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How to Handle Non-Disclosure Agreements (NDAs) When You Write Your UX Case Study

Most designers are familiar with non-disclosure agreements. Usually, your employer asks you to sign such an agreement to prevent you from revealing confidential information. But when you write your UX case studies , your NDAs suddenly seem like an obstacle. How should you write about your design projects if you’ve signed an NDA? Well, a simple solution is to ask for permission—but if that fails, there are other options you can explore. Let’s go through the basics of how to handle NDAs in your UX case studies.

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What are NDAs?

Let’s begin with a quick explainer of what non-disclosure agreements are. Companies usually ask people who work with them to sign these agreements to prevent the loss of trade secrets. That’s because there might be huge financial losses if a competitor finds out about how a company operates.

Your NDA restricts your ability to share confidential information relating to your work. So, what counts as confidential information? Most companies define what they mean by “confidential” in their NDA; nonetheless, to err on the side of caution, you should assume any information that isn’t publicly available is confidential.

This means if you signed an NDA, you by default cannot write a UX case study based on your project. Obviously, many UX designers write case studies about their projects—and they do so ethically and without contravening their agreements. How can you do the same?

Can’t You Just Ignore Your NDA…?

Well, no! If you could, we’d have renamed our headline “How to ignore your non-disclosure agreements”. Unfortunately, you’ll face some consequences if you willingly breach your NDA.

First, your company might act against you. They might file a lawsuit to demand compensation or provide a bad reference (or no reference, which can have the same effect) for your job applications. Even if it’s not likely that your employer will sue you—although you never know, depending on how serious the case is—there are other things you should consider, too.

Perhaps more importantly, you’ll likely look bad to a recruiter if you breach your NDA . If you freely, and without permission, reveal confidential information in your UX case studies and job interviews, then your recruiter will think you cannot be trusted with trade secrets. That’s disastrous for your job application, and it doesn’t make sense for you to take such a risk when the goal of your UX case study is to help you get a job.

So, to avoid any negative impacts on your job applications, you should never ignore your NDAs. Here’s what to do instead.

Public Content is Public

Websites and apps which are publicly available are always safe to use. That way, you’re free to include any public design results you’ve created in your case studies. This might not include content or designs which are behind a paywall—if your design is behind a paywall, read on to see what you could do. On top of that, you may also not be allowed to share the work process which led to the result. Here’s how you find out what you can and cannot do.

First, Read Your Contract

Find out the terms of your NDA. Your contract usually spells out what it considers “confidential”. Use it to determine if it’s okay to write about a project without getting permission from your employer. If in doubt, contact them about it, anyway.

Ask for Permission to Write About a Project

Next, ask your employer for permission to write a UX case study based on your project. You’ll most likely get the green light to go ahead as long as you clearly explain what you’ll include in your case study.

When you ask for permission, it’s best to make the following clear:

Which project(s) you will write about;

What parts of the project(s) you will include—for instance, which parts of the design process and even which images, sketches and screenshots you’ll use; and

Where you’ll display the case study—for instance, in your online UX design portfolio.

Even if you’ve not signed an NDA, you should still ask for permission! It’s a nice gesture, and you’ll demonstrate a great deal of professionalism.

Furthermore, you should always send your employer a copy of your final UX case study before you publish it, just in case you accidentally included sensitive information in it. Always ask for a green light.

Sanitize the Information You Include in Your UX Case Studies

Remember to sanitize the information you include in your case studies:

Remove unnecessary information that might reveal confidential details , especially if they don’t help explain your design skills and process.

Show percentages rather than the actual figures. For instance, instead of saying “we saw an increase in the monthly signups from 12,512 to 14,013”, write “we saw a 12% increase in monthly signups”. This way, you clearly communicate your impact without revealing too much.

Generalize the work you’ve done. Share your overall design process, rather than minute details of your project. Don’t share screenshots of detailed behind-the-scenes sketches if they are confidential. Instead, share sketches without confidential information and zoomed-out pictures of Post-its in an ideation session. You’ll cut down on the length of your UX case studies, too.

Sanitize your information before you ask your employer for permission to write your case study. That way, you’ll increase your chances of getting approved.

Ask for Permission to Talk About a Project in Private

If your employer doesn’t want you to publish a UX case study on your project, your next-best solution is to ask for permission to talk about your project to recruiters in private . This could be done either face-to-face, such as in a job interview, or by setting a password to your case study. This way, you can still demonstrate your skills to the people who matter the most in your job applications.

Again, clarity is key when you ask for permission to talk about your project in private. And you can take that from at least one good authority:

“Be specific. Ask your previous employer if you can show X + Y pieces. Let them know how you plan to explain X + Y pieces. Let them know specifically who you’ll be sharing it with, and why. This will give you a much better chance of being given permission to show your work.” —Brittany Mederos, Senior Designer at Microsoft

If you can only talk about your project in private, then the UX case studies you show in your UX design portfolio should be brief summaries. In a paragraph, explain your job scope and role and end with a sentence that says you’ll be willing to talk more in an interview.

