This article describes the development of the social network-based intervention which aims to improve diabetes self-management (DSM) among patients with type 2 diabetes living in socioeconomically deprived neighborhoods by stimulating social support for DSM and diminishing social influences hindering DSM (e.g., peer pressure and social norms). The intervention was specifically developed for patients with Dutch, Turkish, Moroccan, and Surinamese backgrounds. The intervention was developed according to Intervention Mapping. This article describes the first four steps of Intervention Mapping: (1) the needs assessment; (2) development of performance and change objectives; (3) selection of theory-based methods and strategies; and (4) the translation of these into an organized program. These four steps resulted in , a 10-month group-based intervention consisting of 24 meetings, 6 meetings for significant others, and 2 meetings for participants and their spouses. The IM method resulted in a tailored approach with a specific focus on the social networks of its participants. This article concludes that the IM method helped our planning team to tailor the intervention to the needs of our target population and facilitated our evaluation design. However, in hindsight, the intervention could have been improved by investing more in participatory planning and community involvement.
Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain-computer interface (BCI) to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise targeting of implanted electrodes. Here we describe the presurgical imaging procedures used to generate functional maps of the hand area of the somatosensory cortex and subsequent planning that guided the implantation of intracortical microelectrode arrays.
Background: The lymphatic system is the major route of cancer metastasis, and sentinel lymph nodes (SLNs) are the first station for the spread of cancer cells. Accurate identification of SLNs by tracers during surgery is crucial for SLN biopsy and lymphadenectomy. However, conventional monomodal tracers such as blue dyes and carbon nanoparticles often induce a misjudgment of SLNs and thus are still unsatisfying for clinical applications.
Department of Otolaryngology Head and Neck Surgery, the 6th Medical Center of Chinese PLA General Hospital, Chinese PLA Medical School, Beijing, 100853, China.
Objective: To make an overview of global research trends in the etiology of auditory neuropathy (AN) over the past 30 years using a bibliometric approach.
Methods: Bibliometric analyses were conducted by GraphPad Prism 9.0, Citespace 6.
Introduction: Laryngeal cancer diagnosis relies on specialist examinations, but non-invasive methods using voice data are emerging with artificial intelligence (AI) advancements. Mel Frequency Cepstral Coefficients (MFCCs) are widely used for voice analysis, but Octave Frequency Spectrum Energy (OFSE) may offer better accuracy in detecting subtle voice changes.
Problem Statement: Accurate early diagnosis of laryngeal cancer through voice data is challenging with current methods like MFCC.
Background: Theta burst stimulation (TBS) has garnered widespread attention in the scientific community, but a comprehensive bibliometric analysis of TBS research remains absent. This study aims to fill this gap by elucidating the characteristics, hotspots, and trends in TBS publications over the past 20 years using bibliometric methods.
Methods: We retrieved TBS-related publications from January 1, 2004, to December 31, 2023, from the Web of Science Core Collection (WoSCC).
