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CDM test prep - Certified Dietary Manager Updated: 2024

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Exam Code: CDM Certified Dietary Manager test prep January 2024 by Killexams.com team

CDM Certified Dietary Manager

- Management of Foodservice

- Sanitation & Food Safety

- Nutrition & Medical Nutrition Therapy

- Human Resource Management

- Career Skills

- Utilize the systems approach to procure, produce, and serve food to all customers.

- Provide a safe and sanitary environment for employees.

- Utilize appropriate supervisory management techniques.

- Provide appropriate quality nutritional care for the client.

- Meet all licensing and regulatory agency standards.

- Utilize business, marketing, and public relation skills to improve foodservice and nutrition to peers, patients, and community.

- Constantly strive for improved performance as a Dietary Manager.

- Participate in the professional activities of the Association of Nutrition & Foodservice Professionals.

Critical Thinking Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.

 Access data, references, patient education materials, consumer and other information from credible sources.

 Perform nutrition screening and identify clients or patients to be referred to a registered dietitian nutritionist.

 Evaluate information to determine if it is consistent with accepted scientific evidence. Problem Solving Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.

 Participate in quality improvement and customer satisfaction activities to improve delivery of nutrition services.

 Modify recipes and menus for acceptability and affordability that accommodate the cultural diversity and health status of various populations, groups and individuals.

Interpersonal Behavioral and Social Skills

The ability to show cultural competence in interactions with clients, colleagues and staff.

 Demonstrate an understanding of cultural competence/sensitivity.

 Show cultural competence in interactions with clients, colleagues and staff.

 Implement interventions to effect change and enhance wellness in diverse individuals and groups.

Oral and Written Communication 1. The ability to listen to and understand information and ideas presented through spoken words and sentences.

2. The ability to communicate information and ideas in

 Prepare and deliver sound food and nutrition presentations to a target audience.

 Provide nutrition and lifestyle education to well populations.

 Promote health improvement, food safety, wellness and disease speaking so others will understand.

3. The ability to read and understand information and ideas presented in writing.

4. The ability to communicate information and ideas in writing so others will understand. prevention for the general population.

 Develop nutrition education materials for disease prevention and health improvement that are culturally and age appropriate and designed for the educational level of the audience.

Active Listening Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times.

Physical activities Performing physical activities that require considerable use of your arms and legs and moving your whole body, such as climbing, lifting, balancing, walking, stooping, and handling of materials.

 Demonstrate sufficient upperbody strength and manual dexterity to operate and clean household and institutional equipment required for food preparation and food.

 Travel to clinical sites and have mobility within and around the sites.

Activities may involve standing, sitting, stooping and be in hot and cold facilities.

 Demonstrate the ability to exert maximum muscle force to lift, push, pull, or carry objects such as food supplies, small equipment and delivery of meals.

 Sensing

 Visual

 Hearing

 Taste

 Smell

1. The ability to see details at close range (within a few feet of the observer).

2. The ability to taste and smell to determine acceptability of foods and supplements.

3. The ability to hear spoken words.

 Demonstrate sufficient vision, smell and taste to evaluate the appearance, aroma, and flavor of food.

 Demonstrate sufficient vision to observe compliance with food sanitation and safety codes.

Professional Attributes Practicing professional skills required in entry-level positions.

 Attend scheduled classes, labs and supervised practices and be present for examination and testing. Be prepared for class.

 Maintain professional demeanor in class and during supervised practice.

 Maintain personal hygiene and dress code policies.
Certified Dietary Manager
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Certified Dietary Manager
Question: 59
Which of the following is true for reactive hypoglycemia?
A. It is defined as a plasma glucose level less than 70 mg/dl.
B. It is treated with a diet high in complex carbohydrates.
C. It is diagnosed by measuring blood glucose levels one hour after eating.
D. Peak insulin activity occurs 90-180 minutes after food is eaten.
Answer: D
In reactive hypoglycemia peak insulin activity occurs 90-180 minutes after food is
eaten, vs. the normal insulin response which occurs 30-60 minutes after eating.
Reactive hypoglycemia is defined as a plasma glucose level than 50 mg/dl, is
treated with a moderate carbohydrate (40 to 55%) diet, and is diagnosed by
measuring blood glucose levels immediately after eating.
Question: 60
During disaster planning a consulting RD be asked to participate in which of the
following activities:
A. Development of a list of all food vendors with delivery schedules
B. Assessing food inventory for adequacy
C. Preparing a checklist of food safety procedures
D. All of the above
Answer: D
During disaster planning a consulting RD might be asked to help develop a list of
all food vendors with delivery schedules, assess food inventory for adequacy, and
prepare a checklist of food safety procedures. Registered dietitians need to be
knowledgeable and competent in all areas related to food procurement,
production, and delivery.
Question: 61
In behavior modification, the term extinction is defined as:
A. Punishing undesirable behaviors with negative feedback
B. Encouraging repetition of desirable behaviors
C. Reducing undesirable behaviors by withholding positive reinforcement
D. Identifying behaviors that were common in childhood
Answer: C
In behavior modification, extinction is the attempt to reduce undesirable
behaviors by withholding positive reinforcement, such as praise or other rewards.
The technique of repeatedly refusing to reward an undesirable behavior is
believed to lead to the gradual reduction and elimination (extinction) of that
Question: 62
Features of the Nutrition Screening Initiative (NSI) include:
A. Use of a 20-question checklist to assess nutritional and health status of elders
B. Identification of factors that place elders at increased nutritional risk
C. A focus on elders between the ages of 65 and 75 years
D. Identification of elders who have a BMI of less than 20
Answer: B
Features of the Nutrition Screening Initiative (NSI) include identification of
factors that place elders at nutritional risk (such as illness and food availability).
A 10-question checklist is used to assess the nutritional and health status of
elders. The NSI is particularly interested in assessing the nutritional health of
individuals 80 years of age and older.
Question: 63
Which of the following is true for the mini-max stock method for placing food
A. Actual need might be greater than the amount ordered.
B. The amount ordered is higher in some months than others.
C. The method should not be used to order items whose usage fluctuates.
D. A & C
Answer: D
The mini-max stock method establishes minimum and maximum inventory
amounts. When the minimum level is reached, an order is place to replenish
inventory only to the maximum level. This means that the same amount is ordered
each time. as a result, actual need might be greater than the ordered amount, and
that the method is not suitable for maintaining stock of items with variable usage.
Question: 64
The Feingold Diet used to treat Attention Deficit Hyperactivity Disorder (ADHD)
in children eliminates:
A. Lactose and sorbitol
B. Artificial food colorings, additives, and preservatives
C. Gluten and casein
D. Fructose and phenols
Answer: B
The Feingold Diet used to treat Attention Deficit Hyperactivity Disorder (ADHD)
in children eliminates artificial food colorings, additives and preservatives, since
these substances are believed to trigger and worsen symptoms of hyperactivity.
Question: 65
Proxemics refers to:
A. The ability to read small print
B. Formulas used to calculate electrolytes in enteral feedings
C. A management style used in major corporations
D. An individual's position, orientation, and distance from other people in a room
Answer: D
Proxemics refers to the manner in which an individual positions himself in a
room, in relation to other people. Counselors can use the distance between people
to assess how comfortable individuals are in the classroom and other learning
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Medical Certified test prep - BingNews https://killexams.com/pass4sure/exam-detail/CDM Search results Medical Certified test prep - BingNews https://killexams.com/pass4sure/exam-detail/CDM https://killexams.com/exam_list/Medical Why ISSA’s Corrective Exercise Course Stands Out: A Trainer’s Take No result found, try new keyword!A certified personal trainer tests and reviews the ISSA Corrective Exercise Specialist course to see if it is worth adding to your skill set. Thu, 04 Jan 2024 15:41:00 -0600 text/html https://www.si.com/showcase/fitness/issa-corrective-exercise-review The Princeton Review's Company Look Back at 2023 and Look Ahead to 2024

NEW YORK, Dec. 29, 2023 /PRNewswire/ -- The Princeton Review ®, one of the nation's leading education providers, today shared its annual look back at some of the company's key offerings over the past year and look ahead to some projects in the works for the year ahead.

Millions of people use one or more of The Princeton Review's education resources each year. Students use the company's products and services to score their best on tests; tackle school assignments; improve their grades; research and gain admission to undergraduate, graduate, and medical schools, and maximize their prospects for scholarships and financial aid. Post-graduates use the company's resources to upskill for career advancement as well as prepare for and pass professional licensing exams.

In 2023, The Princeton Review's products and services included:

Test-prep Courses. Offered for more than 26 tests, the courses are available in various options and formats from live online to self-paced. Some carry the company's Better Score Money Back Guarantee. Among The Princeton Review courses for tests taken by applicants to graduate and medical schools—the GMAT®, GRE®, LSAT®, and MCAT®—the company's LSAT 165+ and MCAT 515+ courses were the most popular in 2023. Among its courses for tests taken by applicants to colleges—the SAT®, ACT®, and AP® subject tests—The Princeton Review's SAT 1400+ course was the most popular in 2023.

