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  • 文章类型: Journal Article
    OpenAI对ChatGPT的引入引起了极大的关注。在其能力中,释义突出。
    本研究旨在调查该聊天机器人产生的释义文本中剽窃的令人满意的水平。
    向ChatGPT提交了三个不同长度的文本。然后指示ChatGPT使用五个不同的提示来解释所提供的文本。在研究的后续阶段,案文分为不同的段落,ChatGPT被要求单独解释每个段落。最后,在第三阶段,ChatGPT被要求解释它以前生成的文本。
    ChatGPT生成的文本中的平均抄袭率为45%(SD10%)。ChatGPT在提供的文本中表现出抄袭的大幅减少(平均差异-0.51,95%CI-0.54至-0.48;P<.001)。此外,当将第二次尝试与初始尝试进行比较时,抄袭率显着下降(平均差-0.06,95%CI-0.08至-0.03;P<.001)。文本中的段落数量表明与抄袭的百分比有值得注意的关联,由单个段落组成的文本表现出最低的抄袭率(P<.001)。
    尽管ChatGPT显著减少了文本中的抄袭,现有的抄袭水平仍然相对较高。这突显了研究人员在将这种聊天机器人纳入他们的工作时的关键谨慎。
    UNASSIGNED: The introduction of ChatGPT by OpenAI has garnered significant attention. Among its capabilities, paraphrasing stands out.
    UNASSIGNED: This study aims to investigate the satisfactory levels of plagiarism in the paraphrased text produced by this chatbot.
    UNASSIGNED: Three texts of varying lengths were presented to ChatGPT. ChatGPT was then instructed to paraphrase the provided texts using five different prompts. In the subsequent stage of the study, the texts were divided into separate paragraphs, and ChatGPT was requested to paraphrase each paragraph individually. Lastly, in the third stage, ChatGPT was asked to paraphrase the texts it had previously generated.
    UNASSIGNED: The average plagiarism rate in the texts generated by ChatGPT was 45% (SD 10%). ChatGPT exhibited a substantial reduction in plagiarism for the provided texts (mean difference -0.51, 95% CI -0.54 to -0.48; P<.001). Furthermore, when comparing the second attempt with the initial attempt, a significant decrease in the plagiarism rate was observed (mean difference -0.06, 95% CI -0.08 to -0.03; P<.001). The number of paragraphs in the texts demonstrated a noteworthy association with the percentage of plagiarism, with texts consisting of a single paragraph exhibiting the lowest plagiarism rate (P<.001).
    UNASSIGNED: Although ChatGPT demonstrates a notable reduction of plagiarism within texts, the existing levels of plagiarism remain relatively high. This underscores a crucial caution for researchers when incorporating this chatbot into their work.
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  • 文章类型: Journal Article
    新发布的SegmentAnythingModel(SAM)是图像处理中使用的一种流行工具,由于其优越的分割精度,各种输入提示,培训能力,高效的模型设计。然而,它当前的模型是在不适合医学图像的不同数据集上训练的,特别是超声图像。超声图像往往有很多噪声,使得难以分割出重要的结构。在这个项目中,我们开发了ClickSAM,它使用超声图像的单击提示来微调“段任意模型”。ClickSAM有两个训练阶段:第一个阶段是在以真实轮廓为中心的单击提示上进行训练,第二阶段的重点是通过额外的正面和负面点击提示来提高模型性能。通过将第一阶段的预测与地面真相面具进行比较,真积极,假阳性,并计算假阴性段。使用真阳性和假阴性段生成阳性点击,和否定点击使用假阳性段生成。然后采用中心Voronoi细分算法在每个段中收集用于在第二阶段训练期间增强模型性能的正面和负面点击提示。使用单击训练方法,与其他现有的超声图像分割模型相比,ClickSAM具有出色的性能。
    The newly released Segment Anything Model (SAM) is a popular tool used in image processing due to its superior segmentation accuracy, variety of input prompts, training capabilities, and efficient model design. However, its current model is trained on a diverse dataset not tailored to medical images, particularly ultrasound images. Ultrasound images tend to have a lot of noise, making it difficult to segment out important structures. In this project, we developed ClickSAM, which fine-tunes the Segment Anything Model using click prompts for ultrasound images. ClickSAM has two stages of training: the first stage is trained on single-click prompts centered in the ground-truth contours, and the second stage focuses on improving the model performance through additional positive and negative click prompts. By comparing the first stage\'s predictions to the ground-truth masks, true positive, false positive, and false negative segments are calculated. Positive clicks are generated using the true positive and false negative segments, and negative clicks are generated using the false positive segments. The Centroidal Voronoi Tessellation algorithm is then employed to collect positive and negative click prompts in each segment that are used to enhance the model performance during the second stage of training. With click-train methods, ClickSAM exhibits superior performance compared to other existing models for ultrasound image segmentation.
