Michael V. Heinz

987 total citations · 1 hit paper
37 papers, 481 citations indexed

About

Michael V. Heinz is a scholar working on Experimental and Cognitive Psychology, Applied Psychology and Clinical Psychology. According to data from OpenAlex, Michael V. Heinz has authored 37 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Experimental and Cognitive Psychology, 17 papers in Applied Psychology and 12 papers in Clinical Psychology. Recurrent topics in Michael V. Heinz's work include Mental Health Research Topics (19 papers), Digital Mental Health Interventions (17 papers) and Mental Health via Writing (5 papers). Michael V. Heinz is often cited by papers focused on Mental Health Research Topics (19 papers), Digital Mental Health Interventions (17 papers) and Mental Health via Writing (5 papers). Michael V. Heinz collaborates with scholars based in United States, Israel and Germany. Michael V. Heinz's co-authors include Nicholas C. Jacobson, Matthew D. Nemesure, George Price, Damien Lekkas, Paul Barr, Amanda C Collins, Daniel M. Mackin, Elad Yom‐Tov, Seo Ho Song and Subigya Nepal and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Computers in Human Behavior.

In The Last Decade

Michael V. Heinz

30 papers receiving 466 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Randomized Trial of a Generative AI Chatbot for Mental Health Treatment

2025 45 citations Michael V. Heinz, Daniel M. Mackin et al. NEJM AI profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael V. Heinz United States	11	167	160	159	120	50	37	481
Alex Luedtke United States	11	142 0.9×	74 0.5×	238 1.5×	116 1.0×	42 0.8×	39	588
Eileen Bendig Germany	11	127 0.8×	241 1.5×	87 0.5×	115 1.0×	61 1.2×	21	453
Michael Tanana United States	14	204 1.2×	292 1.8×	190 1.2×	232 1.9×	117 2.3×	31	707
Julia Bondar United States	5	178 1.1×	106 0.7×	88 0.6×	66 0.6×	59 1.2×	5	476
Jonathan Marsh United States	6	63 0.4×	82 0.5×	79 0.5×	150 1.3×	104 2.1×	8	379
Russell Fulmer United States	5	150 0.9×	315 2.0×	72 0.5×	127 1.1×	82 1.6×	10	477
Athena Robinson United States	15	185 1.1×	357 2.2×	308 1.9×	132 1.1×	66 1.3×	39	811
Sarah Pajarito United States	6	93 0.6×	163 1.0×	115 0.7×	54 0.5×	34 0.7×	12	318
Christina S. Soma United States	9	96 0.6×	118 0.7×	124 0.8×	138 1.1×	55 1.1×	20	366
Blanca S. Pineda United States	7	99 0.6×	113 0.7×	102 0.6×	79 0.7×	12 0.2×	14	288

Countries citing papers authored by Michael V. Heinz

Since Specialization

Citations

This map shows the geographic impact of Michael V. Heinz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael V. Heinz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael V. Heinz more than expected).

Fields of papers citing papers by Michael V. Heinz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael V. Heinz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael V. Heinz. The network helps show where Michael V. Heinz may publish in the future.

Co-authorship network of co-authors of Michael V. Heinz

This figure shows the co-authorship network connecting the top 25 collaborators of Michael V. Heinz. A scholar is included among the top collaborators of Michael V. Heinz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael V. Heinz. Michael V. Heinz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Collins, Amanda C, et al.. (2025). A comparison of objective and subjective measures of physical activity, sedentary and sleep behaviors between persons with and without depressive symptoms. Journal of Affective Disorders. 375. 22–26.

Lekkas, Damien, Amanda C Collins, Michael V. Heinz, et al.. (2025). Acute suicidal ideation in context: highlighting sentiment-based markers through the diary entries of a clinically depressed sample. BMC Psychiatry. 25(1). 650–650. 1 indexed citations

Tlachac, ML, et al.. (2025). Datasets of Smartphone Modalities for Depression Assessment: A Scoping Review. IEEE Transactions on Affective Computing. 16(4). 2599–2619.

Heinz, Michael V., et al.. (2025). Response to Letters about “Randomized Trial of a Generative AI Chatbot for Mental Health Treatment”. NEJM AI. 2(9).