During this transitional year for the SAT, the company provided test-prep programs that supported students in the U.S. preparing for the final administrations of the current SAT as well as programs for international students preparing to take the Digital SAT which debuted in test centers abroad in January. The Digital SAT will debut in the U.S. in March 2024. This year, the company has also been diligently tracking planned (or implemented) revisions on other major tests and updating its resources for students preparing to take them.

Princeton Review courses and resources for professional licensing and certification exams include its USMLE® Test Pack for MD candidates taking the medical licensing exam, and its suite of resources for the NCLEX-RN®, the exam required for licensing as a Registered Nurse. These include its NCLEX-RN LiveOnline course, NCLEX Self-Paced course, and NCLEX-RN QBank . In 2023, the company updated its NCLEX-RN products to align them with the NGN (Next Generation NCLEX) revision of the text which debuted in April.

The company also has test prep courses for the Level I, Level II, and Level III CFA® (Chartered Financial Analyst®) exams. In 2023, the company updated its course materials for these exams to align them with revisions that will be in the 2024 administrations of the tests. This year, Princeton Review also added free practice tests for the Level I CFA exam to its CFA exam prep resources.

In March, a marketing partnership with Surgent Accounting & Financial Education enabled The Princeton Review to offer its customers exclusive discounts on Surgent's exam review products for the CPA® (Certified Public Accountant), CMA® (Certified Management Accountant), and CISA® (Certified Information Systems Auditor) exams.

Tutoring online and on demand 24/7 in 80+ subjects via The Princeton Review's hubs, The Academy and Homework Help. At The Academy, tutors help students in grades 6–12 earn higher grades in their school subjects and prepare for tests. In 2023, the top two subjects for which the company's tutors provided academic help were Algebra and Pre-Calculus. At the Homework Help hub, tutors help students tackle school assignments. In 2023, the top two subjects for which the tutors provided homework help were Algebra II and Calculus.

Admissions Counseling for college and medical school applicants. Some of the "dream" schools to which students working with Princeton Review college admission counselors gained admission in 2023 are Columbia, Cornell, Duke, Harvard, and Stanford. Overall, students were accepted at 205 unique institutions and awarded more than $8M in financial aid. Applicants to medical schools who worked with the company's admissions counselors this year gained admission to the top 20 medical schools in the U.S. as well as top medical schools outside of the U.S. including the University of Cambridge, the University of Melbourne, and the University of Toronto.

Books. The Princeton Review's line of 150+ books, distributed by Penguin Random House, includes test-prep guides, college guides, and study aids. In 2023, the company published the 38th annual edition of its first-ever test-prep book, its guide to the SAT, and the 35th annual edition of its guide to the ACT. The Princeton Review has also published regularly updated guides to the GMAT, GRE, LSAT and MCAT for decades. In 2023, several of the company's guides to AP subject tests were designated as bestsellers by Amazon.com in its AP Subject Test Guides category. In recent weeks, four of the five bestselling AP test guides in this category have been Princeton Review books, including the #1 bestseller which is The Princeton Review Premium Prep Guide to the AP U.S. History test. The company's guide to the Digital SAT has been the #1 bestseller in the Amazon.com College Entrance Test Guides category. Other Princeton Review books published in 2023 include: GMAT & GRE Math Made Easy, SAT Level Up! Math, SAT Level Up! Verbal, Essays That Kicked Apps, The K&W Guide to Colleges for Students with Learning Differences (16th Edition), and the 32nd annual edition of the company's flagship college guide, The Best 389 Colleges.

AI Tools. This year, The Princeton Review debuted its first generative AI-based tools: AI College Admissions Essay Counseling and AI Homework Essay Feedback. Students using these innovative resources can upload essays they have written and within seconds receive feedback, evaluation, and recommendations of ways to make their essays even better. Designed with input from The Princeton Review's college admission and tutoring experts, the tools provide feedback on clarity, coherence, conciseness, grammar, spelling, punctuation, and more. (Note: These products do not write the student's essays.) On December 14, these two tools were named 2023 New Product of the Year award winners by Campus Technology and THE Journal, two of the leading edtech publications.

In 2023, The Princeton Review also:

Reported school rankings in dozens of categories, including its:

Best Business Schools and Best Law Schools (January)
Top Undergrad and Grad Schools to Study Game Design (March)
Best Value Colleges (April)
Best Colleges (August)
Top Green Colleges (October)
Top Undergrad and Grad Schools to Study Entrepreneurship (November)

Conducted national education surveys, including its:

College Hopes & Worries 2023 Survey. This survey, which The Princeton Review has annually conducted since 2003, polled 12,225 college applicants and their parents in February on their application perspectives, need for financial aid, levels of stress about college admission, "dream" college (the school they wished they (or their child) could attend if acceptance was a given and cost not a concern), and other topics. Among the findings reported in March: the #1 "dream" college among students surveyed was the Massachusetts Institute of Technology while Princeton was #1 among surveyed parents; 82% of respondents overall said financial aid would be "very necessary" to pay for college.

College Administrator Summer 2023 Survey. Now in its 4th year, this Princeton Review survey polled administrators at 229 colleges in July on their enrollment forecasts, test optional policies, and views on the Digital SAT, AI, the recent Supreme Court ruling on affirmative action, and more. Among the findings: the majority (89%) of administrators surveyed reported their colleges were test optional while 10% reported their schools were test blind, and 1% said their schools required test scores. College-level coursework on applicant transcripts is gaining importance in admission decisions. Nearly two-thirds (61%) of respondents to the 2023 survey deemed AP, IB, or dual enrollment coursework "important" on an applicant's transcript—a 7% increase over respondents so indicating in 2022.

In 2023, The Princeton Review also surveyed administrators at 2,000+ higher education institutions about their school offerings, policies, applicant requirements, and more. The company also surveyed students at hundreds of colleges and graduate schools about their campus experiences at their schools and ratings of them. Data collected from these surveys informs The Princeton Review's school rankings and its school profiles on PrincetonReview.com and in the company's annual Best Colleges guide.

Provided free resources for students, parents, teachers, counselors and working professionals:

From college night talks to test strategy sessions to career-related webinars, The Princeton Review hosted thousands of free events in 2023. The company's education experts also wrote and recorded dozens of videos that were uploaded to The Princeton Review's YouTube channel which now comprises 575 videos. These lively videos present company experts sharing updates on changes in standardized tests, tips for taking and scoring well on exams, strategies for gaining school admission, and short features about colleges. In 2023, the video most viewed on The Princeton Review YouTube channel was: "The New Digital SAT: Everything You Need to Know."

Was widely referenced in media programs, articles, and newscasts:

Each year, many national, regional, and local members of the media reach out to The Princeton Review for information, comment, and interviews about education issues. In 2023, Rob Franek, editor in chief of The Princeton Review, appeared on several national broadcasts including an August 18segment on NBC TODAY that was his 30th appearance on the show. It featured his advice for college applicants, report on the company's annual Best Colleges rankings, and comments on education issues in the news. Other national media interviewing Rob or fellow Princeton Review author/experts in 2023 included: CNBC; Yahoo Finance Live!, The Chronicle of Higher Education; and Teen Kids News. Media also reported on the company's rankings of hundreds of institutions that publicized their Princeton Review rankings in their news releases, websites, and social media channels in 2023. Many schools are citing them anew in their end-of-year retrospectives of their school distinctions.

Projects The Princeton Review has in the works for 2024 include:

Continuing updates of the company's website and its online, tutoring, and book resources for the many standardized tests that have undergone (or will be undergoing) substantial revisions. These include the new Digital SAT and new Digital PSAT/NMSQT®, a new edition of the GMAT (the GMAT Focus), a new format for the LSAT, and changes in professional licensing exams including the NCLEX-RN.

A new MCAT in-person course. Debuting in January, this intensive course will feature new uses of technology and a team-teaching approach. It will concentrate on weekend, in-person sessions that will enable students to connect with the instructors and their fellow learners.

Updated editions of the company's college-related books. Among them: The Best 390 Colleges: 2025 Edition, which will reveal the top 25 schools in 50 categories based on the company's surveys of 165,000 college students who rated and reported on their schools for this project, and Paying for College: 2025 Edition, which will include detailed guidance on completing the 2025-26 FAFSA® (Free Application for Federal Student Aid). The FAFSA has undergone a major overhaul that was mandated by the U.S. Congress in 2019 with the passage of the FAFSA Simplification Act. The significantly revised (although not entirely simplified) 2024-25 FAFSA will be released on December 31, 2023. (Note: the FAFSA is annually updated.)

A campaign to expand awareness of mental health services on college campuses. Supported by a partnership with the Ruderman Family Foundation, this Princeton Review project is collecting data from administrators at more than 2,800 colleges about the availability of mental health services and resources at their schools. The company is also surveying college students about their awareness of such services and resources on their campuses. In late summer 2024, The Princeton Review will output this data in various ways, including reporting information about the schools' mental health services in its college profiles on PrincetonReview.com.

"As The Princeton Review begins its 43rd year, we remain committed as ever to the company's mission: to help students learn, score their best on tests, and succeed in school and beyond" said Joshua HJ Park, CEO of The Princeton Review and Tutor.com. "Since The Princeton Review's founding in 1981, the company has delivered its services across an ever-expanding range of instructional formats and pioneered innovative uses of technology to advance education. Our launch this year of our first AI products—two resources that could only have been imagined in 1981—underscores our commitment to our founding mission. We look forward to developing new and exciting ways to help students learn in 2024 and succeed in their education and career goals." 

