Vinayak K. Nahar

1.7k total citations
96 papers, 1.1k citations indexed

About

Vinayak K. Nahar is a scholar working on Dermatology, Public Health, Environmental and Occupational Health and General Health Professions. According to data from OpenAlex, Vinayak K. Nahar has authored 96 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Dermatology, 24 papers in Public Health, Environmental and Occupational Health and 15 papers in General Health Professions. Recurrent topics in Vinayak K. Nahar's work include Skin Protection and Aging (24 papers), Obesity, Physical Activity, Diet (12 papers) and Behavioral Health and Interventions (11 papers). Vinayak K. Nahar is often cited by papers focused on Skin Protection and Aging (24 papers), Obesity, Physical Activity, Diet (12 papers) and Behavioral Health and Interventions (11 papers). Vinayak K. Nahar collaborates with scholars based in United States, India and Iran. Vinayak K. Nahar's co-authors include Manoj Sharma, M. Allison Ford, Martha A. Bass, Robert E. Davis, Robert T. Brodell, Paul Johnson, Javier F. Boyas, Amanda H. Wilkerson, Ross Pearlman and Jeffrey S. Hallam and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Medicine & Science in Sports & Exercise.

In The Last Decade

Vinayak K. Nahar

91 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vinayak K. Nahar United States 20 254 209 181 177 157 96 1.1k
Mary L. Adams United States 21 67 0.3× 218 1.0× 154 0.9× 180 1.0× 143 0.9× 58 1.2k
Latrice C. Pichon United States 19 353 1.4× 90 0.4× 64 0.4× 330 1.9× 68 0.4× 63 997
Daniel P. Krowchuk United States 23 684 2.7× 245 1.2× 498 2.8× 405 2.3× 184 1.2× 56 2.4k
Shanchita R. Khan Australia 18 47 0.2× 221 1.1× 286 1.6× 257 1.5× 98 0.6× 33 983
Anne Russell Australia 18 714 2.8× 183 0.9× 59 0.3× 144 0.8× 114 0.7× 29 1.7k
Salvatore Zaffina Italy 20 136 0.5× 86 0.4× 300 1.7× 278 1.6× 48 0.3× 62 1.3k
Maria Lia Scribano Italy 20 57 0.2× 192 0.9× 251 1.4× 312 1.8× 123 0.8× 54 2.7k
Judith O’Haver United States 13 39 0.2× 285 1.4× 235 1.3× 234 1.3× 84 0.5× 25 763
Peter Jacoby Australia 25 68 0.3× 601 2.9× 282 1.6× 139 0.8× 151 1.0× 46 2.0k
Jennifer L. P. Protudjer Canada 24 145 0.6× 389 1.9× 409 2.3× 140 0.8× 377 2.4× 134 1.8k

Countries citing papers authored by Vinayak K. Nahar

Since Specialization
Citations

This map shows the geographic impact of Vinayak K. Nahar'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 Vinayak K. Nahar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vinayak K. Nahar more than expected).

Fields of papers citing papers by Vinayak K. Nahar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vinayak K. Nahar. 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 Vinayak K. Nahar. The network helps show where Vinayak K. Nahar may publish in the future.

