ÖĞRETMEN ADAYLARININ DİJİTAL OKURYAZARLIKLARI İLE YAŞAM BOYU ÖĞRENME BECERİLERİ ARASINDAKİ İLİŞKİNİN İNCELENMESİ

Çalışmada öğretmen adaylarının dijital okuryazarlık ve yaşam boyu öğrenme becerileri incelenmiştir. Eğitim fakültesinde öğrenim gören öğrencilerin dijital okuryazarlık ve yaşam boyu öğrenme becerileri arasındaki ilişkiyi belirlemek amacıyla gerçekleştirilmiştir. Araştırma ilişkisel tarama deseninde yapılan nicel araştırmadır. Üniversite öğrencilerinin bölümleri basit rastlantısal örnekleme modeli ile belirlenmiştir. Farklı bölümlerde öğrenim gören öğrencilerden ise tabakalı örnekleme modeline uygun olacak şekilde 309 kişiden veri toplanmıştır. Veri toplama aracı olarak Tutum’, ‘Teknik’, ‘Bilişsel’ ‘Sosyal’ olmak üzere dört alt boyut ve 17 sorudan oluşan dijital okuryazarlık ölçeği; “Öğrenme” ve “Gelişim” alt boyutları olmak üzere iki alt boyuttan ve 17 sorudan oluşan Yaşam boyu öğrenme ölçeği kullanılmıştır. Çalışma sonuçlarına göre, öğretmen adaylarının dijital okuryazarlık ve yaşam boyu öğrenme becerilerinin yüksek düzeyde olduğu; sivil toplum kuruluşuna üye olma, çevrimiçi kurslara katılım sağlama ve kişisel bilgisayarı bulunma durumlarına göre farklılık gösterdiği belirlenmiştir. Öğretmen adaylarının dijital okuryazarlık ve yaşam boyu öğrenme becerileri arasında ilişki olduğu sonucuna ulaşılmış; yaşam boyu öğrenme becerilerinin öğretmen adaylarının dijital okuryazarlıklarının yordayıcısı olduğu belirlenmiştir

Specialist versus primary care prostate cancer follow-up:A process evaluation of a randomized controlled trial

Background: A randomized controlled trial (RCT) is currently comparing the effectiveness of specialist- versus primary care-based prostate cancer follow-up. This process evaluation assesses the reach and identified constructs for the implementation of primary care-based follow-up. Methods: A mixed-methods approach is used to assess the reach and the implementation through the Consolidated Framework for Implementation Research. We use quantitative data to evaluate the reach of the RCT and qualitative data (interviews) to indicate the perspectives of patients (n = 15), general practitioners (GPs) (n = 10), and specialists (n = 8). Thematic analysis is used to analyze the interview transcripts. Results: In total, we reached 402 (67%) patients from 12 hospitals and randomized them to specialist- (n = 201) or to primary care-based (n = 201) follow-up. From the interviews, we identify several advantages of primary care- versus specialist-based follow-up: it is closer to home, more accessible, and the relationship is more personal. Nevertheless, participants also identified challenges: guidelines should be implemented, communication and collaboration between primary and secondary care should be improved, quality indicators should be collected, and GPs should be compensated. Conclusion: Within an RCT context, 402 (67%) patients and their GPs were willing to receive/provide primary care-based follow-up. If the RCT shows that primary care is equally as effective as specialist-based follow-up, the challenges identified in this study need to be addressed to enable a smooth transition of prostate cancer follow-up to primary care. Netherlands Trial Registry, Trial NL7068 (NTR7266)

