scholarly journals Cancer Risk Assessment Tools in Primary Care: A Systematic Review of Randomized Controlled Trials

2015 ◽  
Vol 13 (5) ◽  
pp. 480-489 ◽  
Author(s):  
J. G. Walker ◽  
S. Licqurish ◽  
P. P. C. Chiang ◽  
M. Pirotta ◽  
J. D. Emery
Keyword(s):  
Systematic Review ◽  
Risk Assessment ◽  
Primary Care ◽  
Cancer Risk ◽  
Randomized Controlled Trials ◽  
Assessment Tools ◽  
Cancer Risk Assessment ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Risk Assessment Tools

scholarly journals Practical and validated tool to assess falls risk in the primary care setting: a systematic review

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e045431
Author(s):  
Wytske MA Meekes ◽  
Joke C Korevaar ◽  
Chantal J Leemrijse ◽  
Ien AM van de Goor
Keyword(s):  
Systematic Review ◽  
Risk Assessment ◽  
Primary Care ◽  
Older People ◽  
Care Setting ◽  
Primary Care Setting ◽  
Predictive Performance ◽  
Assessment Tools ◽  
Falls Risk ◽  
Risk Assessment Tools

ObjectiveAlthough several falls risk assessment tools are available, it is unclear which have been validated and which would be most suitable for primary care practices. This systematic review aims to identify the most suitable falls risk assessment tool for the primary care setting (ie, requires limited time, no expensive equipment and no additional space) and that has good predictive performance in the assessment of falls risk among older people living independently.DesignA systematic review based on prospective studies.MethodsAn extensive search was conducted in the following databases: PubMed, Embase, CINAHL, Cochrane and PsycINFO. Tools were excluded if they required expensive and/or advanced software that is not usually available in primary care units and if they had not been validated in at least three different studies. Of 2492 articles published between January 2000 and July 2020, 27 were included.ResultsSix falls risk assessment tools were identified: Timed Up and Go (TUG) test, Gait Speed test, Berg Balance Scale, Performance Oriented Mobility Assessment, Functional Reach test and falls history. Most articles reported area under the curve (AUC) values ranging from 0.5 to 0.7 for these tools. Sensitivity and specificity varied substantially across studies (eg, TUG, sensitivity:10%–83.3%, specificity:28.4%–96.6%).ConclusionsGiven that none of the falls risk assessment tools had sufficient predictive performance (AUC <0.7), other ways of assessing high falls risk among independently living older people in primary care should be investigated. For now, the most suitable way to assess falls risk in the primary care setting appears to involve asking patients about their falls history. Compared with the other five tools, the falls history requires the least amount of time, no expensive equipment, no training and no spatial adjustments. The clinical judgement of healthcare professionals continues to be most important, as it enables the identification of high falls risk even for patients with no falls history.Trial registraion numberThe Netherlands Trial Register, NL7917; Pre-results.

scholarly journals A systematic review of artificial intelligence chatbots for promoting physical activity, healthy diet, and weight loss

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Yoo Jung Oh ◽  
Jingwen Zhang ◽  
Min-Lin Fang ◽  
Yoshimi Fukuoka
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Randomized Controlled Trials ◽  
Weight Management ◽  
Weight Status ◽  
Experimental Studies ◽  
Assessment Tools ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Quasi Experimental

