No, You’re Probably Not Dying. How to Stop Your Smartwatch Health Anxiety


It began as a headache, but by the end of the rabbit hole I fell down, I was staring at the possibility of a deadly brain tumor. Just weeks later, a slight cough spiraled into fears that I’d contracted a first-of-its-kind, pandemic-style illness that would bring about my own — and the world’s — demise.

I’m a wellness writer with health anxiety. Otherwise known as hypochondria or illness anxiety disorder, it’s a condition that makes me worry I am or may become ill even when I’m healthy.

What’s ironic is that part of my job involves testing devices that monitor my health, wearables including fitness trackers and smart rings. While I love exploring this technology and do think it can help you learn more about your body, I have to be careful about how I use it so my anxiety isn’t triggered. I know I’m not alone

“Healthy adults and individuals with pre-existing medical conditions are increasingly using these devices to manage their health,” says Dr. Lindsey Rosman, assistant professor of medicine in the Division of Cardiology and co-director of the Cardiovascular Device and Data Science Lab at the University of North Carolina School of Medicine. “Whether 24/7 access to health information from a wearable actually helps or potentially harms people is really unclear.”

To collect health data, you used to have to visit your doctor or rely on single-purpose devices such as blood pressure or heart rate monitors. Now, advancements in wearable technology over the last decade have built an entire industry focused on around-the-clock health tracking that can help you train more efficiently or even alert you to signs of potential illness.

Yet, being inundated with health data isn’t just bothersome; it can be harmful. Especially when you consider the widespread impact: About one in five US adults regularly wear a smartwatch or a wearable fitness tracker, according to a July 2019 Pew Research Center survey. That number has likely grown as the number of wearables on the market continues to increase.  

When you add in the ability to search your symptoms online or ask an AI chatbot in your wearable’s app every health question under the sun, it becomes even more difficult to discern between what’s helpful and harmful. 

To help myself and others with health anxiety navigate the world of wearables so we can either enjoy using them or know when it’s time to stop, I reached out to experts for their advice.

1. Turn off the alerts that cause panic

Rosman has observed clinically that it can be beneficial to either scale back or turn off the features that make you anxious. This can be especially helpful for people with pre-existing conditions that are already being treated, such as atrial fibrillation (AFib, an irregular heartbeat), as your wearable’s irregular heart rhythm notifications will only make you anxious and can prompt you to see your doctor when it’s not medically necessary.

Plus, certain medications can affect the accuracy of wearable sensors, provoking false alarms. 

“We published a case report on a patient who performed over 900 EKGs [electrocardiograms or ECGs, which measure the heart’s electrical activity] on her smartwatch in a single year,” says Rosman. While most of the EKGs were normal, inconclusive alerts fueled her anxiety, leading to multiple ER visits, spousal conflict and the need for therapy to reclaim her daily life. The patient had no psychiatric history prior to getting a smartwatch.

An Apple Watch 11 showing the "Possible Hypertension" alert

When you get an unexpected health alert on your device, it can understandably cause panic.

Cole Kan/CNET/Apple

Dr. Karen Cassiday, author of Freedom from Health Anxiety and owner and managing director of the Anxiety Treatment Center of Greater Chicago, says that even patients who don’t have health anxiety can find wearables to be intrusive when they get too many alerts. “They discover they want to be less aware of every moment of their body’s functioning,” she says.

Thankfully, most wearable health features can be turned off completely or customized. 

For instance, Shyamal Patel, SVP of science at Oura, maker of the Oura Ring, shares that the device’s Personalized Activity Goals allow you to choose to see steps instead of calories, adjust your daily activity goal or hide calories completely, which can be necessary for anyone who finds calorie counting triggering or overly rigid. 

2. Be intentional about checking your device 

Referring to a 2024 study she worked on that examined the impact of wearables on the psychological well-being of patients with AFib, Rosman says that about half of the participants were checking their heart rate every day out of habit, not because they felt symptoms. 

