# Every source behind the notes

> 40 studies and 14 primary documents, grouped by topic. Each one has its own page: what it found, where the evidence stops, and a link to the original.

- Page: https://tre-up.com/research/sources
- What each source found and where its evidence stops: on its own page, in the topic files (e.g. https://tre-up.com/research/topics/timing-and-receptivity.md) and in https://tre-up.com/research/index.json
- Last reviewed 2026-10-07
- 40 studies, 14 laws, guidelines and standards, 50 institutions, 10 countries, 21 studies free to read online

## 01 Timing and receptivity (8 sources)

When help lands, and when the same help is just noise. Topic: https://tre-up.com/research/topics/timing-and-receptivity

- **Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support**. Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, Murphy SA (2018). Annals of Behavioral Medicine 52(6):446–462. https://doi.org/10.1007/s12160-016-9830-8 · Our summary: https://tre-up.com/research/sources/nahum-shani-2018-jitai
  - University of Michigan (United States); Northwestern University (United States); Pennsylvania State University (United States); University of New Mexico (United States) · Design framework
- **Just-in-Time Adaptive Interventions: Where Are We Now and What Is Next?** Nahum-Shani I, Murphy SA (2026). Annual Review of Psychology 77:679–703. https://doi.org/10.1146/annurev-psych-121024-044244 · Our summary: https://tre-up.com/research/sources/nahum-shani-murphy-2026-jitai-review
  - University of Michigan (United States); Harvard University (United States) · Review
- **My Phone and Me: Understanding People's Receptivity to Mobile Notifications**. Mehrotra A, Pejovic V, Vermeulen J, Hendley R, Musolesi M (2016). Proceedings of CHI 2016, 1021–1032. https://doi.org/10.1145/2858036.2858566 · Our summary: https://tre-up.com/research/sources/mehrotra-2016-receptivity
  - University of Birmingham (United Kingdom); University College London (United Kingdom); University of Ljubljana (Slovenia); University of Calgary (Canada) · Field study with phone logging and experience sampling
- **Real-world large-scale study on adaptive notification scheduling on smartphones**. Okoshi T, Tsubouchi K, Tokuda H (2018). Pervasive and Mobile Computing 50:1–24. https://doi.org/10.1016/j.pmcj.2018.07.005 · Our summary: https://tre-up.com/research/sources/okoshi-2018-adaptive-scheduling
  - Keio University (Japan); Yahoo Japan Corporation (Japan) · Large-scale deployment in a commercial app
- **Efficacy of Contextually Tailored Suggestions for Physical Activity: A Micro-randomized Optimization Trial of HeartSteps**. Klasnja P, Smith S, Seewald NJ, Lee A, Hall K, Luers B, Hekler EB, Murphy SA (2019). Annals of Behavioral Medicine 53(6):573–582. https://doi.org/10.1093/abm/kay067 · Our summary: https://tre-up.com/research/sources/klasnja-2019-heartsteps
  - University of Michigan (United States); University of California, San Diego (United States); Harvard University (United States) · Micro-randomized trial
- **To Prompt or Not to Prompt? A Microrandomized Trial of Time-Varying Push Notifications to Increase Proximal Engagement With a Mobile Health App**. Bidargaddi N, Almirall D, Murphy S, Nahum-Shani I, Kovalcik M, Pituch T, Maaieh H, Strecher V (2018). JMIR mHealth and uHealth 6(11):e10123. https://doi.org/10.2196/10123 · Our summary: https://tre-up.com/research/sources/bidargaddi-2018-to-prompt-or-not
  - Flinders University (Australia); University of Michigan (United States); Harvard University (United States) · Micro-randomized trial
- **Micro-Randomized Trials: An Experimental Design for Developing Just-in-Time Adaptive Interventions**. Klasnja P, Hekler EB, Shiffman S, Boruvka A, Almirall D, Tewari A, Murphy SA (2015). Health Psychology 34(Suppl):1220–1228. https://doi.org/10.1037/hea0000305 · Our summary: https://tre-up.com/research/sources/klasnja-2015-micro-randomized-trials
  - University of Michigan (United States); Arizona State University (United States); University of Pittsburgh (United States) · Methods paper
- **Attention-Sensitive Alerting**. Horvitz E, Jacobs A, Hovel D (1999). Proceedings of UAI 1999, 305–313. https://www.microsoft.com/en-us/research/publication/attention-sensitive-alerting/ · Our summary: https://tre-up.com/research/sources/horvitz-1999-attention-sensitive-alerting
  - Microsoft Research (United States) · Decision-theory model and system

