Orthopedic NursingNCT07688499
A Practical Exploration of Developing a Full-English Orthopedic Nursing Curriculum Based on DeepSeek Intelligence
A study testing Based on the all-English courses of DeepSeek in people with Orthopedic Nursing and Education, Nursing, run by The Fourth Affiliated Hospital of Zhejiang University School of Medicine.
Trial summary
This educational reform study aims to explore whether a full English course built on the DeepSeek artificial intelligence platform can improve orthopedic nurses' professional English competence. It will also examine nurses' satisfaction with AI-assisted teaching. Read more about this study
- Who is it for?
- Ages 20 to 40 yearsHealthy volunteers can take part
- Conditions the study is for
- Orthopedic Nursing, Education, Nursing, Artificial Intelligence
- What is being tested?
- Based on the all-English courses of DeepSeek
- Type of treatment
- Pill or oral medicine
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 20 participants
- Where
- No sites listed yet
- Study dates
- 1 Jul 2026to 1 Jul 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 40 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- ① On-duty nurses in the orthopedics department ② Obtained the nurse professional qualification certificate ③ Obtained the patient's informed consent and signed the informed consent form ④ The research was approved by the ethics committee of this hospital.
Who cannot join
- Nurses who have not completed 1/2 of the course content
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
This educational reform study aims to explore whether a full English course built on the DeepSeek artificial intelligence platform can improve orthopedic nurses' professional English competence. It will also examine nurses' satisfaction with AI-assisted teaching. The main questions it seeks to answer include:
Will the DeepSeek-based full English course improve orthopedic nurses' professional English test scores?
Read more
Will nurses' transcultural nursing self-efficacy and nurse-patient therapeutic interaction ability improve after the course training?
What are nurses' experiences when using the DeepSeek AI platform for learning?
Researchers will compare the English proficiency changes of the same group of orthopedic nurses before and after the training to observe the course effects.
Participants will:
Attend an 11-week full English course based on the DeepSeek platform, approximately 1-2 hours per week
Complete a professional English written test and an oral proficiency assessment before and after the training
Complete the Transcultural Self-Efficacy Tool (TSET-CV) and the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) before and after the training
Complete a teaching satisfaction and AI learning experience questionnaire after the course
Read the detailed description
This educational reform study aims to explore whether a full English course built on the DeepSeek artificial intelligence platform can improve orthopedic nurses' professional English competence and international service capabilities.
Background: With the advancement of the "Belt and Road" Initiative, international exchange and cooperation in orthopedic nursing have become increasingly frequent, placing higher demands on nurses' professional English proficiency. However, orthopedic nurses currently generally lack adequate professional English competence. Traditional nursing English education suffers from a single course structure, disconnection between teaching content and clinical practice, and a lack of personalized learning pathways. DeepSeek, as a leading domestic AI model, possesses powerful natural language processing, intelligent speech recognition, and personalized recommendation capabilities, yet its application in nursing English education remains unexplored.
Objective: This study aims to construct a DeepSeek-based full English course system for orthopedic nurses, explore effective pathways for AI-empowered nursing English teaching, and verify its practical effects on improving orthopedic nurses' professional English competence, transcultural nursing self-efficacy, and nurse-patient therapeutic interaction ability.
Study Design: A quasi-experimental study with a one-group pretest-posttest design will be adopted. Sixty registered orthopedic nurses will be recruited to participate in an 11-week blended online and offline full English course based on the DeepSeek platform. The effectiveness of the course intervention will be evaluated by comparing changes in nurses' professional English test scores, oral proficiency assessment results, Transcultural Self-Efficacy Tool (TSET-CV) scores, and Nurse-Patient Therapeutic Interaction Scale (NuPTIS) scores before and after the training.
