Intervention system for psychological adaptation of families of children with epilepsy based on ADOPT mode

Abstract

This invention discloses an ADOPT-based family psychological adaptation intervention system for children with epilepsy, relating to the field of epilepsy diagnosis and treatment auxiliary technology. It includes a medical staff inquiry and explanation module, a family inquiry question collection module, a family psychological assessment module, and an intervention plan storage and adjustment module. The medical staff inquiry and explanation module is used to obtain the content that medical staff need to explain and the content they need to ask, generating medical staff explanation and inquiry data. This ADOPT-based family psychological adaptation intervention system for children with epilepsy, by setting up the medical staff inquiry and explanation module, the family inquiry question collection module, and the family psychological assessment module, can understand the guardian's problems and emotional attitudes while explaining to the guardian of the child with epilepsy, provide answers and positive guidance, promptly identify problems existing in the guardian, and adjust the intervention plan based on the problems identified in the guardian.

Description

Technical Field

[0001] This invention relates to the field of epilepsy diagnosis and treatment assistance technology, specifically to a family psychological adaptation intervention system for children with epilepsy based on the ADOPT model. Background Technology

[0002] The psychological state of families with children suffering from epilepsy is not merely an "emotional problem" or "personal feeling." It is an indispensable part of the comprehensive treatment system, directly affecting the success or failure of treatment and the quality of life of the child. Without good family psychological support, even the most perfect drug treatment plan cannot be effectively implemented. Therefore, it is necessary to intervene and guide the psychological well-being of families with children suffering from epilepsy. Summary of the Invention

[0003] The purpose of this invention is to provide a family psychological adaptation intervention system for children with epilepsy based on the ADOPT model, in order to overcome the above-mentioned shortcomings in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a family psychological adaptation intervention system for children with epilepsy based on the ADOPT model, including a medical staff inquiry and explanation module, a family inquiry question collection module, a family psychological assessment module, and an intervention plan storage and adjustment module; The medical staff inquiry and explanation module is used to obtain the content that medical staff need to explain and the content that they need to ask, and to generate medical staff explanation and inquiry data. The family inquiry and answer collection module is used to obtain the questions that the family guardians of the sick child want to ask and their answers to the medical staff's explanations and inquiries, and to generate the family inquiry and answer data of the sick child. The family psychological data assessment module is used to assess the emotional attitude of the guardians of the child's family based on the medical staff's explanation and inquiry data, the child's family's inquiry and response data, and the historical emotional attitude level assessment data, and to generate family psychological assessment data. The intervention plan storage and adjustment module is used to store standard family intervention plan data, and based on the family psychological assessment data and the intervention plan and assessment data mapping data, adjust the standard family intervention plan data of the child's family guardian to generate intervention plan adjustment data.

[0005] Furthermore, the medical staff inquiry and explanation module generates medical staff inquiry and explanation data, including the following steps: Collect data on standard explanation content that needs to be explained to the family guardians of sick children, and generate medical and nursing explanation data; the standard explanation content can include disease knowledge such as the causes of epilepsy, risk factors, epilepsy medications (such as sodium valproate, carbamazepine, phenytoin sodium, etc.), and the impact of the caregiver's psychological state on the sick child and themselves. Collect all questions asked by medical staff to the family guardians of sick children and generate a list of questions to be asked by medical staff; based on historical communication data with the family guardians of sick children, expert advice and relevant clinical experience and knowledge, compile a list of questions that may be asked and generate a list of questions to be asked by medical staff. Based on the answers from the patient's family guardians, medical staff select the data they want to ask from the medical inquiry list and generate medical inquiry data. Based on the data obtained from the questions and answers from the child's family, medical staff provide explanations and answers, generating a data set of medical staff explanation questions. Collect the aforementioned medical and nursing explanation data, medical and nursing question explanation data, and medical and nursing inquiry data to generate medical and nursing explanation and inquiry data. Each medical and nursing explanation and inquiry data can be used... Let i represent the data obtained from the i-th medical staff's explanation and inquiry. , This represents the content of the medical and nursing explanation data, medical and nursing question explanation data, or medical and nursing question data corresponding to the i-th medical and nursing explanation and question data. This indicates that the medical staff explanation and inquiry data is of type p, where p=1, 2, and 3 represent the corresponding data types of medical staff explanation and inquiry data as medical staff explanation data, medical staff question explanation data, and medical staff inquiry data, respectively.

