| Course | NUR-7110 Nursing Informatics Consumer Informatics and Communications Technologies |
|---|---|
| Module | Module 5 |
| Paper type | Consumer informatics paper: health app privacy and data sharing |
| Length | About 1,018 words, 6 pages |
| Format | APA 7 student paper |
| School | Thomas Edison State University |
| Program | M.S. in Nursing, Nursing Informatics |
| Updated | October 2026 |
Free sample paper for NUR 7110 Module 5
Free Apps, Shared Data: Building a Privacy Review Before a Princeton Clinic Recommends Mental Health Apps
Student Name
M.S. in Nursing, Nursing Informatics, Thomas Edison State University
NUR-7110: Nursing Informatics: Consumer Informatics and Communications Technologies
Mentor Name
Month Day, Year
Free Apps, Shared Data: Building a Privacy Review Before a Princeton Clinic Recommends Mental Health Apps
The Request
The clinic and the apps described here are invented composites. An outpatient behavioral health clinic in Princeton serves adults with depression, anxiety and substance use. Therapists and psychiatric nurse practitioners often suggest apps for mood tracking, breathing exercises and sleep, and patients ask which ones to use. The clinical director asked the informatics nurse to prepare an official list. The informatics nurse agreed on one condition: before any app went on the list, it would be reviewed for what it does with patients' data, because a mood diary is among the most sensitive records a person can keep.
What Apps Do With Data
Grundy et al. (2019) studied 24 popular medicines-related apps on Android, simulating real use and capturing the network traffic each app produced. Most of the apps shared user data with outside entities, and the data traveled to dozens of third parties, many of them owned by a small number of large technology and advertising companies, which could combine data across apps. Shared data included device identifiers and, in some cases, information that users had entered. The authors noted that privacy policies were often vague about these transfers and that users had little way to know where their information went.
Huckvale et al. (2015) assessed health and wellness apps accredited by a national health service library, which had been reviewed and endorsed for clinical use. Most transmitted information to online services. Many that sent identifying information did so without encryption, none encrypted personal data stored on the device, and several lacked a privacy policy or did not follow the one they had. The study showed that endorsement by a trusted body did not guarantee privacy.
Why the Law Does Not Cover It
Cohen and Mello (2018) explained that the HIPAA Privacy Rule protects health information held by covered entities, meaning health plans, clearinghouses and providers who bill electronically, and their business associates. Health data created by consumers in apps, wearables and websites usually fall outside the rule unless the app works on behalf of a covered entity. Patients often assume that any health information is protected by HIPAA, but an app downloaded from a store and used independently is governed mainly by its own terms of service and by general consumer protection law. The authors argued that the gap between people's expectations and the law's coverage is growing.
| Source | Finding | Implication for the clinic |
|---|---|---|
| Grundy et al. (2019) | Most top medicines apps shared data with third parties | Check network behavior, not only the policy |
| Huckvale et al. (2015) | Accredited apps sent data unencrypted; some lacked policies | Endorsement is not enough |
| Cohen and Mello (2018) | HIPAA usually does not cover consumer apps | Patients need to be told what protection they do not have |
The Review Process
The informatics nurse, a therapist and the clinic's privacy officer built a review with three parts.
Clinical value. Is the app's content consistent with evidence-based approaches, such as cognitive behavioral techniques, and appropriate for the clinic's patients? Does it handle crisis content safely, for example by showing a crisis line when a user reports thoughts of self-harm?
Privacy and security. Does the app have a clear privacy policy that says what data are collected, with whom they are shared and how to delete them? Does it allow use without creating an account or linking social media? Does it share data with advertisers or analytics companies? The informatics nurse checked each candidate by reading the policy, reviewing the permissions it requested and, for the final candidates, using a free network monitoring tool on a test phone to see which outside servers the app contacted.
Usability and access. Is it free or low-cost, available on both major platforms and in Spanish, and usable by someone with limited literacy?
Results
Of 19 candidate apps, 6 passed all three parts. Eleven failed privacy: eight shared data with advertising or analytics companies, two required a social media login and one had no privacy policy at all. Two were not consistent with evidence-based approaches. Two of the most popular mood trackers that therapists had been suggesting were among those that failed privacy.
Guidance for Patients
The clinic's list includes the six approved apps and a single-sheet guide, printed in both English and Spanish, explaining that apps are not covered by the same privacy rules as the clinic's records, how to check an app's privacy settings, how to use an app without an account when possible and how to delete data. Therapists discuss privacy when they suggest an app, and patients remain free to choose apps not on the list.