About The Princeton Review
The Princeton Review is a leading tutoring, test prep, and college admissions services company. Every year, it helps millions of college- and graduate school-bound students as well as working professionals achieve their education and career goals through its many education services and products. These include online and in-person courses delivered by a network of more than 4,000 teachers and tutors; online resources; a line of more than 150 print and digital books published by Penguin Random House; and dozens of categories of school rankings. The company's Tutor.com brand, now in its 23rd year, is one of the largest online tutoring services in the US. It comprises a community of thousands of tutors who have delivered more than 25 million one-to-one tutoring sessions. The Princeton Review, headquartered in New York, NY, is not affiliated with Princeton University. For more information, visit PrincetonReview.com and the company's Media Center. Follow the company on X (formerly Twitter) (@ThePrincetonRev) and Instagram (@theprincetonreview).

All tests are registered trademarks of their respective owners. None of the trademark holders are affiliated with The Princeton Review.

CFA Institute does not endorse, promote, or warrant the accuracy or quality of the products or services offered by The Princeton Review. CFA® and Charted Financial Analyst® are trademarks owned by CFA Institute.

LSAT® is a trademark registered by Law School Admission Council, Inc., which is not affiliated with, and does not endorse, The Princeton Review.

MCAT® is a registered trademark of the Association of American Medical Colleges.

SAT® and AP® are trademarks registered by the College Board, which is not affiliated with, and does not endorse, The Princeton Review or its offerings.

WEBSITE: www.princetonreview.com 

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Mobile CPR training stations teach lifesaving skills

The News10NBC Team details breaking News, Traffic and Weather.

VICTOR, N.Y. – Tuesday marks one year since Buffalo Bills safety Damar Hamlin collapsed on the field during their game against the Cincinnati Bengals.

And that started a flurry of people learning and becoming certified in CPR and using an automatic external defibrillator or AED.

Now, the University of Rochester Medical Center and the American Heart Association are expanding CPR accessibility at the Eastview Mall. The two organizations put a mobile, hands-only CPR training station in the mall right outside of Dick’s House of Sport for people to learn and practice on.

The machine runs through a training and practice session and then a 30 second test. Overall, the whole experience may take five minutes, but you’ll have the knowledge for a lifetime.

“It doesn’t take long to do. And it just makes you feel like, yes, I know what this is like. I can do this,” Judy Dumar, who used the machine said.

Dumar and Joy Jennejohn both used the machine, and decided they wanted to become CPR certified after finishing.

“It’s physically harder than I thought, but it’s simple,” Jenne John said.

“My heart is still beating from doing this. So yay to first responders and doctors and nurses. I congratulate you, but I’m glad that I did this,” Dumar said.

And Cardiologist Robert Rosenblatt says that when someone knows CPR and administers it, it can increase the survival rate of the person who needs it by 20 to 30 percent.

“Survival rates historically for cardiac arrest are pretty poor. About one in ten people or 10% of people survive. And out-of-hospital, cardiac arrest, early CPR and just, you know, good CPR awareness from bystanders and initiation of CPR can increase the survival rates two to three times,” Rosenblatt said.

And not only are these available a year after Damar Hamlin collapsed, but it’s also been two weeks since a 15-year-old Monroe High School student collapsed on the court during his JV basketball game.

“There’s many reasons for a young athlete to go down, like what happened to Damar, and I think what happened to that 15-year-old was commotio cordis, I think he got hit in the chest and it it happens. It’s not that infrequent. And we have had several cases locally, I think years before. I think there was a kid that went down in Brighton, if I remember correctly, you know, in years gone by, unfortunately the survival rate for that was very low,” Rosenblatt said.

This is why Rosenblatt says it is extremely important to learn CPR and have these machines in an accessible place like the mall.

The mobile station will be available for people to use through January 31.

And if you’re looking to get CPR certified, you can find a list of classes in the Rochester area here.

Tue, 02 Jan 2024 13:53:00 -0600 en-US text/html https://www.whec.com/top-news/mobile-cpr-training-stations-teach-lifesaving-skills/
An Exploratory Look At Whether Generative AI Can Pass An Official Mental Health Counseling Licensing Exam That Professionals Take

In today’s column, I will be closely looking at whether generative AI could potentially pass an official mental health counseling licensing exam. This is part of my ongoing in-depth series about generative AI or large language models (LLMs) that are or can be anticipated to be used for mental health guidance or advisement.

Before I dive into today’s particular topic, I’d like to provide a quick background for you so that you’ll have a suitable context about the arising use of generative AI for mental health advisement purposes. I’ve mentioned this in prior columns and believe the contextual establishment is essential overall. If you are already familiar with the overarching background on this topic, you are welcome to skip down below to the next section of this discussion.

The use of generative AI for mental health treatment is a burgeoning area of tremendously significant societal ramifications. We are witnessing the adoption of generative AI for providing mental health advice on a widescale basis, yet little is known about whether this is beneficial to humankind or perhaps contrastingly destructively adverse for humanity.

Some would affirmatively assert that we are democratizing mental health treatment via the impending rush of low-cost always-available AI-based mental health apps. Others sharply decry that we are subjecting ourselves to a global wanton experiment in which we are the guinea pigs. Will these generative AI mental health apps steer people in ways that harm their mental health? Will people delude themselves into believing they are getting sound mental health advice, ergo foregoing treatment by human mental therapists, and become egregiously dependent on AI that at times has no demonstrative mental health improvement outcomes?

Hard questions are aplenty and not being given their due airing.

Furthermore, be forewarned that it is shockingly all too easy nowadays to craft a generative AI mental health app, and just about anyone anywhere can do so, including while sitting at home in their pajamas and not knowing any bona fide substance about what constitutes suitable mental health therapy. Via the use of what are referred to as establishing prompts, it is easy-peasy to make a generative AI app that purportedly gives mental health advice. No coding is required, and no software development skills are needed.

We sadly are faced with a free-for-all that bodes for bad tidings, mark my words.

I’ve been hammering away at this topic and hope to raise awareness about where we are and where things are going when it comes to the advent of generative AI mental health advisement uses. If you’d like to get up-to-speed on my prior coverage of generative AI across a wide swath of the mental health sphere, you might consider for example these cogent analyses:

  • (1) Use of generative AI to perform mental health advisement, see the link here.
  • (2) Role-playing with generative AI and the mental health ramifications, see the link here.
  • (3) Generative AI is both a cure and a curse when it comes to the loneliness epidemic, see the link here.
  • (4) Mental health therapies struggle with the Dodo verdict for which generative AI might help, see the link here.
  • (5) Mental health apps are predicted to embrace multi-modal, e-wearables, and a slew of new AI advances, see the link here.
  • (6) AI for mental health got its start via ELIZA and PARRY, here’s how it compares to generative AI, see the link here.
  • (7) The latest online trend entails using generative AI as a rage-room catalyst, see the link here.
  • (8) Watching out for when generative AI is a mental manipulator of humans, see the link here.
  • (9) FTC aiming to crack down on outlandish claims regarding what AI can and cannot do, see the link here.
  • (10) Important AI lessons learned from the mental health eating-disorders chatbot Tessa that went awry and had to be shut down, see the link here.
  • (11) Generative AI that is devised to express humility might be a misguided approach including when used for mental health advisement, see the link here.
  • (12) Creatively judging those AI-powered mental health chatbots via the use of AI levels of autonomy, see the link here.
  • (13) Considering whether generative AI should be bold and brazen or meek and mild when proffering AI mental health advisement to humans, see the link here.
  • (14) Theory of Mind (ToM) is an important tool for mental health therapists and the question arises whether generative AI can do the same, see the link here.
  • And so on.

Here’s how I will approach today’s discussion.

First, I will introduce you to a pioneering research study that sought to assess whether generative AI could potentially pass an exam taken by medical school students as part of their pursuit of achieving their medical degree. The exam is known as the United States Medical Licensing Exam (USMLE). This study received a great deal of headlines since it showcased that generative AI seems to do well on the arduous medical exams taken by budding doctors. Next, I will share with you some salient details about an exam for mental health professionals known as the National Clinical Mental Health Counseling Examination (NCMHCE).

I’m guessing you might be wondering whether generative AI might be able to do well on that type of exam. Great question, thanks. I opted to use a popular generative AI app called ChatGPT to try out a half-dozen questions from the NCMHCE. Please note that this was merely an official sample set and not by any means the full exam.

Would you be surprised to know that the generative AI was able to successfully answer many of the sampled sample questions? I provide some important caveats and limitations about this mini experiment of sorts, and I want to emphasize this was principally done on an ad hoc basis and merely intended to be illustrative.

Here’s the deal.

Please do not jump the shark on this matter. Hold your horses. My mainstay aims here are simply to inspire others to do a deep dive on this and perform a fully comprehensive rigorous research study of an akin nature, perhaps modeled somewhat on the same approach taken by the study on the USMLE or similar such professional licensing domains.

Anyway, I believe you will find this interesting, engaging, and possibly whet your appetite to find out more on these topics. My discussion is yet another angle to considering where we are and where things are going pertaining to generative AI and the field of mental health therapy.