[0006] Furthermore, the family inquiry and answer collection module generates inquiry and answer data from the child's family, including the following steps: Collect the responses of the child's family guardians to the medical staff's explanations and inquiries, and generate corresponding family response data for the child. Collect the questions asked by the family guardians of the sick children and generate family inquiry data for the sick children; The data collected includes responses from the families of the affected children and questions from their families. This data is then used to generate family question-and-answer data, which can be represented as follows: This indicates that it corresponds to the i-th medical staff explanation and inquiry data. , This represents the family's response data or family inquiry data corresponding to the i-th medical staff explanation and inquiry data. express The data types are q=1 and q=2, which represent the data of responses from the families of the sick children and the data of inquiries from the families of the sick children, respectively.

[0007] Furthermore, the generation of medical staff inquiry data includes the following steps: Using historical data on family inquiries about sick children as input and corresponding data on medical staff inquiries as output, the first deep learning model is trained to generate an automatic inquiry model. The first deep learning model is either a Transformer-based Models model, such as GPT, T5, or BART, or a Seq2Seq (Encoder-Decoder) with Attention model. The data from the patient's family's inquiries and responses is input into the automated inquiry model, which then outputs corresponding medical staff inquiry data. This process automatically selects appropriate questions to ask or prompts medical staff to ask questions based on the inquiries and responses from the patient's family guardians.

[0008] Furthermore, the family psychological data assessment module generates family psychological assessment data, including the following steps: The family psychological data assessment module is used to assess the emotional attitude of the guardians of the child's family based on the medical staff's explanation and inquiry data, the child's family's inquiry and response data, and the historical emotional attitude level assessment data, and to generate family psychological assessment data. The facial expressions of the child's family guardians are captured by a high-definition camera while listening to medical staff's explanations and answering questions from the child's family, thus generating facial expression data of the child's family. Using historical facial expression data of children with illnesses as input and corresponding emotional attitude level labels as output, a second deep learning model is trained to generate a first emotional level assessment model. The second deep learning model can be a CNN model, such as VGG, ResNet, EfficientNet, etc.; or an RNN model, such as LSTM or GRU. Before training, the facial expression data of children with illnesses' families also needs to be preprocessed, including face detection, alignment, cropping, and normalization. Among them, the family psychological assessment data corresponds one-to-one with the medical staff's explanation and inquiry data and the child's family's inquiry and response data, that is, each medical staff explanation and inquiry data and each child's family's inquiry and response data correspond to one family psychological assessment data; The facial expression data of the child's family is input into the first emotion level assessment model, which outputs the corresponding emotion and attitude level labels to generate family psychological assessment data.

[0009] Furthermore, the family psychological data assessment module generates family psychological assessment data, which also includes the following steps: The voice data of the family guardians during the questioning and answering of the child's family is collected by the recording device to generate the child's family voice data. Using historical family audio data of sick children as input and corresponding emotional attitude level labels as output, a third deep learning model is trained to generate a second emotional level assessment model. During model training, the audio waveforms in the historical family audio data of sick children can be converted into spectrograms first, and then an appropriate deep learning model, such as Mel-Spectrogram, VGG, ResNet, DenseNet, CRNN, RNN (LSTM or GRU), Transformer, etc., can be selected for training as needed. The voice data of the child's family is input into the second emotion level assessment model, and the corresponding emotion and attitude level labels are output to generate family psychological assessment data. The family psychological assessment data corresponds one-to-one with the medical staff's explanation and inquiry data and the child's family's inquiry and answer data. That is, each medical staff explanation and inquiry data and each child's family inquiry and answer data corresponds to one family psychological assessment data.

[0010] Furthermore, the family psychological data assessment module generates family psychological assessment data, which also includes the following steps: Using historical data on family inquiries about sick children as input and corresponding emotional attitude level labels as output, a fourth deep learning model is trained to generate a third emotional level assessment model. During model training, an appropriate deep learning model can be selected as needed, such as using pre-trained word vectors like Word2Vec, GloVe, or FastText to map each word in the text to a dense vector, and then training an RNN / LSTM / GRU / CNN to obtain the third emotional level assessment model. Input all the family inquiry and response data generated in this stage of assessment into the third emotion level assessment model, output the corresponding emotion and attitude level labels, and generate family psychological assessment data. Among them, the family psychological assessment data is the overall emotion and attitude level label of this stage of assessment.