Veri madenciliği yaklaşımı ile sosyal ağ analizi

Günümüzde internet kullanmnn yaygnla³masyla geli³tirilen uygulamalar hem ileti³im hem de e§lence amaçl olarak ortaya çkm³tr. Sosyal a§lar olarak adlandrlan bu uygulamalar ki³iler, toplumlar hakknda büyük miktarda veriye internet üzerinden kolay ³ekilde eri³im imkan sunmaktadr. Sosyal a§lar üzerinde yaplan veri madencili§i çal³malar ise son yllarda bu alandaki geli³meler ile art³ göstermi³tir. Pek çok ara³trmann konusu olarak geni³ kitleler hakknda yararl bilgiler elde edilmeye çal³lm³tr. Bu tez çal³masnda sosyal a§larda yaplan veri madencili§i çal³malar ve problemleri ara³trlm³tr. Twitter uygulamas üzerinden verilere eri³ilerek Türkçe Tweetlerin duygu analizi yaplm³tr. Duygu snandrma i³lemi için Naive Bayes, Destek Vektör Makineleri ve K en yakn kom³u algoritmalar kullanlm³tr. Twitter kullanclarnn belirlenen sektördeki kurumsal ³irketler ile ilgili tweetleri duygu polaritesi açsndan incelenerek sosyal a§lar üzerinde kurumsal itibar en yüksek kurulu³ tespit edilmeye çal³lm³tr.azarlk Beyan iii Öz iv Te³ekkür vi ekil Listesi x Tablo Listesi xi Ksaltmalar xii 1 Giri³ 1 2 Veri Madencili§i 3 2.1 Veri Madencili§i Nedir? . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Veri Madencili§i Geli³im Süreci . . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Veri Madencili§i Modelleri . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3.1 Tanmlayc Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3.2 Tahmin Edici Model . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3 Veri Madencili§i A³amalar 8 3.1 Problemi Anlama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.1.1 Prol Analizi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.1.2 Segmentasyon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.1.3 Yant Modeli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.1.4 Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3.1.5 Aktivasyon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.1.6 Çapraz Sat³ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.1.7 Ypranma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.1.8 Net Bugünkü De§er . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.1.9 Ömür Boyu De§er . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.2 Veriyi Anlama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 Modelleme için Veri Seçme . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.4 Modelleme Metodolojisini Seçme . . . . . . . . . . . . . . . . . . . . . . . 15 3.5 Veri Hazrlama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.5.1 Örnekleme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.5.2 Veri Kalitesinin Sürdürülmesi . . . . . . . . . . . . . . . . . . . . . 16 3.5.3 Aykr De§er Analizi . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.5.4 Kayp De§er . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 3.6 De§i³kenlerin Seçimi ve Dönü³türülmesi . . . . . . . . . . . . . . . . . . . 18 3.7 Modelin Uygulanmas ve De§erlendirilmesi . . . . . . . . . . . . . . . . . . 18 3.8 Modelin Kullanlmas ve zlenmesi . . . . . . . . . . . . . . . . . . . . . . 19 3.8.1 De§erleme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.8.2 Yaynlama . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 4 Veri Madencili§i ³levleri 21 4.1 Karakterizasyon ve Ayrt Etme . . . . . . . . . . . . . . . . . . . . . . . . 21 4.2 Birliktelik Kural . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.3 Snandrma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.4 Tahmin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.5 Kümeleme Analizi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 4.6 Aykr Veri Analizi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.7 De§i³im Analizi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 4.8 Görselle³tirme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 5 Veri Madencili§i Algoritmalar 26 5.1 Karar A§açlar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 5.2 Genetik Algoritmalar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 5.3 Sinir A§lar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.4 statistik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 6 Veri Madencili§i Uygulama Alanlar 32 6.1 Bilimsel ve Mühendislik Verileri . . . . . . . . . . . . . . . . . . . . . . . . 32 6.2 Sa§lk Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 6.3 ³ Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 6.4 Al³veri³ Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6.5 Bankaclk ve Finans Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6.6 E§itim Alan Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6.7 nternet Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6.8 Doküman Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 6.9 Askeri Veriler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 6.10 Sosyal A§ Verileri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 7 Sosyal A§lar 35 7.1 Çizge Teorisi Yakla³m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 7.2 Sosyal A§larn Genel Özellikleri . . . . . . . . . . . . . . . . . . . . . . . . 36 7.3 Sosyal A§ Uygulamalarnda leti³im . . . . . . . . . . . . . . . . . . . . . 37 7.4 Sosyal A§ Uygulamalar . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 8 Sosyal A§larda Veri Madencili§i 38 8.1 Web Madencili§i . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 8.2 Sosyal A§larda Web Madencili§i . . . . . . . . . . . . . . . . . . . . . . . 39 8.2.1 Kaynak Bulma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 8.2.2 Bilgi Çkarm ve Ön ³leme . . . . . . . . . . . . . . . . . . . . . . 40 8.2.3 Genelle³tirme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 8.2.4 Çözümleme (Analiz) . . . . . . . . . . . . . . . . . . . . . . . . . . 40 8.3 Web Madencili§i Yöntemleri . . . . . . . . . . . . . . . . . . . . . . . . . . 40 8.3.1 Web çerik Madencili§i . . . . . . . . . . . . . . . . . . . . . . . . . 41 8.3.2 Web Yap Madencili§i . . . . . . . . . . . . . . . . . . . . . . . . . 41 8.3.3 Web Kullanm Madencili§i . . . . . . . . . . . . . . . . . . . . . . . 41 8.4 Fikir Madencili§i . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 8.5 lgili Çal³malar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 9 Uygulama 51 9.1 Veri Seti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 9.2 Uygulamada Kullanlan Program . . . . . . . . . . . . . . . . . . . . . . . 52 9.3 Yaplan Çal³ma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 9.4 De§erlendirme Ölçütleri . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 9.4.1 Do§ruluk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 9.4.2 Hassasiyet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 9.4.3 Kesinlik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 9.4.4 Hatal Pozitif Oran . . . . . . . . . . . . . . . . . . . . . . . . . . 69 9.4.5 E§ri Alt Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 9.5 Analiz Sonuçlar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 10 Sonuç 80 A Java Kodu 81 B Mutluluk/Üzgünlük Bildiren Karakter ve Kelimeler 83 Kaynaklar 8

