Modeling community integration in workers with delayed recovery from mild traumatic brain injury

Background: Delayed recovery in persons after mild traumatic brain injury (mTBI) is poorly understood. Community integration (CI) is endorsed by persons with neurological disorders as an important outcome. We aimed to describe CI and its associated factors in insured Ontario workers with delayed recovery following mTBI. Methods: A cross-sectional study of insured workers in the chronic phase following mTBI was performed at a rehabilitation hospital in Ontario, Canada. Sociodemographic, occupational, injury-related, clinical, and claim-related data were collected from self-reports, medical assessments, and insurers’ referral files. Community Integration Questionnaire (CIQ) scores were compared using analysis of variance or Spearman’s correlation tests. Stepwise multivariable linear regression models were used to evaluate the associations with CI. Results: Ninety-four workers with mTBI (45.2 ± 9.9 years old, 61.2 % male) at 197 days post-injury (interquartile range, 139–416 days) were included. The CIQ total and subscale scores were similar to those reported in more severe TBI samples. The CIQ scores were moderately to strongly correlated with various sociodemographic, claim-related, and clinical variables. In the multivariable regression analysis, several covariates accounted for 36.4 % of the CIQ variance in the final fully adjusted model. Discussion: This study evaluated CI in workers with mTBI, and analyzed its associated variables. Analysis revealed insomnia, head or neck pain, being married or in a relationship, time since injury, and a diagnosis of possible/probable malingering were independently associated with limited CI. Conclusions: Workers with delayed recovery from mTBI experience difficulty with CI. Insomnia is a particularly relevant covariate, explaining the greater part of its variance. To enhance participation, care should focus on clinical and non-clinical covariates

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Hearing loss without overt metabolic acidosis in ATP6V1B1 deficient MRL mice, a new genetic model for non-syndromic deafness with enlarged vestibular aqueducts.

Mutations of the human ATP6V1B1 gene cause distal renal tubular acidosis (dRTA; OMIM #267300) often associated with sensorineural hearing impairment; however, mice with a knockout mutation of Atp6v1b1 were reported to exhibit a compensated acidosis and normal hearing. We discovered a new spontaneous mutation (vortex, symbol vtx) of Atp6v1b1 in an MRL/MpJ (MRL) colony of mice. In contrast to the reported phenotype of the knockout mouse, which was developed on a primarily C57BL/6 (B6) strain background, MRL-Atp6v1b1vtx/vtx mutant mice exhibit profound hearing impairment, which is associated with enlarged endolymphatic compartments of the inner ear. Mutant mice have alkaline urine but do not exhibit overt metabolic acidosis, a renal phenotype similar to that of the Atpbv1b1 knockout mouse. The abnormal inner ear phenotype of MRL- Atp6v1b1vtx/vtx mice was lost when the mutation was transferred onto the C57BL/6J (B6) background, indicating the influence of strain-specific genetic modifiers. To genetically map modifier loci in Atp6v1b1vtx/vtx mice, we analysed ABR thresholds of progeny from a backcross segregating MRL and B6 alleles. We found statistically significant linkage with a locus on Chr 13 that accounts for about 20% of the hearing threshold variation in the backcross mice. The important effect that genetic background has on the inner ear phenotype of Atp6v1b1 mutant mice provides insight into the hearing loss variability associated with dRTA caused by ATP6V1B1 mutations. Because MRL-Atp6v1b1vxt/vtx mice do not recapitulate the metabolic acidosis of dRTA patients, they provide a new genetic model for nonsyndromic deafness with enlarged vestibular aqueduct (EVA; OMIM #600791). Hum Mol Genet 2017 Oct 1; 26(19):3722-3735

[[alternative]]Study on the relationships between junior high school mathematics teachers' TPACK and teaching beliefs in Taipei area

