The ethical attributes of a Muslim radiographer: An integrative review based on the Qur'an, Sunnah and contemporary radiography literature

Abstract

Radiography is a healthcare profession in which technical competence, patient-centred care, professional judgement, and radiation protection are inseparable. Radiographers are entrusted with patient communication, positioning, image acquisition, confidentiality, exposure control, radiation justification, optimisation, and safe use of imaging modalities. Although contemporary radiography practice is guided by professional standards on patient safety, communication, confidentiality, competence and radiation protection, limited attention has been given to how Qur’anic and Prophetic ethical principles can shape the professional identity and daily conduct of Muslim radiographers. This integrative review synthesises Islamic normative texts, professional standards and guidelines, and contemporary radiography literature to identify the ethical attributes of a Muslim radiographer and align them with radiographic practice. The review identifies ten ethical attributes which are amanah (trustworthiness), ihsan (excellence), hifz al-nafs (preservation of life), justice, protection of dignity and privacy, compassion, truthfulness, knowledge and competence, patience and sincerity. These attributes align closely with contemporary radiography ethics, particularly beneficence, non-maleficence, justice, autonomy, privacy, confidentiality, competence, accountability, justification, optimisation, and dose management. The study concludes that Islamic ethics does not replace professional radiography standards; rather, it provides a moral and spiritual foundation through which Muslim radiographers may internalise professional duties as ethical responsibilities. Future research should focus on evaluating the impact of Qur’an-Sunnah-based ethics education on radiographic practice, developing validated Islamic ethical assessment tools, and exploring patient perspectives alongside ethical responses to artificial intelligence in medical imaging.