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Heart failure (HF) is a growing global health issue, with increasing prevalence among aging populations. In Turkey, the prevalence of HF was 2.114% in 2022, affecting approximately three million individuals. HF patients often experience poor sleep quality due to symptoms like dyspnea, fatigue, and fluid retention, which significantly impact their overall health and quality of life. Sleep disorders, particularly obstructive and central sleep apnea, are commonly reported among HF patients, exacerbating disease progression and increasing morbidity. Nurses play a crucial role in improving HF patients' self-care behaviors, including sleep hygiene interventions. Sleep hygiene consists of non-pharmacological strategies to improve sleep quality, such as maintaining a regular sleep schedule, avoiding electronic devices before bed, and minimizing caffeine and alcohol intake. However, behavior change in sleep hygiene requires structured intervention models, such as the Transtheoretical Model (TTM), which provides a stepwise approach to behavioral change, moving individuals through different stages from precontemplation to maintenance. TTM has been successfully applied in chronic disease management, including smoking cessation, diabetes self-care, hypertension control, and physical activity promotion. However, its application in HF patients, particularly for sleep interventions, remains underexplored. The limited existing studies suggest that HF patients often remain in the contemplation or preparation stages, indicating the need for tailored interventions to facilitate behavior change.
Advancements in digital health have enabled home-based sleep monitoring through wearable devices and mobile applications. Smartwatches, such as the Mi Band, provide real-time data on sleep parameters, offering a non-invasive alternative to traditional clinical sleep studies. Additionally, WhatsApp-based interventions have gained attention in healthcare, proving effective in chronic disease management by enhancing patient education, treatment adherence, and remote monitoring. WhatsApp facilitates real-time communication between patients and healthcare providers, reducing hospital readmissions and improving self-care practices. This study proposes a WhatsApp-based, TTM-guided sleep intervention for HF patients to improve sleep quality and self-care behaviors. Unlike previous studies, which primarily focus on general self-care education, this project integrates TTM with a digital platform to support sustained behavior change. Participants will receive personalized sleep hygiene guidance through WhatsApp, with regular reminders and real-time support. Sleep quality will be assessed using the Pittsburgh Sleep Quality Index (PSQI) and Sleep Hygiene Index (SHI), alongside objective sleep parameters measured via smartwatches. The impact on quality of life (QoL) will be evaluated using the Minnesota Living with Heart Failure Questionnaire (MLHFQ).
Hypotheses H1. The WhatsApp-based, TTM-guided sleep health program will significantly improve subjective sleep quality in HF patients.
H2. The WhatsApp-based, TTM-guided sleep health program will significantly improve sleep hygiene in HF patients.
H3. The WhatsApp-based, TTM-guided sleep health program will significantly improve quality of life in HF patients.
This project is the first study to integrate TTM-based behavior change strategies with a WhatsApp sleep intervention for HF patients. The findings will provide novel insights into digital health interventions for chronic disease management and offer a scalable, cost-effective approach to improving sleep hygiene in HF populations.
HF is a major global health concern, particularly in aging populations. In Turkey, HF prevalence reached approximately 2.114% in 2022, affecting nearly three million individuals. The condition leads to high hospitalization rates and significant healthcare costs. Given its increasing prevalence, improving self-care behaviors among HF patients is crucial. HF is a chronic disease that impairs the heart's ability to pump blood efficiently, leading to symptoms such as dyspnea, fatigue, and fluid retention. Beyond physical symptoms, HF patients frequently experience psychological issues like depression and anxiety, further compromising their QoL. Among the key determinants of reduced QoL in HF patients is poor sleep quality, which affects daily functioning and overall health status. Studies indicate that HF patients frequently suffer from sleep disturbances, including insomnia, obstructive sleep apnea (OSA), and central sleep apnea (CSA), all of which contribute to disease progression and increased morbidity risk. Addressing sleep quality in HF patients is an essential component of improving disease management and patient outcomes. Nurses, as key healthcare providers, play a pivotal role in implementing interventions to improve sleep hygiene, a critical yet often overlooked aspect of HF care. However, behavior change in sleep hygiene requires structured, evidence-based interventions that account for the complexities of adopting new habits.
Sleep hygiene refers to a set of non-pharmacological strategies designed to promote better sleep quality. These strategies include:
Despite these well-established guidelines, adherence to sleep hygiene recommendations remains a challenge, particularly among HF patients. Behavior change in chronic illness management is complex, requiring systematic approaches that help individuals transition from awareness to action and long-term maintenance. One effective approach for guiding behavior change is the TTM. TTM outlines five distinct stages of change:
This study aims to develop and test a WhatsApp-based, TTM-guided sleep hygiene intervention for HF patients, evaluating its impact on sleep quality and overall quality of life. The intervention integrates TTM principles with a digital platform to promote sustainable sleep hygiene behaviors. Unlike previous HF interventions, which primarily focus on general self-care education, this project specifically targets sleep hygiene, using WhatsApp to provide continuous support, reminders, and feedback.