Cassidy explains that while people with health anxiety may initially find wearables helpful, compulsively checking to make sure their vitals are normal can accidentally become a form of negative reinforcement that further propels the anxiety.

“Often when I work with anxious people, we try to cut back or eliminate the need to compulsively check for reassurance on their wearables, as well as with ChapGPT or other digital ‘doctors,’” says Cassiday. 

When people refrain from compulsively checking, wearables can provide useful feedback that counters the false belief that something terrible will happen to their health.  

If checking your health metrics causes anxiety, try reducing how often you view them on your device or in its app. Setting an alert to check weekly, at a minimum, could help — especially since it’ll give you a broader picture, making you less likely to hyperfocus on a single data point that seems off. 

You should also avoid checking your wearable’s health information right after you wake up or before you go to bed, as this can set the tone for an anxious day or make it harder to fall asleep. 

If having a screen on your wrist makes it difficult for you to stop checking, a screenless smart ring or fitness tracker such as the Whoop 5.0 may be a better option, since they rely on apps instead of screens.

A close-up of the silver Oura Ring 4 on a pointer finger in front of a white wall.

A screenless smart ring may help you stop compusively checking your device.

Anna Gragert/CNET

“You choose how much or how little you engage with the app, which gives those who might be anxious about their health the option to limit the amount of time they spend with their data,” says Patel.

3. Focus on long-term trends, not one-off metrics

When I asked both Patel and Dr. Jacqueline Shreibati, head of clinical for platforms and devices at Google, how people who wear their devices can reduce health anxiety, they emphasized the importance of tracking trends — not individual metrics.  

“We focus on long-term trends (rather than isolated metrics) to help users maintain a balanced relationship with their data,” says Shreibati. “What being healthy means differs for everyone, and we encourage users to consult their physician if they have any concerns.”

Patel points to the Tags and Trends features in the Oura app. Tags lets you tag lifestyle factors such as travel, alcohol, meditation or late meals, which you can then view in Trends to see how your behavior affects your recovery and sleep over weeks, rather than looking at a single score that may one day seem abnormal.

Sleet tracking Apple Watch Series 11

Instead of viewing a single sleep or stress score, consider looking at that data weekly or monthly.

Vanessa Hand Orellana/CNET

4. Remember: Your smartwatch can’t replace your doctor

“Most consumer wearables were originally developed as personal wellness devices, which are not required to demonstrate safety and efficacy like traditional medical devices (e.g., a blood pressure cuff or pacemaker),” Rosman explains. 

Yet we’ve begun using these wearables to monitor our health, using metrics such as heart rate and rhythm, blood oxygen, stress, sleep and physical activity. Now, some of these devices have medical-grade sensors, software and algorithms approved by the US Food and Drug Administration to detect irregular heart rhythms, hypertension and sleep apnea.

Despite FDA approval, wearables are simply not doctors, and they cannot provide medical diagnoses or treatment. That’s why it’s essential to understand what your device actually measures.

The ECG feature on many smartwatches is just one example of this. FDA-cleared as it may be, a single-lead ECG that only uses one electrode to record your heart’s electrical activity from your wrist is not the same as the 12-lead, hospital-grade ECG a cardiologist would use. 

While your wearable’s ECG can surface a potential symptom worth investigating with your doctor, it can’t replace a professional or their medical-grade equipment.

apple watch ultra 3 ecg

Performing an ECG on your smartwatch is not the same as having that same measurement taken in a doctor’s office.

Viva Tung/CNET/Apple

The gap is even wider for features including stress and sleep scores, which haven’t been clinically validated because there’s no one single gold standard to validate against. These numerical scores are calculated from bodily signals such as heart rate, temperature, movement and heart rate variability, which tend to correlate with your stress and sleep states. But the translation from raw signal to “your stress score is 74” is more of an educated estimate.

“What you’re seeing is a rough indicator of how your nervous system is functioning, not a medical diagnosis,” Rosman emphasizes.