Intervention: The full English course built on the DeepSeek platform spans 11 weeks and is divided into six modules:
Weeks 1-2 (Basic English for Orthopedic Nursing): Learning anatomical terms such as bones, muscles, and joints, as well as basic doctor-patient consultation dialogues Weeks 3-4 (Trauma Orthopedic Nursing): Learning English abbreviations for fracture classification and English instructions for orthosis use Weeks 5-6 (Joint Replacement and Nursing): Learning English preoperative education and postoperative complication prevention knowledge for hip and knee replacement surgeries Weeks 7-8 (Spinal Disorders and Nursing): Learning English expressions for common spinal diseases and reading English literature Weeks 9-10 (Common Orthopedic Nursing and Orthoses): Learning English instructions for the use of cervical collars, lumbar supports, crutches, and other orthoses Week 11 (Clinical Cross-cultural Communication): Comprehensive training in cross-cultural communication skills, completing a full-process simulated dialogue test from admission consultation to discharge instructions
Outcome Measures: The following indicators will be measured before and after the training:
Professional English written test score (self-developed test, total score 100) Oral proficiency assessment score (including fluency, accuracy, and terminology mastery, rated by the AI system) Transcultural Self-Efficacy Tool (TSET-CV, 30 items, covering three dimensions: cognitive, practical, and affective) Nurse-Patient Therapeutic Interaction Scale (NuPTIS, 20 items, covering four dimensions: emotional support, empathic communication, patient-centered care, and supportive communication process) Self-rated English ability and learning needs survey
Post-training data collection: teaching satisfaction questionnaire, AI learning experience questionnaire, and DeepSeek backend learning behavior data Statistical Analysis: SPSS 26.0 software will be used. Paired sample t-tests or Wilcoxon signed-rank tests will be employed to compare indicators before and after the training. Effect sizes will be reported as Cohen's d or r values. The significance level is set at α = 0.05.
Expected Outcomes: Develop a complete full English course system for orthopedic nurses (including a course syllabus, 11 sets of courseware, a specialized vocabulary bank, and AI scenario scripts), produce one teaching reform research report, publish one paper in a core journal, and achieve a participant satisfaction rate of ≥ 95%.
- Being tested
- Based on the all-English courses of DeepSeek
- Keywords
- DeepSeek; artificial intelligence; orthopedic nursing; full English course; nursing English teaching; transcultural nursing; nursing education
- Medical subject headings
- Language
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Based on the all-English courses of DeepSeekOther
This intervention is an 11-week full English course training for orthopedic nursing based on the DeepSeek artificial intelligence platform. The course adopts a blended online and offline teaching model, deeply integrating AI technology with nursing English education. It covers six modules: Basic English for Orthopedic Nursing, Trauma Orthopedic Nursing, Joint Replacement and Nursing, Spinal Disorders and Nursing, Common Orthopedic Nursing and Orthoses, and Clinical Cross-cultural Communication. During the training period, nurses engage in personalized learning through the DeepSeek platform, including intelligent vocabulary memorization, AI speech correction exercises, virtual doctor-patient dialogue simulations, AI case analysis, and English literature reading comprehension. These are combined with offline activities such as role-playing, workshops, and case discussions to systematically enhance orthopedic professional English competence and cross-cultural communication skills.
| Study group | Role | What they receive |
|---|---|---|
| DeepSeek AI-Based Full English Course Training Arm | Experimental | Participants in this arm are 60 registered orthopedic nurses who receive an 11-week full English course training for orthopedic nursing based on the DeepSeek AI platform. The course adopts a blended online and offline teaching model, covering six modules. Participants undergo professional English written tests, oral assessments, the Transcultural Self-Efficacy Tool (TSET-CV), and the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) before and after the training. Receives: Other: Based on the all-English courses of DeepSeek |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in Professional English Written Test Score from Baseline to Week 11
Change in Professional English Written Test Score from Baseline to Week 11
Measured: from Baseline to Week 11
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Jul 2026
- Study start1 Jul 2026 (estimated)
- Primary completion1 Jul 2027 (estimated)
- Study completion1 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Orthopedic NursingStudies of the same condition, open and under way.
- More trials run by The Fourth Affiliated Hospital of Zhejiang University School of MedicineThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 20 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07688499
- Sponsor's protocol ID
- KY-2026-105
- Status last verified
- Jul 2026
- First submitted
- 1 Jul 2026
- Last updated
- 7 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Nature of the Study: This is an educational reform study rather than a clinical drug or device trial. The data collected consist primarily of nurses' English test scores, scale assessments, and teaching satisfaction feedback, which do not involve patient health information or clinical efficacy data. Data Sensitivity: The research data include participants' individual learning performance, English proficiency assessments, and questionnaire feedback, which contain information that could indirectly identify individuals (e.g., employee ID, study code, platform usage records). Although data have been anonymized, there remains a potential risk of re-identification within a small institutional setting. Informed Consent Limitations: The informed consent form for this study did not include authorization for sharing data to public repositories. Participants only consented to the use of their data for analysis and publication of this study.
