A systematic review of articles using qualitative methods to generate questionnaire items identified in MEDLINE and PsycINFO from 2000 to 2014 was carried out. Articles were analyzed for (a) year of publication and journal domain, (b) qualitative data collection methods, (c) method of data content analysis, (d) professional experts' input in item generation, and (e) debriefing of the newly developed items. In total, 371 articles were included and results showed (a) an acceleration of published articles, (b) individual interviews and focus groups were common ways of generating items and no emergent approach was identified, (c) the content analysis was usually not described (43% of articles), (d) experts were involved in eliciting concepts in less than a third of articles, (e) 61% of articles involved a step of further submission of newly developed items to the population of interest. This review showed an insufficient reporting of qualitative methods used to generate new questionnaires despite previous recommendations.

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BackgroundAlthough most physicians in medical settings have to deliver bad news, the skills of delivering bad news to patients have been given insufficient attention. Delivering bad news is a complex communication task that includes verbal and nonverbal skills, the ability to recognize and respond to patients’ emotions and the importance of considering the patient’s environment such as culture and social status. How bad news is delivered can have consequences that may affect patients, sometimes over the long term.ObjectiveThis project aimed to develop a Web-based formative self-assessment tool for physicians to practice delivering bad news to minimize the deleterious effects of poor way of breaking bad news about a disease, whatever the disease.MethodsBReaking bAD NEws Tool (BRADNET) items were developed by reviewing existing protocols and recommendations for delivering bad news. We also examined instruments for assessing patient-physician communications and conducted semistructured interviews with patients and physicians. From this step, we selected specific themes and then pooled these themes before consensus was achieved on a good practices communication framework list. Items were then created from this list. To ensure that physicians found BRADNET acceptable, understandable, and relevant to their patients’ condition, the tool was refined by a working group of clinicians familiar with delivering bad news. The think-aloud approach was used to explore the impact of the items and messages and why and how these messages could change physicians’ relations with patients or how to deliver bad news. Finally, formative self-assessment sessions were constructed according to a double perspective of progression: a chronological progression of the disclosure of the bad news and the growing difficulty of items (difficulty concerning the expected level of self-reflection).ResultsThe good practices communication framework list comprised 70 specific issues related to breaking bad news pooled into 8 main domains: opening, preparing for the delivery of bad news, communication techniques, consultation content, attention, physician emotional management, shared decision making, and the relationship between the physician and the medical team. After constructing the items from this list, the items were extensively refined to make them more useful to the target audience, and one item was added. BRADNET contains 71 items, each including a question, response options, and a corresponding message, which were divided into 8 domains and assessed with 12 self-assessment sessions. The BRADNET Web-based platform was developed according to the cognitive load theory and the cognitive theory of multimedia learning.ConclusionsThe objective of this Web-based assessment tool was to create a “space” for reflection. It contained items leading to self-reflection and messages that introduced recommended communication behaviors. Our approach was innovative as it provided an inexpensive distance-learning self-assessment tool that was manageable and less t...