A domesticated shopping mall in modern Tehran

Habibi, Rana

doi:10.4324/9781315584799-6

Cited by 2 publications

(2 citation statements)

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“…As a final step, modeling was performed using “path analysis” in Amos®. Path analysis states which path is more important or meaningful (Habibi and Sarabadani, 2022).…”

Section: Methodsmentioning

confidence: 99%

Extraction of effective cycles on reducing patients’ depression in the design of treatment spaces

Faghiholislam,

Azemati,

Keshmiri

et al. 2023

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Purpose The most common reaction to an acute physical illness is anxiety, which may be followed by depression. In patients with chronic diseases, the prevalence of anxiety disorders and depression is almost twice as high as in other diseases. This study aims to extract prominent components in the design of treatment spaces on reducing hospitalized patients’ depression from both experts and patients/users’ point of views. A final model is also presented based on the findings. Design/methodology/approach This research used an exploratory mixed method. The effective components were extracted through the administration of two Likert-scale researcher-made questionnaires in two phases. Q factor analysis was conducted to reach the components. A total of 205 patients were admitted to Namazi Hospital in Shiraz, and 20 architecture and psychology experts participated in the survey. Final modeling of the data was done through path analysis. Findings Six factors were found to be effective by experts in reducing depression in therapeutic spaces: nature-oriented space, targeted social space, diverse space, visual comfort, logical process and safe space. On the part of patients, seven components were deemed to be effective: visual perception, naturalism, functionalism, physical security, logical process, psychological safety and diversity. Also, four main cycles were extracted from the final model with the direct effect of diversity and the other five cycles were mediated by naturalism. Research limitations/implications A total of 15 interviews with architects and psychologists, who were available at the time of the study, were conducted in January 2018. The only general question during interviews was “In your opinion, what factors are effective in reducing the level of depression of patients in the design of treatment spaces?” This may have limited the range of factors that could be surveyed in the study. After collecting the effective factors from the aforementioned expert’s points of view, the questionnaire of experts was designed (Appendix). The expert questionnaires were distributed and edited in two stages in January 2019 among 20 architect experts who were available at the time of the study. The one-year interval between designing and administering the questionnaires occurred because of the limitations posed by the COVID-19 pandemic situation. However, the interval did not pose methodological obstacles for the study. Originality/value Evidence-based investigation of the effectiveness of proper design components of therapeutic spaces in reducing the symptoms of patients with chronic secondary depression has received little attention in the literature. Using a “conceptual model,” the present study brought the issue into its focus so as to find effective components in the design of treatment spaces that can alleviate depression symptoms in chronically hospitalized patients.

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“…As a final step, modeling was performed using “path analysis” in Amos®. Path analysis states which path is more important or meaningful (Habibi and Sarabadani, 2022).…”

Section: Methodsmentioning

confidence: 99%

Extraction of effective cycles on reducing patients’ depression in the design of treatment spaces

Faghiholislam,

Azemati,

Keshmiri

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Therefore, our analysis applied residential floor area per capita (m 2 /person) to measure the socio-economic inequality in hospitals and hospital beds because there was no data on income per capita of the people. Despite income per capita is a direct measure of SES [28], the residential floor area per capita is a comprehensive indicator of the economic, social, cultural, and environmental dimensions of people living in a given urban area [35, 36].…”

Section: Methodsmentioning

confidence: 99%

Inequality in geographical distribution of hospitals and hospital beds in densely populated metropolitan cities of Iran

Chavehpour

Rashidian

Woldemichael

et al. 2019

BMC Health Serv Res

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Background This study aims to assess geographical distribution of hospitals and extent of inequalities in hospital beds against socioeconomic status (SES) of residents of five metropolitan cities in Iran. Methods A cross-sectional analysis was conducted to measure geographical inequality in hospital and hospital bed distributions of 68 districts in five metropolitan cities during 2016 using geographic information system (GIS), and Gini and Concentration indices. Correlation analysis was performed to show the relationship between the SES and inequality in hospital beds densities. Results The study uncovered marked inequalities in hospitals and hospital beds distributions. The Gini indices for hospital beds were greater than 0.55. The aggregated concentration indices for public and private hospital beds were 0.33 and 0.49, respectively. The GIS revealed that 216 (70.6%) hospitals were located in two highest socioeconomic status classes in the cities. Only 29 (9.5%) hospitals were located in the lowest class. The public, private, and the cumulative hospitals beds distributions in Tehran and Esfahan showed significant ( p < 0.05) positive correlation with SES of the residents. Conclusions The high inequalities in hospital and hospital beds distributions in our study imply an overlooked but growing concern for geographical access to healthcare in rapidly urbanizing metropolitan cities in Iran. Thus, regardless of ownership, decision-makers should emphasize the disadvantaged areas in metropolitan cities when need arises for the establishment of new healthcare facilities in order to ensure fairness in healthcare. The metropolitan cities and rapid urbanization settings in other countries could learn lessons to reduce or prevent similar issues which might have hampered access to healthcare.

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A domesticated shopping mall in modern Tehran

Cited by 2 publications

References 0 publications

Extraction of effective cycles on reducing patients’ depression in the design of treatment spaces

Extraction of effective cycles on reducing patients’ depression in the design of treatment spaces

Inequality in geographical distribution of hospitals and hospital beds in densely populated metropolitan cities of Iran

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