Study at a glance
From the registry record, last updated by the sponsor on 7 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Practical Exploration of Developing a Full-English Orthopedic Nursing Curriculum Based on DeepSeek Intelligence
- ClinicalTrials.gov ID
- NCT07688499
- Acronym / sponsor ID
- KY-2026-105
- Keywords
- DeepSeek; artificial intelligence; orthopedic nursing; full English course; nursing English teaching; transcultural nursing; nursing education
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 20 participants (estimated)
- Lead sponsor
- The Fourth Affiliated Hospital of Zhejiang University School of MedicineUniversity, hospital or other
- Study start
- 1 Jul 2026 (estimated)
- Primary completion
- 1 Jul 2027 (estimated)
- Study completion
- 1 Jul 2027 (estimated)
- First posted
- 7 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This educational reform study aims to explore whether a full English course built on the DeepSeek artificial intelligence platform can improve orthopedic nurses' professional English competence. It will also examine nurses' satisfaction with AI-assisted teaching. The main questions it seeks to answer include:
Will the DeepSeek-based full English course improve orthopedic nurses' professional English test scores?
Will nurses' transcultural nursing self-efficacy and nurse-patient therapeutic interaction ability improve after the course training?
What are nurses' experiences when using the DeepSeek AI platform for learning?
Researchers will compare the English proficiency changes of the same group of orthopedic nurses before and after the training to observe the course effects.
Participants will:
Attend an 11-week full English course based on the DeepSeek platform, approximately 1-2 hours per week
Complete a professional English written test and an oral proficiency assessment before and after the training
Complete the Transcultural Self-Efficacy Tool (TSET-CV) and the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) before and after the training
Complete a teaching satisfaction and AI learning experience questionnaire after the course
Detailed description
This educational reform study aims to explore whether a full English course built on the DeepSeek artificial intelligence platform can improve orthopedic nurses' professional English competence and international service capabilities.
Background: With the advancement of the "Belt and Road" Initiative, international exchange and cooperation in orthopedic nursing have become increasingly frequent, placing higher demands on nurses' professional English proficiency. However, orthopedic nurses currently generally lack adequate professional English competence. Traditional nursing English education suffers from a single course structure, disconnection between teaching content and clinical practice, and a lack of personalized learning pathways. DeepSeek, as a leading domestic AI model, possesses powerful natural language processing, intelligent speech recognition, and personalized recommendation capabilities, yet its application in nursing English education remains unexplored.
Objective: This study aims to construct a DeepSeek-based full English course system for orthopedic nurses, explore effective pathways for AI-empowered nursing English teaching, and verify its practical effects on improving orthopedic nurses' professional English competence, transcultural nursing self-efficacy, and nurse-patient therapeutic interaction ability.
Study Design: A quasi-experimental study with a one-group pretest-posttest design will be adopted. Sixty registered orthopedic nurses will be recruited to participate in an 11-week blended online and offline full English course based on the DeepSeek platform. The effectiveness of the course intervention will be evaluated by comparing changes in nurses' professional English test scores, oral proficiency assessment results, Transcultural Self-Efficacy Tool (TSET-CV) scores, and Nurse-Patient Therapeutic Interaction Scale (NuPTIS) scores before and after the training.
Intervention: The full English course built on the DeepSeek platform spans 11 weeks and is divided into six modules:
Weeks 1-2 (Basic English for Orthopedic Nursing): Learning anatomical terms such as bones, muscles, and joints, as well as basic doctor-patient consultation dialogues Weeks 3-4 (Trauma Orthopedic Nursing): Learning English abbreviations for fracture classification and English instructions for orthosis use Weeks 5-6 (Joint Replacement and Nursing): Learning English preoperative education and postoperative complication prevention knowledge for hip and knee replacement surgeries Weeks 7-8 (Spinal Disorders and Nursing): Learning English expressions for common spinal diseases and reading English literature Weeks 9-10 (Common Orthopedic Nursing and Orthoses): Learning English instructions for the use of cervical collars, lumbar supports, crutches, and other orthoses Week 11 (Clinical Cross-cultural Communication): Comprehensive training in cross-cultural communication skills, completing a full-process simulated dialogue test from admission consultation to discharge instructions
Outcome Measures: The following indicators will be measured before and after the training:
Professional English written test score (self-developed test, total score 100) Oral proficiency assessment score (including fluency, accuracy, and terminology mastery, rated by the AI system) Transcultural Self-Efficacy Tool (TSET-CV, 30 items, covering three dimensions: cognitive, practical, and affective) Nurse-Patient Therapeutic Interaction Scale (NuPTIS, 20 items, covering four dimensions: emotional support, empathic communication, patient-centered care, and supportive communication process) Self-rated English ability and learning needs survey
Post-training data collection: teaching satisfaction questionnaire, AI learning experience questionnaire, and DeepSeek backend learning behavior data Statistical Analysis: SPSS 26.0 software will be used. Paired sample t-tests or Wilcoxon signed-rank tests will be employed to compare indicators before and after the training. Effect sizes will be reported as Cohen's d or r values. The significance level is set at α = 0.05.