Please buckle up and prepare yourself for quite a ride.

Generative AI And Medical School Standardized Licensing Exam

Let’s talk about tests.

We generally assume that to practice medicine a test of some kind should be required to attest to the proficiency of the person that will be serving as a medical professional. I’d like to start by discussing perhaps one of the most famous such medical proficiency tests known as the United States Medical Licensing Examination (USMLE). This is the test typically expected of those attaining a medical degree in the United States.

The USMLE was devised to aid in standardizing upon one major medical examination test that would be acceptable across every state and ensure that MDs were meeting the same set of standards. The test is composed of three separate stages and is taken during medical school and also upon graduation from medical school.

Here’s some additional detail as noted on the USMLE website:

  • “In the United States and its territories, the individual medical licensing authorities (‘state medical boards’) of the various jurisdictions grant a license to practice medicine. Each medical licensing authority sets its own rules and regulations and requires passing an examination that demonstrates qualification for licensure. Results of the USMLE are reported to these authorities for use in granting the initial license to practice medicine. The USMLE provides them with a common evaluation system for applicants for initial medical licensure.”
  • “USMLE was created in response to the need for one path to medical licensure for allopathic physicians in the United States. Before USMLE, multiple examinations (the NBME Parts examination and the Federation Licensing Examination [FLEX]) offered paths to medical licensure. It was desirable to create one examination system accepted in every state, to ensure that all licensed MDs had passed the same assessment standards – no matter in which school or which country they had trained.”
  • “The United States Medical Licensing Examination® (USMLE®) is a three-step examination for medical licensure in the U.S. The USMLE assesses a physician's ability to apply knowledge, concepts, and principles, and to demonstrate fundamental patient-centered skills, that are important in health and disease and that constitute the basis of safe and effective patient care.”

Humans take the USMLE to showcase their proficiency in medicine. When you encounter a medical doctor, you are likely to assume they probably took the test and passed it. On an intuitive basis we realize that having to pass such an arduous test is impressive and helps to provide us comfort that the person knows their stuff when it comes to the medical field.

Shift gears.

Can generative AI potentially also be proficient enough to pass the USMLE?

That’s an interesting and some would say important question worthy of considering.

First, some quick background about generative AI.

Realize that generative AI is not sentient and only consists of mathematical and computational pattern matching. The way that generative AI works is that a great deal of data is initially fed into a pattern-matching algorithm that tries to identify patterns in the words that humans use. Most of the modern-day generative AI apps were data trained by scanning data such as text essays and narratives that were found on the Internet. Doing this was a means of getting the pattern-matching to statistically figure out which words we use and when we tend to use those words. Generative AI is built upon the use of a large language model (LLM), which entails a large-scale data structure to hold the pattern-matching facets and the use of a vast amount of data to undertake the setup data training.

There are numerous generative AI apps available nowadays, including GPT-4, Bard, Gemini, Claude, ChatGPT, etc. The one that is seemingly the most popular would be ChatGPT by AI maker OpenAI. In November 2022, OpenAI’s ChatGPT was made available to the public at large and the response was astounding in terms of how people rushed to make use of the newly released AI app. There are an estimated one hundred million active weekly users at this time.

Using generative AI is relatively simple.

You log into a generative AI app and enter questions or comments as prompts. The generative AI app takes your prompting and uses the already devised pattern matching based on the original data training to try and respond to your prompts. You can interact or carry on a dialogue that appears to be nearly fluent. The nature of the prompts that you use can be a make-or-break when it comes to getting something worthwhile out of using generative AI and I’ve discussed at length the use of state-of-the-art prompt engineering techniques to best leverage generative AI, see the link here.

Shortly after ChatGPT was made publicly available, many AI researchers began to test the AI app by administering various well-known standardized tests to see how the AI app would do. In February 2023, a research study was posted that indicated ChatGPT had performed surprisingly well on the USMLE. The study was entitled “Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models” by Tiffany H. Kung, Morgan Cheatham, ChatGPT, Arielle Medenilla, Czarina Sillos, Lorie De Leon, Camille Elepaño, Maria Madriaga, Rimel Aggabao, Giezel Diaz-Candido, James Maningo, Victor Tseng, PLOS Digital Health, and posted on February 9, 2023.

Here is what the research paper stated overall (excerpts):

  • “We evaluated the performance of a large language model called ChatGPT on the United States Medical Licensing Exam (USMLE), which consists of three exams: Step 1, Step 2CK, and Step 3. ChatGPT performed at or near the passing threshold for all three exams without any specialized training or reinforcement. Additionally, ChatGPT demonstrated a high level of concordance and insight in its explanations.”
  • “USMLE questions are textually and conceptually dense; text vignettes contain multimodal clinical data (i.e., history, physical examination, laboratory values, and study results) often used to generate ambiguous scenarios with closely-related differential diagnoses.”

Consider mindfully those above-noted remarks from the AI research effort.

ChatGPT was able to score either at or near the passing threshold for the three staged USMLE. Thus, an arduous medical proficiency exam that we expect human medical doctors to pass was nearly passed by a generative AI app. Some would decry this result as misleading in the sense that the generative AI was doing this without actual “knowledge” akin to what humans seem to possess. The concern is that generative AI is nothing more than a so-called stochastic parrot that mimics human wording and fails to “understand” or “comprehend” what is going on.

Nonetheless, the aspect that generative AI could accomplish such a feat is unto itself impressive, even if done via smoke and mirrors as some suggest. The result is additionally surprising because the researchers used ChatGPT out of the box, as it were, namely the generic version of ChatGPT. Another approach would be to add additional data training on the medical field to ChatGPT, but that’s not what they did in this experiment. A generic data-trained generative AI was able to do well on a highly specialized medical domain exam. For more about how generic generative AI can be fine-tuned to specific domains, see my coverage at the link here.

Let’s consider a few other detailed aspects about the notable research result and then I’ll move to my next topic of discussion.

The research paper noted these salient details (excerpted):

  • “The data analyzed in this study were obtained from USMLE sample question sets which are publicly available.”
  • “376 publicly-available test questions were obtained from the June 2022 sample exam release on the official USMLE website. Random spot checking was performed to ensure that none of the answers, explanations, or related content were indexed on Google prior to January 1, 2022, representing the last date accessible to the ChatGPT training dataset. All sample test questions were screened, and questions containing visual assets such as clinical images, medical photography, and graphs were removed. After filtering, 305 USMLE items (Step 1: 93, Step 2CK: 99, Step 3: 113) were advanced to encoding.”
  • “In this present study, ChatGPT performed at >50% accuracy across all examinations, exceeding 60% in most analyses. The USMLE pass threshold, while varying by year, is approximately 60%.”
  • “Therefore, ChatGPT is now comfortably within the passing range. Being the first experiment to reach this benchmark, we believe this is a surprising and impressive result. Moreover, we provided no prompting or training to the AI, minimized grounding bias by expunging the AI session before inputting each question variant, and avoided chain-of-thought biasing by requesting forced justification only as the final input.”

I’d like to bring your attention to a few points made in those excerpts.

Notice that the experiment consisted of identifying a sample of publicly available questions associated with the exam. The idea is to usually feed samples of questions and not necessarily an entire test per se. It is important to consider how a sample was chosen and whether the sample is suitably representative of what the full test might contain. Fair is fair.

Another fairness consideration is that there is always a chance that the generative AI might have been initially data-trained on the very same questions. If those questions were found when the startup data training took place, you could say it is absurd to feed the same questions into the generative AI. The answers will likely already be known simply due to having seen the questions and their answers beforehand.

If you select questions that arose after the cutoff date of the generative AI app’s data training, you are somewhat comfortable that the content wasn’t encountered already. But even that is readily questioned since the questions might have appeared in other guises. Some exams modify old questions and reuse them in later versions of the exam. There is a chance that a new question is close enough to an older question that perhaps this gives the generative AI a leg up on answering the new question.

My point is that you need to carefully consider how these experiments are conducted. Overall, make sure to look at what sample was chosen and how appropriate it is. What are the odds that the generative AI has previously encountered the same or similar questions? As much as feasible, the goal is to set a fair and square playing field to see whether the generative AI can genuinely answer questions that have not previously been used as part of the data training effort.

You now have a semblance of what takes place when trying to assess generative AI about being able to pass exams such as the pervasive USMLE in the medical domain.

Let’s continue our exploration.

Generative AI And Mental Health Therapy Exam Taking

The research study that explored the use of generative AI such as ChatGPT on the USMLE can serve as a role model for similar kinds of studies. The conception is to identify publicly available sample questions, administer the questions to the generative AI, and see how well or poorly the generative AI scores on answering the questions. As much as possible, try to keep the playing field level and fair.

I decided to try this quickly for the field of mental health therapy or mental health counseling.

There is a well-known exam known as the National Clinical Mental Health Counseling Examination (NCMHCE). Sample questions are publicly posted online. I selected some of the sample questions and fed them into ChatGPT. I opted to use ChatGPT due to its immense popularity and it has generally been the default choice of similar research studies.

I might note that a more advanced generative AI such as GPT-4 by OpenAI or others would likely do a better job than ChatGPT. In that manner, you could interpret the ChatGPT usage as the floor and that we might expect heightened results by using a more advanced generative AI app. There isn’t an ironclad guarantee that a more advanced generative AI will do better. The odds though are in that direction.