The same rule about sanitizing your information applies when you speak to recruiters about your projects! Don’t gush about minute details of your work. Instead, focus on general design processes. Use percentages if you must talk about numerical metrics. It can be hard to refrain from letting secret details slip in the heat of the moment in an interview. Remember, though—it pays to come across as trustworthy and honorable. Any good recruiter will prefer that over discovering someone who they think may give away secrets sometime in the future.

Don’t Blur or Black Out Parts of Your UX Case Study

If you really want to showcase your work for a client but cannot do so due to your NDA, you might have considered removing sensitive parts of your case study. This means removing or replacing all confidential information, such as client logos, financial data, user names and habits, etc.

However, we don’t recommend that you black out parts of your UX case study . This is because:

You still run the risk of violating your NDA if your employer or client finds out and is unhappy that you wrote your UX case study.

You might miss out or forget to remove some confidential information.

Information that you think can be included in your UX case study might turn out to be sensitive.

It provides a bad reading experience, as recruiters essentially get a story with gaping holes in it.

You’ll likely look bad to a recruiter if you freely risk revealing confidential information, and the recruiter will think you cannot be trusted with trade secrets.

As we mentioned above, you’ll be far better off doing your own personal project that demonstrates the same skills.

The Take Away

When you write your UX case studies, NDAs can feel like huge obstacles. Thankfully, they’re usually not. Companies just want to protect their trade secrets. So, as long as you sanitize your information and ask for permission to write your case study, you are likely to get the go-ahead.

We suggest you do the following to handle your NDA:

First, check your contract to learn the terms of your NDA.

Next, get permission to write about your project in a UX case study.

If that fails, ask if you can talk privately about your project, for instance in a job interview.

References and Where to Learn More

Read more tips on NDAs by Brittany Mederos: NDAs and confidentiality

Hero image: Author / Copyright holder: Jelleke Vanooteghem. Copyright terms and license: Unsplash License.

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Which legal documents are required in user research?

What kind of legal agreement do we have to solicit from user research participants prior to involving them in a user study? I'm specifically interested in diary studies, but I guess it's pretty much the same in all methods.

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• What kind of legal agreement are you talking about? What are your concerns when there isn't one? –  jazZRo Commented Nov 18, 2013 at 12:46

2 Answers 2

Caveat: I am not a lawyer, I am a user researcher. If you are concerned about what legal agreement is necessary before you conduct research, you should talk to a lawyer.

In general, most user research has a Non-Disclosure Agreement in place with the participant that states that the research participant will not discuss the research that they took part in with anyone else. This is done to protect your intellectual property. If you work for a company, you should have your legal counsel draw up a NDA (if they don't have one already).

If your research participants are professionals who will be completing the research representing their company (for example, if you were doing diary studies with medical professionals in a hospital), the individual might not be empowered to sign an NDA. It will probably need to go through their company's legal department. In this case, you will probably need to let your legal counsel talk to their legal counsel.

If you are dealing with participants in an enterprise environment, or healthcare, or any other research in which they could be revealing their own confidential information to you, you might also need to sign an NDA that you will not reveal anything confidential either. This is to protect the company's intellectual property, as well as deal with any privacy concerns either on the part of the individual who is participating in our research or any information that the individual has access to about others. To go back to my medical professional example, they will probably want to ensure that you don't reveal anything about their hospital's practices, as well as anything else that you could encounter during the course of your research. If you have to do this, you should talk to your legal counsel to ensure that the NDA is compatible with the research that you want to do.

In short, you should talk to a lawyer. If you work for a company, talk to your employer's lawyers. If you are an individual, you should talk to a lawyer that specializes in intellectual property law to ensure that your IP is protected and that you are not doing anything that could run you afoul of any relevant IP, privacy, or other laws.

• 1 This focus on NDA sounds like US practice? I have done user research in Germany, and the major legal concerns are to prove that we are not hurting the users' Informationelle Selbstbestimmung rights (privacy-related) and Arbeitsnehmer rights (their right to not be discriminated against by their employer). We had to get our questionnaire approved by the Betriebsrat, an organ looking after employees' rights. Nobody cared about any NDAs. This is why I think that the whole questionnaire is unanswerable: the answer will differ for each legislation. –  Rumi P. Commented Nov 19, 2013 at 11:14
• I do work for a US company. When I have done research with participants overseas, the NDA requirements have been the same, including the participant's company requiring an NDA with me and my company. I can't speak to the experience of someone who is not working in the US and is conducting research with people who are not in the US. –  nadyne Commented Nov 19, 2013 at 17:56
• It is understandable that you cannot speak of things out of what you have experienced. I just wanted to point out that it will vary a lot between countries, so the information of the context (in this case country) about which you are speaking is an important part of the answer. –  Rumi P. Commented Nov 20, 2013 at 10:11

I agree with nadyne's answer that you should consult with a lawyer regarding proprietary information regarding the organization and NDA.