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  • 文章类型: Randomized Controlled Trial
    准确评估个人的饮食对于管理个人营养和研究饮食对健康的影响至关重要。尽管它很重要,可用于饮食评估的工具要么过于不精确,贵,或繁重的临床或研究使用。基于图像的方法为提高饮食评估的可靠性和可及性提供了潜在的新工具。虽然很有希望,基于图像的方法对粘附敏感,因为图像无法从已经消耗的食物中捕获。可以通过经由文本消息的适当定时的提示来改善对基于图像的方法的坚持。
    本研究旨在定量检查提示时间对坚持基于图像的饮食记录的影响,并定性地探索参与者的饮食评估体验,以便为设计新颖的基于图像的饮食评估工具提供信息。
    这项研究使用了随机交叉设计,以检查3种提示设置对基于图像的饮食记录中捕获的图像数量的个体内影响。提示设置是控制,没有发送提示;标准,提示是在上午7:15发送的,11:15AM,为每位参与者提供5:15PM;并量身定制,及时的时间安排是为每个参与者的习惯性用餐时间量身定做的。参与者在基线时完成了基于文本的饮食记录,以确定定制提示的时间。参与者被随机分配到6个研究序列中的1个,每个都有3个提示设置的唯一顺序,每个3天的基于图像的饮食记录由至少7天的清除期分开。定性部分包括半结构化访谈和问卷调查,探索饮食评估的经验。
    共招募了37人,和30名参与者(11名男性,19名女性;平均年龄30岁,标准差10.8岁),完成所有基于图像的饮食记录。与对照相比,标准设置中的图像速率每天增加0.83个图像(P=.23),与对照相比,定制设置中的图像速率每天增加1.78个图像(P≤.001)。我们发现13/21(62%)的参与者更喜欢使用基于图像的饮食记录,而不是基于文本的饮食记录,但报告了每种方法的特定方法挑战。特别是在用餐后无法通过图像记录。
    定制提示可提高对基于图像的饮食评估的依从性。未来基于图像的饮食评估工具应使用量身定制的提示,并提供基于图像和书面输入选项,以提高记录的完整性。
    UNASSIGNED: Accurately assessing an individual\'s diet is vital in the management of personal nutrition and in the study of the effect of diet on health. Despite its importance, the tools available for dietary assessment remain either too imprecise, expensive, or burdensome for clinical or research use. Image-based methods offer a potential new tool to improve the reliability and accessibility of dietary assessment. Though promising, image-based methods are sensitive to adherence, as images cannot be captured from meals that have already been consumed. Adherence to image-based methods may be improved with appropriately timed prompting via text message.
    UNASSIGNED: This study aimed to quantitatively examine the effect of prompt timing on adherence to an image-based dietary record and qualitatively explore the participant experience of dietary assessment in order to inform the design of a novel image-based dietary assessment tool.
    UNASSIGNED: This study used a randomized crossover design to examine the intraindividual effect of 3 prompt settings on the number of images captured in an image-based dietary record. The prompt settings were control, where no prompts were sent; standard, where prompts were sent at 7:15 AM, 11:15 AM, and 5:15 PM for every participant; and tailored, where prompt timing was tailored to habitual meal times for each participant. Participants completed a text-based dietary record at baseline to determine the timing of tailored prompts. Participants were randomized to 1 of 6 study sequences, each with a unique order of the 3 prompt settings, with each 3-day image-based dietary record separated by a washout period of at least 7 days. The qualitative component comprised semistructured interviews and questionnaires exploring the experience of dietary assessment.