We also have to be watchful for in a sense polluting an experiment by perchance using questions that have already been seen by the generative AI during the initial data-training. Furthermore, if the generative AI is hooked up to the Internet, the AI might simply go out and find the questions and their answers, similar to a search engine, rather than trying to directly answer the questions. ChatGPT in that sense is a handy choice because the free version does not readily allow for Internet access to perform its activities and the data training was last cut off in January 2022 (at the time of writing of this discussion).

Let’s dive into the ad hoc experiment by first establishing the nature of the mental health therapy or mental health counseling exam.

The National Clinical Mental Health Counseling Examination (NCMHCE) is devised and administered via an organization known as the National Board for Certified Counselors, Inc. Here is what the website for the organization says (excerpts):

  • “The National Board for Certified Counselors, Inc. and Affiliates (NBCC) is the premier credentialing body for counselors, ensuring that counselors who become nationally certified have achieved the highest standard of practice through education, examination, supervision, experience, and ethical guidelines.”
  • “Established as a not-for-profit, independent certification organization in 1982, NBCC’s original and primary purposes have broadened, and its divisions and affiliates have taken on additional responsibilities to advance the counseling profession and enhance mental health worldwide.”
  • “Today, there are over 69,000 National Certified Counselors (NCCs) in more than 40 countries.”

The gist is that this is a well-known and widely accepted organization, and the exam is likewise well-known and widely accepted. I bring this up in case you read a study that used generative AI on some relatively unknown exam or less than a stellar reputational exam, in which case, you would want to gauge the result of the study as partially on the rigor and standing of the test being given at the get-go.

Here is what the website about the NCMHCE says about the exam (excerpts):

  • “The National Clinical Mental Health Counseling Examination (NCMHCE) is designed to assess the knowledge, skills, and abilities determined to be important for providing effective counseling services. The NCMHCE is a requirement for counselor licensure in many states. It is one of two examination options for the National Certified Counselor (NCC) certification and also fulfills the examination requirement for the Certified Clinical Mental Health Counselor (CCMHC) specialty certification.”
  • “The NCMHCE measures an individual’s ability to apply and evaluate knowledge in core counselor skills and competencies and to practice competently as a professional counselor. Specifically, it assesses an entry-level clinical mental health counselor’s ability to apply knowledge of theoretical and skill-based tenets to clinical case studies. The case studies are designed to capture a candidate’s ability to identify, analyze, diagnose, and develop plans for treatment of clinical concerns.”
  • “Candidates for the NCMHCE must have a graduate-level degree or higher from a counseling program accredited by the Council for Accreditation of Counseling and Related Educational Programs (CACREP) or administered by an institutionally accredited college or university. The counseling degree program must contain courses in eight requirement areas.”

Observe some key points mentioned in those excerpts.

First, the exam is used to assess entry-level clinical mental health counselors. You might say that this is handy for my ad hoc experiment since I want to focus on the keystone threshold needed to be considered suitably knowledgeable for proceeding to perform mental health therapy with actual clients or patients. Other exams might be used to assess more advanced skill levels, but I’m aiming here to start with the usual starting point. I’m sure that other researchers are or will try to do the same for more advanced instances.

Second, note that candidates who want to sit for the exam must have a graduate-level degree or higher from an accredited counseling program or as administered by an accredited college or university. This sets the bar higher than perhaps allowing an undergraduate to take the exam or maybe wantonly opening the exam to anyone who wants to take it. We can presume that the test is likely to ask questions of a hard nature. That’s good since we would want to make sure we give something challenging to generative AI rather than some easy-peasy questions or materials. We might also note that of course, generative AI would not qualify to officially take the exam since it has not met all the criteria to do so.

The official exam website provides an NCMHCE Sample Case Study that indicates the case study is considered updated as of March 2023. I selected six sample questions from this sample set. I want to loudly emphasize that this is an ad hoc selection and I do so merely to be illustrative of what might be done on a more rigorous basis.

Though the date says March 2023, there of course is a chance that these questions and their answers have been around before that date, for which ChatGPT might have seen before the January 2022 cutoff date. I tried to do various probing into ChatGPT to see if the content had already been prior encountered. By and large, it doesn’t seem to be, but that’s not known for sure, and a deeper analysis would need to be undertaken to ascertain this. For the moment, let’s go with the flow and assume that the sample questions weren’t previously seen by ChatGPT during its data training.

The six sampled sample questions cover these six respective topics:

  • Q1. Establish a therapeutic alliance.
  • Q2. Identify strengths that improve the likelihood of goal attainment.
  • Q3. Discuss limits of confidentiality.
  • Q4. Determine a diagnosis.
  • Q5. Assess the presenting problem and level of distress.
  • Q6. Establish short- and long-term counseling goals consistent with the client’s diagnosis.

Keep that in mind as I walk you through what ChatGPT provided as answers to the posed questions.

The test is essentially based on case studies. For these six sampled sample questions, a case study was provided in the publicly posted material. The case study was fed into ChatGPT for this analysis. Rather than displaying for you the entirety of the case study, I will do a quick recap to bring you up to speed.

In this instance, the case study entails a divorced female of age 35 who is first undertaking a mental health counseling session with a mental health therapist who has some background about the client or patient but otherwise, this is the first meeting of the two. The client or patient has already been provisionally diagnosed as having a major depressive disorder.

Additional background is given about the client or patient. For example, after her divorce, she began staying in bed quite a lot and moved back in with her mother. She got fired from her job. She has had financial difficulties. Most days, she feels sad, empty, and anxious. She has joint legal custody with her ex-husband of their two children, respectively aged 10 and 12. And so on.

That outlines the nature of the underlying case study.

Questions And The Answers Generated By The Generative AI

I am going to walk you through each of the six multiple-choice questions and also showcase the answers that were generated by ChatGPT so that you can follow along step-by-step.

My initiating prompt asks ChatGPT to provide answers plus explain why each chosen answer was considered the correct answer by ChatGPT. Asking for an explanation is not necessary, but I thought getting explanations might be interesting to see.

There is also a bit of prompting strategy involved, namely that by asking for an explanation the chances are that a generative AI app might be more extensive in trying to solve a given question or problem, see my discussion at the link here. You could suggest that I was aiding the generative AI by giving an establishing prompt that would urge it to do a better job than otherwise. Whenever you look at research studies doing just about anything with generative AI, make sure to find out what prompts they used. This is a significant factor related to the performance of the generative AI. Studies that fail to showcase their prompts are unfortunately doing a bit of a disservice by not revealing how they got the generative AI to undertake things.

The sampled sample questions are based on the case study, and I’ve placed them in quotes to indicate they came from the case study. In some instances, the wording is slightly reworded merely and strictly for purposes of feeding them into ChatGPT.

I am purposely not going to speculate or comment on the answers that are given by ChatGPT. I will simply note whether ChatGPT selected the correct multiple-choice selection as stipulated in the sample set. I’m guessing that mental health therapists and mental health counselors will undoubtedly find the explanations of special interest and will indubitably get them extensively mulling over what ChatGPT had to say.

Here is my establishing prompt and the answer provided by ChatGPT:

  • My prompt: “I am going to ask you a series of questions about the case study. The questions are multiple-choice. You are to select an answer of either A, B, C, or D from the choices provided for each question. I want you to carefully read each question and then indicate which answer is the best answer of the choices provided. You are to also explain why the answer you’ve chosen is the best answer. Are you ready to answer the first question?”
  • ChatGPT generated a response: “Yes, I'm ready. Please proceed with the first question.”

Okay, we are good to go.

Here’s the first question:

“Q1. What would be the best way for a mental therapist to at initial intake seek to establish a therapeutic relationship with this person?”

“A. Reflect on what is irrational about the woman’s self-evaluations.”

“B. Advise her about how to manage her painful experiences.”

“C. Summarize her emotions and her desire for change.”

“D. Explore how she could improve her role in relationships.”

  • ChatGPT generated response:

“Answer to Q1 is C. Summarize her emotions and her desire for change.”

“Explanation: Establishing a therapeutic relationship involves demonstrating empathy, understanding, and acknowledging the client's emotions. Summarizing her emotions and desire for change (Option C) helps validate her experiences and shows that the therapist is actively listening and comprehending her situation. This approach helps build rapport and sets the foundation for a collaborative therapeutic relationship. It also allows the client to feel heard and understood, creating a safe space for further exploration and intervention.”

End of ChatGPT response

ChatGPT selected answer C, which is considered the correct answer as per the sample set.

The explanation indicates the presumed basis. I could have also asked ChatGPT to explain why the other answers weren’t as good as the selected answer. That would have gotten quite wordy and didn’t seem needed for this ad hoc analysis. A deeper study might want to consider getting a lengthier reply with a more elaborate explanation.

We move to the second question:

“Q2. What information should a mental health therapist explore to help the client remember her strengths?”

“A. The client’s disclosure about her previous level of functioning.”

“B. The client’s recollections of past mistakes.

“C. The client’s feelings about her mother paying for counseling.”

“D. The client’s use of cognitive distortions.”

  • ChatGPT generated response:

“Answer to Q2 is A. The client’s disclosure about her previous level of functioning.”