However, I'd also add that users should sign a usability test consent form. This will be necessary if you are recording the session (audio and/or video). The form should include how the participant's data will be used, what the session will consist of and allowing the participant to end the session at any time. There are a couple of stock consent forms around the internet. I hope this helps!

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Obtaining Consent for User Research

July 3, 2022 2022-07-03

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To ensure that user research provides meaningful data, UX teams must get feedback from representative customers. You can certainly reach out to a customer for a quick phone call about their experiences without calling it a research session or needing a consent form. However, as soon as you transcribe quotes from that call or share that person’s information with other people on your team, you are technically (mis)using that person’s data in a manner to which they did not agree.

In other words, by not informing your participants about how you will use their data and by misleading them into believing that they were having a private conversation, you may be violating research ethics principles and taking advantage of that person’s kindness and willingness to help.

Informed consent is an exchange of information in which both of the following must occur:

• The researcher informs the participant about what involvement in the study entails and the potential consequences of participating.
• The participant fully understands the terms of the study and can make an informed decision about whether they would like to voluntarily participate.

A research consent form (also known as an informed consent form ) serves as written documentation of this exchange.

A downloadable template can be found here , but for the best results, please continue reading for more information about how you may adapt the template to better fit your study needs.

In This Article:

Why is informed consent important, informed consent means respecting and protecting participants, are consent forms really necessary, what belongs in a consent form.

While researchers may be well-intended in their hopes of learning about user behaviors, the intent does not matter nearly as much as the execution of the study and its impact. There are many documented cases of unethical research and its dangerous outcomes. One famous example of research abuse is the Nuremberg doctors’ trial. The doctors were placed on trial for war crimes, due to harmful and lethal experiments on inmates at Nazi concentration camps. This trial led to the creation of the Nuremberg Code, which is a set of ethics principles for human experimentation.

The Tuskegee syphilis study is also notorious for its lethal impact on more than 100 of the 400 African American participants, all of whom were not fully informed on the nature of the experiment, which studied the effects of untreated syphilis. This trial led to creation of the National Research Act and the Belmont Report, which outlines additional “ethical principles and guidelines for the protection of human subjects” for both biomedical and behavioral research.

To avoid further harm, most research institutions (like universities) have established institutional review boards (IRBs) that provide ethical oversight and approval authority on any planned research. Whether your organization has an IRB or not, informed consent is a fundamental part of an ethical research program that respects participants and does not take advantage of (or deceive) them.

While most user research with digital products will typically be nonclinical in nature (and, thus, relatively low-risk), there is still risk to the participants' wellbeing, especially if the tasks they conduct during the study cause temporary hardship, distress, discomfort, or pain. This is particularly true for vulnerable populations who are already experiencing these things due to injury, abuse, trauma, or general misfortune. To be clear, we can still do research on sensitive topics or with vulnerable or disadvantaged populations, but we must take extra precautions and communicate the study’s potential impact in advance to protect participants’ wellbeing.

It’s worth noting that there are populations who are vulnerable or incapable of granting informed consent, due to the criteria of the second bullet point: the participant’s understanding and voluntary participation. For example, children/minors , adults with cognitive impairments, low or no literacy, or mentally incapacitated individuals (e.g., unconscious or under the influence of alcohol or drugs) may not be capable of fully understanding the terms of the study or lack the full agency needed to make voluntary decisions (at times relying upon guardians to make these decisions). Thus, these parties cannot offer informed consent on their own, and researchers need the consent of their guardian before conducting any research, no matter how low-risk.

Similarly, inmates and prisoners are already performing an involuntary task, so the second criteria, voluntary participation, is not always possible. The decisions with these populations are rarely fully voluntary, and voluntary withdrawal may not be seen as a valid option due to fear of authorities or retribution. Furthermore, there may be additional legal requirements like consent of a prisoner representative and approval from an IRB before any research is conducted.

Writing out consent forms may seem like unnecessary work when you could just tell the participant what the study will be like. However, written consent forms are critical for a number of reasons:

• They consistently inform every participant with the same level of detail, whether they are the first or the 1,000th participant in the study and regardless of which researcher works with them. The written documentation serves as a paper trail to ensure that the researcher satisfactorily informed all participants and that all the key study details were covered every single time.
• They hold researchers accountable to protect the welfare and wellbeing of study participants and their data. A participant may forget what they initially consented to, but a signed form empowers the participant to be in control of their participation and protect their own welfare, wellbeing, and data, should the researcher deviate from the original plan.
• They prevent the research team (to some extent) from running a poor study. Granted, there can still be poor studies with consent forms, but consent-form writing helps researchers think through all the nuances of their study, including the activities the participant will do, the data that is truly needed, and how that data will be protected during and after the session.

That said, there are exceptions where a consent form is not necessary. A/B testing , for example, can be characterized as routine use of a product, and therefore, does not require additional involvement on the part of the participant. Plus, data from any single user is used only as part of a bigger statistic.

