Informing nursing policy: An exploration of digital health research by nurses in England

AIMS

Digital health technologies are designed, implemented, and evaluated to support clinical practice, enable patients to self-manage illness, and further public and global health. Nursing and health policies often emphasise the importance of evidence-based digital health services to deliver better care. However, the contribution nurses make to digital health research in many countries is unknown. Hence, this study aims to examine digital health research conducted by nurses in England.

DESIGN

A bibliometric analysis.

METHODS

The CINAHL, MEDLINE, and Scopus databases were searched between 2000 and 2022, and supplemented with a hand search of nurses' research profiles. Results were screened by title, abstract, and full text against eligibility criteria. Data were extracted and bibliometric analysis used to summarise the findings.

RESULTS

Mental health nurses produced the most digital health research in England, followed by nurses working in community care, with several disciplines underrepresented or missing. Web/online health services or information was the most researched technology, followed by mobile health and telehealth. Nurses based in the south-east and north-west of England produced the most digital health research, with other regions less well represented.

CONCLUSION

Nurse leaders should support nurses to conduct more digital health research by providing dedicated time, funding, and professional development opportunities, particularly in under researched clinical areas, technologies, and geographic regions to further evidence-based practice and patient care. More digital nursing data is needed to support nurse led research in areas like artificial intelligence and data science. The findings supported the national Philips Ives Review by identifying areas of digital nursing research that need more investment in England.

The application and use of artificial intelligence in cancer nursing: A systematic review

PURPOSE

Artificial Intelligence is being applied in oncology to improve patient and service outcomes. Yet, there is a limited understanding of how these advanced computational techniques are employed in cancer nursing to inform clinical practice. This review aimed to identify and synthesise evidence on artificial intelligence in cancer nursing.

METHODS

CINAHL, MEDLINE, PsycINFO, and PubMed were searched using key terms between January 2010 and December 2022. Titles, abstracts, and then full texts were screened against eligibility criteria, resulting in twenty studies being included. Critical appraisal was undertaken, and relevant data extracted and analysed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed.

RESULTS

Artificial intelligence was used in numerous areas including breast, colorectal, liver, and ovarian cancer care among others. Algorithms were trained and tested on primary and secondary datasets to build predictive models of health problems related to cancer. Studies reported this led to improvements in the accuracy of predicting health outcomes or identifying variables that improved outcome prediction. While nurses led most studies, few deployed an artificial intelligence based digital tool with cancer nurses in a real-world setting as studies largely focused on developing and validating predictive models.

CONCLUSION

Electronic cancer nursing datasets should be established to enable artificial intelligence techniques to be tested and if effective implemented in digital prediction and other AI-based tools. Cancer nurses need more education on machine learning and natural language processing, so they can lead and contribute to artificial intelligence developments in oncology.

The lived experience of adults with cystic fibrosis: what they would tell their younger selves about the gut

Background

Little is known about adults’ experience of living with cystic fibrosis (CF) specifically in relation to the gut. However, their unique perspectives may be meaningful to children with CF and inform the understanding and practice of dietitians. The present study aimed to explore adults’ lived experience of the CF gut and how they learnt to manage the gut as they were growing up.

Methods

Semi‐structured interviews were conducted with adult inpatients (n = 10). Interviews were audio‐recorded, transcribed verbatim and accounts analysed using interpretative phenomenological analysis.

Results

Three super‐ordinate themes were identified: taking Creon, the learning process and this much I (now) know. Participants accounts of how CF affects the gut predominantly focused on taking Creon (pancreatin, Mylan). Various strategies were employed for coping with peer responses to taking Creon at school. Several participants reached adulthood before they understood and/or accepted that taking Creon consistently needed to be normal for them. Knowledge and understanding developed over time, with ‘CF experience’ and was shaped by family, CF care teams and other children with CF. All had unmet information needs when growing up. Having key explanations earlier, to make connections between eating, taking Creon, gaining weight and growth, did or would have helped most participants. Participants urged children to be assertive, ask questions and not only be involved in managing their diet and gut, but also begin to take control of this aspect of their CF.

Conclusions

Supporting development of knowledge, skills and confidence to manage diet and the gut needs to be integral to care throughout childhood.

Is the hospital setting the place for teaching breast self-examination?

The purpose of this study was to investigate the effects of an instructional program for nurses educating them to teach breast self-examination (BSE) to hospitalized patients. Nurses' knowledge, attitudes, self-practice, and practice of teaching breast self-examination to patients were measured in a group who attended such a program and compared with those of a control group who did not attend. The researchers found that the instructional program increased nurses' teaching of BSE to their patients, but did not affect their own self-practice. Nurses' attitudes to teaching BSE were less favorable than for self-practice. Issues related to environments for teaching BSE are discussed.

Measurement of sialyl transferase activity and serum glycoproteins in malignant and beningn (hyperparathyroid) hypercalcemia

Serum sialyl tranferase activity (STA) and protein bound carbohydrate were measured in hypercalcemic patients with surgically documented hyperparathyroidism (n = 15) or with cancer without skeletal metastases (n = 10). Precipitable protein-bound sialic acid and hexosamine, but not neutral hexoses or fucose were significantly (P less than 0.025) increased 40% and 21% respectively, in the perchlorate treated sera of cancer patients. Measurements of some specific serum glycoproteins by radial immunodiffusion assay were also different (P less than 0.05). Mean seromucoid protein was almost twice as great in the group with cancer (P less than 0.005), but four of these values overlapped those from the patients with hyperparathyroidism. The mean STA was 21.1 (range, 9.0-46.8) activity units in the patients with the cancer and 9.2 (range 1.0-17.8) in the patients with hyperparathyroidism (P less than 0.005). Six of the patients with cancer had values above the upper limit of the group with hyperparathyroidism. A discriminant function generated from these data correctly classified all the patients with hyperparathyroidism and 70% of those with cancer. Measurements of seromucoid and STA deserve further consideration as a way to discriminate some cases of hypercalcemia.