## 02 Interruptions and attention (10 sources)

What a ping, a switch or an unfinished task costs the mind. Topic: https://tre-up.com/research/topics/interruptions-and-attention

- **The attentional cost of receiving a cell phone notification**. Stothart C, Mitchum A, Yehnert C (2015). Journal of Experimental Psychology: Human Perception and Performance 41(4):893–897. https://doi.org/10.1037/xhp0000100 · Our summary: https://tre-up.com/research/sources/stothart-2015-notification-cost
  - Florida State University (United States) · Lab experiment
- **"Silence Your Phones": Smartphone Notifications Increase Inattention and Hyperactivity Symptoms**. Kushlev K, Proulx JDE, Dunn EW (2016). Proceedings of CHI 2016, 1011–1020. https://doi.org/10.1145/2858036.2858359 · Our summary: https://tre-up.com/research/sources/kushlev-2016-silence-your-phones
  - University of Virginia (United States); University of British Columbia (Canada) · Field experiment, two one-week conditions
- **An in-situ study of mobile phone notifications**. Pielot M, Church K, de Oliveira R (2014). Proceedings of MobileHCI 2014. https://doi.org/10.1145/2628363.2628364 · Our summary: https://tre-up.com/research/sources/pielot-2014-in-situ-notifications
  - Telefónica Research (Spain) · Field study with phone logging and diaries
- **Productive, Anxious, Lonely: 24 Hours Without Push Notifications**. Pielot M, Rello L (2017). Proceedings of MobileHCI 2017. https://doi.org/10.1145/3098279.3098526 · Our summary: https://tre-up.com/research/sources/pielot-rello-2017-24-hours
  - Telefónica Research (Spain) · Field experiment: a day without notifications against a normal day
- **Batching smartphone notifications can improve well-being**. Fitz N, Kushlev K, Jagannathan R, Lewis T, Paliwal D, Ariely D (2019). Computers in Human Behavior 101:84–94. https://doi.org/10.1016/j.chb.2019.07.016 · Our summary: https://tre-up.com/research/sources/fitz-2019-batching-notifications
  - Duke University (United States); Georgetown University (United States) · Randomized field experiment
- **Checking email less frequently reduces stress**. Kushlev K, Dunn EW (2015). Computers in Human Behavior 43:220–228. https://doi.org/10.1016/j.chb.2014.11.005 · Our summary: https://tre-up.com/research/sources/kushlev-dunn-2015-email
  - University of British Columbia (Canada) · Within-person field experiment
- **Effects of intelligent notification management on users and their tasks**. Iqbal ST, Bailey BP (2008). Proceedings of CHI 2008. https://doi.org/10.1145/1357054.1357070 · Our summary: https://tre-up.com/research/sources/iqbal-bailey-2008-breakpoints
  - University of Illinois Urbana-Champaign (United States) · System with two user studies
- **The cost of interrupted work: more speed and stress**. Mark G, Gudith D, Klocke U (2008). Proceedings of CHI 2008, 107–110. https://doi.org/10.1145/1357054.1357072 · Our summary: https://tre-up.com/research/sources/mark-2008-cost-of-interrupted-work
  - University of California, Irvine (United States); Humboldt-Universität zu Berlin (Germany) · Lab experiment
- **If Not Now, When? The Effects of Interruption at Different Moments Within Task Execution**. Adamczyk PD, Bailey BP (2004). Proceedings of CHI 2004, 271–278. https://doi.org/10.1145/985692.985727 · Our summary: https://tre-up.com/research/sources/adamczyk-bailey-2004-if-not-now
  - University of Illinois Urbana-Champaign (United States) · Lab experiment
- **Why is it so hard to do my work? The challenge of attention residue when switching between work tasks**. Leroy S (2009). Organizational Behavior and Human Decision Processes 109(2):168–181. https://doi.org/10.1016/j.obhdp.2009.04.002 · Our summary: https://tre-up.com/research/sources/leroy-2009-attention-residue
  - University of Minnesota (United States) · Two lab experiments