Abstract Background This systematic review aimed to evaluate AI chatbot characteristics, functions, and core conversational capacities and investigate whether AI chatbot interventions were effective in changing physical activity, healthy eating, weight management behaviors, and other related health outcomes. Methods In collaboration with a medical librarian, six electronic bibliographic databases (PubMed, EMBASE, ACM Digital Library, Web of Science, PsycINFO, and IEEE) were searched to identify relevant studies. Only randomized controlled trials or quasi-experimental studies were included. Studies were screened by two independent reviewers, and any discrepancy was resolved by a third reviewer. The National Institutes of Health quality assessment tools were used to assess risk of bias in individual studies. We applied the AI Chatbot Behavior Change Model to characterize components of chatbot interventions, including chatbot characteristics, persuasive and relational capacity, and evaluation of outcomes. Results The database search retrieved 1692 citations, and 9 studies met the inclusion criteria. Of the 9 studies, 4 were randomized controlled trials and 5 were quasi-experimental studies. Five out of the seven studies suggest chatbot interventions are promising strategies in increasing physical activity. In contrast, the number of studies focusing on changing diet and weight status was limited. Outcome assessments, however, were reported inconsistently across the studies. Eighty-nine and thirty-three percent of the studies specified a name and gender (i.e., woman) of the chatbot, respectively. Over half (56%) of the studies used a constrained chatbot (i.e., rule-based), while the remaining studies used unconstrained chatbots that resemble human-to-human communication. Conclusion Chatbots may improve physical activity, but we were not able to make definitive conclusions regarding the efficacy of chatbot interventions on physical activity, diet, and weight management/loss. Application of AI chatbots is an emerging field of research in lifestyle modification programs and is expected to grow exponentially. Thus, standardization of designing and reporting chatbot interventions is warranted in the near future. Systematic review registration International Prospective Register of Systematic Reviews (PROSPERO): CRD42020216761.

scholarly journals Hubungan Interval Waktu Antara Usia Menarche Dan Usia Saat Melahirkan Anak Pertama Cukup Bulan Dengan Kejadian Kanker Payudara Di Rsup Dr.M.Djamil Padang Pada Tahun 2014-2017

2019 ◽  
Vol 8 (1) ◽  
pp. 10
Author(s):  
Rusydah Syarlina ◽  
Azamris Azamris ◽  
Avit Suchitra ◽  
Wirsma Arif Harahap
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
National Cancer Institute ◽  
Case Control ◽  
Assessment Tools ◽  
Cancer Risk Assessment ◽  
Breast Cancer Risk Assessment ◽  
Risk Assessment Tools

Interval usia saat menarche dan usia saat melahirkan anak pertama cukup bulan merupakan panjang waktu antara usia saat haid pertama kali dan usia saat melahirkan bayi cukup bulan pertama kali. Interval ini diduga merupakan salah satu faktor risiko terhadap KPD. Tujuan penelitian ini adalah menentukan hubungan antara interval usia saat menarche dan usia saat melahirkan anak pertama cukup bulan terhadap kejadian kanker payudara di RSUP Dr.M.Djamil Padang pada tahun 2014-2017. Penelitian ini merupakan studi case control terhadap 102 orang yang terbagi menjadi 2 kelompok, yaitu kelompok kasus dan kelompok kontrol. Pengumpulan data dilakukan melalui wawancara menggunakan tabel faktor risiko kanker payudara yang merupakan modifikasi dari Breast Cancer Risk Assessment Tools–National Cancer Institute dan data pasien dari bagian Bedah RSUP Dr.M.Djamil Padang tahun 2014-2017. Hasil analisis statistik menunjukkan usia menarche tertinggi pada kasus adalah 12 dan 13 tahun dan pada kontrol 13 tahun. Usia saat melahirkan anak pertama cukup bulan tertinggi pada kasus dan kontrol adalah 23 tahun. Frekuensi berdasarkan interval waktu usia menarche dan usia saat melahirkan anak pertama cukup bulan ≥ 10 tahun pada kasus dan kontrol secara berurutan adalah 58,8% dan 66,7%. Simpulan studi ini ialah tidak terdapat hubungan bermakna secara statistik antara interval waktu usia menarche dan usia saat melahirkan anak pertama cukup bulan ≥ 10 tahun dengan kejadian kanker payudara (p > 0,05).

scholarly journals The readability of online breast cancer risk assessment tools

2015 ◽  
Vol 154 (1) ◽  
pp. 191-199 ◽  
Author(s):  
Sarah Cortez ◽  
Melissa Milbrandt ◽  
Kimberly Kaphingst ◽  
Aimee James ◽  
Graham Colditz
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Assessment Tools ◽  
Cancer Risk Assessment ◽  
Breast Cancer Risk Assessment ◽  
Risk Assessment Tools
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