You may also not need a full-length consent form for an intercept study , which is the equivalent of interrupting someone while they are in the middle of a task to get their thoughts on that particular task. That said, you should still begin the intercept study with an agreement page containing a brief summary of how the information they provide will be used, stored, shared, and deleted. Also, if you are physically intercepting them in a public location, you should still get written permission from any physical establishment in which you are recruiting, to avoid getting in trouble for soliciting on a private property — which is illegal in many countries.

While you can repurpose this  consent-form template  for future research, remember that your consent forms should be carefully considered and crafted based on the unique needs and format of each study .

 In general, a consent form should have the following information:

• High-level purpose of the study Provide just enough detail to inform the participant about the nature of the study, without giving away any hypotheses or details that may skew behavior during the study. That said, this statement shouldn’t be as vague as “to learn about our customers.” Consider mentioning the objective of the research — for instance, to improve an existing product or strategize for future service development.
• Format of the study (activities, tasks, and duration) Describe the types of activities and tasks the participant may complete. This is where you can say how the data will be collected and to what extent the participant can expect to interact with the researcher(s). With that, the duration of the study should be clearly stated. “Umbrella” consent forms in which the user consents to an indefinite timeframe of research for current and future studies can be very problematic in their lack of specificity and susceptibility to abuse (and, generally, participants probably will not want to participate in something that has no defined end point).
• Voluntary-participation clause While research participants usually understand that they have volunteered to participate in the study, it may not always be clear that withdrawal is voluntary, or that it’s permissible for them to change their minds. Signing paperwork often can feel very “final,” so this clause helps to reassure that the participant is always in control of their participation.
• Will data be anonymized? If so, how much of it will be anonymized?
• How will it be used, accessed, and stored? Who has access to this information?
• Will it ever be published anywhere?
• When will the raw, recorded data be deleted (if ever)?
• Can the participant request that information is deleted?
• Consent statement While many consent forms will simply have a signature block for participants to indicate consent or a single checkbox labeled,  I consent to the terms of this study , this section should be carefully formatted and worded to instill confidence and give the participant agency and choices over their involvement.
• I agree to the terms of this study and consent to participate.
• I consent to audio being recorded during the session for analysis purposes.
• I consent to video being recorded during the session for analysis purposes.

This modular consent form increases the likelihood that the participant will participate and contribute data to the study, even if they do not consent to recordings.

Other optional information to include, if applicable:

• Compensation If you will be providing compensation for the participants’ time, be it monetary or as free products or services, clearly state it in the consent form. Regardless which method you choose, make it clear that compensation is not based on the participants’ abilities or on whether they provide positive feedback. Especially during any form of “testing,” participants can sometimes feel like they are being tested for their abilities and performance, rather than the design. Tip: For in-person testing, it helps to reinforce this idea by paying participants at the beginning of the session, before tasks begin, right after they sign the consent form.
• Parent or guardian involvement and approval If your participant is a minor or an adult with a guardian, a parent or guardian will likely accompany them into the session. Include a designated Parent or guardian signature block, to make it clear the signature belongs to a parent or guardian and that the participant was not coerced into signing. Any special considerations regarding studies with minors or other adults with guardians should be clearly communicated in the consent form.
• Information (or debrief) sheet Some study formats may warrant an additional information sheet (separate from the signed consent form) which contains a more detailed description of the study’s purpose. Such an information sheet is usually given to the participant at the end of the study, to avoid priming them to behave differently during the study.

Lastly, regardless if you use a separate information sheet or not, you should always give the participant a copy of the signed consent form, so they can refer to it after the study. This ensures the participant knows what they signed and who to contact for further questions about the research.

Human-centered design begins with human-centered research, and, as such, improvements to a design should never come at the cost of another person’s wellbeing. Getting informed consent from participants is critical for researchers to carry out fair, transparent, and accurate research while doing their part to minimize harm. By writing a thorough consent form, researchers can think through important details of their study and build trust and confidence with participants.

Shuster, E. Fifty Years Later: The Significance of the Nuremberg Code.  New England Journal of Medicine 337 , 20 (1997), 1436-1440.

The Belmont Report.  Office for Human Research Protections , 1979. https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html.

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NDAs and confidentiality agreements: What you need to know Protection of confidential information within an organization is usually a vital business priority. Learn what you need to know when structuring confidentiality agreements.

Nearly all businesses have valuable confidential information, and for many, confidential information is a dominant asset. Companies also share, receive, and exchange confidential information with and from customers, suppliers and other parties in the ordinary course of business and in a wide variety of commercial transactions and relationships.

Contractual confidentiality obligations are fundamental and necessary to help protect the parties that disclose information in these situations. Depending on the circumstances, these obligations can be documented in either:

• A free-standing confidentiality agreement (also known as a nondisclosure agreement or NDA)
• Clauses within an agreement that covers a larger transaction

When is a confidentiality agreement needed?

A range of commercial transactions and relationships involve either the disclosure of confidential information by one party to the other or a reciprocal exchange of information. In both cases, the parties should have a confidentiality agreement in place.