[0011] Furthermore, the intervention plan storage and adjustment module generates intervention plan adjustment data, including the following steps: Collect standard family intervention plan steps corresponding to each of the medical staff's explanation and inquiry data and the child's family's inquiry and response data; Data on the adjustment steps of each standard family intervention plan were collected at each emotional attitude level label corresponding to the family psychological assessment data. Based on the emotional attitude level labels corresponding to the family psychological assessment data, the corresponding intervention plan adjustment step data is selected to adjust the standard family intervention plan step data, generating the adjusted standard family intervention plan step data. Collect the adjusted steps of the standard family intervention plan, arrange them in the order of steps, and generate intervention plan adjustment data.

[0012] In one embodiment, if there is a one-to-one correspondence between family psychological assessment data, medical staff explanation and inquiry data, and the child's family inquiry and response data, then the emotional attitude level label corresponding to the average of all family psychological assessment data corresponding to a standard family intervention plan step data, rounded to the nearest whole number, is used as the family psychological assessment data for that standard family intervention plan step data. Then, the standard family intervention plan step data is selected and adjusted according to the family intervention plan adjustment step data corresponding to the corresponding emotional attitude level label to generate the adjusted standard family intervention plan step data.

[0013] If the family psychological assessment data is the overall emotional attitude level label for this stage of assessment, then for each standard family intervention plan step data, the family intervention plan adjustment step data corresponding to the output emotional attitude level label is selected and adjusted to generate the standard family intervention plan adjusted step data.

[0014] Furthermore, it also includes a comparison module, which is used to compare the emotional state of the same child's family at each stage of the assessment and the child's treatment effect data, and the emotional state of different children's families at the same stage of the assessment and the child's treatment effect data.

[0015] 1. Compared with the prior art, the family psychological adaptation intervention system for children with epilepsy based on the ADOPT model provided by the present invention, by setting up a medical staff inquiry and explanation module, a family inquiry question collection module, and a family psychological assessment module, can understand the guardian's problems and emotional attitudes while explaining to the family guardian of the child with epilepsy, and provide answers and positive guidance.

[0016] 2. Compared with the prior art, the ADOPT-based family psychological adaptation intervention system for children with epilepsy provided by this invention, through the intervention plan storage and adjustment module, realizes the identification of problems of the guardian based on the different answers and emotional attitudes of the family guardian of the child with epilepsy to different questions, as well as the guardian's inquiry. Based on the problems of the guardian, the intervention plan is adjusted to make the intervention plan more suitable for the guardian and more conducive to the treatment and maintenance of a good condition of the child with epilepsy. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a system structure block diagram provided for an embodiment of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0020] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0021] Exemplary embodiments will be described more fully below with reference to the accompanying drawings; however, these exemplary embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will enable those skilled in the art to fully understand the scope of this disclosure.

[0022] Where there is no conflict, the various embodiments of this disclosure and the features thereof in the embodiments may be combined with each other.

[0023] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0024] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded.

[0025] The embodiments described herein can be described with reference to plan views and / or cross-sectional views using the ideal schematic diagrams of this disclosure. Therefore, the example illustrations can be modified according to manufacturing techniques and / or tolerances. Therefore, the embodiments are not limited to those shown in the drawings, but include modifications to configurations formed based on manufacturing processes. Therefore, the areas illustrated in the drawings are schematic in nature, and the shapes of the areas shown in the figures illustrate specific shapes of areas of an element, but are not intended to be limiting.

[0026] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art.

[0027] Please see Figure 1 The ADOPT-based family psychological adaptation intervention system for children with epilepsy includes modules for medical staff inquiry and explanation, family inquiry question collection, family psychological assessment, and intervention plan storage and adjustment.

