1.Relationship of trust on selected health information sources and COVID-19 vaccine acceptance among older adults
Eunice Simone R. Tung ; Danielle Janica Ballescas ; Xyle Arani Ysabel B. Balquiedra ; Rowell Kian B. Carig ; Rommel Angelo P. Sanchez ; Vincent Gerald M. Santos ; Janelle P. Castro ; Tricia Kaye F. Palola ; Jocelyn M. Molo
Health Sciences Journal 2023;12(2):78-84
Introduction:
In order to suppress the COVID-19 virus, several vaccines have been developed. The
administration of COVID-19 vaccines entails its acceptance. However, misinformation and vaccine
uncertainty are main factors that affect vaccine acceptance. This study aimed to determine the most
trusted health information source, the most frequently accessed health information source, and health
literacy of older adults within Metro Manila.
Methods:
This study employed a quantitative non-experimental design utilizing correlational and descriptive
approaches. Convenience sampling was utilized via Facebook to recruit participants. The survey was
adapted from four different questionnaires and went through reliability testing and expert validation.
Results
The researchers collected responses from a total of 123 participants. The participants were noted
to have an overall high level of acceptance for the COVID-19 vaccine ( 4.10, SD ± 0.22).
The study revealed that doctors were the highly trusted health information source (( =3.69, SD ± 1.30),
followed by government health agencies (( =3.18, SD ± 0.73), whereas religious organizations and leaders
(( =2.45, SD ± 0.48) were the least trusted sources. However, despite being the least trusted source,
religious organizations and leaders were shown to be positively related (p=0.049) and highly predictive of
COVID-19 vaccine acceptance. The most frequently accessed health information source, health workers,
have a weak correlation (r=.323) and were found to be significantly positively related (p=0.008) and highly
predictive of the acceptance of the COVID-19 vaccine. The credibility of health information sources is
likely to influence their selection, influencing decisions and behaviors.
SARS-CoV-2
;
Geriatrics
2.A correlational study of burnout, compassion fatigue, and moral injury related to resilience of nurses in COVID-19 wards of a public hospital in Metro Manila.
Adam Zedrick Z. Bautista ; Mark Joshua T. Baptista ; Alexine Jan Kiana D. Cortez ; Ivanabel E. Echaluse ; Erica Kaye A. Guiling ; Joshua M. Sabando ; Jill Hannah N. Tolentino ; Alena Kyrene C. Varez ; Jocelyn M. Molo ; Janelle P. Castro ; Tricia Kaye P. Valerio
Health Sciences Journal 2023;12(1):37-43
INTRODUCTION:
Increased healthcare demands due to the COVID-19 pandemic have overwhelmed nurses
worldwide. Resilience of nurses has been impacted due to many factors (e.g., longer work shifts) causing
psychological distress. The study aimed to determine the correlation of burnout, compassion fatigue,
and moral injury with resilience among nurses assigned in COVID-19 wards.
METHODS:
Virtual survey tools were sent to nurses of a public hospital to obtain data. Data were analyzed
using JAMOVI and SPSS.
RESULTS:
Levels of burnout showed moderate burnout in personal burnout (f=44) (65.7%); Moderate
burnout in work-telated burnout (f=36) (53.7%); no/low level of burnout in client-related burnout (f=48)
(71.6%). Level of compassion fatigue showed job burnout (f=59) (88.1%). Level of moral injury indicated
“requiring clinical attention” (f=52) (77.6%). Level of resilience showed medium resilience (f=45) (67.2%).
Correlation between burnout and resilience yielded negligible negative correlations between personal
burnout and resilience (r=-0.160, p=0.031), work-related burnout and resilience (r=-0.222, p=0.008), and
client-related burnout and resilience (r=-0.120, p=0.741). Correlation yielded weak negative correlations
between compassion fatigue and resilience (r=-0.254, p=0.038) and between moral injury and resilience
(r=-0.318, p=0.009). The linear regression showed no significant correlations between personal burnout
and resilience (p=0.063), work-related burnout and resilience (p=0.070), client-related burnout and
resilience (p=0.331), compassion fatigue and resilience (p=0.080), moral injury and resilience (p=0.227).
CONCLUSION
The findings showed significant correlations between personal burnout and resilience, work-
related burnout and resilience, compassion fatigue and resilience, and moral injury and resilience. There
were no significant correlations between client-related burnout and resilience. Multiple linear regression
indicated burnout, compassion fatigue, and moral injury are not predictive factors for resilience.
Resilience
;
burnout
;
compassion fatigue
;
moral injury