Dexmedetomidine-fentanyl combination in awake craniotomy Uyanık kraniyotomide deksmedetomidin-fentanil kombinasyonu

Awake craniotomy is a common procedure in resection of lesions near critical functional regions, particularly the speech and motor areas. During awake craniotomy, patients need to be fully alert and cooperative during testing. On the other hand, it is desirable to keep them sedated, avoiding discomfort, anxiety and pain over the rest of the surgery. In this case report, we report our successful use of dexmedetomidine-fentanyl combination for sedation in intracranial tumor resection with awake craniotomy. Dexmedetomidine-fentanyl combination was well tolerated in this adolescent patient and provided good surgical conditions and patient comfort during tumor resection and testing

Diş Çekimi Sonrası Bilateral Santral Seröz Koryoretinopat

Kırkiki yaşında erkek hasta, yaklaşık 2 haftadır özellikle okur-ken aniden görme bulanıklaşması ile kliniğimize başvurdu. Detaylı hikâyesinde hastanın diş ağrısı nedeniyle diş hekimine başvurduğu öğrenildi. Hastanın okuma ile ilgili şikâyetleri diş çekiminden 2 hafta sonra başlamıştı. Hasta diş çekilmesinden 1 ay öncesinde amoksisilin, sonrasında 2 hafta süreyle non-steroid anti-inflamatuar ilaç kullanmıştı. Bu vakada diş çekimi sonra-sında görülen çift taraflı SSKR olgusu sunulmuşturA 42-year-old male presented to our clinic with acute blurring of vision in both eyes especially in reading for about 2 weeks. Detailed history revealed that the patient recently applied to his dentist because of tooth ache. The patient's complaints abo-ut reading had started 2 weeks after tooth extraction. He had a medication of amoxicillin for a month prior to tooth removal and non-steroidal anti-inflammatory drugs after extraction. In this case we report a bilateral CSCR case after tooth extractio

The Results of Toric Intraocular Lens Implantation in Cataract Patients with Preexistıng Corneal Astigmatism

