Digital Education Interventions, Knowledge Types (Mechanistic Versus Procedural)
Conditions
Brief summary
The increasing shift from face-to-face to online patient-clinician encounters in the healthcare system requires patients to be more involved in their medical care. This raises the urgent need to evaluate the extent to which proactive patients' self-care can be supported, particularly by informed telemedicine digital channels. Despite this imperative, research offering evidence-based instructional design of digital education remains surprisingly scarce. Embracing the framework of science education, which highlights the functional role of different knowledge types in educational processes, the current study seeks to evaluate an educational approach aimed at supporting cancer patients undergoing chemotherapy. Cancer treatment serves as an exemplar health condition, demanding daily self-management from patients. The objectives of our research are as follows: (1) To delineate the types of knowledge required for effective symptom management, active participation in one's healthcare, and judicious decision-making regarding emergency room (ER) visits, with a focus on mechanistic knowledge pertaining to the rationale for treatment and procedural knowledge concerning the treatment regimen. (2) To appraise the impact of a digital learning environment in contrast to traditional methods on patients' acquisition of mechanistic and procedural knowledge. (3) To identify how patients engage with the digital patient education environment aiming to outline leaning patterns. The investigators hypothesize that implementing digital education will enhance patients' understanding of both the 'why' (mechanistic) and 'how' (procedural) aspects of their treatment. Importantly, the investigators expect that mechanistic knowledge will be more impactful than procedural knowledge, leading to better symptom management and patient involvement, and ultimately reducing unnecessary visits to the ER.
Interventions
BEHAVIORALDigital education
Patients assigned to the experimental group will learn about symptom self-management in a digital learning environment.
Sponsors
Weizmann Institute of Science
Tel Aviv University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Gastrointestinal (GI) cancer patients * Chemotherapy session within a specific round of treatment, with eligible treatments including FOLFOX, FOLFIRINOX, and FLOT. * Hebrew speakers.
Exclusion criteria
* Impaired or degraded cognitive capabilities that may hinder effective learning. * Individuals who discontinue their treatments due to terminal advancement of their disease or death.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Symptom self-management knowledge | The test will be conducted in two time-points of the study, Time 0 (pre) and Time 2 (after two months) | Measured by performance accuracy in a cancer-specific knowledge test |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Self-efficacy in symptom management | The questionnaire will be administered three times: Time 0 (pre) and Time 2 (after two months) | Measured by self-report Self-Efficacy for Managing Chronic Disease 6-Item Scale. The scale ranges from 1 (not confident) to 10 (very confident). A higher score is interpreted as a better self-efficacy. |
| Confidence in decision making | The questionnaire will be administered in two time-points of the study, Time 0 (pre) and Time 2 (after two months) | Measured by the self-report Decision Self-Efficacy Scale, which assesses patients' self-confidence in their ability to make decisions. It includes 11 items on a scale ranging from 0 (not at all confident) to 4 (very confident). A higher score is interpreted as higher confidence. |
| Patients engagement while learning | on Time 2, namely about two weeks to four weeks after recruitment | Patients engagement with patient education material will be captured by psychophysiological parameters of eye-tracking and facial expressions |
Countries
Israel
Contacts
Primary ContactIlana Dubovi
Outcome results
None listed