“Exploring the client's disclosure about her previous level of functioning (Option A) would be most relevant to identify and highlight her strengths. Understanding her past achievements, abilities, and positive aspects of her life before the onset of depressive symptoms can help the therapist and the client focus on resources that can be tapped into for recovery. This approach emphasizes a strengths-based perspective and encourages the client to recognize her capabilities, fostering a more positive outlook on her current situation.”

End of ChatGPT response

The answer indicated by ChatGPT is answer A, which is also the correct answer per the sample set. We are now two-for-two in terms of having gotten the questions right.

Next, let’s see what happens with the third question:

“Q3. How should a mental health therapist handle the client’s concern about confidentiality?”

“A. Explain that as a mental therapist, they will share progress updates with the mother but not provide any details.”

“B. Clarify what can and cannot be shared through informed consent.”

“C. Request the mother’s assent to the treatment and obtain the client’s consent.”

“D. Ask the client for a signed release that would include her mother as part of the treatment process.”

  • ChatGPT generated response:

“Answer to Q3 is B. Clarify what can and cannot be shared through informed consent.”

“The best approach is to clarify confidentiality issues through informed consent (Option B). The therapist should explain the limits of confidentiality, outlining what information can be shared and under what circumstances. This empowers the client to make an informed decision about what aspects of her treatment will remain confidential and what may need to be shared. It respects the client's autonomy and privacy while addressing concerns about the involvement of her mother in the therapy process.”

End of ChatGPT response

The answer indicated by ChatGPT is B, which is also the correct answer via the sample set. Three for three, so far.

Here’s the fourth question:

“Q4. From the perspective of the mental health therapist, what self-report from the client is a discernable criterion for the given diagnosis?”

“A. Her disagreements with her mother.”

“B. Her increased psychomotor agitation.”

“C. Her difficulty managing her children.”

“D. Her decreased pleasure in her activities.”

  • ChatGPT generated response:

“Answer to Q4 is D. Her decreased pleasure in her activities.”

“A discernible criterion for a major depressive disorder is often a pervasive and persistent decrease in pleasure or interest in previously enjoyed activities. This is commonly referred to as anhedonia. The client's report of not being able to remember the last time she enjoyed something and the cessation of an activity she used to find enjoyable (creating jewelry) aligns with this criterion. While other aspects, such as disagreements with her mother (Option A) or difficulty managing her children (Option C), may be related to her emotional state, the decreased pleasure in activities is a more specific indicator for depression.”

End of ChatGPT response

The answer indicated by ChatGPT is D, which is the correct answer according to the sample set. You will also note that this time the explanation opted to explain why the chosen answer was considered a better choice than some of the other proposed answers.

We are at four of four in terms of getting the correct answers.

Let’s see what occurs with the fifth question:

“Q5. What criteria were likely used to determine the severity specified for the client’s major depressive disorder?”

“A. The number of symptoms is not substantially in excess of those needed to make the diagnosis, yet functional impairment exists.”

“B. The intensity of the symptoms is distressing but manageable, and results in minor impairment of social or occupational functioning.”

“C. The intensity of symptoms is high and is accompanied by psychomotor agitation and mixed features associated with a major depressive episode.”

“D. The number of symptoms and their intensity are distressing and unmanageable and interfere with the client’s social and occupational functioning.”

  • ChatGPT generated response:

“Answer to Q5 is D. The number of symptoms and their intensity are distressing and unmanageable and interfere with the client’s social and occupational functioning.”

“The severity specified for major depressive disorder is often determined by the number and intensity of symptoms, as well as their impact on the client's social and occupational functioning. In this case, the client reports feeling sad, empty, and anxious most days, experiences tension every day, has difficulty getting out of bed, and has ceased engaging in previously enjoyed activities. Additionally, she has lost her job, faces financial difficulties, and expresses guilt about her interactions with her children. These factors suggest a significant impact on both social and occupational functioning, aligning with the criteria for a more severe form of major depressive disorder.”

End of ChatGPT response

ChatGPT indicates the answer should be D, but the sample set indicates the correct answer is A. This is the first miss by ChatGPT in this set of sampled sample questions.

I was curious whether ChatGPT could justify the answer D versus the answer A.

One thing to keep in mind is that some generative AI apps such as ChatGPT tend to immediately back down when you challenge them about an answer. The AI will indicate that it was wrong and switch to the answer that you say is the correct answer. In a sense, this is somewhat disconcerting because you would generally prefer the AI to moderately push back and support an answer that was chosen.

I am not saying this should be doggedly dogmatic. It certainly makes sense to have the AI back down if the user is telling the AI that the answer is wrong, though I think you can see how this might be a dangerous slope to slide upon. Just because a user says that something is wrong does not mean that it indeed is wrong. You can end up with the AI being too easily convinced of falsehoods simply because the user said they were truths. This is an ongoing issue of concern about generative AI, see my analysis at the link here.

All in all, rather than telling the AI that it was wrong, which would possibly get it to collapse like a deck of cards, I came to the matter politely and tangentially. I merely asked ChatGPT to compare the answer D with the answer A. I didn’t tip my hand that the answer A is considered the correct answer.

Here we go:

  • My prompt: “I'd like you to compare the answer D that you selected to the choice A. What makes answer D better than answer A?”
  • ChatGPT generated response:

“Let's compare options D and A:”

“D. The number of symptoms and their intensity are distressing and unmanageable and interfere with the client’s social and occupational functioning.”

“A. The number of symptoms is not substantially in excess of those needed to make the diagnosis, yet functional impairment exists.”

“The main distinction lies in the severity of functional impairment. Option D suggests that the number of symptoms and their intensity are distressing and unmanageable, leading to significant interference with social and occupational functioning. This aligns with a more severe form of major depressive disorder, where the impairment is substantial.”

“On the other hand, Option A acknowledges functional impairment but does not emphasize the distressing and unmanageable nature of the symptoms. It leaves room for interpretation that the impairment might be present but not to the extent that it is distressing or unmanageable.”

“In the context of major depressive disorder, severity is often determined not just by the presence of symptoms but also by the impact on daily functioning. Option D explicitly addresses the distress and interference with functioning, making it a more comprehensive and accurate description of a severe presentation of major depressive disorder.”

End of ChatGPT response

I’d bet that mental health professionals could readily debate the indication of ChatGPT about why one of the answers is construed as better than the other. Please do so at your leisure.

Moving to the sixth and final question, take a look at this one:

“Q6. From the perspective of the mental health therapist, what short-term goal would guide the treatment of the client’s presenting problem?’

“A. Spend one hour each day rewriting difficult childhood memories with her mother.”

“B. Return to her previous sleep schedule to be more present with her children.”

“C. Spend one hour each day journaling about her vision for her next marriage.”

“D. Return to full-time work in nursing to boost her self-image and mood.”

  • ChatGPT generated response:

“Answer is B. Return to her previous sleep schedule to be more present with her children.”

“The most appropriate short-term goal would be to address the immediate issue affecting her daily functioning, which is her disrupted sleep schedule. Returning to her previous sleep schedule (Option B) can have a positive impact on her mood, energy levels, and ability to engage with her children. This goal is specific, achievable, and directly addresses a key factor contributing to her distress. It also aligns with improving her overall well-being and functioning in the short term.”

End of ChatGPT response

The answer selected by ChatGPT is answer B, which is the correct answer according to the sample set.


Please do not try to calculate the percentage of times that ChatGPT was able to correctly answer the sampled sample. Doing so would be ridiculous as this was not a rigorous experiment but instead an ad hoc one and meant solely to get the juices flowing about examining how generative AI might do on these kinds of tests. That being said, I believe there is enough indication that performing a thorough study would be worthwhile. Had the generative AI got none of the answers correctly I would probably be leaning toward suggesting that a full-on study wasn’t likely worth the effort. This snippet suggests that doing more might be valuable.

There are flies in the ointment on these matters.

One argument about having generative AI take these various types of tests is that there isn’t any human soul or human connection that is also being assessed, see my discussion at the link here. In other words, just because a generative AI app can answer questions on a dry test does not mean that we would want the generative AI to interact with real people in real life and provide advice as to whatever domain or realm of expertise is being tested.

The argument is further amplified when considering the topic of mental health. Some would assert that only another human can adequately counsel another human. An AI system is not human and does not have human experience under its belt. A counterviewpoint is that notwithstanding humanness, there is still a place for AI to aid humans, including in the sphere of mental health guidance or advice.

Let’s conclude this discussion for now by invoking a famous line.

The renowned American psychologist Carl Rogers purportedly said this: “In my early professional years, I was asking the question, how can I treat, or cure, or change this person? Now I would phrase the question in this way, how can I provide a relationship that this person may use for their personal growth?”

Can generative AI form a relationship with humans and if so, do we want that to be how mental health is conveyed or advised?

More questions ostensibly need more answers; thus, the endeavor must continue.

Mon, 01 Jan 2024 09:36:00 -0600 Lance Eliot en text/html https://www.forbes.com/sites/lanceeliot/2024/01/01/an-exploratory-look-at-whether-generative-ai-can-pass-an-official-mental-health-counseling-licensing-exam-that-professionals-take/
How long it takes to get 6 different health care degrees and how much they pay

(Stacker) - Demand for health care services is on the rise.

