Background Physiotherapists are increasingly expected to act as first-contact practitioners in many healthcare systems. With the growing expansion of direct access to physiotherapy services, clinicians must be able to identify serious medical conditions that require referral to a physician rather than physiotherapeutic treatment. These conditions are commonly described as "Red Flags." Red flag screening refers to the clinical process of identifying signs and symptoms that may indicate serious underlying pathology such as malignancy, fracture, infection, neurological compromise, or cardiovascular disease. Failure to recognize these conditions may delay appropriate medical care and can pose a significant risk to patient safety. Despite the growing responsibility of physiotherapists in primary care settings, research suggests that screening competencies among physiotherapy students and early-career clinicians may vary considerably depending on the structure and emphasis of educational programs. Many physiotherapy curricula still primarily focus on musculoskeletal management, while structured training in clinical screening and differential decision-making remains inconsistently implemented. In response to these developments, international professional organizations such as the International Federation of Orthopaedic Manipulative Physical Therapists (IFOMPT) have published clinical frameworks and recommendations emphasizing the importance of systematic screening in physiotherapy practice. However, empirical research investigating how screening competencies can be effectively developed and assessed during undergraduate physiotherapy education remains limited. This gap in the literature represents an important challenge for physiotherapy education and patient safety. The overarching goal of this PhD project is therefore to investigate whether digitally standardized, video-based training and assessment approaches can improve red flag screening competencies among physiotherapy bachelor students.
Background Physiotherapists are increasingly expected to act as first-contact practitioners in many healthcare systems. With the growing expansion of direct access to physiotherapy services, clinicians must be able to identify serious medical conditions that require referral to a physician rather than physiotherapeutic treatment. These conditions are commonly described as "Red Flags." Red flag screening refers to the clinical process of identifying signs and symptoms that may indicate serious underlying pathology such as malignancy, fracture, infection, neurological compromise, or cardiovascular disease. Failure to recognize these conditions may delay appropriate medical care and can pose a significant risk to patient safety. Despite the growing responsibility of physiotherapists in primary care settings, research suggests that screening competencies among physiotherapy students and early-career clinicians may vary considerably depending on the structure and emphasis of educational programs. Many physiotherapy curricula still primarily focus on musculoskeletal management, while structured training in clinical screening and differential decision-making remains inconsistently implemented. In response to these developments, international professional organizations such as the International Federation of Orthopaedic Manipulative Physical Therapists (IFOMPT) have published clinical frameworks and recommendations emphasizing the importance of systematic screening in physiotherapy practice. However, empirical research investigating how screening competencies can be effectively developed and assessed during undergraduate physiotherapy education remains limited. This gap in the literature represents an important challenge for physiotherapy education and patient safety. The overarching goal of this PhD project is therefore to investigate whether digitally standardized, video-based training and assessment approaches can improve red flag screening competencies among physiotherapy bachelor students. Overall Aim of the Project The primary aim of the doctoral project is to enhance screening competencies in physiotherapy undergraduate education by developing and evaluating innovative teaching and assessment formats. The project specifically seeks to: Assess baseline screening competencies among physiotherapy students. Evaluate the effectiveness of a targeted screening training program. Explore the cognitive processes underlying expert clinical reasoning during red flag identification. The findings aim to contribute to evidence-based curriculum development in physiotherapy education and support improved patient safety through earlier recognition of serious medical conditions. Project Structure The doctoral project consists of two complementary research phases. Phase 1: Multicentric Randomized Longitudinal Study The first phase of the project focuses on the quantitative evaluation of screening competencies among physiotherapy students. Study Design This phase is designed as a multicentric randomized longitudinal study conducted across several universities offering physiotherapy bachelor programs. Participating students evaluate standardized video-based clinical cases that simulate typical patient presentations in physiotherapy practice. The videos represent realistic clinical encounters including patient history, symptom presentation, and elements of physical examination. Students are required to classify each case according to clinical urgency using predefined decision categories: Medically critical condition (Red Flag) - immediate medical referral required Non-critical condition - physiotherapy treatment appropriate Trial treatment with monitoring These classifications allow structured evaluation of students' ability to identify potential red flag conditions. Intervention Following the baseline assessment, students in the intervention group participate in a structured screening training program consisting of: Face-to-face teaching sessions Online learning modules Case-based discussions Clinical reasoning exercises focused on red flag recognition The program emphasizes systematic screening strategies, structured patient history taking, and decision-making frameworks based on international guidelines. A control group continues with the standard