

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The release of COVID-19 vaccinations has been a symbol of hope to many people — -and a source of hesitancy to some. For our second survey on COVID-19 vaccination perceptions and behaviors (which we will refer to as “survey 2” throughout this blog post), we wanted to understand how people were feeling about the vaccines as people first started getting access to them. We launched the survey in January 2021, and are excited to share some preliminary results with you!

Participants

100,080 people (“participants”) completed survey 2. 54,701 have completed all surveys in the study so far. The mean age of survey 2 participants was 37.4 (standard deviation: 12.2 years). The majority of survey 2 participants identified as female (80.8%) and identified as white (78.0%).

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Vaccination Likelihood and Hesitancy

One of our main focuses for this survey was to examine how COVID-19 vaccination likelihood and hesitancy has evolved over time.

11.4% of participants had already gotten a COVID-19 vaccine when they took the survey, with an additional 0.6% reporting participating in COVID-19 vaccination trials:

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Overall, survey 2 participants reported being more positive about COVID-19 vaccination than they had been previously. 30% of participants reported feeling more likely to get a COVID-19 vaccine than they had been a month ago:

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People reported a range of reasons for their likelihood of vaccination increasing, with some common responses including:

• Feeling more informed about COVID vaccination overall (for example, “learned more information about it”, “just thinking and researching”)
• Feeling more confident about COVID vaccination safety as more data and research were released (for example, “more data on potential side effects”, “studies are getting better and more people are receiving it.”)
• Feeling more confident about COVID vaccination safety as they saw their friends, family, and community starting to get vaccinated (for example, “seeing those I respect get it”, “watching people I know get it with little adverse side effects”)

We saw a similar trend looking at the differences between reported vaccination likelihood in the first and second surveys; mean reported likelihood was 4.93 in survey 1 (median=5), and 6.53 in survey 2 (median=8.0):

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Although the majority of participants (51.5%) still report being more hesitant about COVID-19 vaccines than other vaccines, a higher percentage of survey 2 participants reported being equally or less hesitant than survey 1 participants:

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Vaccination Informedness

As mentioned above, one common reason people gave for their increase in vaccination likelihood was feeling more informed about the vaccines. Our data reflect this increase in self-reported informedness; in survey 1, only 27.1% of participants reported feeling “informed” or “very informed”, but 53.3% did so in survey 2:

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The most common pieces of information unvaccinated participants reported needing to know before deciding to get the COVID-19 vaccine were all potential side effects (62.7%) and possible long-term impacts of vaccination (58.9%).

We look forward to further investigating these current perceptions and behaviors and see how they change as more people become eligible for vaccination!

Next Steps

To understand how people’s perceptions and behaviors related to COVID-19 vaccination continue to evolve as vaccines become available more broadly, we will send additional surveys over the following months asking for Evidation Members’ perceptions and behaviors. The exact dates of these future surveys will depend on developments in the pandemic and COVID-19 vaccination, so stay tuned for more!

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If you’d like to get vaccinated, see this CDC page with resources to find appointments near you.

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Our Research, Analytics, and Learning team is exploring and analyzing data from our Evidation platform, where members contribute to research and help us uncover insights that could improve their health and the health of others.

During this year’s presidential election there was high voter turnout which included record-breaking numbers of mail-in ballots due to COVID-19. As we now know, this high volume of ballots required multiple days to count, so no final winner could be projected on Election Day. We decided to look at Evidation Members activity data to see what changes the election may have caused for our members.

We used Fitbit data contributed by Evidation Members, to explore sleep characteristics and schedules for the month leading up to Election Day in 2020. We looked specifically at the time that each member went to bed in their local timezone. Equivalent time periods in 2017–2019 were used for comparison. These periods were aligned across years based on week rather than calendar date, so that differences in weekend and weekday sleep cycles would line up. This also syncs the end of daylight saving time, which happened on November 1, 2020, the Sunday two days before Election Day, and temporarily shifts our sleep cycles earlier. Positioning the data in this way allows for appropriate comparisons of data across years.

So, did anything about our sleep change? This plot shows the average time Evidation Members started sleeping on the weeks leading up to and immediately after daylight saving time from 2017–2020:

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There is a clear weekly pattern: we go to bed later on Friday and Saturday nights, when we have a weekend day ahead of us. On daylight savings weekend we started sleeping slightly earlier as we adjusted to the end of daylight saving time, a trend which continues through the following week as we slowly adjust to going to bed later again. However, on Election Day 2020 this pattern was disrupted; bedtimes spiked up over 20 minutes from Sunday and Monday night.

You may also notice the interesting pattern of later bedtimes in 2017, leading up to daylight saving time. This lines up with Halloween night and games 6 and 7 of the 2017 World Series. We’ve examined the impact of the 2017 World Series on sleep in the past.

