Physiology EducationPBLNCT07608315
AI-Assisted Adaptive Simulation in Physiology Education
A study testing AI-Assisted Algorithm-Supported Adaptive Simulation and Conventional Physiology Instruction in people with Physiology Education and Simulation-Based Learning, run by Saveetha University at 1 site in India.
Trial summary
This randomized controlled trial evaluated whether an AI-assisted, rule-based adaptive screen-based simulation module could improve physiology learning outcomes among undergraduate health science students compared with conventional instruction. Read more about this study
- Who is it for?
- Ages 18 to 25 yearsHealthy volunteers can take part
- Conditions the study is for
- Physiology Education, Simulation-Based Learning, v
- What is being tested?
- AI-Assisted Algorithm-Supported Adaptive Simulation and Conventional Physiology Instruction
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 672 participants
- Where
- 1 siteIndia
- Study dates
- 1 Aug 2025to 31 Jan 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 18 to 25 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Undergraduate students enrolled in Health Science programs including Physiotherapy, Occupational Therapy, Nursing, and Allied Health Sciences
- Registered for a Human Physiology course during the study period
- Age between 18 and 25 years
- Proficiency in English language
- Access to an internet-enabled personal device capable of supporting web-based educational applications
- Willingness to provide written informed consent for participation
Who cannot join
- Prior formal exposure to structured simulation-based physiology instruction
- Prior exposure to adaptive digital learning platforms related to physiology education
- Inability to access or use internet-enabled educational applications required for the intervention
- Declined or withdrew informed consent for participation
Trial locations and contacts
1 site in 1 country.
India1 site
Saveetha Institute of Basic Medical Sciences (SIBMS), Saveetha Institute of Medical and Technical Sciences (SIMATS)
Chennai, Tamil Nadu, 602105
About this study
Official title: Effect of Adaptive AI-Supported Simulation on Physiology Learning Outcomes Among Medical Students: A Randomized Controlled Trial
This randomized controlled trial evaluated whether an AI-assisted, rule-based adaptive screen-based simulation module could improve physiology learning outcomes among undergraduate health science students compared with conventional instruction. A total of 672 students from Physiotherapy, Occupational Therapy, Nursing, and Allied Health Sciences were randomly assigned in a 1:1 ratio to either the adaptive simulation group or the conventional teaching group. The intervention used web-based clinical physiology cases with algorithm-supported case sequencing, automated formative feedback, and structured faculty-led debriefing, while the control group received standard lectures, textbook reading, tutorial sessions, and laboratory practicals. The primary outcomes were physiological knowledge and reasoning ability, and the secondary outcomes were conceptual understanding, engagement, cognitive load, and academic self-efficacy. Assessments were performed at baseline, immediately after the 12-week intervention, and again at four-week follow-up.
Read the detailed description
This study was designed as a prospective, two-arm, parallel-group randomized controlled trial with repeated-measures assessment at three time points: baseline, immediately post-intervention, and four weeks after the intervention. It was conducted at Saveetha Institute of Basic Medical Sciences, India, between August 2025 and January 2026, and received institutional ethical approval before enrollment. Participants were undergraduate health science students aged 18 to 25 years who were enrolled in a Human Physiology course and had access to an internet-enabled personal device. Students with prior formal exposure to simulation-based physiology instruction or adaptive digital learning platforms were excluded. After baseline assessment, participants were randomized in a 1:1 ratio to the intervention or control group, with allocation concealment and blinded outcome assessment.
The intervention group received physiology instruction through a screen-based adaptive simulation environment over 12 weeks. The module was intentionally designed as a bundled educational strategy integrating adaptive case sequencing, automated formative feedback, and faculty-led debriefing. The adaptive component used predefined rule-based logic to personalize learning by adjusting case difficulty and feedback pathways according to learner performance; it did not use autonomous generative artificial intelligence or clinical decision-making. Participants completed structured simulation sessions for two hours per week, including pre-briefing, individual case-based simulation, and facilitated debriefing. The control group received conventional curriculum-based physiology instruction over the same 12-week period, including didactic lectures, prescribed textbook readings, tutorial sessions, and laboratory practicals.
The study prioritized objective learning outcomes. Physiological knowledge was measured using a 40-item multiple-choice test, physiological reasoning ability using a scenario-based rubric-scored assessment, and conceptual understanding using a physiology concept inventory. Secondary outcomes included student engagement measured with the USEI, cognitive load measured with NASA-TLX, and academic self-efficacy measured with an adapted CASES scale. Outcomes were collected at baseline, post-intervention, and follow-up using the same instruments across all time points.