Talking With Patients About Privacy
Therapists asked for help discussing privacy without frightening patients away from useful tools. The informatics nurse wrote three short talking points: that the clinic's own records are protected by federal privacy law but most apps are not; that a few settings, such as using an app without an account and turning off sharing, reduce risk; and that patients can always keep a paper mood diary instead. Therapists practiced the talk in a staff meeting. Several patients who heard it chose a listed app over one they had been using, and two decided to keep paper diaries, choices the clinic treats as equally valid.
Keeping the List Current
Apps change their policies and code with updates. The review is repeated for each listed app every six months and whenever a news report or patient raises a concern.
Limits
Network monitoring on a test phone captures only the behavior seen during testing. Privacy policies change without notice. A short list may discourage patients from apps that would help them.
Conclusion
A list of recommended apps would have sent patients' mood diaries to advertisers if it had been built on popularity alone. Studies of data sharing and of accredited apps showed the risk, and an analysis of HIPAA explained why the law does not close the gap. A review of value, privacy and access, repeated over time and paired with patient guidance, lets the clinic recommend apps responsibly.
References
Cohen, I. G., & Mello, M. M. (2018). HIPAA and protecting health information in the 21st century. JAMA, 320(3), 231-232. https://doi.org/10.1001/jama.2018.5630
Grundy, Q., Chiu, K., Held, F., Continella, A., Bero, L., & Holz, R. (2019). Data sharing practices of medicines related apps and the mobile ecosystem: Traffic, content, and network analysis. BMJ, 364, l920. https://doi.org/10.1136/bmj.l920
Huckvale, K., Prieto, J. T., Tilney, M., Benghozi, P.-J., & Car, J. (2015). Unaddressed privacy risks in accredited health and wellness apps: A cross-sectional systematic assessment. BMC Medicine, 13, Article 214. https://doi.org/10.1186/s12916-015-0444-y
What the NUR 7110 Module 5 instructions ask for
Consumer support through health technologies, and the trends that shape it, appear in TESU's catalog description of NUR-7110, and the course syllabus is not published, so module five is planned as an app privacy and review paper. Write a paper that states the clinical purpose of recommending apps, reviews evidence on what consumer health apps do with data, explains the limits of legal protection, builds review criteria that cover clinical value, privacy and access, applies them to candidate apps with results and gives patients guidance. Some sections focus on wearables or direct-to-consumer genetic testing instead. Check whether you may name real apps in the paper; many briefs prefer composites or categories to avoid appearing to endorse or accuse a product. Plan how clinicians will talk with patients about the risks you find.
Inside the NUR 7110 Module 5 example
An invented Princeton clinic's request for a list of recommended mental health apps opens the paper. A study of medicines-related apps shows most shared data with third parties, an assessment of accredited apps shows endorsement did not ensure privacy and an analysis of HIPAA explains why consumer apps fall outside it. A three-row table turns the evidence into review principles. The three-part review is described, and results show 6 of 19 apps passing, with two popular mood trackers failing privacy. Patient guidance and a schedule for repeat review come next, then limits and the close. Annotations point to evidence-based criteria and reported outcomes. A section on talking points shows therapists discussing privacy without discouraging patients from useful tools.
NUR 7110 Module 5 rubric: what earns full marks
App privacy papers are rewarded for stating why apps are being recommended, for accurate evidence on data sharing and on endorsed apps, a correct explanation of HIPAA's coverage, review criteria that include privacy alongside clinical value and access, criteria applied with reported results and guidance that helps patients protect themselves. Mentors notice when a review checks what an app does, not only what its policy says. Telling patients what protections they lack shows respect for their autonomy. Planning repeat review shows understanding that apps change. Cite each study with its article number or page as APA requires. Giving clinicians words to use with patients turns a review into practice.
NUR 7110 Module 5 help from the desk
App recommendation papers often rank apps by stars and downloads; check what each app does with data first. Another common gap is assuming HIPAA protects anything health-related. Read the privacy policy, check permissions and, if you can, watch where the app sends data. Report how many apps failed and why. Give patients a plain guide. Repeat the review when apps update. Give clinicians simple words for discussing privacy with patients. The desk drafts a privacy review for your own clinic's question at no cost, following the Princeton model.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Thomas Edison State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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NUR 7110 Module 5 questions, answered
Where can I find a free NUR 7110 Module 5 sample paper?
The app privacy paper for an invented Princeton behavioral health clinic, from the review criteria to the six approved apps, appears in full on this page.
Do health apps share user data?
Grundy and colleagues found that most of 24 popular medicines-related Android apps shared user data with third parties.
Are accredited health apps private?
Huckvale and colleagues found many accredited apps sent personal information without encryption, and some lacked privacy policies.
Does HIPAA protect data in health apps?
Usually not; HIPAA covers health plans, providers and their business associates, not most consumer apps used independently.
How should a clinic review apps before recommending them?
Check clinical value, privacy and security, including data sharing, and usability and access, then repeat the review over time.