Cervical Cancer Prevention Week is an annual initiative that takes place the last week of January with the goal of raising awareness about cervical cancer, encouraging women to attend cervical screenings, and educating about the human papillomavirus (HPV) vaccine.

Cervical cancer is most often caused by an infection with high-risk types of HPV, leading abnormal cells in the cervix to form a tumor. While cervical cancer was once one of the most common causes of cancer death in American women, this has decreased by more than 50% since the 1970s due to the increased use of screenings and preventative methods, as well as advances in treatment.

Living with cervical cancer involves navigating a range of challenges, from managing the logistics of treatment and medical appointments, to coping with the emotional impacts of the disease.

Let’s listen to a 41- to 45-year-old woman with cervical cancer describe what it’s like for her to live with this condition and some of the challenges she faces.

Question 1 Response 159

Understanding the patient voice is at the heart of 

, which we approach holistically by analyzing what is said, how it’s said, and how it sounds.

Looking first at what she is saying and how, this patient conveys the two main elements of her disease experience. On the one hand, she describes the feeling of having cervical cancer in evocative terms: “terrifying” and “super scary.” On the other, she acknowledges the roles preventative care and management play in making the disease “manageable and controllable”. While it is “very treatable,” the logistical burden of doctor’s appointments adds an additional challenge to manage on top of the fear of relapsing or progressing.

, she describes the disease itself with strongly negative emotionality (‘valence’), which emphasizes the frustrations and fear of living with a life-threatening condition and her frustration with the burdens of treatment. As she describes the care process, however, this negative emotionality lessens, as well as the acoustic signals of stress (‘activation’), corresponding with the low-level frustration patients with chronic conditions often describe.

Taken together, this patient’s response underscores the importance of early detection of cervical cancer. Although the condition is scary, and treatment can be burdensome, routine screenings to detect abnormal cells help those living with cervical cancer to keep their condition under control.

Our Listening Platform makes it simple for patients to speak with us about their experiences in an open and authentic way and easy for you to engage with their perspectives directly.

If you’re interested in hearing from more patients like this one so that you can gain insight into their experiences, beliefs, behaviors, and desires, 

Learn about Cervical Cancer Prevention Week through a patient's perspective on diagnosis, treatment, and hope. Discover how early detection and proper care make this condition manageable.

In Observation of Cervical Cancer Prevention Week (January 20-26, 2025)

As we ring in the new year, we would like to call attention to two ongoing awareness campaigns in the world of metabolic health. The United Kingdom has designated this Obesity Awareness Week, and January is Thyroid Awareness Month, with both campaigns seeking to raise awareness of both prevention and treatment in their overlapping therapeutic areas.

Obesity is a common condition throughout the world, but it is often misperceived and stigmatized as solely arising from poor lifestyle choices. While diet and exercise can help prevent or reduce the risk of obesity for some patients, understanding it as a disease is important to diagnosing any comorbidities, learning the relevant risk factors, and determining treatments. For example, since thyroid irregularities can lead to changes in appetite and weight, obesity can co-occur with both hypothyroidism and hyperthyroidism

Obesity is often a chronic condition, and its negative physical impacts can compound over time, making movement and other daily activities more difficult. Aside from the direct effects of weighing more, obesity also increases the risk of cardiovascular and endocrine conditions (among others). Stigma can compound these issues, making it difficult understand obesity as a disease and seek treatment accordingly.

Let’s listen to a 51- to 55-year-old woman describe her experience with obesity and the social and physical challenges she faces.

Question 1 Response 44

Let us look first at what this patient is saying. The patient starts with social impacts, moves briefly into the physical effects, then returns to interpersonal troubles that can come from obesity, which underscores that the judgment she perceives from other people is the most keenly-felt aspect of her condition.

The way that the patient goes through the list is also worth some scrutiny. When listing both physical and social symptoms of obesity, the patient trails off and labels the consequences as “various/a lot of things.” This tracks both with her feeling resigned to these effects and the specific problems obesity brings about being too many to name.

This resignation is confirmed when we take our 

 to this data, where we see negative emotionality (‘valence’) and low enthusiasm (‘activation’) throughout her description of obesity. These signals corroborate what you can likely already hear - a depressed-sounding affect in this patient’s speech.

By taking these perspectives into account, we can draw out some of the most important parts of the patient experience with obesity: a chronic, cumulative physical burden which is difficult to disentangle from the interpersonal impacts of the disease. Whether these patients are possible treatment users or potential enrollees in a clinical trial, manufacturers need to be able to address this complexity in order to properly help obesity patients.