- Conditions
- Physiology Education, Simulation-Based Learning, v, Artificial Intelligence in Education, Health Professions Education
- Being tested
- AI-Assisted Algorithm-Supported Adaptive Simulation, Conventional Physiology Instruction
- Keywords
- AI-assisted adaptive simulation, Screen-based simulation, Physiology learning, Clinical reasoning, Educational technology, Undergraduate health sciences, Cognitive load
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted Algorithm-Supported Adaptive SimulationBehavioural
Also called Adaptive Screen-Based Simulation, AI-Assisted Adaptive Simulation, Rule-Based Adaptive Simulation, Adaptive Physiology Simulation Platform
The intervention consisted of an AI-assisted algorithm-supported adaptive screen-based physiology simulation delivered over 12 weeks. Participants engaged in structured web-based simulation sessions involving interactive clinical case scenarios, animated physiological visualizations, adaptive case sequencing, automated formative feedback, and faculty-led debriefing. The adaptive instructional system operated through predefined rule-based educational algorithms that adjusted case difficulty, feedback pathways, and learning progression according to participant performance within faculty-defined parameters. Sessions included pre-briefing, individual simulation-based clinical reasoning activities, adaptive feedback, and reflective debriefing. The intervention was implemented in alignment with the INACSL Healthcare Simulation Standards of Best Practice and focused on improving physiological knowledge, conceptual understanding, and clinical reasoning skills.
Conventional Physiology InstructionBehavioural
Also called Standard Curriculum-Based Teaching, Conventional Teaching, Didactic Physiology Education, Traditional Physiology Instruction
Participants received standard curriculum-based physiology instruction over a 12-week period according to institutional teaching guidelines. Conventional instruction included didactic lectures, prescribed textbook readings, faculty-guided tutorial sessions, and scheduled laboratory practicals covering cardiovascular, respiratory, renal, neurological, endocrine, gastrointestinal, musculoskeletal, and integumentary physiology. Tutorial sessions focused on instructor-led clarification of physiological concepts, small-group discussion, and question-and-answer interactions. Laboratory practicals included supervised physiological measurements, observation of physiological demonstrations, interpretation of experimental findings, and guided analysis of physiological responses. The control condition did not include adaptive simulation, automated formative feedback, algorithm-supported instructional adaptation, or structured simulation-based clinical reasoning activities.
| Study group | Role | What they receive |
|---|---|---|
| I-Assisted Adaptive Simulation Group | Experimental | Participants received AI-assisted algorithm-supported adaptive screen-based physiology simulation over a 12-week period. The intervention included adaptive case sequencing, automated formative feedback, interactive clinical reasoning activities, animated physiological visualization, and structured faculty-led debriefing sessions aligned with physiology curriculum objectives. Receives: Behavioral: AI-Assisted Algorithm-Supported Adaptive Simulation |
| Conventional Instruction Group | Active comparator | Participants received standard curriculum-based physiology instruction over a 12-week period, including didactic lectures, prescribed textbook readings, faculty-guided tutorial sessions, and scheduled laboratory practicals covering core physiological systems. Receives: Behavioral: Conventional Physiology Instruction |
What is being measured
The primary outcome is the main question the study is designed to answer.
Physiological Reasoning Ability
Physiological reasoning ability was assessed using a scenario-based assessment requiring hypothesis generation, interpretation of physiological data, and application of physiological mechanisms to management decisions. Responses were scored using a standardized four-point analytic rubric assessing reasoning and clinical interpretation skills. Higher scores indicate better physiological reasoning ability.
Measured: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Physiological Knowledge
Physiological knowledge was assessed using a faculty-developed 40-item multiple-choice assessment designed to evaluate conceptual understanding and applied physiological reasoning across eight core physiological systems, including cardiovascular, respiratory, renal, neurological, endocrine, gastrointestinal, musculoskeletal, and integumentary physiology. Higher scores indicate better physiology knowledge performance.
Measured: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Conceptual Understanding
Conceptual understanding was assessed using a faculty-developed Physiology Concept Inventory designed to evaluate deep conceptual understanding, integration of physiological mechanisms across systems, and identification of common physiological misconceptions. Higher scores indicate better conceptual understanding of physiology concepts.