[0028] The medical staff inquiry and explanation module is used to obtain the content that medical staff need to explain and the content they need to ask, and to generate medical staff inquiry and explanation data, including the following steps: (1) Collect standard explanation content data that needs to be explained to the family guardians of the sick children and generate medical and nursing explanation data; among which the standard explanation content can be knowledge of diseases such as epilepsy onset, risk factors, epilepsy drugs (such as sodium valproate, carbamazepine, phenytoin sodium, etc.), and the impact of the caregiver's psychological state on the sick children and themselves. (2) Collect all questions asked by medical staff to the family guardians of the child and generate a list of questions to be asked by medical staff; Based on historical communication data with the family guardians of the child, expert advice and relevant clinical experience and knowledge, compile a list of questions that may be asked and generate a list of questions to be asked by medical staff. (3) Based on the patient's family guardian's answers to the questions, medical staff select the data they want to ask from the medical inquiry checklist to generate medical inquiry data, which includes the following steps: a. Using historical patient family inquiry and response data as input and corresponding medical staff inquiry data as output, train the first deep learning model to generate an automatic inquiry model; wherein, the first deep learning model is selected as a Transformer-based Models model, such as GPT, T5 or BART, or a Seq2Seq (Encoder-Decoder) with Attention model. b. Input the patient's family's inquiry and answer data into the automatic inquiry model, and output the corresponding medical staff inquiry data. Through the above process, the system can automatically select corresponding questions to ask or remind medical staff to ask questions based on the questions and answers from the patient's family guardians.

[0029] (4) Medical staff provide answers and explanations based on the data from the child's family's inquiry, generating data on medical staff's question explanations; (5) Collect medical and nursing explanation data, medical and nursing problem explanation data, and medical and nursing inquiry data to generate medical and nursing explanation and inquiry data. Each medical and nursing explanation and inquiry data can be used... Let i represent the data obtained from the i-th medical staff's explanation and inquiry. , This represents the content of the medical and nursing explanation data, medical and nursing question explanation data, or medical and nursing question data corresponding to the i-th medical and nursing explanation and question data. This indicates that the medical staff explanation and inquiry data is of type p, where p=1, 2, and 3 represent the corresponding data types of medical staff explanation and inquiry data as medical staff explanation data, medical staff question explanation data, and medical staff inquiry data, respectively.

[0030] In one embodiment, during the explanation and inquiry, the team member in charge can conduct an in-depth assessment of the parents' attitude tendencies in caring for the child, guiding them towards an optimistic direction and instructing the parents of the child with epilepsy to maintain positive emotions and a pleasant mood while caring for the child. If negative emotional tendencies are found during the conversation, the source of the negative emotions can be understood, and parents with experience in caring for children with epilepsy can share their experiences. The bedside nurse can introduce successful cases to help establish a positive care attitude, or encourage caregivers to recall their previous successful experiences in caring for other family members to increase their sense of value and accomplishment.

[0031] The family inquiry and answer collection module is used to obtain the questions that the child's family guardians want to ask and their answers to the medical staff's explanations and inquiries, generating the child's family inquiry and answer data, including the following steps: (1) Collect the answers of the child’s family guardians to the medical staff’s explanation and inquiry data, and generate the corresponding family answer data; (2) Collect the content of the questions asked by the guardians of the child's family and generate the family inquiry data of the child; (3) Collect the answer data and inquiry data from the families of the sick children to generate the family inquiry and answer data, wherein the family inquiry and answer data can be represented as follows: This indicates that it corresponds to the i-th medical staff explanation and inquiry data. , This represents the family's response data or family inquiry data corresponding to the i-th medical staff explanation and inquiry data. express The data types are q=1 and q=2, which represent the data of responses from the families of the sick children and the data of inquiries from the families of the sick children, respectively.

[0032] In one embodiment, the child's family caregiver (such as parents) can use open-ended questions to identify the most urgent or pressing care issues (including the child's diet, medication, and monitoring of their condition). They can then express their concerns about the child's physical and mental well-being through open communication, and be guided to take slow, steady, deep breaths, pause briefly after inhaling, and then exhale slowly and steadily, paying attention to the rhythm and speed of relaxation. Progressive muscle relaxation is then employed, tensing and relaxing different muscle groups from head to toe in sequence. For example, first furrowing the brow, then relaxing; clenching the teeth, then relaxing. The same process is then performed on the neck, shoulders, arms, chest, abdomen, and legs, experiencing the different states of muscle tension and relaxation to achieve a sense of physical and mental relief. Music therapy can also be added, selecting soothing and gentle music; the child can create a list of their problems and ask themselves how they feel when thinking about these persistent issues; medical staff and experts can encourage and guide the child's family caregiver during this emotional catharsis process.