    UNASSIGNED: A total of 37 people were recruited, and 30 participants (11 male, 19 female; mean age 30, SD 10.8 years), completed all image-based dietary records. The image rate increased by 0.83 images per day in the standard setting compared to control (P=.23) and increased by 1.78 images per day in the tailored setting compared to control (P≤.001). We found that 13/21 (62%) of participants preferred to use the image-based dietary record versus the text-based dietary record but reported method-specific challenges with each method, particularly the inability to record via an image after a meal had been consumed.
    UNASSIGNED: Tailored prompting improves adherence to image-based dietary assessment. Future image-based dietary assessment tools should use tailored prompting and offer both image-based and written input options to improve record completeness.
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  • 文章类型: Journal Article
    背景:大型语言模型(LLM)在自然语言处理(NLP)中显示出非凡的能力,特别是在标记数据稀缺或昂贵的领域,例如临床领域。然而,为了解开隐藏在这些LLM中的临床知识,我们需要设计有效的提示,引导他们在没有任何任务特定训练数据的情况下执行特定的临床NLP任务.这被称为上下文学习,这是一门艺术和科学,需要了解不同LLM的优势和劣势,并迅速采用工程方法。
    目的:本研究的目的是评估各种即时工程技术的有效性,包括2个新引入的类型-启发式和合奏提示,使用预训练的语言模型进行零射和少射临床信息提取。
    方法:这项全面的实验研究评估了不同的提示类型(简单的前缀,简单的完形填空,思想链,预期,启发式,和合奏)跨越5个临床NLP任务:临床意义消歧,生物医学证据提取,共同参照决议,药物状态提取,和药物属性提取。使用3种最先进的语言模型评估了这些提示的性能:GPT-3.5(OpenAI),双子座(谷歌),和LLaMA-2(Meta)。该研究将零射与少射提示进行了对比,并探讨了合奏方法的有效性。
    结果:研究表明,针对特定任务的提示定制对于LLM在零射临床NLP中的高性能至关重要。在临床意义上的消歧,GPT-3.5在启发式提示下达到0.96的准确性,在生物医学证据提取中达到0.94的准确性。启发式提示,伴随着一连串的思想提示,跨任务非常有效。在复杂的场景中,很少有机会提示提高性能,和集合方法利用了多种即时优势。GPT-3.5在任务和提示类型上的表现始终优于Gemini和LLaMA-2。
    结论:本研究对即时工程方法进行了严格的评估,并介绍了临床信息提取的创新技术,证明了临床领域上下文学习的潜力。这些发现为未来基于提示的临床NLP研究提供了明确的指导方针。促进非NLP专家参与临床NLP进步。据我们所知,这是在这个生成人工智能时代,对临床NLP的不同提示工程方法进行实证评估的首批作品之一,我们希望它能激励和指导未来在这一领域的研究。
    BACKGROUND: Large language models (LLMs) have shown remarkable capabilities in natural language processing (NLP), especially in domains where labeled data are scarce or expensive, such as the clinical domain. However, to unlock the clinical knowledge hidden in these LLMs, we need to design effective prompts that can guide them to perform specific clinical NLP tasks without any task-specific training data. This is known as in-context learning, which is an art and science that requires understanding the strengths and weaknesses of different LLMs and prompt engineering approaches.
    OBJECTIVE: The objective of this study is to assess the effectiveness of various prompt engineering techniques, including 2 newly introduced types-heuristic and ensemble prompts, for zero-shot and few-shot clinical information extraction using pretrained language models.