Co-authorship network of co-authors of Vinayak K. Nahar

This figure shows the co-authorship network connecting the top 25 collaborators of Vinayak K. Nahar. A scholar is included among the top collaborators of Vinayak K. Nahar 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 Vinayak K. Nahar. Vinayak K. Nahar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Huynh, Thy, et al.. (2023). An Integrated Teledermatology Model: Attacking Access to Skin Care in a Rural State. Current Dermatology Reports. 12(3). 101–106.
3.
Dobbs, Page D., et al.. (2022). Psychological Help-Seeking Among College Students: Applying the Multi-Theory Model of Health Behavior Change in Assessing Telehealth Use for Psychological Help-Seeking. American Journal of Lifestyle Medicine. 19(3). 450–462. 3 indexed citations
4.
Daniel, C. Ralph, et al.. (2022). Holiday Reindeer Trivia for Physicians Who Like Hair and Nails. Skin Appendage Disorders. 8(4). 314–316. 1 indexed citations
5.
Sharma, Manoj, et al.. (2021). Utility of Multi-Theory Model (MTM) to Explain the Intention for PAP Adherence in Newly Diagnosed Sleep Apnea Patients. Nature and Science of Sleep. Volume 13. 263–271. 4 indexed citations
6.
Sharma, Ankur, Meena Jain, Vinayak K. Nahar, & Manoj Sharma. (2020). Determining predictors of change in sugar sweetened beverage consumption behaviour among university students in India. International Journal of Adolescent Medicine and Health. 34(1). 7 indexed citations
7.
Sharma, Ankur, Meena Jain, Vinayak K. Nahar, & Manoj Sharma. (2020). Predictors of behaviour change for unhealthy sleep patterns among Indian dental students. International Journal of Adolescent Medicine and Health. 33(5). 6 indexed citations
8.
Sharma, Manoj, Kavita Batra, & Vinayak K. Nahar. (2020). Alcohol Consumption in COVID-19 Pandemic: Implications for Alcohol Education. Journal of alcohol and drug education. 64(2). 8–19. 2 indexed citations
9.
Davis, Robert E., et al.. (2020). An Investigation of the Associations between Drug-Related Self-Stigmatizing Beliefs, Depression, and Suicidal Ideation among Collegiate Drug Users.. Journal of alcohol and drug education. 64(1). 52–80. 1 indexed citations
10.
Nahar, Vinayak K., et al.. (2020). Non-Traditional and Non-Invasive Approaches in Facial Rejuvenation: A Brief Review. Cosmetics. 7(1). 10–10. 7 indexed citations
11.
12.
Sharma, Manoj, et al.. (2019). A survey of knowledge and use of telehealth among veterinarians. BMC Veterinary Research. 15(1). 474–474. 31 indexed citations
13.
Davis, Robert E., et al.. (2019). Association between prescription opioid misuse and dimensions of suicidality among college students. Psychiatry Research. 287. 112469–112469. 36 indexed citations
14.
Nahar, Vinayak K., et al.. (2019). Utilizing Multi-Theory Model in Determining Intentions to Smoking Cessation Among Smokers. SHILAP Revista de lepidopterología. 12. 1179173X19843524–1179173X19843524. 9 indexed citations
15.
Nahar, Vinayak K., Amanda H. Wilkerson, Brian Martin, et al.. (2018). Skin cancer knowledge, attitudes, beliefs, and prevention practices among medical students: A systematic search and literature review. International Journal of Women’s Dermatology. 4(3). 139–149. 35 indexed citations
16.
Nahar, Vinayak K., et al.. (2018). Predicting Physical Activity Behavior in African American Females: Using Multi Theory Model.. PubMed. 18(2). e00410–e00410. 15 indexed citations
17.
Martin, Brian, et al.. (2018). Skin Cancer Knowledge, Attitudes, and Practices among Chinese Population: A Narrative Review. Dermatology Research and Practice. 2018. 1–9. 16 indexed citations
18.
Sharma, Manoj, et al.. (2017). Applying Multi-Theory Model (MTM) of Health Behavior Change to Predict Water Consumption Instead of Sugar-Sweetened Beverages.. PubMed. 17(1). e00370–e00370. 27 indexed citations
19.
Nahar, Vinayak K., Brian Martin, Javier F. Boyas, et al.. (2017). Perceptions and Practices of the Iranian Population regarding Skin Cancers: A Literature Review. Journal of Skin Cancer. 2017. 1–13. 5 indexed citations
20.
Knowlden, Adam P., Manoj Sharma, & Vinayak K. Nahar. (2016). Using Multitheory Model of Health Behavior Change to Predict Adequate Sleep Behavior. Family & Community Health. 40(1). 56–61. 30 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.

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