Self-care Behaviors and Technology Used During COVID-19: Systematic Review
Bibliographic record
Abstract
BACKGROUND: Self-care behaviors are essential for people living with chronic conditions; however, the outbreak of the COVID-19 pandemic has imposed additional complications on their daily routines. Few studies have analyzed how self-care behaviors have changed during COVID-19 and the role of digital technology, especially among people with chronic conditions. OBJECTIVE: This study aims to review how self-care behaviors have changed for people with chronic conditions during the COVID-19 pandemic, and what technology they have adopted to manage their conditions during that period. METHODS: A systematic review was conducted using narrative synthesis. Data were extracted from PubMed, MEDLINE, EMBASE, PsycINFO, CINAHL, and Google Scholar, including articles from December 2019 onward. Eligible studies focused on adults diagnosed with chronic conditions undertaking any self-care tasks in line with the middle-range theory of self-care of chronic illness (ie, self-care maintenance, monitoring, and management). The methodological quality of the included articles was assessed with the McMaster Critical Review Forms for Quantitative or Qualitative Studies. RESULTS: In total, 36 primary research articles were included. Changes to self-care behaviors during COVID-19 among people with chronic conditions were organized according to the middle-range theory of self-care of chronic illness focusing on self-care maintenance (ie, medication adherence, physical activity, and diet control), self-care monitoring (ie, monitoring signs and symptoms), and self-care management (ie, consultations with health care providers). Positive self-care behaviors observed include the following: individuals trying to maintain good glycemic control during COVID-19 increased their medication adherence in 27% (10/36) of studies; and diet control improved in 50% (18/36) of studies. Negative self-care behaviors observed include the following: decline in physical activities and increased sedentariness were observed in 65% (23/36) of studies; poor diet control was observed in 57% (21/36) of studies; and self-monitoring of health status dropped in 43% (15/36) of studies. The use of technology to support self-care of chronic conditions during COVID-19 was reported in 72% (26/36) of studies. The actual use of telehealth in place of physical consultations during COVID-19 was observed in 50% (18/36) of studies, and other digital technologies (eg, social media apps, smartphone apps, web-based platforms, and web browsing) were used in 50% (18/36) of studies. Telehealth was discussed and recommended as the default technology in delivering future health care services during COVID-19 and beyond in 77% (28/36) of studies. CONCLUSIONS: This review highlighted the necessity to rethink how models of self-care should continue to address the demands of chronic conditions while being responsive to the imminent threats of infectious diseases. Perhaps the silver lining of COVID-19 is that adoption of digital technology (especially telehealth) among a vast cross-section of people with chronic conditions is possible. Future research should investigate effective ways to incorporate evidence-based digital health tools into these new models of self-care that address the challenges of chronic and infectious conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".