Amaç: Kataraktı ve ?1.0 D korneal astigmatizması olan gözlerde fakoemülsifikasyon cerrahisi sonrasında uygulanan torik göziçi lens implantasyonunun görsel ve refraktif sonuçlarının değerlendirilmesi. Gereç ve Yöntemler: Özel Kudret Göz Hastanesinde 2010-2012 yılları arasında kataraktı ve ?1.0 D korneal astigmatizması olan komplikasyonsuz fakoemülsifikasyon cerrahisi sonrasında torik göziçi lens implantasyonu uygulanmış 18 hastanın 26 gözüne ait veriler retrospektif olarak incelendi. Hastaların cerrahi öncesi ve 1.ay, 3.ay, 6.ay düzeltilmemiş ve en iyi düzeltilmiş görme keskinlikleri (logMAR), astigmatizma değerleri, rotasyon dereceleri kaydedildi. Bulgular: Hastaların ortalama yaşı 57.8±15.4 (47-78) yıl olup 12 hasta kadın ve 6 hasta erkekti. Cerrahi sonrası takip süresi 4.1±2.3 (1-12) ay idi. Cerrahi öncesi düzeltilmemiş GK 1.03±0.32 (logMAR) ve düzeltilmiş GK 0.48±0.25 (logMAR) iken cerrahi sonrası 1. ayda düzeltilmemiş GK 0.32±0.28 (logMAR) ve düzeltilmiş uzak GK 0.18±0.15 (logMAR) seviyesinde idi. Ortalama refraktif silindirik değerler cerrahi öncesinde -2.94±1.0 D ve cerrahi sonrası 1. ayda -0.65±0.60 D saptandı. Son kontrol muayenelerinde GK 0.13±0.15 (logMAR) seviyesine yükseldi ve astigmatizma değeri -0.79±0.65 D saptandı. Cerrahi sonrası 1. ayda yapılan kontrollerde GİL rotasyon değerleri 6.42±2.45 derece ölçüldü. Tartışma: Katarakt cerrahisinde torik göziçi lens implantasyonu cerrahi öncesi korneal astigmatizmayı düzeltmek için etkili ve güvenilir bir cerrahi seçenektir. Çalışmamızda torik GİL implantasyonunun astigmatizmayı belirgin olarak azalttığı, görme keskinliğinde belirgin düzelme sağladığı gösterilmiştir.Purpose: Evaluating visual and refractive results of toric intraocular lens implantation after phacoemulsification surgery in patients with cataract and ≥1.0 D corneal astigmatism. Materials and Methods: The records of 26 eyes of 18 patients who had cataract, ≥1.0 D corneal astigmatism and undergone uncomplicated phacoemulsification surgery with toric intraocular lens implantation between 2010 and 2012 were retrospectively evaluated. Uncorrected and best corrected visual acuity (logMAR), astigmatism values preoperatively and in the postoperative first, third and sixth month and intraocular lens axis rotation degrees were recorded. Results: The mean age was 57.8±15.4 (47-78) years. Twelve were women and 6 were men. The mean postoperative follow up period was 4.1±2.3 (1-12) months. Preoperative uncorrected visual acuity was 1.03±0.32 (logMAR) and best corrected visual acuity was 0.48±0.25 (logMAR). In the postoperative first month uncorrected visual acuity was 0.32±0.28 (logMAR) and best corrected visual acuity was 0.18±0.15 (logMAR). The mean cylinder values was -2.94±1.0 D preoperatively and -0.65±0.60 D in the postoperative first month. At last visits the mean best corrected visual acuity was improved to 0.13±0.15 (logMAR) and the mean astigmatism values was -0.79±0.65 D. The mean axis rotation was 6.42±2.45 degree in the first postoperative month. Conclusion: Toric intraocular lens implantation is an effective safe surgical option in correcting preexisting corneal astigmatism. In our study it is shown that toric intraocular lens implantation reduced astigmatism and improved visual acuity significantly

Specialist versus Primary Care Prostate Cancer Follow-Up: A Process Evaluation of a Randomized Controlled Trial

Background: A randomized controlled trial (RCT) is currently comparing the effectiveness of specialist-versus primary care-based prostate cancer follow-up. This process evaluation assesses the reach and identified constructs for the implementation of primary care-based follow-up. Methods: A mixed-methods approach is used to assess the reach and the implementation through the Consolidated Framework for Implementation Research. We use quantitative data to evaluate the reach of the RCT and qualitative data (interviews) to indicate the perspectives of patients (n = 15), general practitioners (GPs) (n = 10), and specialists (n = 8). Thematic analysis is used to analyze the interview transcripts. Results: In total, we reached 402 (67%) patients from 12 hospitals and randomized them to specialist-(n = 201) or to primary care-based (n = 201) follow-up. From the interviews, we identify several advantages of primary care-versus specialist-based follow-up: it is closer to home, more accessible, and the relationship is more personal. Nevertheless, participants also identified challenges: guidelines should be implemented, communication and collaboration between primary and secondary care should be improved, quality indicators should be collected, and GPs should be compensated. Conclusion: Within an RCT context, 402 (67%) patients and their GPs were willing to receive/provide primary care-based follow-up. If the RCT shows that primary care is equally as effective as specialist-based follow-up, the challenges identified in this study need to be addressed to enable a smooth transition of prostate cancer follow-up to primary care

