Framework analysis: A worked example from a midwifery research

Arifin, Siti Roshaidai Mohd; Cheyne, Helen; Maxwell, Margaret; Pien, Lee Siew

doi:10.1016/j.enfcli.2019.04.112

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…The recorded interviews will be transcribed verbatim and uploaded into the NVivo 12 for analyses using the framework approach [38]. The framework approach involves 3 interconnected steps that include familiarization with the transcript, deciding initial themes or categories, and summarizing or synthesizing the data [39]. For quantitative data, statistical analyses will be performed using the IBM-SPSS software for Windows (version 27; IBM Corp).…”

Section: Discussionmentioning

confidence: 99%

Developing an mHealth Intervention to Reduce COVID-19–Associated Psychological Distress Among Health Care Workers in Nigeria: Protocol for a Design and Feasibility Study

Akinsulore¹,

Aloba²,

Oginni³

et al. 2022

JMIR Res Protoc

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Background Globally, COVID-19–related psychological distress is seriously eroding health care workers’ mental health and well-being, especially in low-income countries like Nigeria. The use of mobile health (mHealth) interventions is now increasingly recognized as an innovative approach that may improve mental health and well-being. This project aims to develop an mHealth psychological intervention (mPsyI) to reduce COVID-19–related psychological distress among health care workers in Nigeria. Objective Our objective is to present a study protocol to determine the level of COVID-19–related psychological distress among health care workers in Nigeria; explore health care workers’ experience of COVID-19–related psychological distress; develop and pilot test mPsyI to reduce this distress; and assess the feasibility of this intervention (such as usability, engagement, and satisfaction). Methods A mixed (quantitative and qualitative) methods approach is used in which health care workers will be recruited from 2 tertiary health care facilities in southwest Nigeria. The study is divided into 4 phases based on the study objectives. Phase 1 involves a quantitative survey to assess the type and levels of psychosocial distress. Phase 2 collects qualitative data on psychosocial distress among health care workers. Phase 3 involves development of the mHealth-based psychological intervention, and phase 4 is a mixed methods study to assess the feasibility and acceptability of the intervention. Results This study was funded in November 2020 by the Global Effort on COVID-19 Health Research, and collection of preliminary baseline data started in July 2021. Conclusions This is the first study to report the development of an mHealth-based intervention to reduce COVID-19–related psychological distress among health care workers in Nigeria. Using a mixed methods design in this study can potentially facilitate the adaptation of an evidence-based treatment method that is culturally sensitive and cost-effective for the management of COVID-19–related psychological distress among health care workers in Nigeria. International Registered Report Identifier (IRRID) DERR1-10.2196/36174

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Section: Discussionmentioning

confidence: 99%

Developing an mHealth Intervention to Reduce COVID-19–Associated Psychological Distress Among Health Care Workers in Nigeria: Protocol for a Design and Feasibility Study

Akinsulore¹,

Aloba²,

Oginni³

et al. 2022

JMIR Res Protoc

View full text Add to dashboard Cite

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How digital transformation can influence workflows, teaching practices and curricula in (bio)process science and engineering—An interview series with stakeholders

Buyel

2024

Future in Educational Research

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A massive digital transformation is underway in biotechnology and process engineering fueled by recent advances in machine learning and so‐called artificial intelligence, especially in the large language model field (e.g., ChatGPT). Training courses and curricula will need to adapt to keep pace, but the speed of progress is such that guidelines for the implementation of a digital transformation are probably already outdated. We therefore interviewed stakeholders from the fields of didactics, biotechnology and process engineering to collect the latest perspectives on the impact of digital transformation and to solicit recommendations for the adaptation of curricula and training courses to reflect new work profiles in academia and industry. We conducted semi‐structured interviews with 17 stakeholders and used a framework analysis approach to structure and evaluate the collected information. For example, data handling was the dominant general activity affected by digital transformation, whereas multitasking was relevant to work, and the design and implementation of new didactic methods and content was linked to teaching. The interviews revealed that an increasingly diverse set of skills and competences (in addition to those in current curricula) will be expected from the next generation of biotechnologists and process engineers. This includes profound programming skills, model building abilities, as well critical data interpretation and data literacy in the widest sense. The corresponding key challenges will be a reasonable and structured disinvestment in other areas to provide slots for the new content and to secure resources for the implementation of necessary modifications.

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Framework analysis: A worked example from a midwifery research

Cited by 2 publications

References 10 publications

Developing an mHealth Intervention to Reduce COVID-19–Associated Psychological Distress Among Health Care Workers in Nigeria: Protocol for a Design and Feasibility Study

Developing an mHealth Intervention to Reduce COVID-19–Associated Psychological Distress Among Health Care Workers in Nigeria: Protocol for a Design and Feasibility Study

How digital transformation can influence workflows, teaching practices and curricula in (bio)process science and engineering—An interview series with stakeholders

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