    METHODS: This comprehensive experimental study evaluated different prompt types (simple prefix, simple cloze, chain of thought, anticipatory, heuristic, and ensemble) across 5 clinical NLP tasks: clinical sense disambiguation, biomedical evidence extraction, coreference resolution, medication status extraction, and medication attribute extraction. The performance of these prompts was assessed using 3 state-of-the-art language models: GPT-3.5 (OpenAI), Gemini (Google), and LLaMA-2 (Meta). The study contrasted zero-shot with few-shot prompting and explored the effectiveness of ensemble approaches.
    RESULTS: The study revealed that task-specific prompt tailoring is vital for the high performance of LLMs for zero-shot clinical NLP. In clinical sense disambiguation, GPT-3.5 achieved an accuracy of 0.96 with heuristic prompts and 0.94 in biomedical evidence extraction. Heuristic prompts, alongside chain of thought prompts, were highly effective across tasks. Few-shot prompting improved performance in complex scenarios, and ensemble approaches capitalized on multiple prompt strengths. GPT-3.5 consistently outperformed Gemini and LLaMA-2 across tasks and prompt types.
    CONCLUSIONS: This study provides a rigorous evaluation of prompt engineering methodologies and introduces innovative techniques for clinical information extraction, demonstrating the potential of in-context learning in the clinical domain. These findings offer clear guidelines for future prompt-based clinical NLP research, facilitating engagement by non-NLP experts in clinical NLP advancements. To the best of our knowledge, this is one of the first works on the empirical evaluation of different prompt engineering approaches for clinical NLP in this era of generative artificial intelligence, and we hope that it will inspire and inform future research in this area.
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  • 文章类型: Randomized Controlled Trial
    背景:学校食堂是影响青少年营养的推荐设置,因为它们可以改善学生的食物选择。在线午餐订购系统(“在线食堂”)被越来越多地使用,并代表了有吸引力的基础设施,以实施选择架构干预措施,推动用户选择更健康的食物。最近的一项整群随机对照试验证明了选择架构干预措施的短期有效性(2个月的随访),以增加高中生从网上食堂购买的食物的健康状况。然而,很少有证据表明,针对青少年食品购买的选择架构干预措施具有长期有效性,特别是那些在线交付。
    目的:本研究旨在在15个月的随访中确定嵌入在高中在线食堂基础设施中的多策略选择架构干预的长期有效性。
    方法:对新南威尔士州的1331名学生(来自9所高中)进行了一项整群随机对照试验,澳大利亚。学校被随机分配接受自动选择架构干预(包括菜单标签,定位,反馈,和提示策略)或控制(标准在线订购)。根据新南威尔士州健康食堂的策略,购买的食物被分类为“每天,\"\"偶尔,“或”不应出售。“主要结果是每天的平均比例,\"\"偶尔,“和”不应该出售每个学生购买的物品。次要结果是平均能量,饱和脂肪,糖,和购买的钠含量。使用在线食堂收集的常规数据评估结果。
    结果:从基线到15个月的随访,平均而言,干预组的学生订购的“日常”项目明显更多(+11.5%,95%CI7.3%至15.6%;P<.001),和明显更少的“偶尔”(-5.4%,95%CI-9.4%至-1.5%;P=0.007)和“不应出售”项目(-6%,95%CI-9.1%至-2.9%;P<.001),相对于控制。随着时间的推移,平均能量没有组间差异,饱和脂肪,糖,或午餐订单的钠含量。
    结论:鉴于其长期有效性,通过在线食堂提供的选择架构干预措施可能是政策制定者支持高中生健康饮食的一个有希望的选择。
    背景:澳大利亚临床试验ACTRN12620001338954,https://anzctr.org。au/Trial/Registration/TrialReview.aspx?id=380546;开放科学框架osf.io/h8zfr,https://osf.io/h8zfr/.
    BACKGROUND: School canteens are a recommended setting to influence adolescent nutrition due to their scope to improve student food choices. Online lunch ordering systems (\"online canteens\") are increasingly used and represent attractive infrastructure to implement choice architecture interventions that nudge users toward healthier food choices. A recent cluster randomized controlled trial demonstrated the short-term effectiveness (2-month follow-up) of a choice architecture intervention to increase the healthiness of foods purchased by high school students from online canteens. However, there is little evidence regarding the long-term effectiveness of choice architecture interventions targeting adolescent food purchases, particularly those delivered online.