## 03 Engagement is not benefit (3 sources)

Why opening an app more often is not proof that it helps. Topic: https://tre-up.com/research/topics/engagement-is-not-benefit

- **Impact of Push Notifications on Physical Activity and Sodium Intake Among Patients with Hypertension: Microrandomized Trial of a Just-in-Time Adaptive Intervention**. Golbus JR, Dorsch MP, Chen Y, Basu T, Luff E, Klasnja P, Newman MW, Skolarus LE, Dempsey W, Nallamothu BK (2026). Journal of Medical Internet Research 28:e78218. https://doi.org/10.2196/78218 · Our summary: https://tre-up.com/research/sources/golbus-2026-mybpmylife
  - University of Michigan (United States) · Micro-randomized trial within a 6-month randomized trial
- **How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial**. Bell L, Garnett C, Bao Y, Cheng Z, Qian T, Perski O, Potts HWW, Williamson E (2023). JMIR mHealth and uHealth 11:e38342. https://doi.org/10.2196/38342 · Our summary: https://tre-up.com/research/sources/bell-2023-drink-less-notifications
  - London School of Hygiene & Tropical Medicine (United Kingdom); University College London (United Kingdom); Harvard University (United States) · Micro-randomized trial
- **Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis**. Baumel A, Muench F, Edan S, Kane JM (2019). Journal of Medical Internet Research 21(9):e14567. https://doi.org/10.2196/14567 · Our summary: https://tre-up.com/research/sources/baumel-2019-mental-health-app-engagement
  - University of Haifa (Israel); Partnership for Drug-Free Kids (United States); Northwell Health (United States) · Usage analysis of real-world panel data

## 04 Autonomy and wording (3 sources)

Why people push back on advice, and the words that make it easier to hear. Topic: https://tre-up.com/research/topics/autonomy-and-wording

- **Reducing Psychological Reactance to Health Promotion Messages: Comparing Preemptive and Postscript Mitigation Strategies**. Richards AS, Bessarabova E, Banas JA, Bernard DR (2022). Health Communication 37(3):366–374. https://doi.org/10.1080/10410236.2020.1839203 · Our summary: https://tre-up.com/research/sources/richards-2022-reactance
  - Affiliation not yet confirmed · Experiment with a one-week follow-up
- **A Theory of Psychological Reactance**. Brehm JW (1966). Academic Press (book). https://ci.nii.ac.jp/ncid/BA02256417?l=en · Our summary: https://tre-up.com/research/sources/brehm-1966-reactance
  - Affiliation not yet confirmed · Theory (book)
- **The "What" and "Why" of Goal Pursuits: Human Needs and the Self-Determination of Behavior**. Deci EL, Ryan RM (2000). Psychological Inquiry 11(4):227–268. https://doi.org/10.1207/S15327965PLI1104_01 · Our summary: https://tre-up.com/research/sources/deci-ryan-2000-self-determination
  - University of Rochester (United States) · Theory paper

## 05 Trust and uncertainty (10 sources)

How people come to rely on automated advice, and how a system should admit what it doesn't know. Topic: https://tre-up.com/research/topics/trust-and-uncertainty