As we looked closer at our sleep data, we were curious to see if members on the East Coast stayed up later in their time zone than those on the West Coast while they waited for results, so we examined average bedtimes in each time zone. On election night, members on the East Coast stayed up the latest (11:51 PM), compared to members in the Central (11:39 PM), Mountain (11:39 PM), and Pacific (11:43 PM) time zones. Compared to the previous night, members in Eastern Standard Time stayed up 22 minutes later, Central Standard Time 20 minutes later, and Mountain Standard Time 23 minutes later, while members in Pacific Standard Time stayed up only 14 minutes later.

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Regardless of where we live, sleep is an important part of our health. Fortunately, later bedtimes due to the election were confined to Tuesday night. Bedtimes returned to normal after Election Day, as it became clear that election results would take at least several more days to be projected.

Did you stay up late on Election Day? If you have tips to reduce stress or improve sleep, we’d love to hear them.

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We are all looking forward to the end of the COVID-19 pandemic and the disruptions it’s caused in our lives. A safe and effective COVID-19 vaccine will form part of the public health strategy to help us reach this endpoint faster. As many organizations work to develop and release such a vaccine, we wanted to understand people’s evolving perceptions and behaviors related to COVID-19 and vaccinations. We launched the first set of surveys in our study in October, and are excited to share some preliminary results with you!

Objectives

This study’s goal is to describe people’s perceptions and behaviors around the COVID-19 vaccine. For example, what reasons do people have for getting or not getting the COVID-19 vaccine? How likely are they to get it once it’s released? Has the pandemic encouraged people to get the flu shot? This study will investigate whether and how these perceptions and behaviors change over time, as COVID-19 vaccines are developed and released.

Methods

To describe people’s perceptions and behaviors, and how those perceptions and behaviors change over time, we are asking for people’s input through a series of online surveys. These surveys will be sent throughout the development and release of COVID-19 vaccines.

So far, we’ve launched 2 surveys: one to understand the backgrounds of the people participating (for example, their demographics, where they live, whether they’re at risk for COVID-19), and one to characterize current perceptions and behaviors. We have started analyzing the data collected between October 9th, 2020 and November 11th, 2020. We won’t be able to understand how perceptions and behaviors have changed until we launch the next survey, but we can start to describe how people are currently feeling about the COVID-19 vaccine!

Preliminary Results

Here are some preliminary results from our first 2 surveys.

Participants

64,750 people (“participants”) have completed the first perceptions and behaviors survey. Mean age was 38.5 (SD: 11.7 years), and the majority of participants identified as female (79.7%) and identified as white (80.0%).

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All 50 states (plus Puerto Rico and Washington, DC) are represented:

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Vaccination Likelihood, Motivators, and Barriers

On average, participants were on the fence in terms of likelihood of getting the COVID-19 vaccine when it’s released (mean=4.93, median=5). The distribution shows a wide range of opinions, with the largest numbers of people reporting at:

• 0 (“Very unlikely”): 18.8%
• 5: 13.6%
• 10 (“Very likely”): 14.3%

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The most common reasons people reported for getting the COVID-19 vaccine were to:

• help protect their family, friends, or community (59.9%)
• lower their chances of getting COVID-19 (56.7%)
• lower their chances of having to go to the doctor or getting hospitalized due to severe COVID-19 symptoms (53.7%)
• feel more comfortable spending time with their friends, family, or community (55.7%)

The most common reasons people had to not get vaccinated were because they were:

• concerned the vaccine is being approved too quickly (61.3%)
• concerned about possible side effects (60.1%)
• not sure the vaccine will be safe (56.2%)
• not sure the vaccine will be effective (57.0%)

Relative Vaccination Hesitancy

Most participants reported feeling more hesitant about the COVID-19 vaccine than other vaccines (68.0%), with 24.9% feeling equally hesitant and 7.1% feeling less hesitant:

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Vaccination Informedness

We’ve also found that people don’t feel particularly well-informed about the COVID-19 vaccine in general. 19.8% of participants report feeling “Not at all informed”, 22.7% “Slightly informed”, 30.4% “Moderately informed”, 19.2% “Informed”, and only 7.9% “Very informed”:

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Pandemic Influence on Flu Shot Plans and Behavior

The CDC has stressed that getting the flu shot this season is more important than ever, to help protect oneself and others and to minimize burden on the healthcare system. Many participants seem to agree: of the 35,997 participants who had not gotten the flu shot yet (or were unsure), 20.2% reported being more likely to get it this season due to the pandemic:

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Of the 28,753 participants who had gotten the flu shot, 20.0% reported that the pandemic encouraged them to get it, and 9.1% reported the pandemic was the primary reason they did so:

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We are excited to continue to investigate these current perceptions and behaviors and see how they change over the coming months!