    OBJECTIVE: This study aimed to determine the long-term effectiveness of a multi-strategy choice architecture intervention embedded within online canteen infrastructure in high schools at a 15-month follow-up.
    METHODS: A cluster randomized controlled trial was undertaken with 1331 students (from 9 high schools) in New South Wales, Australia. Schools were randomized to receive the automated choice architecture intervention (including menu labeling, positioning, feedback, and prompting strategies) or the control (standard online ordering). The foods purchased were classified according to the New South Wales Healthy Canteen strategy as either \"everyday,\" \"occasional,\" or \"should not be sold.\" Primary outcomes were the average proportion of \"everyday,\" \"occasional,\" and \"should not be sold\" items purchased per student. Secondary outcomes were the mean energy, saturated fat, sugar, and sodium content of purchases. Outcomes were assessed using routine data collected by the online canteen.
    RESULTS: From baseline to 15-month follow-up, on average, students in the intervention group ordered significantly more \"everyday\" items (+11.5%, 95% CI 7.3% to 15.6%; P<.001), and significantly fewer \"occasional\" (-5.4%, 95% CI -9.4% to -1.5%; P=.007) and \"should not be sold\" items (-6%, 95% CI -9.1% to -2.9%; P<.001), relative to controls. There were no between-group differences over time in the mean energy, saturated fat, sugar, or sodium content of lunch orders.
    CONCLUSIONS: Given their longer-term effectiveness, choice architecture interventions delivered via online canteens may represent a promising option for policy makers to support healthy eating among high school students.
    BACKGROUND: Australian Clinical Trials ACTRN12620001338954, https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380546 ; Open Science Framework osf.io/h8zfr, https://osf.io/h8zfr/.
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  • 文章类型: Clinical Trial
    背景:鉴于标牌,消息传递,广告(广告)是许多自杀预防干预措施的门户,重要的是,我们要了解哪种类型的消息最适合谁。
    目的:我们调查了明确提及自杀是否会增加使用互联网广告的参与度,方法是调查使用不同类别关键词搜索的广告活动的参与度,这可能反映了不同的认知状态。
    方法:我们在澳大利亚进行了一项双臂研究,有或没有带有明确自杀措辞的广告。我们分析了低风险(苦恼但不是明确自杀)的明确和非明确广告活动的参与度是否存在差异,高风险(明确自杀),和寻求自杀关键字的帮助。
    结果:我们的分析表明,使用明确的措辞会产生相反的效果,取决于所使用的搜索词:明确的措辞降低了搜索低风险关键词的个体的参与度,但增加了使用高风险关键词的个体的参与度.
    结论:研究结果表明,意识到自己自杀倾向的个体对明确使用“自杀”一词的活动反应更好。“我们发现,搜索低风险关键词的人也会对明确的广告做出回应,建议一些有自杀倾向的人搜索低风险的关键词。
    BACKGROUND: Given that signage, messaging, and advertisements (ads) are the gateway to many interventions in suicide prevention, it is important that we understand what type of messaging works best for whom.
    OBJECTIVE: We investigated whether explicitly mentioning suicide increases engagement using internet ads by investigating engagement with campaigns with different categories of keywords searched, which may reflect different cognitive states.
    METHODS: We ran a 2-arm study Australia-wide, with or without ads featuring explicit suicide wording. We analyzed whether there were differences in engagement for campaigns with explicit and nonexplicit ads for low-risk (distressed but not explicitly suicidal), high-risk (explicitly suicidal), and help-seeking for suicide keywords.
    RESULTS: Our analyses revealed that having explicit wording has opposite effects, depending on the search terms used: explicit wording reduced the engagement rate for individuals searching for low-risk keywords but increased engagement for those using high-risk keywords.