[0033] The family psychological data assessment module is used to assess the emotional attitudes of the child's guardians based on medical staff explanation and inquiry data, the child's family's inquiry and response data, and historical emotional attitude level assessment data, generating family psychological assessment data. This includes the following steps: (1) Use a high-definition camera to collect facial images of the child’s family guardians while listening to the medical staff’s explanations and asking questions, and while answering questions from the child’s family, to generate facial expression data of the child’s family; (2) Using historical facial expression data of children with illnesses as input and corresponding emotional attitude level labels as output, train a second deep learning model to generate a first emotional level assessment model. The second deep learning model can be a CNN model, such as VGG, ResNet, EfficientNet, etc.; or an RNN model, such as LSTM or GRU. Before training, the facial expression data of children with illnesses needs to be preprocessed, including face detection, alignment, cropping and normalization, etc. Among them, the family psychological assessment data corresponds one-to-one with the medical staff's explanation and inquiry data and the child's family's inquiry and response data, that is, each medical staff explanation and inquiry data and each child's family's inquiry and response data correspond to one family psychological assessment data; (3) Input the facial expression data of the child’s family into the first emotion level assessment model, output the corresponding emotion and attitude level labels, and generate family psychological assessment data.

[0034] Furthermore, the family psychological data assessment module generates family psychological assessment data, which also includes the following steps: (1) Collect the voice data of the family guardian when answering questions about the child’s family using a recording device, and generate the child’s family voice data; (2) Using historical family audio data of sick children as input and corresponding emotional attitude level labels as output, train the third deep learning model to generate the second emotional level assessment model; when training the model, the audio waveforms in the historical family audio data of sick children can be converted into spectrograms first, and then a suitable deep learning model can be selected as needed, such as Mel-Spectrogram, VGG, ResNet, DenseNet, CRNN, RNN (LSTM or GRU), Transformer, etc. for training; (3) Input the voice data of the patient’s family into the second emotion level assessment model, output the corresponding emotion and attitude level label, and generate family psychological assessment data. The family psychological assessment data corresponds one-to-one with the medical staff’s explanation and inquiry data and the patient’s family’s inquiry and answer data. That is, each medical staff explanation and inquiry data and each patient’s family’s inquiry and answer data corresponds to a family psychological assessment data.

[0035] Furthermore, the family psychological data assessment module generates family psychological assessment data, which also includes the following steps: (1) Using historical data of family questions and answers of sick children as input and corresponding emotional attitude level labels as output, train the fourth deep learning model to generate the third emotional level assessment model; when training the model, you can choose a suitable deep learning model as needed, such as using pre-trained word vectors such as Word2Vec, GloVe or FastText to map each word in the text into a dense vector, and then train RNN / LSTM / GRU / CNN to obtain the third emotional level assessment model; (2) Input all the family inquiry and answer data generated in this stage of assessment into the third emotion level assessment model, output the corresponding emotion and attitude level labels, and generate family psychological assessment data, wherein the family psychological assessment data is the overall emotion and attitude level label of this stage of assessment.

[0036] The intervention plan storage and adjustment module stores standard family intervention plan data and, based on family psychological assessment data and the mapping data between intervention plans and assessment data, adjusts the standard family intervention plan data for the child's family guardians to generate intervention plan adjustment data, including the following steps: (1) Collect standard family intervention plan steps data corresponding to the medical staff's explanation and inquiry data and the children's family's inquiry and response data; (2) Collect data on the adjustment steps of the family intervention plan for each standard family intervention plan at each emotional attitude level label of the corresponding family psychological assessment data; (3) Based on the emotional attitude level labels corresponding to the family psychological assessment data, select the corresponding intervention plan adjustment step data to adjust the standard family intervention plan step data, and generate the standard family intervention plan adjusted step data; (4) Collect the step data of the standard family intervention plan after adjustment, and arrange them in the order of the steps to generate intervention plan adjustment data.

[0037] If the family psychological assessment data corresponds one-to-one with the medical staff's explanation and inquiry data and the child's family's inquiry and response data, then the emotional attitude level label corresponding to the average of all family psychological assessment data corresponding to a standard family intervention plan step data, rounded to the nearest whole number, is used as the family psychological assessment data for that standard family intervention plan step data. Then, this standard family intervention plan step data is selected and adjusted according to the corresponding emotional attitude level label in the family intervention plan adjustment step data to generate the adjusted standard family intervention plan step data.