curriculum without additional screening training. Outcome Measures Students complete a post-intervention assessment using new standardized video cases, allowing comparison of screening performance between the intervention and control groups. The main outcomes include: Accuracy of red flag identification Clinical decision-making accuracy Changes in screening competency over time The use of standardized video cases enables consistent assessment across institutions and facilitates scalable evaluation of clinical competencies. Phase 2: Qualitative Investigation of Clinical Reasoning While Phase 1 investigates whether screening competencies can be improved through structured training, Phase 2 aims to better understand how experienced clinicians make screening decisions in clinical practice. Study Objective The objective of the second phase is to explore the cognitive processes involved in red flag recognition and clinical decision-making among experienced physiotherapists. Methodology This phase uses a qualitative research design employing the Think-Aloud method. Experienced physiotherapists will analyze standardized clinical cases similar to those used in the student assessments. While reviewing these cases, participants verbalize their thoughts and reasoning processes in real time. These verbalized cognitive processes provide insight into: Clinical reasoning strategies Pattern recognition Hypothesis generation Risk evaluation Decision-making pathways The interviews are audio-recorded and transcribed verbatim. Data Analysis The qualitative data will be analyzed using structured content analysis according to Kuckartz, allowing systematic identification of themes and reasoning patterns. The analysis aims to identify: Key decision-making strategies used by expert clinicians Typical reasoning pathways during red flag detection Differences between novice and expert decision processes Expected Contributions This doctoral project is expected to make several contributions to physiotherapy education and clinical practice. 1. Evidence-Based Curriculum Development The results will provide empirical data on the effectiveness of structured screening training programs within physiotherapy bachelor education. This evidence may support the integration of dedicated screening modules into physiotherapy curricula. 2. Improved Competency Assessment The project introduces video-based assessment formats as a standardized tool to evaluate clinical reasoning and screening competencies in physiotherapy students. Such formats could enable more objective and reproducible competency assessments across institutions. 3. Insights into Clinical Reasoning The qualitative component will provide valuable insights into the cognitive mechanisms underlying expert clinical decision-making. Understanding these processes can help educators design teaching strategies that better reflect real clinical reasoning. 4. Enhanced Patient Safety Ultimately, improving screening competencies among physiotherapy students may contribute to earlier identification of serious medical conditions and improved patient safety. Long-Term Perspective In the long term, the findings of this project may support the development of innovative educational approaches, including: digital case-based learning environments AI-assisted screening tools standardized competency assessments across physiotherapy programs The project therefore contributes to the ongoing evolution of physiotherapy education in response to expanding professional responsibilities and increasingly complex healthcare environments.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
SINGLE
Enrollment
400
The intervention is distinguished by the use of digitally standardized, video-based clinical cases that simulate authentic physiotherapy consultations from patient history to elements of clinical examination. Unlike traditional educational interventions that rely mainly on lectures or written case studies, this approach exposes students to dynamic clinical scenarios requiring real-time clinical reasoning and triage decisions. A further distinguishing feature is the integration of training and competency assessment within the same structured digital framework, enabling objective benchmarking across institutions. The intervention also combines face-to-face teaching, online learning modules, and case-based decision training, creating a blended-learning environment specifically designed to strengthen red flag screening skills. Additionally, the project links quantitative competency testing with a qualitative investigation of expert reasoning processes, allowing the educational intervention
Paracelsus medical university
Salzburg, Austria
Red Flag Screening
Primary Outcome Measure Accuracy of Red Flag Identification The primary outcome of the study is the accuracy with which physiotherapy students identify potentially serious medical conditions (Red Flags) when evaluating standardized video-based clinical cases. Participants are required to classify each case into predefined clinical decision categories: medically critical condition requiring immediate referral, non-critical condition suitable for physiotherapy treatment, or trial treatment with monitoring. Accuracy is determined by comparing student responses with expert-defined reference classifications developed prior to the study. The outcome will be quantified as the percentage of correct classifications across all presented cases.
Time frame: 18 weeks
Red Flag Screening
Primary Outcome Measure Accuracy of Red Flag Identification The primary outcome of the study is the accuracy with which physiotherapy students identify potentially serious medical conditions (Red Flags) when evaluating standardized video-based clinical cases. Participants are required to classify each case into predefined clinical decision categories: medically critical condition requiring immediate referral, non-critical condition suitable for physiotherapy treatment, or trial treatment with monitoring. Accuracy is determined by comparing student responses with expert-defined reference classifications developed prior to the study. The outcome will be quantified as the percentage of correct classifications across all presented cases.
Time frame: 16 weeks
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.