    CONCLUSIONS: The findings suggest that individuals who are aware of their suicidality respond better to campaigns that explicitly use the word \"suicide.\" We found that individuals who search for low-risk keywords also respond to explicit ads, suggesting that some individuals who are experiencing suicidality search for low-risk keywords.
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  • 文章类型: Journal Article
    新出现的证据表明,决策点信息可能是促进健康食品选择的有效途径。以前的研究表明,整体营养质量有所改善,以及消费不足的食物类别的增加,比如水果和蔬菜,和公众健康关注的营养消耗不足,比如膳食纤维.然而,有多种方法用于传递决策点消息,包括非常简短的信息,提醒个人在选择时要考虑健康,以及提供有关健康益处的教育信息的稍长的消息。虽然这两种方法都显示出对成果的积极影响,没有信息有效性的比较证据。在这项研究中,我们研究了4条信息对两种营养属性的影响,这些营养属性是在有大量(n=33)早餐谷类食物的两轮信息早餐前和后早餐谷类食物选择练习中选择的。数据是通过对从多产消费者小组招募的美国成年居民进行的在线调查收集的。其中三个消息是简单的提醒消息(品尝,健康,纤维),而另外还有一个更长的纤维聚焦信息,详细说明了纤维的健康益处。研究结果表明,简单的信息胜过较长的教育信息,尽管在一般健康和纤维信息之间存在一些权衡。简单的以膳食纤维为重点的信息导致选择的谷物中的膳食纤维含量明显高于任何其他信息条件,而一般的健康信息并没有导致比简单的纤维信息更高的营养质量指标。研究结果表明,更简单的信息可能更有效地提高食物选择的营养质量。此外,关注特定营养素的信息导致这些营养素含量的显著增加。
    Emerging evidence suggests that point-of-decision messages may be an effective way to promote healthy food choices. Previous studies show improvements in overall nutritional quality, as well as increases in underconsumed food categories, such as fruits and vegetables, and underconsumed nutrients of public health concern, like dietary fiber. However, there have been multiple approaches used for delivering point-of-decision messages, including very brief messages that remind individuals to consider health during choice, as well as longer messages providing educational information about health benefits. While both approaches have demonstrated positive impacts on outcomes, there is no comparative evidence of the messages\' effectiveness. In this study, we examine the impact of four messages on two nutritional attributes of cereals selected in a two-round pre- and post-message breakfast cereal choice exercise with numerous (n = 33) breakfast cereals available. Data were collected via an online survey of adult US residents recruited from the Prolific consumer panel. Three of the messages were simple reminder messages (taste, health, fiber), while there was additionally a longer fiber-focused messaging detailing the health benefits of fiber. Findings show that the simple messages outperformed the longer educational message, though there were some trade-offs between general health and fiber messages. The simple dietary fiber-focused message resulted in significantly higher dietary fiber content in cereals chosen than in any other messaging condition, while the general health message did not result in significantly higher measures of nutritional quality than the simple fiber message. The results of the study suggest that simpler messages may be more effective at increasing the nutritional quality of food choices. Additionally, messages focused on specific nutrients lead to significantly greater increases in the content of those nutrients.