For example, confidentiality agreements may be used when evaluating or engaging a business or marketing consultant or agency, where the hiring company will necessarily disclose confidential information to enable the consultant to perform the assignment. They can also be used when soliciting proposals from vendors, software developers, or other service providers, which usually involves the exchange of pricing, strategies, personnel records, business methods, technical specifications, and other confidential information of both parties.

Finally, your company may need a confidentiality agreement when entering a co-marketing relationship, as an e-commerce business, with the operator of a complementary website or a similar type of strategic alliance.

Why is it necessary to have written confidentiality agreements?

• There are numerous reasons to enter into written confidentiality agreements, such as:
• Avoiding confusion over what the parties consider to be confidential.
• Allowing more flexibility in defining what is confidential.
• Delineating expectations regarding treatment of confidential information between the parties, whether disclosing or receiving confidential information.
• Enforcing written contracts is easier than oral agreements.
• Memorializing confidentiality agreements is often required under upstream agreements with third parties (for example, a service provider's customer agreement may require written confidentiality agreements with subcontractors).
• Maximizing protection of trade secrets, because under state law this protection can be weakened or lost (deemed waived) if disclosed without a written agreement. 
• Covering issues that are indirectly related to confidentiality, such as non-solicitation.
• Maintaining standards that are expected of most commercial transactions and relationships.

The forms of confidentiality agreements

Depending on the type of transaction or relationship, only one party may share its confidential information with the other, or the parties may engage in a mutual or reciprocal exchange of information.

In unilateral confidentiality agreements, the nondisclosure obligations and access and use restrictions will apply only to the party that is the recipient of confidential information, but the operative provisions can be drafted to favor either party.

In mutual confidentiality agreements, each party is treated as both a discloser of its—and a recipient of the other party's—confidential information (such as when two companies form a strategic marketing alliance). In these situations, both parties are subject to identical nondisclosure obligations and access and use restrictions for information disclosed by the other party.

In some circumstances, the parties may share certain confidential information with each other but not on a mutual basis. Instead of entering into a fully mutual confidentiality agreement, the parties enter into a reciprocal confidentiality agreement, in which the scope and nature of the confidential information that each party will disclose is separately defined and their respective nondisclosure obligations and access and use restrictions may differ accordingly.

Limitations and risks of confidentiality agreements

Confidentiality agreements are very useful to prevent unauthorized disclosures of information, but they have inherent limitations and risks, particularly when recipients have little intention of complying with them. These limitations include the following:

• Once information is wrongfully disclosed and becomes part of the public domain, it cannot later be "undisclosed."
• Proving a breach of a confidentiality agreement can be very difficult.
• Damages for breach of contract (or an accounting of profits, where the recipient has made commercial use of the information) may be the only legal remedy available once the information is disclosed. However, damages may not be adequate or may be difficult to ascertain, especially when the confidential information has potential future value as opposed to present value.
• Even where a recipient complies with all the confidentiality agreement's requirements, it may indirectly use the disclosed confidential information to its commercial advantage.

Nondisclosure obligations

In general, recipients of confidential information are subject to an affirmative duty to keep the information confidential, and not to disclose it to third parties except as expressly permitted by the agreement. The recipient's duty is often tied to a specified standard of care. For example, the agreement may require the recipient to maintain the confidentiality of the information using the same degree of care used to protect its own confidential information, but not less than a reasonable degree of care.

Recipients should ensure there are appropriate exceptions to the general nondisclosure obligations, including for disclosures:

• To its representatives. Most confidentiality agreements permit disclosure to specified representatives for the purpose of evaluating the information and participating in negotiations of the principal agreement.
• Required by law. Confidentiality agreements usually allow the recipient to disclose confidential information if required to do so by court order or other legal process. The recipient usually must notify the disclosing party of any such order (if legally permitted to do so) and cooperate with the disclosing party to obtain a protective order.

Disclosing parties commonly try to ensure that recipients are required to have downstream confidentiality agreements in place with any third parties to which subsequent disclosure of confidential information is permitted. In these cases, either the recipient or the discloser may prefer to have these third parties enter into separate confidentiality agreements directly with the discloser.

Term of agreement and survival of nondisclosure obligations

Confidentiality agreements can run indefinitely, covering the parties' disclosures of confidential information at any time, or can terminate on a certain date or event.

Whether or not the overall agreement has a definite term, the parties' nondisclosure obligations can be stated to survive for a set period. Survival periods of one to five years are typical. The term often depends on the type of information involved and how quickly the information changes.

The information in this article was excerpted from Confidentiality and Nondisclosure Agreements. The full practice note, one of more than 65,000 resources, is available at the Thomson Reuters Practical Law website.

The information in this article was excerpted from  Confidentiality and Nondisclosure Agreements . The full practice note, one of more than 65,000 resources, is available at the Thomson Reuters Practical Law website.

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Usability testing non disclosure agreement pdf

We’ve put together a usability testing non disclosure agreement pdf. Download the pdf below and send it to your UX testing participants. Don’t stop at usability testing – send it to participants taking user research studies. Protect yourself again confidential information being released to the public during user tests.