Heinz, Michael V., et al.. (2025). Randomized Trial of a Generative AI Chatbot for Mental Health Treatment. NEJM AI. 2(4). 45 indexed citations breakdown →

Heinz, Michael V., et al.. (2024). A large-scale observational comparison of antidepressants and their effects. Journal of Psychiatric Research. 178. 219–224.

Price, George, Amanda C Collins, Daniel M. Mackin, Michael V. Heinz, & Nicholas C. Jacobson. (2024). Use of passively collected actigraphy data to detect individual depressive symptoms in a clinical subpopulation and a general population.. Journal of Psychopathology and Clinical Science. 134(1). 31–40. 2 indexed citations

Collins, Amanda C, Damien Lekkas, Matthew D. Nemesure, et al.. (2024). Anhedonia in flux: Understanding the associations of emotion regulation and anxiety with anhedonia dynamics in a sample with major depressive disorder. Journal of Affective Disorders. 372. 27–36. 3 indexed citations

Collins, Amanda C, Damien Lekkas, Cara A. Struble, et al.. (2024). From mood to use: Using ecological momentary assessments to examine how anhedonia and depressed mood impact cannabis use in a depressed sample. Psychiatry Research. 339. 116110–116110. 2 indexed citations

10.

Tlachac, ML, et al.. (2024). Symptom Detection with Text Message Log Distributions for Holistic Depression and Anxiety Screening. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 8(1). 1–28. 1 indexed citations

11.

Nemesure, Matthew D., Amanda C Collins, George Price, et al.. (2024). Depressive symptoms as a heterogeneous and constantly evolving dynamical system: Idiographic depressive symptom networks of rapid symptom changes among persons with major depressive disorder.. Journal of Psychopathology and Clinical Science. 133(2). 155–166. 15 indexed citations

12.

Heinz, Michael V., et al.. (2024). Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment. Biomedical Materials & Devices. 2(2). 778–810. 7 indexed citations

13.

Nepal, Subigya, Michael V. Heinz, Xuhai Xu, et al.. (2024). MindScape Study: Integrating LLM and Behavioral Sensing for Personalized AI-Driven Journaling Experiences. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 8(4). 1–44. 6 indexed citations

14.

Lekkas, Damien, Matthew D. Nemesure, Amanda C Collins, et al.. (2024). The role of borderline personality disorder traits in predicting longitudinal variability of major depressive symptoms among a sample of depressed adults. Journal of Affective Disorders. 363. 492–500. 6 indexed citations

15.

Nepal, Subigya, Weichen Wang, Matthew D. Nemesure, et al.. (2023). Investigating Generalizability of Speech-based Suicidal Ideation Detection Using Mobile Phones. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 7(4). 1–38. 10 indexed citations

16.

Price, George, Michael V. Heinz, Amanda C Collins, & Nicholas C. Jacobson. (2023). Detecting major depressive disorder presence using passively-collected wearable movement data in a nationally-representative sample. Psychiatry Research. 332. 115693–115693. 13 indexed citations

17.

Wang, Brian, Matthew D. Nemesure, Chloe Park, et al.. (2023). Leveraging deep learning models to understand the daily experience of anxiety in teenagers over the course of a year. Journal of Affective Disorders. 329. 293–299. 3 indexed citations

18.

Price, George, Michael V. Heinz, Seo Ho Song, Matthew D. Nemesure, & Nicholas C. Jacobson. (2023). Using digital phenotyping to capture depression symptom variability: detecting naturalistic variability in depression symptoms across one year using passively collected wearable movement and sleep data. Translational Psychiatry. 13(1). 381–381. 13 indexed citations

19.

Heinz, Michael V., et al.. (2022). An unsupervised machine learning approach using passive movement data to understand depression and schizophrenia. Journal of Affective Disorders. 316. 132–139. 14 indexed citations

20.

Heinz, Michael V., et al.. (2019). Understanding Urgency in Radiology Reporting: Identifying Associations Between Clinical Findings in Radiology Reports and Their Prompt Communication to Referring Physicians. Studies in health technology and informatics. 264. 1546–1547. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact