An online training system for protective skills based on an IMB model

Abstract

The present application relates to the technical field of health protection training, and particularly relates to an online training system for protection skills based on an IMB model.The present application comprises a training demand acquisition module, an IMB model core training module, an examination and evaluation module and a course optimization module.The IMB model core training module is composed of an information intervention submodule, a motivation intervention submodule and a behavior skill intervention submodule.The examination and evaluation module is used to quantize training results through theoretical examination and PPE putting on and taking off practical operation examination.The course optimization module optimizes training courses based on the training results of the examination and evaluation module and the training results of the IMB model core training module.The present application aims to provide an online training system for protection skills based on an IMB model to solve the problem of limited training effect of the existing training system.

Description

Technical Field

[0001] This invention relates to the field of health protection training technology, and in particular to an online training system for protection skills based on the IMB model. Background Technology

[0002] In recent years, the expansion of human activity, changes in living environments, and rapid mutation of microorganisms have led to a continuous emergence of new infectious diseases. Global infectious disease outbreaks are frequent, widespread, and rapidly spreading. This new situation places higher demands on healthcare capabilities, requiring the rapid establishment of makeshift hospitals and the isolation of sources of infection. Healthcare services face challenges such as high demands for timely treatment, a complex population of those in need, rapid pathogen mutation, and significant difficulties in multi-departmental coordination. The protective capabilities of healthcare personnel are a prerequisite for carrying out medical rescue work. However, domestic and international experience shows that improper use of PPE is a major cause of infection among medical personnel.

[0003] However, existing protective skills training has many shortcomings: 1. The training format is monotonous, mostly using face-to-face lectures or video presentations, lacking systematicity and interactivity; 2. The training lacks specificity, and the uniform training is conducted without differentiation in level or specialty, which fails to meet the differentiated needs of health personnel in hospitals and grassroots units. 3. The assessment is difficult to quantify. The practical assessment of PPE donning and doffing relies heavily on subjective human scoring, which cannot accurately detect the contamination during the doffing process, resulting in insufficient objectivity of the assessment results.

[0004] Therefore, designing an online training system for protection skills based on the IMB model that can solve the above-mentioned technical problems is a technical issue that needs to be addressed. Summary of the Invention

[0005] To address the aforementioned problems, the present invention aims to provide an online training system for protective skills based on the IMB model, thereby resolving the issue of limited training effectiveness in existing training systems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: the solution includes a training needs collection module, an IMB model core training module, an assessment module, and a course optimization module; The core training module of the IMB model consists of an information intervention submodule, a motivation intervention submodule, and a behavioral skills intervention submodule. The assessment module is used to quantify training results through theoretical assessment and practical assessment of PPE donning and doffing. The course optimization module generates training courses based on the training results from the assessment module and the training results from the IMB model core training module.

[0007] Furthermore, the information intervention submodule employs knowledge graph structured coding technology to construct a hierarchical knowledge database containing infectious disease prevention theories, PPE usage guidelines, hand hygiene standards, and infection control requirements. Based on a knowledge gap-based targeted push algorithm, it matches trainees with corresponding online teaching materials, learning documents, and after-class exercises. Simultaneously, based on a BERT semantic matching automatic Q&A model, it enables real-time online answers to prevention knowledge questions and the summarization of common questions.

[0008] Furthermore, the motivation intervention submodule employs a risk level matching algorithm to push corresponding infectious disease infection case warnings based on the exposure risk of personnel in their positions; through a linkage model, it binds individual training progress and assessment results with group safety scores to strengthen occupational protection responsibility and team safety collaboration awareness; at the same time, it sets up a training progress visualization interface to improve trainees' willingness to protect themselves and their training compliance.

[0009] Furthermore, the behavioral skills intervention submodule employs PPE operation action timing coding technology to break down the PPE donning and doffing process into multiple standard action nodes, and includes step-by-step practical videos of donning and doffing, comparison demonstrations of incorrect actions, and slow-motion analysis of key steps. Through a statistical model of the frequency of incorrect actions, it identifies the high-frequency error-prone steps of trainees.

[0010] Furthermore, the practical assessment of PPE donning and doffing in the assessment module adopts the fluorescent marking method. Through the ultraviolet image contamination point identification algorithm, it automatically detects and counts the number of key contaminated parts on the trainee's skin and inner clothing after PPE removal. Combined with the operation process time sequence scoring model, the compliance and duration of each action node are quantitatively scored, and finally a comprehensive practical score is generated through weighted calculation.

[0011] Furthermore, the training needs collection module is used to generate a structured electronic questionnaire that includes gaps in theoretical knowledge, shortcomings in practical skills, preferences for training formats, and characteristics of job scenarios. It collects data from trainees and removes invalid data by verifying the duration of their answers and filtering out duplicate IP addresses, and outputs training needs analysis results.

[0012] The present invention has the following beneficial effects: 1-This invention constructs a structured protection knowledge database through an information intervention submodule and enables precise delivery; it stimulates trainees' proactive protection intentions from three levels: personal safety, professional responsibility, and team collaboration through a motivation intervention submodule; and it comprehensively improves training effectiveness through standardized action breakdown and targeted reinforcement training through a behavioral skills intervention submodule.

[0013] 2- The practical assessment of PPE donning and doffing in this invention uses a fluorescent marking method combined with an ultraviolet image contamination point identification algorithm to automatically detect and count the number of key contaminated areas on the trainee's skin and inner clothing after PPE removal. At the same time, it combines an operation process time sequence scoring model to quantify and score the compliance and duration of each action node, thereby achieving objectivity and standardization of the practical assessment and accurately evaluating the trainee's protective operation level. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the present invention. Detailed Implementation

[0015] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments: See Figure 1 As shown, the solution includes a training needs assessment module, an IMB model core training module, an assessment module, and a course optimization module. The core training module of the IMB model consists of an information intervention submodule, a motivation intervention submodule, and a behavioral skills intervention submodule. The assessment module is used to quantify training results through theoretical assessment and practical assessment of PPE donning and doffing. The course optimization module generates training courses based on the training results from the assessment module and the training results from the IMB model core training module.

[0016] Furthermore, the information intervention submodule employs knowledge graph structured coding technology to construct a hierarchical knowledge database containing infectious disease prevention theories, PPE usage guidelines, hand hygiene standards, and infection control requirements. Specifically, the hierarchical protection knowledge database includes first-level nodes such as infectious disease prevention theories, PPE usage guidelines, hand hygiene standards, and infection control requirements; second-level nodes, such as PPE usage guidelines, which are further divided into PPE selection, donning procedures, doffing procedures, and disposal procedures; and third-level nodes, such as doffing procedures, which are further divided into specific steps for glove removal, protective clothing removal, and goggle removal.

[0017] Based on a knowledge gap-based targeted recommendation algorithm, online teaching materials, learning documents, and after-class exercises are matched to trainees. For example, for trainees with weak knowledge of the "PPE removal process", detailed explanation videos and special practice questions of the removal process are given priority.

[0018] Simultaneously, an automatic Q&A model based on BERT semantic matching enables real-time online answers to protection-related questions and the summarization of common questions. This model is pre-trained using a corpus of over 100,000 protection-related Q&A entries for fine-tuning. Trainees can submit protection-related questions online, and the model automatically matches the optimal answer and responds in real time. The system periodically summarizes frequently asked common questions, generates a Q&A knowledge base, and pushes it to all trainees.

[0019] Furthermore, the motivation intervention submodule employs a risk level matching algorithm to push corresponding infectious disease infection case warnings based on the exposure risk of personnel in their positions; through a linkage model, it binds individual training progress and assessment results with group safety scores to strengthen occupational protection responsibility and team safety collaboration awareness; at the same time, it sets up a training progress visualization interface to improve trainees' willingness to protect themselves and their training compliance.

[0020] Furthermore, the behavioral skills intervention submodule employs PPE operation action timing coding technology to break down the PPE donning and doffing process into multiple standard action nodes. Specifically, the PPE donning and doffing process is broken down into 28 standard action nodes, including 14 nodes for donning and 14 nodes for doffing, and each node is assigned a unique timing code and operation standard. It includes step-by-step practical videos of donning and doffing, comparative demonstrations of incorrect actions, and slow-motion analysis of key steps. Through a statistical model of the frequency of incorrect actions, it identifies frequently made mistakes by trainees.