Expected Outcomes: Develop a complete full English course system for orthopedic nurses (including a course syllabus, 11 sets of courseware, a specialized vocabulary bank, and AI scenario scripts), produce one teaching reform research report, publish one paper in a core journal, and achieve a participant satisfaction rate of ≥ 95%.
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| DeepSeek AI-Based Full English Course Training Arm | Experimental | Other: Based on the all-English courses of DeepSeekParticipants in this arm are 60 registered orthopedic nurses who receive an 11-week full English course training for orthopedic nursing based on the DeepSeek AI platform. The course adopts a blended online and offline teaching model, covering six modules. Participants undergo professional English written tests, oral assessments, the Transcultural Self-Efficacy Tool (TSET-CV), and the Nurse-Patient Therapeutic Interaction Scale (NuPTIS) before and after the training. |
Who may qualify
- Ages
- 20 to 40 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (1 listed)
- ① On-duty nurses in the orthopedics department ② Obtained the nurse professional qualification certificate ③ Obtained the patient's informed consent and signed the informed consent form ④ The research was approved by the ethics committee of this hospital.
Key exclusion criteria (1 listed)
- Nurses who have not completed 1/2 of the course content
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Based on the all-English courses of DeepSeekThis intervention is an 11-week full English course training for orthopedic nursing based on the DeepSeek artificial intelligence platform. The course adopts a blended online and offline teaching model, deeply integrating AI technology with nursing English education. It covers six modules: Basic English for Orthopedic Nursing, Trauma Orthopedic Nursing, Joint Replacement and Nursing, Spinal Disorders and Nursing, Common Orthopedic Nursing and Orthoses, and Clinical Cross-cultural Communication. During the training period, nurses engage in personalized learning through the DeepSeek platform, including intelligent vocabulary memorization, AI speech correction exercises, virtual doctor-patient dialogue simulations, AI case analysis, and English literature reading comprehension. These are combined with offline activities such as role-playing, workshops, and case discussions to systematically enhance orthopedic professional English competence and cross-cultural communication skills. | Other | DeepSeek AI-Based Full English Course Training Arm |
Primary outcome
Change in Professional English Written Test Score from Baseline to Week 11
Time frame: from Baseline to Week 11
Change in Professional English Written Test Score from Baseline to Week 11
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Jul 2026.
- Individual participant dataSharing planned: No. Nature of the Study: This is an educational reform study rather than a clinical drug or device trial. The data collected consist primarily of nurses' English test scores, scale assessments, and teaching satisfaction feedback, which do not involve patient health information or clinical efficacy data. Data Sensitivity: The research data include participants' individual learning performance, English proficiency assessments, and questionnaire feedback, which contain information that could indirectly identify individuals (e.g., employee ID, study code, platform usage records). Although data have been anonymized, there remains a potential risk of re-identification within a small institutional setting. Informed Consent Limitations: The informed consent form for this study did not include authorization for sharing data to public repositories. Participants only consented to the use of their data for analysis and publication of this study.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Questions about this trial
What is this clinical trial studying?
A study testing Based on the all-English courses of DeepSeek in people with Orthopedic Nursing and Education, Nursing, run by The Fourth Affiliated Hospital of Zhejiang University School of Medicine.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 7 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact chuweiwei wei chuww, Bachelor's Degree (+86 0579-89935006, xiaowai_wei@yeah.net), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in Professional English Written Test Score from Baseline to Week 11 (time frame: from Baseline to Week 11). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Jul 2026.