Explore the complex relationship between obesity and thyroid health through patient perspectives. Learn how physical and social challenges impact those living with obesity, featuring real patient insights.

In Support of Obesity Awareness Week and Thyroid Awareness Month

At inVibe, we’ve been working with AI since our founding in 2013, and we were among the first market research agencies to adopt 

large language models (LLMs) back in 2021

, and we released our LLM tools to clients in 2023. AI isn’t a gimmick or a buzzword for us, it’s central to 

: To develop technology that provides cost-effective, high-speed healthcare market research while maintaining the highest quality.

As AI takes a center stage in healthcare with the release of popular LLMs like ChatGPT and Claude, we’ve continued to integrate the latest AI models, features, and functionality into more of the work we do at inVibe. Working with AI every day, we quickly started to see the cracks and have prioritized finding ways to ensure the accuracy and integrity of AI-generated content.

To ensure our clients have reliable AI insights, we designed and implemented an evaluation system to validate our AI tools. Our language experts and prompt engineers leverage this system to iteratively test the quality and reliability of the outputs. By testing different prompts and LLMs in this system, we’re able to ensure that our AI tools meet our clients’ needs and our high standards.

Practically speaking, we do this by having two trained language experts compare two outputs presented next to one another on one screen. Once we review the two outputs, we score each across 6 categories that are based on best practices for evaluating the quality of language data and conversational LLMs.

: To what extent does the output address everything it was asked to?

: How closely does the output align with our understanding of the voice data? (Rating: 1-4)

: How clear is the relationship between the findings and the verbatim evidence in the output? (Rating: 1-4)

: To what extent is the output presently coherently and in the prescribed way? (Rating: 1-4)

: Does the output include consistent formatting that enhances readability? (Rating: 1-2)

: Are findings in the output supported by citations in the prescribed format? (Rating: 1-2)

Let’s take a look at one of these comparisons in action. In the below image, we’re seeing a quality test of two different LLMs that were prompted to report the key findings from the same set of voice data. After reviewing both outputs, the language expert scrolls down to where they assign scores to each output and select a ‘winner.’

Once we have a significant number of ratings for what we’re assessing, we compare the total scores, sub-scores, and selected winners to determine an overall winner (i.e., the model that performed better). This overall winner becomes our new baseline for this task in the next round of testing and becomes the default way that our AI tools perform this operation in our dashboard—until the next upgrade at least.

Through many iterations of this testing, we’ve improved the quality of our models by 46.73% over the last 12 months (and we expect to continue this pace in the next 12 months)! This means that our clients can rest assured that our AI tools will remain best-in-class: offering comprehensive, accurate, transparent, and comprehensible outputs tuned to market research best practices for qualitative voice data.

Are you interested in learning more about how our AI tools can make your qualitative research simpler, more systematic, and more scalable? 

Pioneer in AI-powered healthcare research since 2013: See how inVibe validates enterprise LLMs with a rigorous testing framework that's improved insights quality by 46.73%. Discover our proven approach to reliable, scalable market research.

Responsible AI: Validating LLM Outputs

We get it. With market research timelines and budgets shrinking by the minute, the pressure is on to become faster and leaner — or risk that brands and marketers just skip the research altogether and make decisions from the gut. In hopes of doing more with less, many have wondered whether machine learning and artificial intelligence can deliver new insights from big data without the need for more resources or labor.

But how do we leverage the old and new without fostering a 

 that results in mile-wide responses with inch-deep insights?

How can we use AI and automation to help us answer our most pressing questions, without introducing new complexity and unvalidated algorithms that add confusion, not clarity, to the data?

And most importantly, how can we ensure that in “quantifying the qual” we do not lose the most valuable signal of all — 

How do we leverage the old and new without fostering a 

 that results in mile-wide responses with inch-deep insights?


Next week, our team will gather in Philadelphia for 

 to help answer these very questions. inVibe is proud to be a Platinum Sponsor of IIeX Health, and we’re thrilled to share how our innovative mixed-methods approach can take advantage of AI and automation without compromising the richness of the human story.

If you’re attending IIeX, don’t miss inVibe’s Kathryn Ticknor presenting 

“The Human and the Machine: Empathy-Focused Research in a World of Automation and AI”

Using AI to Drive Empathy

Thanks for reading!

In Observation of Cervical Cancer Prevention Week (January 20-26, 2025)

In Support of Obesity Awareness Week and Thyroid Awareness Month

Responsible AI: Validating LLM Outputs

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