[0021] Furthermore, the practical assessment of PPE donning and doffing in the assessment module adopts the fluorescent marking method. Through the ultraviolet image contamination point identification algorithm, it automatically detects and counts the number of key contaminated parts on the trainee's skin and inner clothing after PPE removal. Combined with the operation process time sequence scoring model, the compliance and duration of each action node are quantitatively scored, and finally a comprehensive practical score is generated through weighted calculation.

[0022] Furthermore, the training needs collection module generates a structured electronic questionnaire that includes theoretical knowledge gaps, practical skills deficiencies, training format preferences, and job scenario characteristics. It collects participant data and removes invalid data through answer time verification and duplicate IP filtering, outputting training needs analysis results. Specifically, the Analytic Hierarchy Process (AHP) is first used to assign questionnaire weights to four core dimensions: theoretical knowledge gaps (weight 0.35), practical skills deficiencies (weight 0.4), training format preferences (weight 0.15), and job scenario characteristics (weight 0.1), generating a structured electronic questionnaire. The electronic questionnaire is then sent to target trainees (such as hospital clinical medical staff and primary healthcare workers) to collect basic participant data. After collection, a multi-dimensional invalid data verification algorithm automatically filters questionnaires: setting an answer time threshold of 5-30 minutes to remove questionnaires with answer times less than 5 minutes or greater than 30 minutes; removing questionnaires submitted repeatedly from the same IP address through IP address verification; and removing questionnaires with contradictory answers through logical consistency verification. The K-means clustering algorithm was used to classify the needs of the valid questionnaire data, and the trainees were divided into three categories: "theoretical weak", "practical weak", and "comprehensive weak". A report analyzing common and differentiated needs was generated.

[0023] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0024] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0025] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0026] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0027] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An online training system for protection skills based on the IMB model, characterized in that: It includes a training needs assessment module, an IMB model core training module, an assessment module, and a course optimization module; The core training module of the IMB model consists of an information intervention submodule, a motivation intervention submodule, and a behavioral skills intervention submodule. The assessment module is used to quantify training results through theoretical assessment and practical assessment of PPE donning and doffing. The course optimization module generates training courses based on the training results from the assessment module and the training results from the IMB model core training module.

2. The online training system for protection skills based on the IMB model according to claim 1, characterized in that: The information intervention submodule employs knowledge graph structured coding technology to construct a hierarchical knowledge database containing infectious disease prevention theories, PPE usage guidelines, hand hygiene standards, and infection control requirements. Based on a knowledge gap-based targeted push algorithm, it matches trainees with corresponding online teaching materials, learning documents, and after-class exercises. Simultaneously, based on a BERT semantic matching automatic Q&A model, it enables real-time online answers to protection knowledge questions and the summarization of common questions.

3. The online training system for protection skills based on the IMB model according to claim 1, characterized in that: The motivation intervention submodule uses a risk level matching algorithm to push corresponding infectious disease infection case warnings based on the exposure risk of personnel in their positions. Through a linkage model, it binds individual training progress and assessment results with group safety scores to strengthen occupational protection responsibility and team safety collaboration awareness. At the same time, it sets up a training progress visualization interface to improve trainees' willingness to protect themselves and their training compliance.

4. The online training system for protection skills based on the IMB model according to claim 1, characterized in that: The behavioral skills intervention submodule uses PPE operation action timing coding technology to break down the PPE donning and doffing process into multiple standard action nodes, and includes step-by-step practical videos of donning and doffing, comparison demonstrations of incorrect actions, and slow-motion analysis of key links. Through a statistical model of the frequency of incorrect actions, it identifies the high-frequency error-prone steps of trainees.

5. The online training system for protection skills based on the IMB model according to claim 1, characterized in that: The practical assessment of PPE donning and doffing in the assessment module adopts the fluorescent marking method and uses an ultraviolet image contamination point identification algorithm to automatically detect and count the number of key contaminated parts on the skin and inner clothing of trainees after PPE removal. By combining the operation process timing scoring model, the compliance and duration of each action node are quantitatively scored, and finally a comprehensive practical score is generated through weighted calculation.

6. The online training system for protection skills based on the IMB model according to claim 1, characterized in that: The training needs collection module is used to generate a structured electronic questionnaire that includes gaps in theoretical knowledge, deficiencies in practical skills, preferences for training formats, and characteristics of job scenarios. It collects data from trainees and removes invalid data by verifying the duration of their answers and filtering out duplicate IP addresses, and outputs training needs analysis results.

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