Patel adds that not all physiological stress is inherently negative. “Some forms of short-term physiological stress can be healthy and adaptive,” he says. “That’s why we aim to pair data with in-app context and insights, so members can better understand what they’re seeing rather than receiving that information in a vacuum.” 

Nonetheless, when you don’t know exactly what your wearable is measuring, a “bad” stress or sleep score can seem scary when it isn’t necessarily a cause for alarm, but rather a sign that you may want to have a deeper conversation with your doctor.

5. Get a temperature check (literally and figuratively)

Just like you should talk to your doctor before starting a new medication or diet, you should get their thoughts on whether you could benefit from using a wearable.

“Education is probably the most underused tool we have,” Rosman says. 

When you don’t know what a healthy heart rate or ECG looks like, one seemingly atypical reading can send you into a panic. That’s why it’s essential to speak with your doctor so you understand your own baseline and if a wearable makes sense for your current health condition.

As a guide, Rosman provides the following questions you can ask your doctor:

  • What type of wearable should I use? 
  • How often should I check this data? 
  • What are healthy numbers for me? 
  • What do I do when I get an alert? 
  • When should I call the clinic or seek emergency care versus waiting? 

“A fast heart rate after climbing stairs is not the same as a dangerous arrhythmia, but without that context, a notification can feel terrifying,” Rosman adds. “So much wearable-related anxiety comes not from the data itself, but from not knowing what to do with it.”

6. Know when it’s time to remove that device and get help

When asked when someone should consider parting with their wearable or seeing a professional for health anxiety, Cassiday says that it’s similar to what many notice when they keep checking their smartphone for the next text, TikTok or other digital data.  

“If you find yourself interrupting pleasurable activities or your free time to check, or if you feel anxious about not checking, you have a problem,” Cassiday states. 

For instance, if you only stop thinking that you’ll have a heart attack when you check your wearable and see your resting heart rate. Or, put simply, if you only feel at peace after someone or something, such as a wearable reassures you that you’re in good health, it’s time to get professional support. 

An aerial view of a version with blonde hair, a yellow shirt and light-wash jeans talking to a therapist while on a gray couch.

If health anxiety is making it difficult for you to enjoy your life, then it’s time to talk to a professional.

Constantinis/Getty Images

To find help, Cassiday recommends using the resources provided by the Anxiety and Depression Association of America or the International OCD Foundation, as health anxiety can be related to obsessive-compulsive disorder. 

7. Consider cognitive behavioral therapy 

When you have health anxiety, the gold standard for care is cognitive behavioral therapy. It involves exposure to health-related worries without any form of reassurance and learning to accept the uncertainty that comes with not knowing our future health status, manner of death or time of death.  

“People need to learn that all the vague symptoms that trigger their health anxiety are just normal variations of normal body functioning and aging,” Cassiday explains. “They have to reframe the symptoms they notice as nothing to examine, discuss or manage and instead trust the facts of their other evidence of good health.”

CBT can help you live in the present instead of spiraling into the anxiety-inducing “What if?” of the future.

Who should and shouldn’t use wearables

Wearables can be great for people who like tracking their fitness to motivate them toward their goals, or for patients and their care teams when medically necessary. Though they usually cost hundreds of dollars, wearables can be less expensive than medical tests. Some are even HSA- or FSA-eligible

“In AFib specifically, being able to correlate your symptoms with actual rhythm data can be genuinely empowering,” Rosman says. She’s observed that the patients who thrive with wearables are those who use the data as information — not as something to fear — and those who don’t participate in 24/7 surveillance.

In Rosman’s 2024 study, two-thirds of AFib patients said their wearable made them feel safer and more in control. Even so, there is still the risk of unintended consequences.

Two fitness tracker watches and a gold Oura Ring on a wrist and finger.

While they can be beneficial, wearables can also come with risks — especially since there isn’t enough research on the subject.