[0038] If the family psychological assessment data is the overall emotional attitude level label for this stage of assessment, then for each standard family intervention plan step data, the family intervention plan adjustment step data corresponding to the output emotional attitude level label is selected and adjusted to generate the standard family intervention plan adjusted step data.

[0039] In one embodiment, the intervention program may include the following steps: Assess care attitude (A): ① Establish a bond of trust: Identify the parents as the primary caregivers for the child with epilepsy, communicate with them, and establish a good relationship of trust.

[0040] ② In-depth understanding of parental care attitudes: The research team used a division of labor to write articles explaining to parents the causes of epilepsy, risk factors, and epilepsy medications (such as sodium valproate, carbamazepine, phenytoin sodium, etc.). They also explained the impact of caregivers' psychological state on the child and themselves. The research team understood the tendencies and levels of care attitudes shown by parents in various aspects such as daily care, disease management, psychological support, and companionship in growth.

[0041] ③ Cultivating a positive attitude: During each communication session, the team member in charge will conduct an in-depth assessment of the parents' attitude tendencies in the process of caring for the child, guiding them towards an optimistic direction, and instructing the parents of the child with epilepsy to maintain a positive and cheerful mood while caring for the child. If negative emotional tendencies are found during the conversation, the source of the negative emotions will be understood, and parents with experience in caring for children with epilepsy will be invited to share their experiences. The bedside nurse will introduce successful cases to help establish a positive care attitude, or the caregiver will be encouraged to recall their previous successful experiences in caring for other family members to increase their sense of value and accomplishment.

[0042] Identify care problems and create a problem list (D): ① Accurately identify key issues: Ask open-ended questions to determine the most urgent or desired care issues (including diet, medication, and monitoring of the condition of children with epilepsy). ② Build a list of questions and explore your emotions: Make a list of your questions and ask yourself how you feel when you think about these questions. ③ Emotional catharsis and ability recognition: Encourage self-expression during the emotional catharsis process, while also recognizing one's own caregiving abilities, which is beneficial for setting goals in the next step.

[0043] ④ Mental and Physical Relaxation Guidance: Address the current mental and physical issues by talking about them, and guide the patient to take slow, steady, deep breaths, pausing briefly after inhaling, and then exhaling slowly and steadily, paying attention to the rhythm and speed of relaxation. Perform progressive muscle relaxation, tightening and relaxing each muscle group from head to toe in sequence. For example, first furrow your brow, then relax; clench your teeth, then relax. Next, perform the same operation on the neck, shoulders, arms, chest, abdomen, and legs, experiencing the different states of muscle tension and relaxation to achieve a mental and physical relaxation effect. Music therapy can also be added, choosing soothing and gentle music.

[0044] Set care goals (O): Based on the problem, with caregivers taking the lead and nursing staff playing a supporting role, formulate the current care goals (short-term goals) that you hope to achieve. ①Goal 1: Within one week, understand the effects and possible side effects of the epilepsy medication and comorbidity medications taken by the child, and be able to guide the child to take the medication correctly as prescribed by the doctor.

[0045] ② Objective 2: How to easily and comfortably cope with the daily life of caring for sick children.

[0046] ③ Goal 3: Reduce the frequency of epileptic seizures in children.

[0047] ④ Goal 4: Guide parents to correctly identify epileptic seizures and handle them in emergencies.

[0048] ⑤ Goal 5: After the child is discharged from the hospital, encourage the child to change unhealthy lifestyle habits at home. Acknowledge the positive role of the parents in the child's home care and provide them with comfort so that they can face the illness correctly.

[0049] Second session (the day before discharge): 40 minutes per person.

[0050] Develop a care plan (P): Work with parents to choose a suitable option and develop a detailed care plan. ① Monitoring and recording of the condition: Instruct parents to observe the symptoms of epileptic seizures, such as the type of seizure, duration, and frequency of seizures, and record them in detail.

[0051] ② Medication Management: Train parents to understand the name, dosage, timing, and method of administration of the antiepileptic drugs their child is taking. Emphasize the importance of taking medication on time and in the correct dosage, establish a medication schedule, and set reminders. Inform them of common adverse drug reactions and how to deal with them, and to communicate with the doctor immediately if any abnormalities occur.