Post-COVID, an increasing number of people are making the choice to focus more fully on their health. According to a survey conducted by The Harris Poll for the Samueli Foundation in May 2020, 80% of people reported that they would try to concentrate more on self-care after the COVID-19 pandemic. Sixty-four percent reported that they were concentrating on their mental health more than they had before.

People are also getting older and living longer. As baby boomers age, they need more medical care to accommodate health problems such as chronic conditions. At the same time, many of the doctors who can treat these patients are reaching retirement age. The Census Bureau reports that 1 in 6 people in the United States were 65 and older in 2020. By 2034, the Association of American Medical Colleges estimates the country will be short 37,800 to 124,000 physicians.

Vivian Health gathered information about health programs across the nation, looking to data from the Bureau of Labor Statistics to outline the timelines, prerequisites, and potential jobs and earnings for six different educational programs in health care.

The health care field encompasses a wide array of professions, such as pharmacy, optometry, medical transcription, EMT, and paramedics. Other careers in health care include dietitians and nutritionists, dentists, and podiatrists, along with many others. Some careers in the health care field require only minimal schooling, such as a diploma or certification.

If you’re interested in a career in the health care industry, continue reading to learn more about possible jobs in this field.

Medical doctorate

  • Time to complete: 4 years
  • Typical prerequisites: Bachelor’s degree
  • Typical job: Physician ($227,180 median annual earnings)

A medical doctorate is one option for students interested in the health care field. Medical school involves myriad training, including courses in psychology and biochemistry, and rotations later in the program. A physician must finish about three to seven years of residency training and become licensed in the state where they plan to practice. There are various kinds of doctors, such as family medicine physicians and emergency medicine physicians.

Nursing degree (associate or bachelor’s)

  • Time to complete: 2-4 years
  • Typical prerequisites: Diploma or GED
  • Typical job: Registered Nurse ($81,220 median annual earnings)

Another possible path for students wishing to enter the medical field is pursuing a nursing degree. Students can earn an associate degree, a bachelor’s degree, or a diploma through a nursing program. Students in these programs can expect to take classes such as microbiology, psychology, and anatomy. A registered nurse must be licensed and can also get certified in a particular specialty, such as gerontology or ambulatory care.

Radiologic technology degree (associate or bachelor’s)

  • Time to complete: 2-4 years
  • Typical prerequisites: Diploma or GED
  • Typical job: Radiologic technologist/technician ($65,140 median annual earnings)

Students may wish to pursue a radiologic technology degree, which they can earn through an associate’s or bachelor’s degree. This program includes classes in image evaluation and pathology. In the majority of states, a radiologic technologist or technician must be certified or licensed. The career is expected to see 6% growth between 2022 and 2032.

Health information technology (certification or associate)

  • Time to complete: 9 months-2 years
  • Typical prerequisites: Diploma or GED
  • Typical job: Health information technologist/medical registrar ($58,250 median annual earnings)

A certification or associate’s degree in health information technology is another educational path students can take. Courses in the program include medical terminology and medical ethics. A health information technologist or medical registrar might need a certification for this type of work. The job outlook for this career has a notable estimated growth of 16% between 2022 and 2032.

Diploma in practical nursing

  • Time to complete: 1 year
  • Typical prerequisites: Diploma or GED
  • Typical job: Licensed practical/licensed vocational nurse ($54,620 median annual earnings)

Some prospective students may wish to earn a diploma in practical nursing. An LPN/LVN program includes classes such as nursing fundamentals and pharmacology, and students receive monitored clinical experience. Licensed practical nurses and licensed vocational nurses provide basic health care treatment to patients, such as monitoring vital signs and maintaining medical records.

Medical assisting (diploma or associate)

  • Time to complete: 10-20 months
  • Typical prerequisites: Diploma or GED
  • Typical job: Medical assistant ($38,270 median annual earnings)

A diploma or associate’s degree in medical assisting is another possible educational path. Medical assistants perform administrative and clinical duties, such as scheduling appointments at the front desk and taking patients’ vitals in the exam room. A medical assistant may need to be certified, and the job outlook for this career is estimated to grow 14% between 2022 and 2032.

Story editing by Shannon Luders-Manuel. Copy editing by Kristen Wegrzyn. Photo selection by Lacy Kerrick.

This story originally appeared on Vivian Health and was produced and distributed in partnership with Stacker Studio.

Tue, 26 Dec 2023 06:00:00 -0600 en text/html https://www.wbay.com/2023/12/26/how-long-it-takes-get-6-different-health-care-degrees-how-much-they-pay/
The Biggest Exercise Mistake People Make in January No result found, try new keyword!Along that same note, you really, really need rest days. Contrary to what some fitness apps that praise exercise streaks may lead you to believe, you don’t get a literal gold star for working out ... Fri, 05 Jan 2024 02:05:00 -0600 en-us text/html https://www.msn.com/ Could researchers develop a vaccine to lower bad cholesterol?
  • All people need some cholesterol, but having too high cholesterol levels can be dangerous, particularly to areas of cardiovascular health.
  • Research is ongoing to find new ways to help people keep cholesterol within a healthy range.
  • Data from a recent study on animals found a vaccine that may be effective at lowering cholesterol.
  • Future research is required before this data can be applied in clinical practice with humans.

Cholesterol levels outside a healthy range can be dangerous for heart health, but what options exist for lowering cholesterol?

Most often, people can manage cholesterol levels by changing components of their lifestyle or taking certain medications. However, the options for assistance with cholesterol management may be expanding.

A study published in npj vaccines examined the effectiveness of a cholesterol-lowering vaccine.

The study looked at mouse and nonhuman primate models, and found that a bivalent vaccine effectively lowered cholesterol levels.

The results point to promising research and the potential development of another way to help people keep cholesterol in a healthy range.

Study author Dr. Bryce Chackerian, Regent’s professor of molecular genetics and microbiology at the University of New Mexico School of Medicine, explained the reasoning behind the research to Medical News Today.

“The common medications to treat elevated cholesterol are statins,” he told us. “However, statins don’t work for everyone, and some patients on statins experience side effects.”

“Recently, a new class of medication, called PCSK9 inhibitors, have been approved to lower cholesterol. PCSK9 inhibitors are very effective at lowering cholesterol, but unfortunately they are also very expensive, which has limited their use. We were interested in developing a lower-cost vaccine-based approach for inhibiting PCSK9. The idea behind this approach is that the vaccine induces antibodies against PCSK9, which then lower cholesterol levels.”

– Dr. Bryce Chackerian

The research notes that the body removes low-density lipoprotein (LDL) cholesterol, also known as “bad” cholesterol, via the low-density lipoprotein receptor (LDL-R).

The protein PCSK9 helps inhibit this process, thus leading to higher levels of LDL cholesterol in the bloodstream. There are a few ways to inhibit PCSK9 — one potential way is through a vaccine.

The study explored the efficacy of these potential vaccines in monkeys and mice. The researchers looked at the effectiveness of two PCSK9 vaccines: single and bivalent.

They found that single and bivalent vaccines lowered cholesterol levels among mice. However, the single vaccine type did not lower LDL cholesterol to a statistically significant level.

Among monkeys, researchers were able to carefully measure cholesterol levels over time to help test vaccine efficacy. They also tested how the vaccines worked in combination with statins.

They found that the bivalent vaccine was effective in lowering LDL cholesterol. However, the single vaccine was not effective on its own and had to be combined with statins to be effective.

Dr. Chackerian, Ph.D. explained: “In our study, we identified a vaccine that dramatically lowers cholesterol in two different animal species. In monkeys, for example, vaccination led to a 30% reduction in LDL cholesterol levels, without requiring statins. Importantly, the vaccine also had long-lasting effects on cholesterol levels, meaning that it is likely that patients would not need frequent injections.”

Is this anti-cholesterol vaccination regime likely to be effective in humans? First of all, the researchers note that their study focused on animals, so more research is required before doctors could use the vaccine in clinical practice with human patients.

The researchers also noted that the average baseline of LDL cholesterol in the monkeys was normal, which might have limited how much LDL was lowered.

It is also not entirely clear why the bivalent vaccine was more effective in the monkeys, so this is another area for researchers to explore.

The research also included a small number of monkeys, meaning future studies could include larger sample groups. More research is needed to determine the vaccine’s long-term effectiveness and the potential need for boosters.

Furthermore, the study authors note that the experimental vaccine in their study was less effective than other cholesterol-lowering methods. Nevertheless, they point out that even lowering cholesterol by a small amount can play a crucial role in decreasing cardiovascular events.

Dr. Richard Wright, a board-certified cardiologist at Providence Saint John’s Health Center in Santa Monica, CA, who was not involved in the current research, commented on the findings, offering the following words of caution:

“Unfortunately, there are insufficient data to show how long, or even if, this type of vaccine would lower the LDL in humans. The larger issue is the magnitude of benefit: no vaccination has been shown to be as effective as current therapies, and in this current study, the magnitude of LDL reduction is less than what is achievable with current inexpensive statin drugs and far less than obtained with administration of exogenous monoclonal antibodies or RNA therapeutics.”

Still, if research moves forward in this area, it could be highly beneficial for individuals at a higher risk for problems from high cholesterol. And it could be potentially used in combination with other therapies.

