資料載入中.....
|
請使用永久網址來引用或連結此文件:
http://libir.tmu.edu.tw/handle/987654321/63494
|
| 題名: | The Diagnosis, Prevalence, and Bereavement Support Interventions for Grief Disorder in Palliative Care |
| 作者: | KUSTANTI, CHRISTINA YENI |
| 貢獻者: | 護理學系博士班
周桂如 |
| 關鍵詞: | meta-analysis;grief disorder;diagnosis;prevalence;bereavement care;bereavement support |
| 日期: | 2023-06-07 |
| 上傳時間: | 2024-01-30 11:38:37 (UTC+8) |
| 摘要: | 背景：之前的研究調查了一般人群的悲傷障礙和非自然死亡的喪親之痛。然而，悲傷障礙診斷工具的性能仍不清楚。此外，由於證據集中在普通人群的悲傷障礙上，因此尚未確定在親人去世後患上悲傷障礙的姑息治療護理人員的百分比。喪親干預的研究檢驗了治療、團體和基於網絡的治療的有效性。還探索了喪親支持以確定其對心理困擾症狀的有效性。尚未研究姑息治療喪親支持干預措施的綜合有效性。
目的：探討姑息治療中悲傷障礙的喪親支持干預的診斷、流行率和有效性。
方法：使用了流行率、診斷和乾預方法的薈萃分析。利用醫學主題詞、關鍵字和布爾運算符的組合對數據庫進行了全面搜索。通過谷歌學術搜索和其他相關網站進行手動搜索，以獲得更多符合條件的研究。 Hoy、QUADAS 2.0 和偏倚風險 2.0 標準評估了研究質量。使用 Comprehensive Meta-Analysis (CMA)、Review Manager 和 R 軟件進行數據分析。使用 I2 和 Cochrane-Q 的值評估研究之間的異質性。進行亞組和元回歸測試以在存在異質性的情況下建立調節變量。進行敏感性分析和發表偏倚測試以評估研究的穩健性。薈萃分析是在 PRISMA 聲明之後報告的，協議已註冊到開放科學框架和 PROSPERO。
結果：六項複雜悲傷量表 (ICG) 研究顯示總體敏感性為 0.93（95%CI：0.87 至 0.97）。同時，特異性為 0.96（95%CI：0.92 至 0.98）。與 0.07 的陰性似然比相比，陽性似然比為 23.4（95%CI：11.2 至 49.0）。長期悲傷障礙 – 13 (PG-13) 的合併特異性值為 0.96（95%CI：0.93 至 0.98），合併敏感性值為 0.51（95%CI：0.42 至 0.6）。 ICG 的匯總靈敏度和特異性的 I2 值分別為 88% 和 82%。
在探索診斷工具的性能後，研究人員調查了因癌症而喪親的個體中悲痛障礙的患病率。使用隨機效應模型是因為 I2 為 91.0%，Q 值為 199.71，p<0.0001。悲傷障礙的合併患病率為 14.2%（95%CI：11.7% 至 16.2%），範圍為 7% 至 39%。去除一項實驗後，敏感性分析顯示為 14.2%。
對於喪親之痛支持的有效性，Hedges 的 g 得分為 –0.198（95%CI：–0.310 至 –0.048）表明喪親之痛支持對悲傷具有統計學上的顯著影響。敏感性分析後，結果仍然顯著，Hedges 的 g 得分為 –0.198（95%CI：–0.309 至 –0.087）。在去除五項具有高偏倚風險的研究後，結果仍然具有統計學意義（Hedges 的 g 分數為 –0.206，95%CI：–0.319 至 –0.014）。 I2 為 44.962%，Q 值為 32.705 (p = 0.018) 表明存在中等異質性。
結論：ICG是一種性能良好的悲傷障礙診斷工具，而PG-13有待進一步探索。使用列出的診斷工具匯集了一組研究，這些研究確定了因癌症相關死亡而導致喪親者的悲傷障礙。與一般人群中的值相比，它們顯示出更高的患病率。喪親支持可被視為可用於喪親護理的方法之一。
Background: Previous studies have examined the general population's grief disorders and the bereavement of unnatural deaths. However, the performance of grief disorder diagnostic instruments remained unclear. Besides, as the evidence focused on grief disorders in the general population, the percentage of palliative care caregivers who develop a grief disorder after a loved one dies has not been identified yet. Studies of bereavement interventions have examined the effectiveness of healing, group, and web-based therapy. Bereavement supports have also been explored to determine their effectiveness towards psychological distress symptoms. The pooled effectiveness of palliative care bereavement support interventions has not been studied.
