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Exploring the Psychosocial Impact of Hospitalization for COVID-19: Insights from Patient Experiences

Year: 2024
Type: article
Abstract: Background The COVID-19 pandemic has severely tested the organizational structure and operational effectiveness of healthcare systems. We aimed to explore the experiences of patients who have been hospitalized due to COVID-19. Methods Employing purposive sampling, semi-structured interviews were conducted covering eight topics: 1) the experience of COVID-19 diagnosis, 2) the most difficult moments during hospitalization, 3) difficulties related to hospital conditions and safety protocols, 4) interactions with healthcare professionals, 5) received support, 6) social stigma, 7) concerns about the future, and 8) post-COVID and long COVID syndrome. Twelve individuals (six women and six men; mean age 57.5 (SD = 13) years; mean length of stay 18.1 (SD = 3.1) days) participated. The data analysis was carried out using the phenomenological method according to Colaizzi. Results Patients reported a spectrum of emotions including loneliness, isolation, abandonment, disappointment, insecurity and fear of death. Interactions with healthcare professionals revealed a dichotomy: experiences of respectful, reassuring care contrasted with encounters lacking psycho-emotional support within an impersonal healthcare setting. Conclusions This study sheds light on the experiences of patients on the nursing wards and their psychosocial burden. Most of them reported negative emotions such as loneliness, isolation, sadness, fear and anxiety rather than positive experiences such as hope, interpersonal connectedness, self-identity, empathy, caring and safety. Key messages • The study highlights psychosocial challenges for COVID-19 patients, emphasizing the urgent need for robust support systems. • The study provides insights for future similar situations and highlights the need for adaptable care models based on principles such as empathy, safety and personalized approaches.
Language: English
Field: Psychology
Open Access status: gold
Estimated APC paid: $3,199
OpenAlex ID: W4403825336
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