What is she best known for?
The fields of study she is best known for:
The scientist’s investigation covers issues in Nursing, Nurse education, MEDLINE, Nursing care and Health care.
She interconnects Family medicine and Competence in the investigation of issues within Nursing.
The study incorporates disciplines such as Qualitative research, Content analysis and Curriculum in addition to Nurse education.
Helena Leino-Kilpi has included themes like Nurse educator, Validity and Patient education in her MEDLINE study.
Her study focuses on the intersection of Nursing care and fields such as Quality of life with connections in the field of Nursing Interventions Classification.
Her Health care study integrates concerns from other disciplines, such as Dementia and Gerontology.
Her most cited work include:
- Nurse competence scale: development and psychometric testing. (279 citations)
- Power and empowerment in nursing: three theoretical approaches. (270 citations)
- Nurses' intention to leave the profession: integrative review. (193 citations)
What are the main themes of her work throughout her whole career to date?
Helena Leino-Kilpi focuses on Nursing, Health care, Nurse education, Family medicine and Nursing care.
Her Nursing research includes elements of Empowerment, Response rate, MEDLINE and Competence.
Her research integrates issues of Autonomy and Nursing management in her study of Health care.
The Nurse education study combines topics in areas such as Nursing research, Content analysis and Curriculum.
Her work on Patient education as part of general Family medicine research is frequently linked to Cross-sectional study, thereby connecting diverse disciplines of science.
The concepts of her Nursing care study are interwoven with issues in Patient satisfaction and Test.
She most often published in these fields:
- Nursing (75.95%)
- Health care (24.88%)
- Nurse education (21.89%)
What were the highlights of her more recent work (between 2018-2021)?
- Nursing (75.95%)
- Health care (24.88%)
- Competence (19.73%)
In recent papers she was focusing on the following fields of study:
Nursing, Health care, Competence, Medical education and Nurse education are her primary areas of study.
Nursing is closely attributed to Patient safety in her study.
Her Health care research integrates issues from Nursing management, Prehospital Emergency Care, Confidentiality and Content analysis.
Helena Leino-Kilpi has researched Competence in several fields, including Anesthesia, General partnership and Nurse educator.
Her study in Medical education is interdisciplinary in nature, drawing from both Ethical code, Health administration, Public health, PsycINFO and Health professionals.
Her work on Clinical learning as part of general Nurse education study is frequently linked to Cross-sectional study, therefore connecting diverse disciplines of science.
Between 2018 and 2021, her most popular works were:
- Predicting caregiver burden in informal caregivers caring for persons with dementia living at home - A follow-up cohort study. (11 citations)
- Predicting caregiver burden in informal caregivers caring for persons with dementia living at home - A follow-up cohort study. (11 citations)
- Preventive interventions for pressure ulcers in long-term older people care facilities: A systematic review. (10 citations)
In her most recent research, the most cited papers focused on:
Her primary areas of investigation include Nursing, Nursing care, Cross-sectional study, CINAHL and Competence.
Her biological study spans a wide range of topics, including Content analysis and Health care.
Her studies in Nursing care integrate themes in fields like Psychometrics, Cronbach's alpha, Disease, Thematic analysis and Rationing.
The various areas that she examines in her CINAHL study include PsycINFO, Functional ability and Psychosocial.
Her MEDLINE study combines topics from a wide range of disciplines, such as Psychological intervention, Nursing Interventions Classification, Distress and Long-term care.
Her work in the fields of Nurse education overlaps with other areas such as Clinical Practice.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