- **Principles of mixed-initiative user interfaces**. Horvitz E (1999). Proceedings of CHI 1999, 159–166. https://doi.org/10.1145/302979.303030 · Our summary: https://tre-up.com/research/sources/horvitz-1999-mixed-initiative
  - Microsoft Research (United States) · Design principles
- **Trust in Automation: Designing for Appropriate Reliance**. Lee JD, See KA (2004). Human Factors 46(1):50–80. https://doi.org/10.1518/hfes.46.1.50_30392 · Our summary: https://tre-up.com/research/sources/lee-see-2004-trust-in-automation
  - University of Iowa (United States) · Review
- **Humans and Automation: Use, Misuse, Disuse, Abuse**. Parasuraman R, Riley V (1997). Human Factors 39(2):230–253. https://doi.org/10.1518/001872097778543886 · Our summary: https://tre-up.com/research/sources/parasuraman-riley-1997-use-misuse
  - Catholic University of America (United States); Honeywell Technology Center (United States) · Review
- **The role of trust in automation reliance**. Dzindolet MT, Peterson SA, Pomranky RA, Pierce LG, Beck HP (2003). International Journal of Human-Computer Studies 58(6):697–718. https://doi.org/10.1016/S1071-5819(03)00038-7 · Our summary: https://tre-up.com/research/sources/dzindolet-2003-trust-reliance
  - Affiliation not yet confirmed · Lab experiments
- **Algorithm appreciation: People prefer algorithmic to human judgment**. Logg JM, Minson JA, Moore DA (2019). Organizational Behavior and Human Decision Processes 151:90–103. https://doi.org/10.1016/j.obhdp.2018.12.005 · Our summary: https://tre-up.com/research/sources/logg-2019-algorithm-appreciation
  - Harvard University (United States); University of California, Berkeley (United States) · Six experiments
- **To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making**. Buçinca Z, Malaya MB, Gajos KZ (2021). Proceedings of the ACM on Human-Computer Interaction 5(CSCW1). https://doi.org/10.1145/3449287 · Our summary: https://tre-up.com/research/sources/bucinca-2021-cognitive-forcing
  - Harvard University (United States) · Online experiment
- **How Much Information? Effects of Transparency on Trust in an Algorithmic Interface**. Kizilcec RF (2016). Proceedings of CHI 2016, 2390–2395. https://doi.org/10.1145/2858036.2858402 · Our summary: https://tre-up.com/research/sources/kizilcec-2016-transparency-trust
  - Stanford University (United States) · Online field experiment
- **Communicating uncertainty about facts, numbers and science**. van der Bles AM, van der Linden S, Freeman ALJ, Mitchell J, Galvao AB, Zaval L, Spiegelhalter DJ (2019). Royal Society Open Science 6(5):181870. https://doi.org/10.1098/rsos.181870 · Our summary: https://tre-up.com/research/sources/van-der-bles-2019-communicating-uncertainty
  - University of Cambridge (United Kingdom); University of Warwick (United Kingdom); Columbia University (United States) · Interdisciplinary review
- **On Calibration of Modern Neural Networks**. Guo C, Pleiss G, Sun Y, Weinberger KQ (2017). Proceedings of ICML 2017, PMLR 70:1321–1330. https://arxiv.org/abs/1706.04599 · Our summary: https://tre-up.com/research/sources/guo-2017-calibration
  - Cornell University (United States) · Machine-learning experiments
- **Selective Classification for Deep Neural Networks**. Geifman Y, El-Yaniv R (2017). Advances in Neural Information Processing Systems 30 (NeurIPS 2017). https://arxiv.org/abs/1705.08500 · Our summary: https://tre-up.com/research/sources/geifman-el-yaniv-2017-selective-classification
  - Technion – Israel Institute of Technology (Israel) · Machine-learning method and experiments