[0052] ③ Safety Care: Instruct parents to remove items that could cause injury to the child, such as sharp objects and slippery carpets. Install protective facilities such as handrails and non-slip mats in areas such as bathrooms and stairwells. Develop an emergency response plan for seizures, such as maintaining the child's airway and preventing injury, and conduct simulation drills.

[0053] ④ Diet and Nutrition: Based on the child's condition and the doctor's advice, a personalized dietary plan will be developed, such as controlling carbohydrate intake and increasing foods rich in vitamins and minerals. Foods and drinks that may trigger seizures should be avoided, such as caffeinated beverages and spicy foods.

[0054] ⑤ Psychological support: Guide parents to pay attention to the child's psychological state, learn psychological counseling methods, and assist parents in helping the child develop good psychological qualities, which is beneficial to the physical and mental health of both parents.

[0055] ⑥ Regular follow-up visits and communication: Develop a follow-up visit plan, remind parents to bring their child to the hospital for follow-up visits on time, and bring the records so that the doctor can understand the changes in the condition.

[0056] ⑦ Establish a "Friends of Caregivers" WeChat group, inviting parents of children with epilepsy to join, thereby building a close communication bridge between medical staff and patients. Parents can seek help through the WeChat group when encountering difficulties in the care process, with professional medical staff providing guidance within the group. Simultaneously, the group encourages experience sharing and emotional support among parents. Team members will push authoritative epilepsy knowledge, cutting-edge treatment information, and practical home care tips monthly. Relevant information should be promptly pushed whenever parents of children with epilepsy join the group.

[0057] Implementation Plan (T): ① Implement the plan according to the established plan, and check and evaluate the implementation status after the plan is completed to see if the established goals have been achieved.

[0058] ② For parents who have had good results, continue to choose new care issues according to their needs.

[0059] ③ For parents whose care is not effective, a joint assessment should be conducted to determine whether the goal is too high or whether the patient's condition has worsened and the desired outcome cannot be achieved. If so, caregivers should assist in lowering the care goals or adjusting the care plan to continue implementation.

[0060] ④ Ask parents open-ended questions about what they learned in the process of solving caregiving problems. This encourages meaningful coping mechanisms after caregiving, guides caregivers to review the entire caregiving process, summarize successful caregiving experiences and insights, and share them in the "Friends of Caregivers" WeChat group, thereby increasing their own and other parents' confidence in caregiving.

[0061] ⑤ Guide parents of children with epilepsy to review the entire care process, help them summarize solutions to problems, and share their experiences and provide references in WeChat groups for other parents.

[0062] Follow-up visits 3-6 (post-discharge follow-up): Follow-up visits 4 times a month after discharge, once a week, each time for 10-20 minutes.

[0063] Within one month of discharge, four follow-up visits should be conducted via WeChat, telephone (telephone follow-up can be used for those who do not receive a response from WeChat follow-up), or face-to-face (when accompanying the patient back to the hospital for a follow-up visit).

[0064] After discharge, psychological adaptation intervention for the children's parents continued according to the ADOPT model. This involved asking about the most pressing caregiving issues they wanted to address or improve, setting achievable goals based on the problems encountered at home, and encouraging parents to express their feelings about home care, thereby releasing negative emotions. Feedback was provided via phone and WeChat to understand any issues parents faced regarding medication, nursing care, and first aid during home care. Parents were guided on how to obtain disease knowledge at home through medical staff, community health information boards, WeChat, Baidu Encyclopedia, and hospital or community health lectures.

[0065] The system also includes a comparison module, which is used to compare the emotional state of the same child's family at each stage of the assessment and the child's treatment effect data, and to compare the emotional state of different children's families at the same stage of the assessment and the child's treatment effect data.

[0066] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A family-based psychological adaptation intervention system for children with epilepsy based on the ADOPT model, characterized in that, It includes modules for explaining medical and nursing inquiries, collecting family questions, assessing family psychology, and storing and adjusting intervention plans. The medical staff inquiry and explanation module is used to obtain the content that medical staff need to explain and the content that they need to ask, and to generate medical staff explanation and inquiry data. The family inquiry and answer collection module is used to obtain the questions that the family guardians of the sick child want to ask and their answers to the medical staff's explanations and inquiries, and to generate the family inquiry and answer data of the sick child. The family psychological data assessment module is used to assess the emotional attitude of the guardians of the child's family based on the medical staff's explanation and inquiry data, the child's family's inquiry and response data, and the historical emotional attitude level assessment data, and to generate family psychological assessment data. The intervention plan storage and adjustment module is used to store standard family intervention plan data, and based on the family psychological assessment data and the intervention plan and assessment data mapping data, adjust the standard family intervention plan data of the child's family guardian to generate intervention plan adjustment data.

2. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to claim 1, characterized in that, The medical staff inquiry and explanation module generates medical staff inquiry and explanation data, including the following steps: Collect data on the standard explanation content that needs to be explained to the family guardians of sick children, and generate medical and nursing explanation data; Collect all questions asked by medical staff to the family guardians of sick children, and generate a list of questions asked by medical staff. Based on the answers from the patient's family guardians, medical staff select the data they want to ask from the medical inquiry list and generate medical inquiry data. Based on the data obtained from the questions and answers from the child's family, medical staff provide explanations and answers, generating a data set of medical staff explanation questions. Collect the medical and nursing explanation data, medical and nursing question explanation data, and medical and nursing inquiry data to generate medical and nursing explanation and inquiry data.

3. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to claim 1, characterized in that, The family inquiry and answer collection module generates inquiry and answer data from the child's family, including the following steps: Collect the responses of the child's family guardians to the medical staff's explanations and inquiries, and generate corresponding family response data for the child. Collect the questions asked by the family guardians of the sick children and generate family inquiry data for the sick children; The data collected from the responses and inquiries of the families of the affected children were used to generate family inquiry and response data.

4. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to claim 2, characterized in that, The generation of medical staff inquiry data includes the following steps: Using historical data on family inquiries about sick children as input and corresponding data on medical staff inquiries as output, the first deep learning model is trained to generate an automatic inquiry model. The data from the patient's family's questions and answers is input into the automatic questioning model, which outputs the corresponding medical and nursing questioning data.

5. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to claim 1, characterized in that, The family psychological data assessment module generates family psychological assessment data, including the following steps: The facial expressions of the child's family guardians are captured by a high-definition camera while listening to medical staff's explanations and answering questions from the child's family, thus generating facial expression data of the child's family. Using historical facial expression data of children with illnesses as input and corresponding emotional attitude level labels as output, a second deep learning model is trained to generate a first emotional level assessment model. The facial expression data of the child's family is input into the first emotion level assessment model, which outputs the corresponding emotion and attitude level labels to generate family psychological assessment data.

6. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to claim 1, characterized in that, The family psychological data assessment module generates family psychological assessment data, and also includes the following steps: The voice data of the family guardians during the questioning and answering of the child's family is collected by the recording device to generate the child's family voice data. Using historical family voice data of sick children as input and corresponding emotional attitude level labels as output, a third deep learning model is trained to generate a second emotional level assessment model. The family audio data of the child is input into the second emotion level assessment model, which outputs the corresponding emotion and attitude level labels to generate family psychological assessment data.

7. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to claim 1, characterized in that, The family psychological data assessment module generates family psychological assessment data, and also includes the following steps: Using historical data on family inquiries about sick children as input and corresponding emotional attitude level labels as output, a fourth deep learning model is trained to generate a third emotional level assessment model. Input all the family inquiry and response data generated in this stage of the assessment into the third emotion level assessment model, output the corresponding emotion and attitude level labels, and generate family psychological assessment data.

8. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to any one of claims 5-7, characterized in that, The intervention plan storage and adjustment module generates intervention plan adjustment data, including the following steps: Collect standard family intervention plan steps corresponding to each of the medical staff's explanation and inquiry data and the child's family's inquiry and response data; Data on the adjustment steps of each standard family intervention plan were collected at each emotional attitude level label corresponding to the family psychological assessment data. Based on the emotional attitude level labels corresponding to the family psychological assessment data, the corresponding intervention plan adjustment step data is selected to adjust the standard family intervention plan step data, generating the adjusted standard family intervention plan step data. Collect the adjusted steps of the standard family intervention plan, arrange them in the order of steps, and generate intervention plan adjustment data.

9. The family psychological adaptation intervention system for children with epilepsy based on the ADOPT model according to claim 1, characterized in that, It also includes a comparison module, which is used to compare the emotional state of the same child's family at each stage of the assessment and the child's treatment effect data, and the emotional state of different children's families at the same stage of the assessment and the child's treatment effect data.

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