Measured: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Secondary outcomes (3)
Student Engagement
Student engagement was assessed using the University Student Engagement Inventory (USEI), which evaluates behavioral, emotional, and cognitive dimensions of learner engagement. Higher scores indicate greater learner engagement during physiology learning activities.
Measured: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Cognitive Load
Cognitive load was assessed using the NASA Task Load Index (NASA-TLX), a multidimensional measure evaluating perceived cognitive workload and task demand during learning activities. Higher scores indicate greater perceived cognitive workload.
Measured: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Academic Self-Efficacy
Academic self-efficacy was measured using an adapted version of the College Academic Self-Efficacy Scale (CASES) to evaluate learner confidence in physiology-related academic tasks and simulation-based learning activities. Higher scores indicate greater academic self-efficacy.
Measured: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 May 2026
- Study start1 Aug 2025
- Primary completion31 Jan 2026
- Study completion31 Jan 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Physiology EducationStudies of the same condition, open and under way.
- 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
- Basic science
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 672 participants (actual)
Sponsor and investigators
- Lead sponsor
- Saveetha University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jeevarathinam Thirumalai, Saveetha University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07608315
- Sponsor's protocol ID
- 24/032/2025/SR/SIBMS
- Acronym
- PBL
- Status last verified
- May 2026
- First submitted
- 15 May 2026
- Last updated
- 27 May 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data (IPD) will not be publicly shared because the dataset contains institution-linked educational performance information and participant-level academic assessment data. De-identified data may be considered for academic collaboration upon reasonable request to the corresponding author, subject to institutional ethical approval and data-sharing regulations.
Publications
Sim JJM, Rusli KDB, Seah B, Levett-Jones T, Lau Y, Liaw SY. Virtual Simulation to Enhance Clinical Reasoning in Nursing: A Systematic Review and Meta-analysis. Clin Simul Nurs. 2022 Aug;69:26-39. doi: 10.1016/j.ecns.2022.05.006. Epub 2022 Jun 15.
PubMed 35754937Elven M, Welin E, Wiegleb Edstrom D, Petreski T, Szopa M, Durning SJ, Edelbring S. Clinical Reasoning Curricula in Health Professions Education: A Scoping Review. J Med Educ Curric Dev. 2023 Oct 25;10:23821205231209093. doi: 10.1177/23821205231209093. eCollection 2023 Jan-Dec.
PubMed 37900617Parodis I, Andersson L, Durning SJ, Hege I, Knez J, Kononowicz AA, Lidskog M, Petreski T, Szopa M, Edelbring S. Clinical Reasoning Needs to Be Explicitly Addressed in Health Professions Curricula: Recommendations from a European Consortium. Int J Environ Res Public Health. 2021 Oct 25;18(21):11202. doi: 10.3390/ijerph182111202.
PubMed 34769721
Study at a glance
From the registry record, last updated by the sponsor on 27 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effect of Adaptive AI-Supported Simulation on Physiology Learning Outcomes Among Medical Students: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07608315
- Acronym / sponsor ID
- PBL / 24/032/2025/SR/SIBMS
- Conditions
- Physiology Education, Simulation-Based Learning, v, Artificial Intelligence in Education, Health Professions Education
- Keywords
- AI-assisted adaptive simulation, Screen-based simulation, Physiology learning, Clinical reasoning, Educational technology, Undergraduate health sciences, Cognitive load
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 672 participants (actual)
- Lead sponsor
- Saveetha UniversityUniversity, hospital or other
- Study start
- 1 Aug 2025 (actual)
- Primary completion
- 31 Jan 2026 (actual)
- Study completion
- 31 Jan 2026 (actual)
- First posted
- 27 May 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 randomized controlled trial evaluated whether an AI-assisted, rule-based adaptive screen-based simulation module could improve physiology learning outcomes among undergraduate health science students compared with conventional instruction. A total of 672 students from Physiotherapy, Occupational Therapy, Nursing, and Allied Health Sciences were randomly assigned in a 1:1 ratio to either the adaptive simulation group or the conventional teaching group. The intervention used web-based clinical physiology cases with algorithm-supported case sequencing, automated formative feedback, and structured faculty-led debriefing, while the control group received standard lectures, textbook reading, tutorial sessions, and laboratory practicals. The primary outcomes were physiological knowledge and reasoning ability, and the secondary outcomes were conceptual understanding, engagement, cognitive load, and academic self-efficacy. Assessments were performed at baseline, immediately after the 12-week intervention, and again at four-week follow-up.