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• Negotiate Agreements

Non-disclosure Agreement (NDA)

Non-Disclosure Agreements (NDA), also known as Confidentiality Agreements, Proprietary Information Agreements, Secrecy Agreements, etc., are commonly requested when two or more parties wish to enter into initial discussions about specific processes, methods or technology for the purpose of determining the potential for a future relationship.  An NDA is a legal agreement which defines information that the parties wish to protect from dissemination and outlines restrictions on use.  NDAs are also valuable to protect the ability to patent an invention, something that can be compromised if a disclosure of the invention becomes public knowledge.  If you are sharing new processes, unpublished data or other confidential information, you should protect your rights by having an NDA in place.

If it is determined that an NDA is necessary, the investigator should initiate the process by completing the on-line Request for NDA. Submitted requests will be reviewed by the Office of Sponsored Programs.

Penn State prefers to use its own standard NDA which can be found below. These terms and conditions have been vetted by Penn State’s legal counsel and have been proven very effective at protecting the needs and interests of both parties.  If a company is willing to accept Penn State’s standard NDA with minimal or no changes, the process is expedited and signatures can usually be obtained within a few days.  However, if a company requires the use of its own terms and conditions, this will require a thorough review and negotiation period to ensure that Penn State’s legal obligations and interests are not unduly compromised.  This review and negotiation period may cause a delay in processing, typically around 10-15 business days or longer.  Please be sure to allow ample time for the review, negotiation and signature of your NDA. 

Penn State views the NDA as a tool to allow initial interactions to take place, such as discussions about Penn State’s capabilities and research interests or collaborating on proposal submissions.   There should be no funded work performed under the scope of an NDA ; this is better handled under a research or services agreement in which there is a clear scope of work defined.  Examples of such funding agreements can be located  here . 

The on-line Request for NDA, as well as additional guidance, can be found below:

• On-line Request for NDA
• Standard NDA Agreement
• Faculty Guide to NDA
• Informational Video on NDAs

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Sample confidentiality/non-disclosure agreement.

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Non-disclosure agreements

Also called secrecy, confidentiality, or proprietary agreements, non-disclosure agreements (NDAs) are an important part of the technology transfer process. NDAs set forth the rights and obligations of two or more parties who wish to exchange sensitive information. NDAs allow researchers and the university to demonstrate the intent to restrict the disclosure of sensitive or proprietary information. Additionally, they are most often used when a researcher is interested in discussing a potential collaborative research opportunity with a for-profit entity, or when researchers wish to disclose unpublished research ideas and data with colleagues at other institutions.

NDAs are usually negotiated and signed by certain individuals within companies, universities, and other entities. This authorized representative is often NOT the individual that the researcher is working with. At NAU, the authorized representative for executing research-related NDAs is the director of NAU Innovations.

NAU uses a standard NDA which can be provided to the other party either by NAU Innovations or by the researcher.

If you would like NAU Innovations to work directly with the other institution, contact the NAU Technology Transfer Coordinator .

• Download the NDA and attach it to an e-mail to send to the colleague or company representative.
• Copy NAU Innovations .
• In the body of the e-mail, include the following text: “Our technology transfer office negotiates and executes NDAs. After you have reviewed the NDA, please return it via e-mail to Cristy Salanga at  [email protected]  .”

NAU Innovations will also negotiate and sign NDAs from other parties. Review of these NDAs can be initiated by contacting  Cristy Salanga .

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An overview of what the NIMH Data Archive (NDA) is and how REDCap can be customized for data sharing to the NDA

Mon, 05/01/2023.

Lisa Hallberg

The research project you’re working on has a data sharing and archiving requirement with the NIMH Data Archive: what does that mean?

This post will answer that question and go over the process of meeting that requirement. Specifically, it will address the best practices for handling your human subjects data in a REDCap project for the purpose of reporting research data to the NIMH Data Archive (NDA). Although the details will focus on the specifics of how the NDA works, what is covered here will also be generalizable to other archiving services.

Please note: this post does not cover reporting genomics or imaging data to the NIMH Data Archive.

Data Dictionaries

An example: the research subject and demographics form, understanding guids, calculating “age in months” (aim), creating reports for output to nda.

Research funded by the National Institute of Mental Health (NIMH) and other NIH institutes increasingly has specific requirements for archiving and sharing the research data collected by funded studies. In the case of NIMH, they have an archiving service specifically dedicated for this purpose: the NIMH Data Archive ( https://nda.nih.gov/ ). It provides both a means to archive the collected data, and a way of disseminating those data to approved researchers and linking the data to published studies.

Studies that use the NDA are required to upload their data semi-annually during the study’s data collection phase. During this phase, the data are not immediately available for dissemination: this ensures both that the data can be reviewed and validated, and that the researchers collecting the data can use and publish the results of the data collection first. After the data go through the validation process and the research team are given a window of opportunity to publish their findings, then the data are made available through the NDA to approved users.

The NDA web site has a lot of information and tutorials to help people understand the process and the web site’s terminology. To summarize, using the NDA follows these basic steps. You can find more detail at https://nda.nih.gov/nda/data-contribution.html .