Objectives: To explore the diagnosis, prevalence, and effectiveness of bereavement support interventions for grief disorder in palliative care.
Methods: Meta-analyses with prevalence, diagnostic, and intervention approaches were used. Databases were comprehensively searched utilizing the combination of Medical Subject Heading Terms, keywords, and Boolean operators. Manual searches were conducted via Google Scholar and other relevant websites for more eligible studies. The Hoy, QUADAS 2.0, and Risk of Bias 2.0 criteria assessed the study quality. Data analyses were performed with Comprehensive Meta-Analysis (CMA), Review Manager, and R software. The heterogeneity between studies was evaluated with the values of I2 and Cochrane-Q. Sub-group and meta-regression tests were conducted to establish the moderator variables in the presence of heterogeneity. Sensitivity analyses and publication bias tests were performed to evaluate the robustness of the study. The meta-analyses were reported following the PRISMA statement, and the protocols were registered to Open Science Framework and PROSPERO.
Results: The six Inventory of Complicated Grief (ICG) studies showed an overall sensitivity of 0.93 (95%CI: 0.87 to 0.97). Meanwhile, the specificity was 0.96 (95%CI: 0.92 to 0.98). Compared to the negative likelihood ratio, which was 0.07, the positive likelihood ratio was 23.4 (95%CI: 11.2 to 49.0). Pooled specificity values for Prolonged Grief Disorder – 13 (PG-13) were 0.96 (95%CI: 0.93 to 0.98), and pooled sensitivity values were 0.51 (95%CI: 0.42 to 0.6). The I2 values for the pooled sensitivity and specificity of the ICG were 88% and 82%, respectively.
After exploring the performance of the diagnosis instruments, the prevalence of grief disorder among bereaved individuals by cancers was investigated. The random-effects model was used because the I2 was 91.0% and Q-value was 199.71 with a p<0.0001. The pooled prevalence of grief disorders was 14.2% (95%CI: 11.7% to 16.2%), ranging from 7% to 39%. The sensitivity analysis showed 14.2% after removing one experiment.
For the effectiveness of bereavement support, the Hedges' g score of –0.198 (95%CI: –0.310 to –0.048) indicates that bereavement support had a statistically significant effect on grief. After sensitivity analysis, the result remained significant, with Hedges' g score of –0.198 (95%CI: –0.309 to –0.087). After removing five studies with a high risk of bias, the result remained statistically significant (Hedges' g score of –0.206, 95%CI: –0.319 to –0.014). I2 at 44.962% and Q-value at 32.705 (p = 0.018) indicated moderate heterogeneity.
Conclusions: ICG was a diagnostic tool for grief disorder with a good performance, while PG-13 needs to be explored more. A group of studies that identified grief disorders among bereaved individuals due to cancer-related deaths was pooled using the diagnostic tools listed. They showed a higher prevalence compared to their value in the general population. Bereavement support can be considered one of the approaches that can be used for bereavement care. |
| 描述: | 博士
指導教授:周桂如
委員:戎瑾如
委員:林彥光
委員:朱信
委員:李信謙
委員:周桂如 |
| 資料類型: | thesis |
| 顯示於類別: | [護理學系] 博碩士論文
|
文件中的檔案:
| 檔案 |
描述 |
大小 | 格式 | 瀏覽次數 |
|---|
| index.html | | 0Kb | HTML | 129 | 檢視/開啟 |
|
在TMUIR中所有的資料項目都受到原著作權保護.
|