Hypotheses H1. The WhatsApp-based, TTM-guided sleep health program will significantly improve subjective sleep quality in HF patients.H2. The WhatsApp-based, TTM-guided sleep health program will significantly improve sleep hygiene in HF patients.
H3. The WhatsApp-based, TTM-guided sleep health program will significantly improve quality of life in HF patients.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| TTM-Guided Digital Sleep Health Program | Experimental | The experimental group will participate in a nurse-led intervention program titled "TTM-Guided Digital Sleep Health Program," designed to enhance sleep quality in HF patients. The intervention consists of:
Patients will track sleep data using smartwatches and share it via WhatsApp. The intervention follows the TTM, guiding patients through behavior change stages to improve and maintain sleep hygiene. |
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| Usual care group | No Intervention | The control group will not receive any intervention and will continue their routine treatment and follow-up in the outpatient clinic. Surveys will be administered at designated data collection time points, and participants will be asked to keep a sleep diary for 14 days. At the end of the intervention (at the end of the 6th month), written educational material will be provided to individuals in the control group. This material will be created by compiling the sleep hygiene recommendations that were shared with the intervention group. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| TTM-Guided Digital Sleep Health Program | Behavioral | This intervention is a TTM-based sleep health improvement program designed for HF patients. It includes three components: (1) Sleep health education sessions (Weeks 1-4) delivered face-to-face and via telehealth, (2) WhatsApp-based sleep hygiene support (Weeks 5-12) with daily reminders, educational messages, and video content, and (3) Follow-up monitoring (Weeks 13-24) with periodic motivational messages. Patients will track their sleep using smartwatches and share data via WhatsApp. The intervention guides behavior change through TTM stages, promoting sustainable sleep hygiene practices. |
| Measure | Description | Time Frame |
|---|---|---|
| Sleep quality | PSQI is the most widely used scale in international literature to assess subjective sleep quality. This scale was developed by Buysse et al. in 1989 and was adapted into Turkish with validity and reliability studies conducted by Ağargün et al. The diagnostic sensitivity of the PSQI is 89.6%, and its specificity is 86.5%. This self-report questionnaire allows for a detailed assessment of sleep quality, sleep disorders, and their severity over the past month. The scale consists of 18 items grouped into seven components. The maximum possible score is 21; scores above 5 indicate poor sleep quality, while scores below 5 indicate good sleep quality. | from baseline to six months |
| Sleep hygiene | SHI is a 13-item scale designed to assess whether and how frequently individuals engage in activities that affect sleep hygiene. Each item is scored from 1 to 5, with a total score ranging from 13 to 65. The scale evaluates sleep schedule regularity, pre-sleep behaviors that may negatively impact sleep hygiene (e.g., tobacco or caffeine consumption, engaging in demanding tasks, computer use), sleep environment conditions, and pre-sleep anxiety levels. Higher scores indicate poorer sleep hygiene. The scale does not have a validated cutoff score. It was developed in 2006 and later adapted into Turkish with validity and reliability studies conducted in 2015. | from baseline to six months |
| Measure | Description | Time Frame |
|---|---|---|
| Subjective Sleep Quality | MLHFQ was developed in 1987 to assess quality of life in HF patients. The scale consists of 21 items divided into two subdomains: physical functioning (8 items: 2,3,4,5,6,7,12,13) and emotional well-being (5 items: 17,18,19,20,21). Items are rated on a Likert scale from 0 (no impact) to 5 (very much impact). Subdomain scores are obtained by summing responses in each category, while the total score (0-105) reflects overall quality of life. Physical function scores range from 0 to 40, and emotional scores from 0 to 105. Lower scores indicate better quality of life (less dysfunction). The scale was adapted into Turkish with validity and reliability studies conducted in 2009, showing Cronbach's alpha values above 0.70 for subdomains and total scores. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Åžeyma Demir ErbaÅŸ, PhD | Abant Izzet Baysal University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Izzet Baysal Training and Research Hospital | Bolu | Bolu | 14230 | Turkey (Türkiye) |
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| ID | Term |
|---|---|
| D006333 | Heart Failure |
| D020447 | Parasomnias |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D012893 | Sleep Wake Disorders |
| D009422 | Nervous System Diseases |
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| from baseline to six months |
| D001523 |
| Mental Disorders |