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.
The prevalence of anxiety and depression among healthcare workers during the COVID-19 pandemic: An umbrella review of meta-analyses
2021193 citationsAli Sahebi, Kosar Yousefi et al.profile →
Post-traumatic stress disorder in medical workers involved in earthquake response: A systematic review and meta-analysis
202356 citationsUlrich Wesemann, Ali Sahebi et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Ali Sahebi'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 Ali Sahebi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ali Sahebi more than expected).
This network shows the impact of papers produced by Ali Sahebi. 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 Ali Sahebi. The network helps show where Ali Sahebi may publish in the future.
Co-authorship network of co-authors of Ali Sahebi
This figure shows the co-authorship network connecting the top 25 collaborators of Ali Sahebi.
A scholar is included among the top collaborators of Ali Sahebi 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 Ali Sahebi. Ali Sahebi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sahebi, Ali, et al.. (2020). The effectiveness of poetry performance on self-esteem and hope of dystmic depressed people. SHILAP Revista de lepidopterología. 19(91). 865–874.
Sahebi, Ali, et al.. (2015). The Effectiveness of Choice Theory in Quality of Life and Resilience of Drug Users. SHILAP Revista de lepidopterología.1 indexed citations
14.
Sahebi, Ali, et al.. (2015). Choice theory: an approach to accountability and. Rooyesh-e- Ravanshenasi Journal(RRJ). 4(2). 113–134.1 indexed citations
15.
Mazaheri, Mohammad Ali, et al.. (2011). THE EFFECT OF COGNITIVE-BEHAVIORAL TRAINING ON MODIFICATION OF IRRATIONAL EXPECTATION, EMOTIONAL MATURITY AND MARITAL DISSATISFACTION IN WOMEN. International behavioral sciences/International journal of behavioral sciences. 5(2). 127–133.5 indexed citations
16.
Hemati, Simin, et al.. (2010). Higher plasma MMP-9 level in breast cancer patients with MMP-9 promoter T allele. 13. 105–111.3 indexed citations
17.
Sahebi, Ali, et al.. (2005). EFFICACY AND EFFECTIVENESS OF BECK'S WITH TEASDALE'S COGNITIVE THERAPIES IN TREATMENT OF DYSTHYMIA. Iranian Journal of Psychiatry and Clinical Psychology. 11(241). 150–163.1 indexed citations
18.
Sahebi, Ali, et al.. (2005). COMPARING EFFICACY AND EFFECTIVENESS OF ERP AND DIRT METHODS IN TREATMENT OF COMPULSIVE WASHING. Iranian Journal of Psychiatry and Clinical Psychology. 11(241). 139–149.1 indexed citations
19.
Sahebi, Ali, et al.. (2004). Effect of behavioral-cognitive education on reduction of anxiety in women with primary infertility who undergo GIFT and ZIFT. Journal of Reproduction & Infertility. 5(218). 170–180.4 indexed citations
20.
Sahebi, Ali, et al.. (2002). IMPACT OF COGNITIVE BEHAVIOUR THERAPY ON ANXIETY LEVEL OF PRIMARY INFERTILE WOMEN UNDERGOING IUI. Journal of Reproduction & Infertility. 3(311). 40–51.6 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.