## 06 Learning a person (5 sources)

How a system can help someone it barely knows yet, and why fresh answers beat old patterns. Topic: https://tre-up.com/research/topics/learning-a-person

- **User Cold Start Problem in Recommendation Systems: A Systematic Review**. Yuan H, Hernandez AA (2023). IEEE Access 11:136958–136977. https://doi.org/10.1109/ACCESS.2023.3338705 · Our summary: https://tre-up.com/research/sources/yuan-hernandez-2023-cold-start
  - Affiliation not yet confirmed · Systematic review
- **Collaborative Filtering with Temporal Dynamics**. Koren Y (2009). Proceedings of KDD 2009, 447–456. https://doi.org/10.1145/1557019.1557072 · Our summary: https://tre-up.com/research/sources/koren-2009-temporal-dynamics
  - Yahoo! Research (Israel) · Method with large-scale evaluation
- **Negative Sampling in Recommendation: A Survey and Future Directions**. Ma H, Xie R, Meng L, Feng F, Du X, Sun X, Kang Z, Meng X (2026). ACM Transactions on Information Systems 44:1–44. https://doi.org/10.1145/3793855 · Our summary: https://tre-up.com/research/sources/ma-2026-negative-sampling
  - Shandong University (China); Tencent (China); University of Science and Technology of China (China) · Survey
- **Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity**. Liao P, Greenewald K, Klasnja P, Murphy S (2020). Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4(1):18. https://doi.org/10.1145/3381007 · Our summary: https://tre-up.com/research/sources/liao-2020-personalized-heartsteps
  - University of Michigan (United States); IBM Research (United States); Harvard University (United States) · Learning algorithm with a pilot deployment
- **Using Personalized Intervention Criteria in a Mobile Just-in-Time Adaptive Intervention for Increasing Physical Activity in University Students: Pilot Study**. Ikegaya M, Foo JC, Murata T, Oshima K, Kim J (2025). JMIR Human Factors 12:e66750. https://doi.org/10.2196/66750 · Our summary: https://tre-up.com/research/sources/ikegaya-2025-personalized-criteria
  - Shizuoka University (Japan); University of Alberta (Canada); Heidelberg University (Germany) · Pilot study, two groups

## 07 Privacy and deletion (15 sources)

What deleting your data really means, from the law to the backup tape. Topic: https://tre-up.com/research/topics/privacy-and-deletion