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  • 文章类型: Journal Article
    背景:在邻国梅毒爆发的背景下,在新南威尔士州的土著社区控制健康服务(ACCHS)实施了多方面的系统变更,以增加对15至29岁的年轻土著人口的性传播感染(STIs)检测,澳大利亚。这些组件包括电子病历提示和自动病理测试集,以增加年度常规健康评估中的STI测试,认证护士和土著卫生从业人员独立进行性传播感染测试,由医生预先签署的病理申请表,并改进了数据报告。
    目的:我们旨在确定系统的变化是否在2019年4月至2020年3月期间增加了将性传播感染检测纳入临床医生的常规健康评估,将梅毒检测纳入性传播感染检测,和STI测试总体吸收。我们还探讨了对员工对系统变更的可接受性和正常化的因素的理解。
    方法:我们使用混合方法设计来评估2019年实施的系统变更的有效性和可接受性。我们计算了包括衣原体检测在内的健康评估的年度比例,淋病,还有梅毒,以及内部控制(血糖水平)。我们在系统变更之前24个月和之后12个月对季度比例进行了中断的时间序列分析,并使用归一化过程理论对ACCHS员工进行了深入的半结构化访谈。
    结果:在2461名患者中,包括任何性传播感染检测在内的健康评估的年度比例从研究期间第一年的16%(38/237)增加到系统变更实施后的42.9%(94/219).当系统发生变化时,立即出现大幅增加(系数=0.22;P=.003),此后12个月没有下降。男性个体的增幅更大,内部控制没有变化。定性数据表明,与电子提示和快捷方式相比,由护士和土著保健医生主导的测试和预先指定的病理表格更难规范化。访谈发现,工作人员理解这些修改鼓励围绕性保健在日常实践中的作用进行文化变革。
    结论:这项研究首次提供了证据,证明以电子方式优化健康评估是一种有效且可接受的策略,可以增加和维持参加ACCHS的年轻原住民的临床医生整合和STI测试的完整性。未来的战略应侧重于增加对健康评估的吸收,并促进整个服务的参与和问责制。
    BACKGROUND: In the context of a syphilis outbreak in neighboring states, a multifaceted systems change to increase testing for sexually transmitted infections (STIs) among young Aboriginal people aged 15 to 29 years was implemented at an Aboriginal Community Controlled Health Service (ACCHS) in New South Wales, Australia. The components included electronic medical record prompts and automated pathology test sets to increase STI testing in annual routine health assessments, the credentialing of nurses and Aboriginal health practitioners to conduct STI tests independently, pathology request forms presigned by a physician, and improved data reporting.
    OBJECTIVE: We aimed to determine whether the systems change increased the integration of STI testing into routine health assessments by clinicians between April 2019 and March 2020, the inclusion of syphilis tests in STI testing, and STI testing uptake overall. We also explored the understandings of factors contributing to the acceptability and normalization of the systems change among staff.
    METHODS: We used a mixed methods design to evaluate the effectiveness and acceptability of the systems change implemented in 2019. We calculated the annual proportion of health assessments that included tests for chlamydia, gonorrhea, and syphilis, as well as an internal control (blood glucose level). We conducted an interrupted time series analysis of quarterly proportions 24 months before and 12 months after the systems change and in-depth semistructured interviews with ACCHS staff using normalization process theory.
    RESULTS: Among 2461 patients, the annual proportion of health assessments that included any STI test increased from 16% (38/237) in the first year of the study period to 42.9% (94/219) after the implementation of the systems change. There was an immediate and large increase when the systems change occurred (coefficient=0.22; P=.003) with no decline for 12 months thereafter. The increase was greater for male individuals, with no change for the internal control. Qualitative data indicated that nurse- and Aboriginal health practitioner-led testing and presigned pathology forms proved more difficult to normalize than electronic prompts and shortcuts. The interviews identified that staff understood the modifications to have encouraged cultural change around the role of sexual health care in routine practice.
    CONCLUSIONS: This study provides evidence for the first time that optimizing health assessments electronically is an effective and acceptable strategy to increase and sustain clinician integration and the completeness of STI testing among young Aboriginal people attending an ACCHS. Future strategies should focus on increasing the uptake of health assessments and promote whole-of-service engagement and accountability.