• The study is added to the NDA and associated with the study’s Primary Investigator (PI) through the NDA Data Submission Agreement (DSA). The PI, as well as other research team members, need to create user accounts on the NDA web site for the purpose of completing the data upload requirement.
• The PI or research team indicate what data they will archive with NDA. These are called the “expected data”. The expected data must take the form of instruments and measures defined in the NDA Data Collection data structures. If a data structure doesn’t already exist in the NDA Data Collection, then there is a process to add new data structures to the Data Collection.
• Study subjects whose data will be reported to the archive are assigned NDA GUIDS (global unique identifiers). All data uploaded to NDA have these GUIDS to identify which study subject the research team collected data about.
• After the start of the data collection phase of the study, the research team needs to report their data every 6 months, in January and July. Data reporting is cumulative, so each time data are reported, all previous data are included in the upload as well. Although this may seem redundant, it is a much easier task to simply report all data collected every time, rather than trying to keep track of what has or has not yet been reported.
• At the end of the data collection phase and after the last 6 month reporting deadline, the PI and research team indicate that they have completed reporting all data and the project goes to “analysis phase”.

Both REDCap and NDA use “data dictionaries”. Understanding what they are and how they should be used can help both with data collection and the NDA data reporting requirements. If you are familiar with either type, hopefully you will quickly see the similarities between the two.

If you are not familiar with the concept of “Data dictionaries”, for both REDCap and NDA, these are documents that list all the fields in a project (in the case of REDCap) or a data structure (in the case of NDA). Both systems use CSV (comma-separated value) text documents that can be read by spreadsheet software such as Excel or Google Sheets. The first line of each file contains the column headers, and all the other lines describe the individual “variables” (for REDCap) or “elements” (for NDA), starting with the variable or element name.

For a research project collecting a variety of measures about the study's subjects, all the data from these clinical measures or surveys, as well as demographics and family contact information, are typically stored in a single REDCap project. You can find all the details in the one REDCap "data dictionary" for the whole project. NDA "data dictionaries", by contrast, represent only a single measure or "data structure". For example, a REDCap project's data dictionary might include an initial enrollment form with contact information, a screening survey with demographics data, and then actual measure data including diagnostic measures and other data points. In the NDA, those data are broken out into separate data structures, each with their own data dictionary files, starting with the basic demographics data (the Research Subject), and then other structures. Examples include measures such as the ADOS2, Mullen Scales, or other standard or novel measures of ability or behavior.

The details of NDA data dictionaries and REDCap data dictionaries are not the same, and there are plenty of differences between the two once you get past the variable/element names. However, NDA data dictionaries are intended to be used by the research team to correctly structure research data for upload to the NDA. They can also be used to help structure a REDCap project to simplify the process of accurately storing and reporting data to NDA, with the least amount of recoding and restructuring.

The one data structure that is almost universal to NDA data sharing reporting, at least in the case of behavioral subjects research, is the Research Subject form ( https://nda.nih.gov/data_structure.html?short_name=ndar_subject01 ). This contains the basic demographic information about the research subject, as shown in the following partial listing of the NDAR Research Subject data dictionary.

The columns to note in this table are:

• ElementName , which will correspond to the “variable” name in REDCap These are the variable names, labels or column names in your data. You will need to be able to map your data names and labels with the NDA "ElementNames" when you build your files for upload.
• Required : these columns must have data in the NDA upload files Many data elements that are listed as "Required" in the NDA data dictionary will often have a "missing" or "unknown" option. Some values such as data collection dates, on the other hand, are required and it is important that your data include those values for all measures.
• DataType : this corresponds somewhat to the REDCap “field type” and is important for data validation Knowing the required data types in the NDA data dictionaries will be important to know for your data submission. In the example above, "sex" is encoded as a "String", but often in REDCap sex or gender take a "radio" Field Type and are stored as numbers and labeled with string values.If that is the case, you will have to recode your values to match the NDA's expected values.
• ValueRange : These are the valid values that can be reported in the NDA data upload. Just as with the DataType, you will need to match your data and possibly recode your values to match what NDA expects.

One important data element to note in this data dictionary example is the "interview_age". This value is an integer, and is the subject's "age in months" at the time of the data collection. Refer to the discussion, below ("Calculating Age In Months"), for more about what this is and how to calculate it.

For comparison, this is the data dictionary of a REDCap project that will be reporting data to NDA:

In this data dictionary, you can see where variables such as “demog_child_sex”, “demog_child_race” and “demog_child_eth” will correspond with “sex”, “race” and “ethnic_group” in the NDA Subject data dictionary. Setting up the Choices options (i.e., Choices, Calculations, or Slider Labels column) to match the valid values required by NDA can save a step in the upload process, so that these values don’t have to be “converted” or “recoded” for reporting to NDA.

GUIDs, or global unique IDs (pronounced “GOO-id”), are a required data field or variable of submitted NDA data; and it is important to understand what they are and how to add them to your data. There is plenty of documentation about NDA GUIDs on the NDA web site ( https://nda.nih.gov/nda/using-the-nda-guid.html ). What follows is a brief summary of what they are and the steps needed to generate them for your data collection.