- **The Protection of Information in Computer Systems**. Saltzer JH, Schroeder MD (1975). Proceedings of the IEEE 63(9):1278–1308. https://doi.org/10.1109/PROC.1975.9939 · Our summary: https://tre-up.com/research/sources/saltzer-schroeder-1975-protection
  - Massachusetts Institute of Technology (United States) · Design principles
- **General Data Protection Regulation, Article 17: Right to erasure**. European Union (2016). Primary document, European Union. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32016R0679 · Our summary: https://tre-up.com/research/sources/gdpr-article-17
- **General Data Protection Regulation, Article 12(3): Time limits for responding to requests**. European Union (2016). Primary document, European Union. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32016R0679 · Our summary: https://tre-up.com/research/sources/gdpr-article-12
- **Right to erasure (UK GDPR guidance)**. UK Information Commissioner's Office (current guidance). Primary document, United Kingdom. https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/individual-rights/individual-rights/right-to-erasure/ · Our summary: https://tre-up.com/research/sources/ico-right-to-erasure
- **Les durées de conservation des données (data retention periods)**. CNIL, French data protection authority (current guidance). Primary document, France. https://www.cnil.fr/fr/passer-laction/les-durees-de-conservation-des-donnees · Our summary: https://tre-up.com/research/sources/cnil-retention
- **Regulation on the Deletion, Destruction or Anonymization of Personal Data**. Turkish Personal Data Protection Authority (KVKK) (2017). Primary document, Türkiye. https://www.resmigazete.gov.tr/eskiler/2017/10/20171028-10.htm · Our summary: https://tre-up.com/research/sources/kvkk-deletion-regulation
- **App Store Review Guidelines 5.1.1(v): Account sign-in and deletion**. Apple (current guidelines). Primary document, United States. https://developer.apple.com/app-store/review/guidelines/#data-collection-and-storage · Our summary: https://tre-up.com/research/sources/apple-guideline-5-1-1-v
- **Data deletion on Google Cloud**. Google Cloud (current documentation). Primary document, United States. https://docs.cloud.google.com/docs/security/deletion · Our summary: https://tre-up.com/research/sources/google-cloud-data-deletion
- **SP 800-88 Rev. 2: Guidelines for Media Sanitization**. U.S. National Institute of Standards and Technology (2025). Primary document, United States. https://csrc.nist.gov/pubs/sp/800/88/r2/final · Our summary: https://tre-up.com/research/sources/nist-sp-800-88-r2
- **Deleting an AWS KMS key**. Amazon Web Services (current documentation). Primary document, United States. https://docs.aws.amazon.com/kms/latest/developerguide/deleting-keys.html · Our summary: https://tre-up.com/research/sources/aws-kms-key-deletion
- **AWS Backup Vault Lock**. Amazon Web Services (current documentation). Primary document, United States. https://docs.aws.amazon.com/aws-backup/latest/devguide/vault-lock.html · Our summary: https://tre-up.com/research/sources/aws-backup-vault-lock
- **Locking objects with Object Lock**. Amazon Web Services (current documentation). Primary document, United States. https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock.html · Our summary: https://tre-up.com/research/sources/amazon-s3-object-lock
- **Soft delete for Azure Backup**. Microsoft (current documentation). Primary document, United States. https://learn.microsoft.com/en-us/azure/backup/backup-azure-security-feature-cloud · Our summary: https://tre-up.com/research/sources/azure-backup-soft-delete
- **Immutable vault for Azure Backup**. Microsoft (current documentation). Primary document, United States. https://learn.microsoft.com/en-us/azure/backup/backup-azure-immutable-vault-concept · Our summary: https://tre-up.com/research/sources/azure-immutable-vault
- **Guidelines 4/2019 on Article 25: Data Protection by Design and by Default**. European Data Protection Board (2020). Primary document, European Union. https://www.edpb.europa.eu/sites/default/files/files/file1/edpb_guidelines_201904_dataprotection_by_design_and_by_default_v2.0_en.pdf · Our summary: https://tre-up.com/research/sources/edpb-guidelines-4-2019

## 50 institutions in 10 countries

Institutions are the authors' affiliations as printed in each publication. Naming them says where the research was done. They are not affiliated with Tre-Up and do not endorse Tre-Up or Pursue.

- United States: Arizona State University; Catholic University of America; Columbia University; Cornell University; Duke University; Florida State University; Georgetown University; Harvard University; Honeywell Technology Center; IBM Research; Massachusetts Institute of Technology; Microsoft Research; Northwell Health; Northwestern University; Partnership for Drug-Free Kids; Pennsylvania State University; Stanford University; University of California, Berkeley; University of California, Irvine; University of California, San Diego; University of Illinois Urbana-Champaign; University of Iowa; University of Michigan; University of Minnesota; University of New Mexico; University of Pittsburgh; University of Rochester; University of Virginia
- United Kingdom: London School of Hygiene & Tropical Medicine; University College London; University of Birmingham; University of Cambridge; University of Warwick
- Canada: University of Alberta; University of British Columbia; University of Calgary
- China: Shandong University; Tencent; University of Science and Technology of China
- Israel: Technion – Israel Institute of Technology; University of Haifa; Yahoo! Research
- Japan: Keio University; Shizuoka University; Yahoo Japan Corporation
- Germany: Heidelberg University; Humboldt-Universität zu Berlin
- Australia: Flinders University
- Slovenia: University of Ljubljana
- Spain: Telefónica Research

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