Next Steps

To understand how people’s perceptions and behaviors related to COVID-19 vaccination evolve over the development and release of vaccines, we will send more surveys over the following months asking for Evidation Member’s perceptions and behaviors. These surveys will be sent as big events happen around the vaccine’s development, like its approval or release. The exact dates of these future surveys will depend on when these events happen, so stay tuned for more!

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This February, in honor of Heart Health Awareness Month, we partnered with the data science team at Evidation to look at patterns of some of our heart healthiest members.

Resting heart rate (your pulse rate while awake, relaxed, and stationary) has been shown in several large epidemiologic studies to be an independent predictor of cardiovascular disease and all-cause mortality in both men and women. Given the importance of resting heart rate for heart and overall health, the team looked at all of the Evidation Members who contributed resting heart rate data in 2018. We explored the trajectory of resting heart rate from week to week and selected a handful of members that significantly dropped their resting heart rate over the year. The individuals we selected had a wide range of resting heart rates to begin the year.

Of the members we selected, 96% were within the normal range of 60–100 beats per minute. According to the Harvard Health blog, “while a heart rate is considered normal if the rate is between 60 and 100 beats per minute, most healthy relaxed adults have a resting heart rate below 90 beats per minute.” Only 4% had resting heart rates below 60 beats per minute at the beginning of the year. Resting heart rates below 60 bpm are often indicative of people who get a lot of physical activity. Near the end of the year, over 30% had reduced their resting heart rate to 60 beats per minute or lower. Overall, we observed an average drop of 11 beats per minute, which corresponds to an average decrease of 15% from the beginning of the year.

We then asked these resting heart rate improvers to tell us a little bit more about what they did in order to better understand their habits throughout the year — everything from how often they checked their heart rate, to the frequency of their workouts, to dietary changes they had made throughout 2018.

Here’s what we found!

Most members who had a significant decrease in resting heart rate in 2018 also noticed the same thing!

Most of our heart healthy members said they checked their resting heart rate frequently — if not every day, then at least a few days per week.

The most common changes that Evidation Members made to their diet included the following:

• Adjusting their portion sizes
• Limiting consumption of fast food
• Consuming more vegetables and fruit

The most common types of physical activity included:

• Walking
• Lifting weights
• Running
• Hiking
• Yoga

When we took a closer look at activity data, we actually saw an increase of 871 steps per day (12.3% increase) for members who had lowered their heart rate. Those who responded that they did more walking in 2018 truly did up their step count.

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Evidation members overwhelmingly said that they had lost weight, made changes to their diet, exercised more often and regularly, and focused on maintaining a healthy weight when sharing some of the changes that they made to their lifestyle in 2018.

In fact, when we took a look at weight tracking for our heart healthy members, the data matched up with the responses. For those who tracked their weight at least once per week for 30 weeks or more, the average weight loss was 12 pounds (a 6% decrease on average).

Not surprisingly, mental health and improved sleep can significantly influence an individual’s overall quality of health. Did you know that sticking to a sleep schedule can help you improve your heart health?

Our community of heart healthy members have recommended to others the value of maintaining a healthy diet, exercising more, and managing stress as tips to improve heart health.

For advice on how to take action today to make your lifestyle a little healthier, check out these additional suggestions from some trusted sources:

• Heart Healthy Recipes from the NIH
• CDC Heart Month Feature from the CDC
• Taking Care of Our Hearts, Together from National Heart, Lung, and Blood Institute‍
  

We know that anxiety and depression affect many of you, with 7 out of 10 adults in the U.S. saying they experience stress or anxiety daily. Depression and anxiety can have a huge impact on our daily lives and overall health. It can affect our mood, social interactions, sleep and more, but can our daily behaviors predict the severity of our anxiety and depression? Our research team sought to find out more.

What we tested

We enrolled over 1,000 participants in a clinical study with self-reported anxiety and depression and assessed the participants’ mental health states by looking at the following for each individual:

• Anxiety and depression symptoms
• Number of hospitalizations and ER visits for anxiety/depression
• Use of anxiety and depression medications

We then looked at participants’ sleep metrics and patterns for the previous three months.

What we learned

Severe depression was significantly associated with inconsistent and disordered sleep patterns, such as spending a great amount of time in bed awake. Individuals taking medications for their anxiety and/or depression were likely to sleep more compared to those not receiving treatment, however, they also had inconsistent sleep patterns. Participants who had been previously hospitalized for anxiety and/or depression were more likely to have inconsistent sleep patterns as well.

What does this mean?

We all know that a lack of sleep can affect our daily lives, but it can also be associated with severe depression and anxiety. This means that certain sleep patterns might be able to predict the severity of an individual’s mental well-being in the future. With further research we’d like to understand if tracking sleep behavior could predict changes in the severity of an individual’s mental health condition.

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Thanks to all of our members who participated in this research about how daily behaviors, like sleep, can tell help researchers to better understand anxiety and depression. If you’re interested in contributing to innovative research, we are regularly running new studies at Evidation.

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