Dr. Cheng-Han Chen, board-certified interventional cardiologist and medical director of the Structural Heart Program at MemorialCare Saddleback Medical Center in Laguna Hills, CA, also not involed in the study, noted that “[t]he potential clinical benefit of such a vaccine would be tremendous.”

“Current PCSK9 inhibitors in clinical use, while extremely efficacious, are very expensive. In addition, these therapeutics require routine administration. A vaccine-based targeting of PCSK9 could potentially provide long-lasting lowering of LDL levels with a longer duration of effect. This would lower health care costs for the system while improving cardiovascular outcomes,” he added.

As noted by the Centers for Disease Control and Prevention (CDC), the liver is the organ that produces cholesterol. Chlesterol is vital for the production of certain hormones and the digestion of foods high in fat.

There is also cholesterol in certain foods. The two main types of cholesterol are LDL cholesterol and high-density lipoproteins (HDL) cholesterol.

LDL cholesterol is sometimes called “bad” cholesterol because when levels of it in the body get too high, it can increase the risk of heart attack and stroke.

Certain lifestyle choices can increase the risk of high cholesterol, such as eating a diet high in saturated fat, not exercising regularly, and smoking.

People can make lifestyle and dietary changes to help lower their cholesterol levels. They can also take medications like statins to help reduce cholesterol levels.

But even with these interventions, cholesterol can still be a challenge to keep in a healthy range. This is why it is crucial that researchers continue to explore potential new ways to manage cholesterol levels.

Mon, 01 Jan 2024 20:30:00 -0600 en text/html https://www.medicalnewstoday.com/articles/could-researchers-develop-a-vaccine-to-lower-bad-cholesterol
What's The Deal With That Cough Everyone Seems To Have Right Now? No result found, try new keyword!It's not COVID or the flu. If you've been sick for a few weeks and have tested negative for everything, here's what's going on. View Entire Post › ... Thu, 04 Jan 2024 11:16:02 -0600 en-us text/html https://www.msn.com/ ChatGPT bombs test on diagnosing kids’ medical cases with 83% error rate
Dr. Greg House has a better rate of accurately diagnosing patients than ChatGPT.
Enlarge / Dr. Greg House has a better rate of accurately diagnosing patients than ChatGPT.

ChatGPT is still no House, MD.

While the chatty AI bot has previously underwhelmed with its attempts to diagnose challenging medical cases—with an accuracy rate of 39 percent in an analysis last year—a study out this week in JAMA Pediatrics suggests the fourth version of the large language model is especially bad with kids. It had an accuracy rate of just 17 percent when diagnosing pediatric medical cases.

The low success rate suggests human pediatricians won't be out of jobs any time soon, in case that was a concern. As the authors put it: "[T]his study underscores the invaluable role that clinical experience holds." But it also identifies the critical weaknesses that led to ChatGPT's high error rate and ways to transform it into a useful tool in clinical care. With so much interest and experimentation with AI chatbots, many pediatricians and other doctors see their integration into clinical care as inevitable.

The medical field has generally been an early adopter of AI-powered technologies, resulting in some notable failures, such as creating algorithmic racial bias, as well as successes, such as automating administrative tasks and helping to interpret chest scans and retinal images. There's also lot in between. But AI's potential for problem-solving has raised considerable interest in developing it into a helpful tool for complex diagnostics—no eccentric, prickly, pill-popping medical genius required.

In the new study conducted by researchers at Cohen Children’s Medical Center in New York, ChatGPT-4 showed it isn't ready for pediatric diagnoses yet. Compared to general cases, pediatric ones require more consideration of the patient's age, the researchers note. And as any parent knows, diagnosing conditions in infants and small children is especially hard when they can't pinpoint or articulate all the symptoms they're experiencing.

For the study, the researchers put the chatbot up against 100 pediatric case challenges published in JAMA Pediatrics and NEJM between 2013 and 2023. These are medical cases published as challenges or quizzes. Physicians reading along are invited to try to come up with the correct diagnosis of a complex or unusual case based on the information that attending doctors had at the time. Sometimes, the publications also explain how attending doctors got to the correct diagnosis.

Missed connections

For ChatGPT's test, the researchers pasted the relevant text of the medical cases into the prompt, and then two qualified physician-researchers scored the AI-generated answers as correct, incorrect, or "did not fully capture the diagnosis." In the latter case, ChatGPT came up with a clinically related condition that was too broad or unspecific to be considered the correct diagnosis. For instance, ChatGPT diagnosed one child's case as caused by a branchial cleft cyst—a lump in the neck or below the collarbone—when the correct diagnosis was Branchio-oto-renal syndrome, a genetic condition that causes the abnormal development of tissue in the neck, and malformations in the ears and kidneys. One of the signs of the condition is the formation of branchial cleft cysts.

Overall, ChatGPT got the right answer in just 17 of the 100 cases. It was plainly wrong in 72 cases, and did not fully capture the diagnosis of the remaining 11 cases. Among the 83 wrong diagnoses, 47 (57 percent) were in the same organ system.

Among the failures, researchers noted that ChatGPT appeared to struggle with spotting known relationships between conditions that an experienced physician would hopefully pick up on. For example, it didn't make the connection between autism and scurvy (Vitamin C deficiency) in one medical case. Neuropsychiatric conditions, such as autism, can lead to restricted diets, and that in turn can lead to vitamin deficiencies. As such, neuropsychiatric conditions are notable risk factors for the development of vitamin deficiencies in kids living in high-income countries, and clinicians should be on the lookout for them. ChatGPT, meanwhile, came up with the diagnosis of a rare autoimmune condition.

Though the chatbot struggled in this test, the researchers suggest it could improve by being specifically and selectively trained on accurate and trustworthy medical literature—not stuff on the Internet, which can include inaccurate information and misinformation. They also suggest chatbots could improve with more real-time access to medical data, allowing the models to refine their accuracy, described as "tuning."

"This presents an opportunity for researchers to investigate if specific medical data training and tuning can improve the diagnostic accuracy of LLM-based chatbots," the authors conclude.

Wed, 03 Jan 2024 09:46:00 -0600 Beth Mole en-us text/html https://arstechnica.com/science/2024/01/dont-use-chatgpt-to-diagnose-your-kids-illness-study-finds-83-error-rate/
Looking for an ob/gyn? Here's how

It's important to find the right OB-GYN to guide you through some of life's greatest joys and troubles.

An obstetrician-gynecologist works with through , pregnancy, childbirth, aging, menopause and sometimes life-threatening diseases. It's important that your personalities mesh.

"You have to feel comfortable sharing intimate details of your life with this person," said Dr. Laura Hunter, an OB-GYN at Penn State Health Obstetrics and Gynecology and Penn State Health Lancaster Medical Center. "If you don't, you should find a different doctor."

A physician can be either an obstetrician or a gynecologist, but many specialize in both. They may work in private practice, through a or in a hospital, women's health clinic or birthing center.

When searching for a new OB-GYN, it's important to double check your . Looking for someone in your insurer's list of network providers boosts the odds that your insurance will cover the doctor's services. The insurance company's website should have a list of providers.

Choose an office near your home or work.

Make sure the OB-GYN has practice privileges at the hospital you plan to use.

You can come up with a list of candidates and then read about their education, training, experience and areas of expertise in online biographies.

Use the American Board of Medical Specialties' Certification Matters tool to verify that the doctor is board-certified.

"Call the local hospital with an obstetrics unit and ask to talk to a nurse," suggested Dr. Christina DeAngelis, an OB-GYN at Penn State Health Obstetrics and Gynecology and an assistant professor of obstetrics gynecology at Penn State College of Medicine. "If you want an honest recommendation for a good OB-GYN, ask a labor and delivery nurse."

Your primary care doctor also may be able to recommend an OB-GYN who's a good fit for you, based on your personality.

Hunter recommends that women follow their instincts when choosing an OB-GYN.

"There's no magic tool for finding an OB-GYN who's a good fit for you," she said, "But you'll know if you feel comfortable or not."

Not being able to talk honestly with your doctor could affect your .

"I can't help someone who's finding it painful to have sex if she's not able to talk to me about that," Hunter said.

A doctor should listen carefully and address your concerns without judgment or personal opinions, DeAngelis said.

"Patients need to know they can trust their OB-GYN," DeAngelis said. "We need to be able to address their concerns, regardless of what they are."

Gynecologic care should begin at age 21, with a Pap test for , or earlier if a woman has a very heavy or painful period, is sexually active or is planning to become sexually active.

"There really is no hard and fast rule of when to begin care," Hunter said. "It depends on the circumstances of each patient."

When pregnant or planning to become pregnant, a woman should see an OB-GYN as soon as possible.

"We consider the needs of every patient and treat each patient accordingly," DeAngelis said. "It's important to focus on every person as an individual."

More information: The American College of Obstetricians and Gynecologists has more on women's health.

Copyright © 2023 HealthDay. All rights reserved.

Citation: Looking for an ob/gyn? Here's how (2023, December 29) retrieved 5 January 2024 from https://medicalxpress.com/news/2023-12-obgyn.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

Thu, 28 Dec 2023 20:30:00 -0600 en text/html https://medicalxpress.com/news/2023-12-obgyn.html

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