Detailed description
This study was designed as a prospective, two-arm, parallel-group randomized controlled trial with repeated-measures assessment at three time points: baseline, immediately post-intervention, and four weeks after the intervention. It was conducted at Saveetha Institute of Basic Medical Sciences, India, between August 2025 and January 2026, and received institutional ethical approval before enrollment. Participants were undergraduate health science students aged 18 to 25 years who were enrolled in a Human Physiology course and had access to an internet-enabled personal device. Students with prior formal exposure to simulation-based physiology instruction or adaptive digital learning platforms were excluded. After baseline assessment, participants were randomized in a 1:1 ratio to the intervention or control group, with allocation concealment and blinded outcome assessment.
The intervention group received physiology instruction through a screen-based adaptive simulation environment over 12 weeks. The module was intentionally designed as a bundled educational strategy integrating adaptive case sequencing, automated formative feedback, and faculty-led debriefing. The adaptive component used predefined rule-based logic to personalize learning by adjusting case difficulty and feedback pathways according to learner performance; it did not use autonomous generative artificial intelligence or clinical decision-making. Participants completed structured simulation sessions for two hours per week, including pre-briefing, individual case-based simulation, and facilitated debriefing. The control group received conventional curriculum-based physiology instruction over the same 12-week period, including didactic lectures, prescribed textbook readings, tutorial sessions, and laboratory practicals.
The study prioritized objective learning outcomes. Physiological knowledge was measured using a 40-item multiple-choice test, physiological reasoning ability using a scenario-based rubric-scored assessment, and conceptual understanding using a physiology concept inventory. Secondary outcomes included student engagement measured with the USEI, cognitive load measured with NASA-TLX, and academic self-efficacy measured with an adapted CASES scale. Outcomes were collected at baseline, post-intervention, and follow-up using the same instruments across all time points.
Study design
- Primary purpose
- Basic science
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| I-Assisted Adaptive Simulation Group | Experimental | Behavioral: AI-Assisted Algorithm-Supported Adaptive SimulationParticipants received AI-assisted algorithm-supported adaptive screen-based physiology simulation over a 12-week period. The intervention included adaptive case sequencing, automated formative feedback, interactive clinical reasoning activities, animated physiological visualization, and structured faculty-led debriefing sessions aligned with physiology curriculum objectives. |
| Conventional Instruction Group | Active comparator | Behavioral: Conventional Physiology InstructionParticipants received standard curriculum-based physiology instruction over a 12-week period, including didactic lectures, prescribed textbook readings, faculty-guided tutorial sessions, and scheduled laboratory practicals covering core physiological systems. |
Who may qualify
- Ages
- 18 to 25 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (6 listed)
- Undergraduate students enrolled in Health Science programs including Physiotherapy, Occupational Therapy, Nursing, and Allied Health Sciences
- Registered for a Human Physiology course during the study period
- Age between 18 and 25 years
- Proficiency in English language
- Access to an internet-enabled personal device capable of supporting web-based educational applications
Key exclusion criteria (4 listed)
- Prior formal exposure to structured simulation-based physiology instruction
- Prior exposure to adaptive digital learning platforms related to physiology education
- Inability to access or use internet-enabled educational applications required for the intervention
- Declined or withdrew informed consent for participation
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 |
|---|---|---|
| AI-Assisted Algorithm-Supported Adaptive SimulationAlso: Adaptive Screen-Based Simulation, AI-Assisted Adaptive Simulation, Rule-Based Adaptive Simulation, Adaptive Physiology Simulation PlatformThe intervention consisted of an AI-assisted algorithm-supported adaptive screen-based physiology simulation delivered over 12 weeks. Participants engaged in structured web-based simulation sessions involving interactive clinical case scenarios, animated physiological visualizations, adaptive case sequencing, automated formative feedback, and faculty-led debriefing. The adaptive instructional system operated through predefined rule-based educational algorithms that adjusted case difficulty, feedback pathways, and learning progression according to participant performance within faculty-defined parameters. Sessions included pre-briefing, individual simulation-based clinical reasoning activities, adaptive feedback, and reflective debriefing. The intervention was implemented in alignment with the INACSL Healthcare Simulation Standards of Best Practice and focused on improving physiological knowledge, conceptual understanding, and clinical reasoning skills. | Behavioural | I-Assisted Adaptive Simulation Group |