Just as in your own research data, in the NDA database, each subject needs to have a unique identifier, in this case the GUID. Additionally, the GUID serves a special purpose: to create a unique identifier that can be used to identify subjects who are included in multiple studies. The NDA has developed their GUID system to facilitate this, while keeping the data uploads free of personally identifiable data. They accomplish this by using identifiable data stored on your local system, not transmitted to NDA. The process is similar to the way a password is encrypted: the subjects’ identifiable data are “encrypted” on the research teams’ own machines and then are used to create a unique value. The important point is that the encrypted value cannot be “decrypted”: the process only goes one way. If another research team provides the same data about a subject, the same encryption will occur and the existing GUID will be found and assigned to that individual.

Because of this need to find existing GUIDs already in the data, the NDA process for creating GUIDs requires a specific list of your subjects’ data, which you should try to collect:

• Middle Name
• Date of Birth
• City/Municipality of Birth

To avoid ambiguity, these values should be reported as they appear on the subjects’ birth certificates, so they do not change over time. If you cannot collect these values, you can instead use the NDA’s “pseudoGUIDs” .

It’s important that you are aware of the need to collect these specific details from your study’s subjects before you even start recruiting. You need to have these fields in your data collection instruments, such as the Demographics or Intake form of your study. And you need to include these data in REDCap, so you can access them when you are ready to report the data to NDA. Once you use these values to generate each subjects’ GUID, you will also need to store the GUID in REDCap as well.

Here is a partial example of a REDCap data dictionary set of variables, illustrating how this might look.

Each of the NDA data structures require two values related to when the data were collected. One is the date on which the data were collected. The second value needs to be related to the subject’s age on that date. Instead of requesting the subject’s date of birth, the NDA expects an integer value representing the age of the subject at the time of data collection , represented in the number of months, rounded to the nearest month, since their birth. The specific wording describing the value in the NDA Data Dictionary is, "Age is rounded to chronological month. If the research participant is 15-days-old at time of interview, the appropriate value would be 0 months. If the participant is 16-days-old, the value would be 1 month. ". This is what is meant by “age in months” or AIM. These values need to be calculated for every measure you collect on your subjects.

This value can be calculated directly in REDCap using the “calc” data type, two “special functions” and two date variables. The special functions are “round”, to round the calculated number of months to the nearest integer, and “datediff”, to calculate the date difference in months. The two variables are the date of data collection and the subject’s date of birth. If the two variables are “nda_date_of_birth” (for the date of birth) and “measure_date”, then the calculation will be:

The “datediff” function takes 3 values: the two dates, and then a code representing the time unit in which to calculate the difference. In this case, the “M” means months. Note that capitalization is important: “M” is not the same as “m”! The “datediff” function is inside the “round” function, to modify the output of “datediff” to the nearest integer.

This is what it looks like in the REDCap field dialog box:

Remember: if you add this calculation or modify this calculated field after you already have data in your project, you can update all your calculated fields by going to the project’s Data Quality tool and running Rule H: “Incorrect values for calculated fields”.

You don’t have to use this type of field to calculate AIM. You can do this calculation externally to REDCap, using Excel or statistical software such as SPSS or even with a scripted language such as Python. This is just one option.

To upload your data to NDA, you will need to create reports or extracts from REDCap . There is no way to create a report using the REDCap default functionality that exactly matches the template structure expected by the NDA. Additionally, because the NDA expects separate files for each data structure or measure, you will likely want to create separate reports for each. Depending on how your data are structured and encoded in REDCap, you may also need to do some manipulation of the output files to prepare them for upload. The following is intended to explain those differences and what you need to do to prepare your data files.

NDA uploads consist of separate files, one for each “data structure”. In addition to the data dictionary, each data structure also has a template file. Template files are comma-separated text files, with two header rows. The first row or line of the files is the “data structure” name and version. The second row is a comma-separated list of all the expected data columns. These column headers correspond to the definitions in the data dictionary, and the uploaded data are expected to match those definitions.

To report data out of REDCap for upload to NDA, these are the basic steps:

• Create REDCap reports based on the NDA data dictionary for each instrument or data structure you need to upload to NDA
• Extract the data as CSV files
• Modify the data as needed to match the NDA data dictionary for each file. For example, you may need to recode some values in your data to match the expected values in the NDA data dictionary, or you may need to fill fields marked in the NDA data dictionary as “required” with a suitable “missing value” if the value is not in your data.
• Apply the header rows of the NDA data structure template to your data file
• Stage your files in a folder on your computer for upload
• Go to the NDA Data Validation and Upload Tool ( https://nda.nih.gov/vt/ ) to upload your data

In practice, executing this list of tasks the first time you have to report your data will likely be somewhat daunting. However, once the process is set up, subsequent uploads should be easier, as several of the steps only need to be completed once.

Lisa Hallberg  is a research engineer with the Life Span Institute's  Research Design and Analysis  team.