Pressure Injury, Wound
Conditions
Keywords
Pressure injury, Wound prediction model, Mobile application system, Knowledge of wound care, Self-efficacy, Anxiety, Depression
Brief summary
Pressure injuries are common in the elderly and patients who reduced physical activities. Its complications significantly impact the health care system and social burden, even causing the death rate to be as high as 68%. This study aims to collect medical data regarding pressure injuries during hospitalization for developing the Pressure Injury Prediction and Education Model using a mobile application system. It can offer a prediction on the risk of pressure injury and be used as a teaching aid for pressure injury care, providing a personalized and evidence-based nursing information platform for patients, caregivers, and health professionals.
Detailed description
This study will conduct a randomized controlled trial among 160 primary caregivers of patients with pressure injuries. They will be randomly assigned to the control group or the experimental group. In the control group, patients are routinely cared for in the ward, and this group will have no intervention. Routine care includes face-to-face training and educational pamphlets by the ward nurse. The experimental group will be provided a pressure injury prediction of the patient and personalized care information of pressure injury by a smart care platform. The participants (primary caregivers) will fill out the questionnaires online at admission (baseline-T0)and before the patient is discharged(T1). The questionnaires will collect the following data, including demographic information(only T0), knowledge, self-efficacy, anxiety, depression of pressure injury care(T0&T1), and satisfaction of the smart care platform(only T1). The time to fill out the questionnaires will be about 10 minutes.
Interventions
DEVICEThe Pressure Injury Prediction and Education model using a mobile application system
Data from the medical records will be used to analyze the probability and risk of wound healing for creating a Pressure Injury Prediction and Education Model using a mobile application system.
Sponsors
National Taipei University of Nursing and Health Sciences
National Taiwan University Hospital Hsin-Chu Branch
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
TRIPLE (Subject, Caregiver, Outcomes Assessor)
Intervention model description
1. pressure injury prediction and education model group 2. control group
Eligibility
Sex/Gender
ALL
Age
20 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
1. The primary caregiver for patients with pressure injury in the hospital. 2. The primary caregiver must be at least 20 years old, have clear consciousness, express independently, communicate in Mandarin and Taiwanese, use an Android phone by himself, and use a mobile phone application after explanation.
Exclusion criteria
The primary caregiver has a mental or cognitive impairment, cannot express consciousness clearly, or cannot operate mobile apps.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change from the baseline score of the knowledge of pressure injury care to before discharge | Data will be collected on admission(baseline-T0) and before discharge(T1). | The investigators designed the ten questions regarding pressure injury care knowledge to detect caregivers' understanding of pressure injury care. The higher scores reflect a greater understanding of pressure injury care. |
| Change from the baseline score of the pressure injury care self-efficacy of caregivers to before discharge | Data will be collected on admission(baseline-T0) and before discharge(T1). | The fourteen items of the self-efficacy of pressure injury care are designed to detect caregivers' self-efficacy on pressure injury care. Response options on the items range from no confidence (1 point) to every confidence (5 points). The higher scores reflect greater self-efficacy on pressure injury care. |
| Change from the baseline score of the General Anxiety Disorder-7(GAD-7) to before discharge | Data will be collected on admission(baseline-T0) and before discharge(T1). | The GAD-7 (Spitzer et al., 2006) is a one-dimensional instrument designed to detect generalized anxiety disorder symptoms defined in the DSM-IV. The item scores range from 0 (not at all) to 3 (nearly every day), resulting in a sum score ranging from 0 to 21. The higher scores reflect greater anxiety severity. |
| Change from the baseline score of the Patient Health Questionnaire-9(PHQ-9) to before discharge | Data will be collected on admission(baseline-T0) and before discharge(T1). | The nine items of the PHQ-9 are designed to capture the nine Diagnostic and Statistical Manual of Mental Disorders (DSM) symptom criteria for a major depressive episode. Response options on the items range from not at all (0 points) to nearly every day (3 points). As a severity measure, the PHQ-9 score can range from 0 to 27. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| the satisfaction score of the smart care platform regarding pressure injury care | Data will be collected before discharge(T1). | The ten items of satisfaction with the smart care platform are designed to detect caregivers' satisfaction with this platform. Response options on the items range from strongly disagree (1 point) to strongly agree (5 points), resulting in a sum score ranging from 10 to 50. |
Countries
Taiwan
Contacts
Primary ContactTzu-Ling Wu, BS
Backup ContactChun-Yi Tai, Ph.D
Outcome results
None listed