Giselle Castro-Sloboda/CNET

Just as doctors would never prescribe a medication without knowing the potential benefits, risks and how to manage them, wearables should be no different. “The technology has moved so much faster than the science, and we need the scientific evidence from clinical trials to catch up,” Rosman explains. 

Since the evidence isn’t there yet, Rosman is hesitant to say anyone should categorically avoid wearables. 

Despite that, people who are highly anxious about their heart or prone to obsessive symptom monitoring should approach with caution. The same goes for those with conditions involving unpredictable, abrupt symptoms, such as paroxysmal AFib and POTS, because the uncertainty of not knowing when the next episode will hit is stressful enough, and constant monitoring can make it worse.

A note on the science (or lack thereof)

Rosman has conducted research on the connection between wearables and anxiety, including a 2025 review describing the psychological effects of wearables on patients with cardiovascular disease and a 2024 study examining their impact on the psychological well-being of patients with AFib. 

The 2025 review found that while wearables can help promote healthy behaviors and provide data for diagnosis and treatment, they also pose risks, such as adverse psychological reactions. 

In the 2024 study, it was concluded that wearables were connected with higher rates of patients becoming preoccupied with their symptoms, being concerned about their treatments and using both formal and informal health care resources.

On the other hand, a 2021 study that analyzed the 2019 and 2020 US-based Health Information National Trends Survey found that using wearable devices for self-tracking can indirectly reduce psychological distress. Still, misinterpretation of wearable data may cause unnecessary panic and anxiety. 

A 2020 qualitative interview study featuring patients with chronic heart disease also found that while wearables’ data may be a resource for self-care, it can create uncertainty, fear and anxiety.

Ultimately, more studies are needed. 

“Honestly, we don’t have good scientific evidence in this area yet,” says Rosman. “Despite widespread use, there have been no clinical trials I’m aware of that have looked at the benefits and potential health risks of specific wearable health features.”

Rosman’s team plans to be the first to investigate this in patients with pre-existing heart conditions.

Wearables’ impact on health care

When wearables cause health anxiety, they can prompt healthy individuals to schedule unnecessary doctor’s appointments. This places a burden on our health care system, which is already experiencing shortages, making it difficult for people who actually require medical attention to access care. 

Rosman’s 2024 study found that those using a wearable sent nearly twice as many patient portal messages to their doctors. Responding to these messages from patients takes time, isn’t reimbursed by insurance and can contribute to burnout.

A person in blue scrubs with long brown hair checking messages on a desktop computer.

When health anxiety caused by wearables prompts people to message their doctors, it can put a strain on the health care system.

MoMo Productions/Getty Images

As a result, Rosman believes we need better systems for managing wearable data in clinical settings before we scale it further: “Wearables are changing how we deliver care in ways we haven’t fully prepared for.”

Wearables can further widen health care inequity due to their cost. 

“These devices are expensive, they were mostly designed and tested in young healthy people and they’re marketed toward higher-income consumers,” Rosman explains. “If we’re not thoughtful about access, wearables could actually widen health disparities rather than close them. That’s the opposite of what we want.”

The bottom line

While wearables have their benefits, there are also risks to consider, especially given the limited research on the subject.

If you purchase a wearable and it triggers health anxiety, you don’t have to use every available feature, wear it constantly or continue to wear it at all. Before you even buy that device, you can arm yourself with anxiety-reducing knowledge by getting your doctor’s expert opinion.  

However, if health anxiety continues to take over your life, it may be time to remove your wearable and seek professional help. 

As for me, writing this piece has been a necessary reminder that, while there’s a lot we can’t control in life, the power is in our hands (or on our wrists or fingers) when it comes to the technology we put on our bodies or invite into our homes. Just like an itchy sweater or a lumpy armchair, we can send the technology that doesn’t serve us packing.  





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Power BI Datasets – Table of Content

What is Power BI?

Power BI is a set of software services, apps, and connectors that work together to turn disparate data sources into coherent, visually immersive, and interactive insights. Your data could be in the form of an Excel spreadsheet or a hybrid data warehouse that is both on-premises and cloud-based. Power BI makes it simple to connect to your data sources, visualize and uncover what matters, and share your findings with whomever you choose.