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  • 文章类型: Randomized Controlled Trial
    背景:数字干预很容易允许捕获参与者参与的数据。如果未来的干预旨在更具互动性,量身定做,或提供给用户的有用资源,检查这些数据可能是有价值的。最近在一项随机对照试验中测试的数字酒精干预中可用的一个模块为参与者提供了自我编写提示的机会,这些提示在他们选择的时候通过短信发送给他们。因此,本研究旨在评估这些自我创作的提示,以增加有关个人如何协商行为改变的知识,并评估将来是否可以改善干预内容。
    方法:使用内容和主题分析的组合对自我撰写的提示进行了定性评估。所确定的主题和子类别使用匿名报价来举例说明,并计算每个识别主题在提示中被编码的频率。基线特征与编写提示的几率之间的关联,以及每个主题中的提示,使用逻辑回归进行调查。
    结果:确定了五个主题(鼓励风格,意识水平,提醒减少/退出的原因,减少/退出的策略,和时间刻度),都有几个子类别。提示模块更有可能被女性和老年人使用,以及那些认为减少饮酒很重要的人,或者谁觉得他们有这样做的诀窍。与延迟使用4个月的参与者(对照组)相比,立即使用支持工具(干预组)的参与者提出提示的可能性(OR=2.36;关联概率>99%)是两倍以上。
    结论:参与提示模块的个人显示了以积极方式使用支持工具中提供的信息的证据,有几个人展示了目标设定和计划来改变他们的饮酒行为。个人也利用这个机会提醒自己,他们想要改变饮酒的个人和具体原因,以及鼓励自己这样做。
    Digital interventions readily permit data capture of participant engagement with them. If future interventions are intended to be more interactive, tailored, or a useful resource offered to users, it may be valuable to examine such data. One module available in a digital alcohol intervention recently tested in a randomised control trial offered participants the opportunity to self-author prompts that were sent to them by a text message at a time of their choosing. This study thus aimed to evaluate these self-authored prompts to increase knowledge on how individuals negotiate behaviour change and assess whether intervention content can be improved in the future.
    The self-authored prompts were evaluated qualitatively using a combination of content and thematic analysis. The identified themes and subcategories are exemplified using anonymized quotes, and the frequency that each identified theme was coded for among the prompts was calculated. Associations between baseline characteristics and the odds of authoring a prompt at all, as well as a prompt within each theme, were investigated using logistic regression.
    Five themes were identified (Encouragement Style, Level of Awareness, Reminders of reasons to reduce/quit, Strategies to reduce/quit, and Timescale), all with several subcategories. The prompts module was more likely to be used by women and older individuals, as well as those for whom reducing alcohol consumption was perceived as important, or who felt they had the know-how to do so. Participants who had immediate access to the support tool (intervention group) were more than twice as likely to author a prompt (OR = 2.36; probability of association > 99%) compared to those with 4-month delayed access (control group).
    Individuals who engaged with the prompts module showed evidence of using the information provided in the support tool in an active way, with several showing goal setting and making plans to change their drinking behaviour. Individuals also used this opportunity to remind themselves of personal and specific reasons they wanted to change their drinking, as well as to encourage themselves to do so.
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  • 文章类型: Journal Article
    提示工程是一个相对较新的研究领域,指的是设计实践,精炼,并实现指导大型语言模型(LLM)输出的提示或指令,以帮助执行各种任务。随着LLM的出现,最受欢迎的是ChatGPT,它在短短两个月内吸引了超过1亿用户的关注,人工智能(AI)尤其是生成AI,已经为大众所接受。这是前所未有的范式转变,不仅因为人工智能的使用变得越来越普遍,而且还因为LLM在医疗保健中可能产生的影响。随着越来越多的患者和医疗专业人员使用基于AI的工具,LLM是该团体中最受欢迎的代表,解决提高这项技能的挑战似乎是不可避免的。本文总结了提示工程的研究现状,同时,旨在为广泛的医疗保健专业人员提供实用建议,以改善他们与LLM的互动。
    Prompt engineering is a relatively new field of research that refers to the practice of designing, refining, and implementing prompts or instructions that guide the output of large language models (LLMs) to help in various tasks. With the emergence of LLMs, the most popular one being ChatGPT that has attracted the attention of over a 100 million users in only 2 months, artificial intelligence (AI), especially generative AI, has become accessible for the masses. This is an unprecedented paradigm shift not only because of the use of AI becoming more widespread but also due to the possible implications of LLMs in health care. As more patients and medical professionals use AI-based tools, LLMs being the most popular representatives of that group, it seems inevitable to address the challenge to improve this skill. This paper summarizes the current state of research about prompt engineering and, at the same time, aims at providing practical recommendations for the wide range of health care professionals to improve their interactions with LLMs.
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