In all academic fields, there are scholars who contribute to the research literature at exceptionally high levels. The goal of the current study was to discover what school psychology researchers with remarkably high levels of journal publication do to be so productive. In Study 1, 94 highly productive school psychology scholars were identified from past research, and 51 (39 men, 12 women) submitted individual, short-answer responses to a 5-item questionnaire regarding their research strategies. A constant comparative approach was employed to sort and code individual sentiments (N=479) into categories. Seven broad categories of counsel for increasing productivity emerged: (a) research and publication practices and strategies, (b) collaboration, mentoring and building relationships, (c) navigating the peer-review process, (d) strategies to bolster writing productivity and excellence, (e) personal character traits that foster productivity, (f) preparation before entering the professoriate, and (g) other noteworthy sentiments. Results are discussed in terms of nine recommendations for scholars and graduate students who wish to increase their productivity. In Study 2, five of the most productive scholars (1 woman, 4 men) participated in a semi-structured interview about their high levels of productivity. Interviews were recorded, transcribed, and analyzed, and a case analysis approach employed to profile each scholar. Study limitations and suggestions for future research are discussed.
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http://dx.doi.org/10.1016/j.jsp.2011.10.003 | DOI Listing |
Dev Cogn Neurosci
December 2024
School of Psychological Science, University of Bristol, UK.
It is well established that faces evoke a distinct neural response in the adult and infant brain. Past research has focused on how the infant face-sensitive ERP components (N290, P400, Nc) reflect different aspects of face processing, however there is still a lack of understanding of how these components reflect face familiarity and how they change over time. Further, there are only a few studies on whether these neural responses correlate with other aspects of development, such as infant temperament.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
School of Nursing, Anhui Medical University, Hefei, China.
Background: Body image issues are prevalent among individuals diagnosed with cancer, leading to detrimental effects on their physical and psychological recovery. eHealth has emerged as a promising approach for enhancing the body image of patients with cancer.
Objective: The purpose of this study was to evaluate the effectiveness of eHealth interventions on body image and other health outcomes (quality of life, physical symptoms, and emotional distress) among patients with cancer.
J Med Internet Res
January 2025
Department of Pediatrics, Medical School, University of Michigan, Ann Arbor, MI, United States.
Background: The mental health crisis among college students intensified amid the COVID-19 pandemic, suggesting an urgent need for innovative solutions to support them. Previous efforts to address mental health concerns have been constrained, often due to the underuse or shortage of services. Mobile health (mHealth) technology holds significant potential for providing resilience-building support and enhancing access to mental health care.
View Article and Find Full Text PDFNoise Health
January 2025
MGEN Foundation for Public Health, Paris, France.
Objective: Besides psychosocial stressors, teachers are exposed to disturbing noise at work, such as students' irrelevant speech. Few studies have focused on this issue and its health consequences. We explored occupational noise exposure among teachers within the French workforce and analyzed how noise and work-related stress are related to their health.
View Article and Find Full Text PDFJ Speech Lang Hear Res
January 2025
Department of Psychology, University of Western Ontario, London, Canada.
Purpose: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification of language disorders in children.
Method: We first describe the current barriers to clinicians' use of language sample analysis, narrative language sampling approaches, and the data processing stages that precede analysis.
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