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What are Datasets in Power BI?

A dataset is a data collection that you can connect to or import. Power BI allows you to connect to and import all kinds of datasets, allowing you to put everything together in one place. Dataflows can also be used for sourcing the data for Datasets. Workspaces are associated with datasets, and a single dataset can be used in multiple workspaces.
We have selected “My workspace” and then the “Datasets + dataflows” tab in the example below

Power BI workspace

Let us now look into the different types of Datasets in Power BI.

Types of Datasets

Datasets in Power BI are ready to report and visualize the source of data. There are five different types of datasets, each of which can be constructed in one of the following ways:

  • An existing data model will be connected that is not hosted in a Power BI capability.
  • Power BI Desktop file needs to be uploaded which includes a model.
  • Uploading a CSV (comma-separated values) file, or uploading an Excel workbook (Includes one or more Excel tables and/or a workbook data model).
  • Creating a push dataset using the Power BI service.
  • Creating streaming or dataset with hybrid streaming using the Power BI service.

Let us now explore different types of Datasets.

1) External-hosted models

Azure Analysis Services and SQL Server Analysis Services are the two types of externally hosted models. Installing the on-premises data gateway, whether on-premises or VM-hosted infrastructure-as-a-service (IaaS), is required to connect to a SQL Server Analysis Services model. A gateway isn’t required for Azure Analysis Services.

When there are existing model investments, such as those that form part of an enterprise data warehouse(EDW), connecting to Analysis Services makes sense. By utilizing the identity of the Power BI report user, Power BI can establish a live connection to Analysis Services, enforcing data permissions. Both tabular models and multidimensional (cubes) are supported by SQL Server Analysis Services. A live connection dataset sends queries to externally hosted models, as demonstrated in the accompanying 

External-hosted models

2) Power BI Desktop-developed models

A model can be created using Power BI Desktop, a client application for Power BI development. The model is essentially a tabular Analysis Services model. Models can be created by importing data from dataflows and blending it with data from external sources. While the characteristics of how modeling can be accomplished are outside the subject of this article, it’s crucial to note that Power BI Desktop supports three different types, or modes, of models. We are going to discuss the datasets in the coming sections.

Row-Level Security (RLS) can be used in externally hosted models and Power BI desktop models to restrict the amount of data that can be obtained for a certain user. Users in the Salespeople security group, for instance, can only see report data for the sales region(s) to which they’ve been assigned. Roles in RLS can be either static or dynamic. Static roles apply the same filters to all users allocated to the position, whereas dynamic roles filter by the report user.

3) Excel workbook models

The creation of a model is automatic when datasets are created from Excel workbooks or CSV files. To construct model tables, Excel tables, and CSV data are imported, and an Excel workbook data model is translated to produce a Power BI model. In every scenario, data from a file is imported into a model.

4) Push Dataset

A Power BI dataset that can only be created and populated using the Power BI API is known as a push dataset. However, the lack of a good user interface for creating a push dataset restricted its adoption to scenarios where a single table was inhabited with real-time data streaming.

5) Hybrid Streaming Dataset

Real-time streaming in Power BI allows you to stream data and update dashboards in real-time. Real-time data and visuals can be displayed and updated in any Power BI visual or dashboard. Factory sensors, social media sources, service usage metrics, and a variety of other time-sensitive data collectors or transmitters can all be used to collect and transmit streaming data.

Hybrid Streaming Dataset

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How to Create a Power BI Dataset?

Before discussing the steps of creation. It is necessary to know that there are three basic ways to retrieve data in Power BI Desktop that you will use to create your visualizations:

1) Live:

Here you will be connecting to a server that carries all the data. Although no data is sent, the model’s metadata is imported into Power BI Desktop. A query is transmitted to the server when you build visualizations, and it is then executed. The outcomes are then visualized and returned to Desktop. With SQL Server Analysis Services (SSAS) models, whether multidimensional or Tabular, live connections are commonly employed. Power BI Desktop behaves like any other thin client in this scenario, like Excel or Reporting Services (SSRS). It is not possible to make major modifications to the model, but you can add new measurements that will be available in that  .pbix file.

