Jack Mearns

2.4k total citations
43 papers, 1.8k citations indexed

About

Jack Mearns is a scholar working on Clinical Psychology, Experimental and Cognitive Psychology and Social Psychology. According to data from OpenAlex, Jack Mearns has authored 43 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Clinical Psychology, 23 papers in Experimental and Cognitive Psychology and 14 papers in Social Psychology. Recurrent topics in Jack Mearns's work include Child and Adolescent Psychosocial and Emotional Development (21 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (18 papers) and Mental Health Research Topics (15 papers). Jack Mearns is often cited by papers focused on Child and Adolescent Psychosocial and Emotional Development (21 papers), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (18 papers) and Mental Health Research Topics (15 papers). Jack Mearns collaborates with scholars based in United States, Japan and Germany. Jack Mearns's co-authors include Salvatore J. Catanzaro, Irving Kirsch, Yoshimi ITO, Paul R. Lees‐Haley, George J. Allen, John T. Dunn, Toshitaka Hamamura, Matthias Backenstraß, J. Conrad Schwarz and Mindy B. Mechanic and has published in prestigious journals such as Journal of Personality and Social Psychology, Personality and Individual Differences and Journal of Personality.

In The Last Decade

Jack Mearns

43 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jack Mearns United States 18 1.1k 706 654 222 181 43 1.8k
Rosa M. Valiente Spain 24 1.3k 1.2× 774 1.1× 691 1.1× 245 1.1× 231 1.3× 66 2.0k
Junko Tanaka‐Matsumi Japan 16 952 0.9× 1.0k 1.4× 542 0.8× 322 1.5× 165 0.9× 42 1.9k
Kathleen C. Gunthert United States 19 991 0.9× 587 0.8× 752 1.1× 301 1.4× 156 0.9× 44 1.8k
Tianqiang Hu China 13 1.2k 1.1× 664 0.9× 309 0.5× 199 0.9× 208 1.1× 21 1.7k
Colleen S. Conley United States 21 1.3k 1.2× 796 1.1× 388 0.6× 245 1.1× 335 1.9× 36 2.0k
Allison S. Troy United States 16 1.3k 1.2× 755 1.1× 987 1.5× 320 1.4× 159 0.9× 19 2.2k
José M. Salguero Spain 26 1.1k 1.0× 1.2k 1.7× 436 0.7× 187 0.8× 172 1.0× 56 2.0k
Julia F. Sowislo Switzerland 11 1.0k 0.9× 744 1.1× 476 0.7× 189 0.9× 184 1.0× 20 1.8k
Jingbo Zhao China 20 913 0.8× 324 0.5× 368 0.6× 176 0.8× 148 0.8× 45 1.2k
Ross B. Wilkinson Australia 22 1.2k 1.1× 861 1.2× 369 0.6× 191 0.9× 105 0.6× 53 1.8k

Countries citing papers authored by Jack Mearns

Since Specialization
Citations

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

Fields of papers citing papers by Jack Mearns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack Mearns. 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 Jack Mearns. The network helps show where Jack Mearns may publish in the future.

Co-authorship network of co-authors of Jack Mearns

This figure shows the co-authorship network connecting the top 25 collaborators of Jack Mearns. A scholar is included among the top collaborators of Jack Mearns 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 Jack Mearns. Jack Mearns 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.
An, Tingting, et al.. (2022). Negative Mood Regulation Expectancies Moderate the Effects of Acculturative Stress on Affective Symptoms Among Chinese International Students in Japan. Japanese Psychological Research. 66(3). 330–339. 3 indexed citations
2.
Mearns, Jack, et al.. (2020). Emotion Regulation and Middle School Adjustment in Japanese Girls: Mediation by Perceived Social Support. Japanese Psychological Research. 62(2). 138–150. 8 indexed citations
3.
4.
Mearns, Jack, et al.. (2017). Measuring generalised expectancies for negative mood regulation in China: The Chinese language Negative Mood Regulation scale. International Journal of Psychology. 54(2). 223–231. 4 indexed citations
5.
Mearns, Jack, et al.. (2014). Negative Mood Regulation Expectancies Moderate the Relationship Between Psychological Abuse and Avoidant Coping. Journal of Interpersonal Violence. 30(9). 1553–1566. 20 indexed citations
6.
Mearns, Jack, et al.. (2013). Developing a Korean Language Measure of Generalized Expectancies for Negative Mood Regulation. 3(1). 89–97. 8 indexed citations
7.
ITO, Yoshimi, et al.. (2012). Risk factors for nonsuicidal self‐injury in Japanese college students: The moderating role of mood regulation expectancies. International Journal of Psychology. 48(6). 1009–1017. 36 indexed citations
8.
Martínez, Vania, et al.. (2012). Preliminary reliability and validity of the Spanish Generalized Expectancies for Negative Mood Regulation Scale.. PubMed. 31(2). 129–34. 7 indexed citations
9.
ITO, Yoshimi, et al.. (2012). Self-Injurious Behavior and Suicide Attempts Among Indonesian College Students. Death Studies. 36(7). 627–639. 57 indexed citations
10.
11.
Backenstraß, Matthias, et al.. (2008). Reliabilität und Validität der deutschsprachigen Version der Generalized Expectancies for Negative Mood Regulation (NMR) Scale. Diagnostica. 54(1). 43–51. 18 indexed citations
12.
Mearns, Jack, et al.. (2003). Relationships between Teachers' Occupational Stress and Their Burnout and Distress: Roles of Coping and Negative Mood Regulation Expectancies. Anxiety Stress & Coping. 16(1). 71–82. 194 indexed citations
13.
Segal, Nancy L., et al.. (2002). Monozygotic and Dizygotic Twins' Retrospective and Current Bereavement-related Behaviors: An Evolutionary Perspective. Twin Research. 5(3). 188–195. 1 indexed citations
14.
Segal, Nancy L., et al.. (2002). Monozygotic and Dizygotic Twins' Retrospective and Current Bereavement-related Behaviors: An Evolutionary Perspective. Twin Research. 5(3). 188–195. 2 indexed citations
15.
Catanzaro, Salvatore J., et al.. (2000). Coping‐related Expectancies and Dispositions as Prospective Predictors of Coping Responses and Symptoms. Journal of Personality. 68(4). 757–788. 82 indexed citations
16.
Mearns, Jack, et al.. (1998). Negative Mood Regulation Expectancies Predict Anger among Police Officers and Buffer the Effects of Job Stress. The Journal of Nervous and Mental Disease. 186(2). 120–125. 52 indexed citations
17.
Mearns, Jack. (1991). Coping with a breakup: Negative mood regulation expectancies and depression following the end of a romantic relationship.. Journal of Personality and Social Psychology. 60(2). 327–334. 115 indexed citations
18.
Catanzaro, Salvatore J. & Jack Mearns. (1990). Measuring Generalized Expectancies for Negative Mood Regulation: Initial Scale Development and Implications. Journal of Personality Assessment. 54(3). 546–563. 247 indexed citations
19.
Catanzaro, Salvatore J. & Jack Mearns. (1990). Measuring Generalized Expectancies for Negative Mood Regulation: Initial Scale Development and Implications. Journal of Personality Assessment. 54(3-4). 546–563. 435 indexed citations
20.
Kirsch, Irving, Jack Mearns, & Salvatore J. Catanzaro. (1990). Mood-regulation expectancies as determinants of dysphoria in college students.. Journal of Counseling Psychology. 37(3). 306–312. 87 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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