Reliability And Validity Of The Schedule For Affective Disorders And Schizophrenia For School-Age Children-Present And Lifetime Version, Dsm-5 November 2016-Turkish Adaptation (K-Sads-Pl-Dsm-5-T)

Objective: The aim of this study was evaluate the reliability and validity of the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version, DSM-5 November 2016 -Turkish Adaptation (K-SADS-PL-DSM-5-T). Method: A total of 150 children and adolescents between 6 and 17 years of age were assessed with K-SADS-PL-DSM-5-T. The degree of agreement between the DSM-5 criteria diagnoses and the K-SADS-PL-DSM-5-T diagnoses were considered as the measure of consensus validity. In addition, concurrent validity was examined by analyzing the correlation between the diagnoses on K-SADS-PL-DSM-5-T and relevant scales. Interrater reliabilities were assessed on randomly selected 20 participants. Likewise, randomly selected 20 other participants were interviewed with K-SADS-PL-DSM-5-T three weeks after the first interview to evaluate test-retest reliability. Results: The consistency of diagnoses was almost perfect for eating disorders, selective mutism and autism spectrum disorder (K=0.92-1.0), substantial for elimination disorders, obsessive-compulsive disorder, oppositional defiant disorder, generalized anxiety disorder, social anxiety disorder, depressive disorders, disruptive mood dysregulation disorder and attention deficit hyperactivity disorder (K=0.67-0.80). Interrater reliability was perfect for selective mucism (K=1.0), substantial for oppositional defiant disorder, disruptive mood dysregulation disorder, attention deficit hyperactivity disorder, depressive disorders and social anxiety disorder (K=0.63-0.73). Test-retest reliability was almost perfect for autism spectrum disorder (K=0.82), substantial for attention deficit hyperactivity disorder, oppositional defiant disorder, disruptive mood dysregulation disorder, depressive disorders and generalized anxiety disorder (K=0.62-0.78). Conclusion: The results of this study show that the K-SADS-PL-DSM-5-T is an effective instrument for diagnosing major childhood psychiatric disorders including selective mutism, disruptive mood dysregulation disorder and autism spectrum disorder which have recently been added to the schedule.WoSScopu

Quality of early prostate cancer follow-up care from the patients’ perspective

Purpose: To develop optimal cancer survivorship care programs, this study assessed the quality of prostate cancer follow-up care as experienced by patients shortly after completion of primary treatment. Methods: We surveyed 402 patients with localized prostate cancer participating in a randomized controlled trial comparing specialist versus primary care–based follow-up. For the current study, we used patient-reported data at the time of the first follow-up visit at the hospital, prior to randomization. We assessed patients’ ratings of the quality of follow-up care using the Assessment of Patient Experiences of Cancer Care survey. This survey includes 13 scales about different aspects of care and an overall rating of care. Multivariable linear regression analysis was used to identify factors associated with perceived follow-up quality. Results: Patients reported positive experiences at first follow-up for 9 of 13 scales, with mean (M) scores ranging from 79 to 97 (on a 0–100 response scale). Patients reported most frequently (over 70%) suboptimal care regarding symptom management (84%; M = 44, SD = 37), health promotion (75%; M = 45, SD = 39), and physician’s knowledge about patients’ life (84%; M = 65, SD = 23). Overall, patients’ lower quality of follow-up ratings were associated with younger age, higher education level, having more than one comorbid condition, having undergone primary surgery, and experiencing significant symptoms. Conclusion: Patients with prostate cancer are generally positive about their initial, hospital-based follow-up care. However, efforts should be made to improve symptom management, health promotion, and physician’s knowledge about patients’ life. These findings point to areas where prostate cancer follow-up care can be improved