碩士[[abstract]]身處二十一世紀，科技已是人們在生活中不可或缺的一部分，資訊運用能力成為教師的必備條件，科技學科教學知識（TPACK）因而成為教育者關心的議題。相關研究發現教師對於教學、學習及資訊融入教學的想法是影響教師運用科技於教學活動中的重要因素，因此若能瞭解教學信念與TPACK的關係，將有助於教師發展TPACK。故本研究將教師對教學與學習、資訊融入教學所持有的觀念及想法列為教學信念主要面向，以問卷調查臺北市與新北市國中數學教師TPACK與教學信念之現況，進一步探討個人背景變項（性別、年齡、任教年資與學校規摸）在TPACK及教學信念的差異情形，並分析TPACK與教學信念之相關性。 問卷抽樣採方便取樣，並考量學校規模，共抽取101學年度臺北市及新北市111位現任國中數學教師參與研究。回收問卷110份，問卷資料經描述性統計分析、t檢驗、單因子變異數分析，得到以下研究結果： 一、臺北市及新北市國中數學教師具有有中上程度的TPACK，但在TPACK 七種知識中，科技教學知識（TPK）方面較需加強。 二、臺北市與新北市國中數學教師具有建構式的教學與學習觀，對資訊融入教學的 認知、評價、感受為正向。 三、不同背景變項的臺北市及新北市國中數學教師TPACK並無顯著差異。 四、不同背景變項的臺北市及新北市國中數學教師教學信念並無顯著差異。 五、臺北市及新北市國中數學教師TPACK與整體教學信念為中度正相關，表示整體教學信念越傾向進步取向的國中數學教師，其TPACK程度也越高。 依據研究結論，研究者建議增加科技教學知識（TPK）課程，持續舉辦建構式教學方面的研習，並積極增加學校科技設備。未來的研究可考慮將其他學科教師納入，以比較不同科目教師的TPACK與教學信念之相關研究。[[abstract]]Living in the 21st century, technology plays an important role in learning and instruction. Studies found that a number of factors, such as gender, age, pedagogical content knowledge and teaching beliefs influence teachers’ use of technology. Recently, educators proposed a Technological Pedagogical Content Knowledge (TPACK) framework to help teachers develop knowledge of technology integration. The purpose of the study is to investigate the relationships between junior high school mathematics teachers’ TPACK and teaching beliefs. Based on Koehler and Mishra’s TPACK framework and related studies, a survey with 51 items was developed to measure TPACK and teaching beliefs. 110 junior high school mathematics teachers in Taipei area completed the survey. The data was analyzed by descriptive statistics, t test, ANOVA. The results showed that mathematics teachers have high-intermediate level in TPACK but TPK is lower than other aspects. Mathematics teacher’s teaching beliefs incline to progressive approach, and the TPACK had middle and positive correlation with the teaching beliefs. Based on the study results, it was suggested that educational administration could hold more professional development activities to improve teachers’ TPK and to encourage constructivist teaching.[[tableofcontents]]中文摘要 i 英文摘要ii 目次iii 表次 v 圖次vii 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的與待答問題 5 第三節 名詞釋義 6 第四節 研究範圍與限制 9 第五節 預期研究貢獻 11 第二章 文獻探討 12 第一節 TPACK理論架構之意涵 12 第二節 TPACK相關實證研究 21 第三節 教師教學信念的意義與內涵 27 第四節 教學信念與資訊科技融入教學 35 第三章 研究方法 40 第一節 研究架構 40 第二節 研究對象與樣本選取 41 第三節 研究流程 43 第四節 研究工具 44 第五節 資料處理與分析 65 第四章 研究結果與討論 67 第一節 國中教師科技學科教學知識現況 67 第二節 國中教師教學信念現況 69 第三節 不同背景變項國中教師的科技學科教學知識差異 70 第四節 不同背景變項國中教師的教學信念差異 74 第五節 國中教師科技學科教學知識與教學信念的相關性 76 第六節 綜合討論 78 第五章 結論與建議 85 第一節 結論 85 第二節 建議 86 參考文獻 89 附錄一 預試問卷 97 附錄二 正式問卷 103 表次 表2- 1 傳統主義者與進步主義者教學信念之比較 ............................... 30 表2- 2 教學信念內涵比較 ....................................................................... 34 表3- 1 研究取樣人數及有效樣本次數分配表 ....................................... 41 表3- 2 調查樣本基本資料分析表 ........................................................... 42 表3- 3 研究實施程序表 ........................................................................... 43 表3- 4 預試取樣人數及有效樣本之次數分配表 ................................... 47 表3- 5 CK 量表項目分析與因素分析結果摘要表 ................................. 49 表3- 6 PK 量表項目分析與因素分析結果摘要表 ................................. 50 表3- 7 TK 量表項目分析與因素分析結果摘要表 ................................. 51 表3- 8 PCK 量表項目分析與因素分析結果摘要表 .............................. 53 表3- 9 TPK 量表項目分析與因素分析結果摘要表 ............................... 54 表3- 10 TCK 量表項目分析與因素分析結果摘要表 ............................ 55 表3- 11 TPACK 量表項目分析與因素分析結果摘要表 ........................ 56 表3- 12 教學與學習觀量表項目分析與因素分析結果摘要表 ............. 57 表3- 13 科技信念量表項目分析與因素分析結果摘要表 ..................... 59 表3- 14 CK 量表項目分析結果摘要表 ................................................... 60 表3- 15 PK 量表項目分析結果摘要表 ................................................... 60 表3- 16 TK 量表項目分析結果摘要表 ................................................... 61 表3- 17 PCK 量表項目分析結果摘要表 ................................................ 62 表3- 18 TPK 量表項目分析結果摘要表 ................................................. 62 表3- 19 TCK 量表項目分析結果摘要表 ................................................ 63 表3- 20 TPACK 量表項目分析結果摘要表 ........................................... 63 表3- 21 教學與學習觀量表項目分析結果摘要表 ................................. 64 表3- 22 科技信念量表項目分析結果摘要表 ......................................... 65 表4- 1 臺北市與新北市國中數學教師TPACK 現況摘要表 ................ 68 表4- 2 臺北市與新北市國中數學教師教學信念現況摘要表 ............... 69 表4- 3 不同性別國中數學教師TPACK 獨立樣本t 考驗分析摘要表 . 70 表4- 4 不同年齡國中數學教師TPACK 單因子變異數分析摘要表 .... 71 表4- 5 不同任教年資數學教師TPACK 單因子變異數分析摘要表 .... 72 表4- 6 不同學校規模數學教師TPACK 單因子變異數分析摘要表 .... 73 表4- 7 不同性別國中數學教師教學信念獨立樣本t 考驗分析摘要表 74 表4- 8 不同年齡國中數學教師教學信念單因子變異數分析摘要表 ... 75 表4- 9 不同任教年資數學教師教學信念單因子變異數分析摘要表 ... 75 表4- 10 不同學校規模數學教師教學信念單因子變異數分析摘要表 . 76 表4- 11 國中數學教師TPACK 與教學信念相關係數摘要表............... 77 圖次 圖2- 1 科技學科教學知識（TPACK）架構圖 ...................................... 15 圖2- 2「教學所需的數學知識」架構圖 ................................................ 18 圖3- 1 研究架構圖 .................................................................................. 40[[note]]學號: 700740128, 學年度: 10