2) DirectQuery:

You can make more modifications to the model here than you can with a Live connection. The data is kept on the server, and queries are run on the server, just like in Live. The Power BI Desktop model, for instance, allows for the creation of relationships.

3) Import:

Power Query queries are used to import the data into a Power BI Desktop file (.pbix). The data is compressed highly so it’s feasible to load records in millions into a file on your system. A model, comparable to an SSAS Tabular model, is built behind the scenes. This is the most versatile mode, as it allows you to blend data from any source. However, all data must be loaded into your model, which can take a long time to refresh.

Now, let’s move to create the dataset. Below are the steps which make you comprehend the creation of the Power BI Dataset.

1) A dataset is connected to the .pbix file where it was created one by one. When you first launch PBI Desktop, click “Get Data” to create a new dataset.

Get Data

Alternatively, you can choose a source from the dropdown menu as shown below:

dropdown menu

2) Let’s assume we imported a few tables from the WideWorldImporters SQL Server sample database (The .pbix file can be downloaded here). The tables and their relationships are visible in the Model view:

.pbix file downloaded

3) You can view the actual data of one table at a time in the “Data view”.

Data view

4) You can create, view, and interact with visualizations built on top of the data and model in the “Report view”. 

Report view

 The dataset is made up of the data as well as the model view. Now, let’s move to the different modes of Dataset available in Power BI.  

[ Related Article : msbi ]

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Dataset modes in the Power BI

These modes of Dataset in Power BI ascertain whether or not data is imported into the model or retained in the data source. The following are the three Dataset modes in Power BI:

  1. Import
  2. DirectQuery
  3. Composite
1) Import

The most popular mode for developing datasets is the import mode. Because of in-memory querying, this mode provides incredibly quick performance. Modelers can also benefit from design flexibility and support for certain Power BI service capabilities (Quick Insights, Q&A, etc.). It’s the default mode when developing a new Power BI Desktop solution because of these advantages.

It’s crucial to realize that all imported data is saved on disk. When the data is refreshed or queried, it should be fully loaded into the memory of Power BI. Import models can yield very rapid query results once they are in memory. It’s also crucial to note that there’s no such thing as a partially loaded Import model in memory. An Import model can also integrate data from any number of supported data source types. The following image illustrates it. 

Import model

2) DirectQuery

Import mode can be replaced by DirectQuery mode. Data is not imported into models created in DirectQuery mode. Instead, they are made up entirely of metadata that defines the model’s structure. If the model is queried, data is retrieved by using the native queries from the underlying data source.

DirectQuery Model

3) Composite

The composite mode can blend DirectQuery and Import modes, or integrate multiple data sources for DirectQuery. The storage mode for every model table can be configured for models created in Composite mode. Calculated tables (defined with DAX) can also be used in this mode.

Composite Model

Import and DirectQuery modes are used in composite models to give you the best of both modes. They can blend the high query performance of in-memory models with the capacity to access near real-time data from data sources when set properly.

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 Conclusion:
We have successfully learned that Power BI lets you connect various datasets for importing and bringing them all together in one place. In this blog, we explored the topics of Datasets in Power BI in a systematic flow by understanding Power BI, then Datasets in Power BI, different types of Datasets and models used for reporting and visualizing data, creating a Dataset for connecting files, and various modes of Datasets in Power BI.

Related Article:

  1. MSBI vs Power BI
  2. Looker vs Power BI
  3. KPI in Power BI
  4. DAX In Power BI
  5. Power BI Architecture
  6. Power BI Components
  7. Power BI Dashboard
  8. Power BI Data Modeling
  9. Power BI Documentation



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