| Conventional Physiology InstructionAlso: Standard Curriculum-Based Teaching, Conventional Teaching, Didactic Physiology Education, Traditional Physiology InstructionParticipants received standard curriculum-based physiology instruction over a 12-week period according to institutional teaching guidelines. Conventional instruction included didactic lectures, prescribed textbook readings, faculty-guided tutorial sessions, and scheduled laboratory practicals covering cardiovascular, respiratory, renal, neurological, endocrine, gastrointestinal, musculoskeletal, and integumentary physiology. Tutorial sessions focused on instructor-led clarification of physiological concepts, small-group discussion, and question-and-answer interactions. Laboratory practicals included supervised physiological measurements, observation of physiological demonstrations, interpretation of experimental findings, and guided analysis of physiological responses. The control condition did not include adaptive simulation, automated formative feedback, algorithm-supported instructional adaptation, or structured simulation-based clinical reasoning activities. | Behavioural | Conventional Instruction Group |
Primary outcome
Physiological Reasoning Ability
Time frame: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Physiological reasoning ability was assessed using a scenario-based assessment requiring hypothesis generation, interpretation of physiological data, and application of physiological mechanisms to management decisions. Responses were scored using a standardized four-point analytic rubric assessing reasoning and clinical interpretation skills. Higher scores indicate better physiological reasoning ability.
Physiological Knowledge
Time frame: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Physiological knowledge was assessed using a faculty-developed 40-item multiple-choice assessment designed to evaluate conceptual understanding and applied physiological reasoning across eight core physiological systems, including cardiovascular, respiratory, renal, neurological, endocrine, gastrointestinal, musculoskeletal, and integumentary physiology. Higher scores indicate better physiology knowledge performance.
Conceptual Understanding
Time frame: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Conceptual understanding was assessed using a faculty-developed Physiology Concept Inventory designed to evaluate deep conceptual understanding, integration of physiological mechanisms across systems, and identification of common physiological misconceptions. Higher scores indicate better conceptual understanding of physiology concepts.
3 secondary outcomes
Student Engagement
Time frame: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Cognitive Load
Time frame: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Academic Self-Efficacy
Time frame: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 27 May 2026.
- Background: PubMed 35754937Sim JJM, Rusli KDB, Seah B, Levett-Jones T, Lau Y, Liaw SY. Virtual Simulation to Enhance Clinical Reasoning in Nursing: A Systematic Review and Meta-analysis. Clin Simul Nurs. 2022 Aug;69:26-39. doi: 10.1016/j.ecns.2022.05.006. Epub 2022 Jun 15.
- Background: PubMed 37900617Elven M, Welin E, Wiegleb Edstrom D, Petreski T, Szopa M, Durning SJ, Edelbring S. Clinical Reasoning Curricula in Health Professions Education: A Scoping Review. J Med Educ Curric Dev. 2023 Oct 25;10:23821205231209093. doi: 10.1177/23821205231209093. eCollection 2023 Jan-Dec.
- Background: PubMed 34769721Parodis I, Andersson L, Durning SJ, Hege I, Knez J, Kononowicz AA, Lidskog M, Petreski T, Szopa M, Edelbring S. Clinical Reasoning Needs to Be Explicitly Addressed in Health Professions Curricula: Recommendations from a European Consortium. Int J Environ Res Public Health. 2021 Oct 25;18(21):11202. doi: 10.3390/ijerph182111202.
- Individual participant dataSharing planned: No. Individual participant data (IPD) will not be publicly shared because the dataset contains institution-linked educational performance information and participant-level academic assessment data. De-identified data may be considered for academic collaboration upon reasonable request to the corresponding author, subject to institutional ethical approval and data-sharing regulations.
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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Assisted Algorithm-Supported Adaptive Simulation and Conventional Physiology Instruction in people with Physiology Education and Simulation-Based Learning, run by Saveetha University at 1 site in India.
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 6 inclusion and 4 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: finished, as of the sponsor's last update on 27 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in India. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Physiological Reasoning Ability (time frame: Baseline (Week 1), post-intervention (Week 13), and follow-up (Week 17)). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07608315, which also lists 3 linked publications.
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 27 May 2026; AzTrials last refreshed its copy on 27 Oct 2026.