2016年10月30日 星期日

Literature review for gender-related DIF of IADL (Renew)

Author (year)
IADL items (red ones indicate having gender-related DIF)
Population (sample size)
How to assess DIF 
DIF criteria
How to deal with DIF
Lutomski et al. (2016)
1. telephone
2. medicine
3. managing finances
4. meal preparation
5. shopping
6. traveling
7. household tasks
*showed non-uniform DIF  in the community-dwelling sample , but showed uniform DIF in the residential care facility sample
Community-dwelling  (n=21,926) or 
residential care facility (n=2,458) older persons
1. An ANOVA of the standardized response residuals of each item by class interval 
(RUMM2030 software was used)
2. Visually inspect the observed item characteristic curve (ICC) by gender group relative to the theoretical ICC
Uniform DIF: a significant main effect for gender
Non-uniform DIF: a significant interaction between gender and class interval  
Uniform DIF: weighting
Non-uniform DIF: remove the item from the scale
Sousa et al. (2015) 
1. IADLs-Household (IADLs-H)
18 items, including domains of conversation and telephone use, meal preparation, housekeeping and home security
2. IADLs-Advanced (IADLs-A): 
17 items, including domains of comprehension and   communication, health-related decision making, finances, going out and transportation use and leisure and interpersonal relationships
Community-dwelling adults and older adults (n=567)
Patients with several neurological or psychiatric diagnoses (n=236)
Total sample size=803
Reference group vs. Focal group 
1. Independent t test with the Bonferroni adjustment to test whether there is significant difference of the difficulty parameters between both groups
2. The Mantel-Haenszel method:  use a chi-square statistic with the Bonferroni adjustment to test whether there is a significant difference between the odd of a correct answer to the item in both groups
(WINSTEPS software was used)
1. DIF: a difference >0.50 logits and statistically significant (Bonferroni’s correction: p=0.05/number of items) between 
2. DIF: a difference > 1.5 Delta-MH (0.64 logits) and statistically significant 
Not mentioned
Hammond et al. (2015)
1. cooking
2. cleaning the house
3. laundry and clothes care
4. moving and transfers
5. communication
6. moving outdoors and shopping
7. gardening and house maintenance
8. caring
9. leisure and social activities
Adults with rheumatoid arthritis (n=502)
Not mentioned
Not mentioned
Not mentioned
Forjaz et al. (2015)
1. bus
2. walking outside
3. shopping
4. preparing meals
5. performing household chores
A random sub-sample of people (n=250) was selected from a sample of people aged 65 and over with at least one disability and receiving personal help with one of the 14 BADL/IADL (n=8381)
* a minimum of 10 people was maintained in each of the response categories
ANOVA  with Bonferroni’s correction  
(RUMM2030 software was used)
DIF: the ANOVA for DIF is significant (p<0.05/14)
Not mentioned
Darzins et al. (2014)
1. clothing:managing laundry
2. nutrition: (1) eat without choking/coughing;
(2) planning meals; (3) preparing meals; (4) using the stove
3. mobility: (1) moving around outdoors; (2) getting to/from appointments
4. safety: (1) managing medicine; (2) avoiding alcohol/substance overuse; (3) coping   without repeated emergency help
5. residence: (1) managing money; (2) managing home security; (3) using basic personal information; (4) shopping for personal/household needs
*uniform DIF
Adults (aged 18 or older) inpatient rehabilitation participants (n=996)
Both uniform and non-uniform DIF were examined. 
(RUMM2030 software was used)
Not mentioned
Contain items that demonstrate DIF (clinically relevant to the scale)
Chen et al. (2013)
1. walk around outside
2. climb stairs
3. get in and out of the car
4. walk over uneven ground
5. cross roads
6. travel on public transport
7. manage to feed yourself
8. manage to make yourself a hot drink
9. take hot drinks from one room to another
10. make yourself a hot snack
11. wash dishes
12. deposit or withdraw money
13. wash small items of clothing
14. do your own housework
15. do your own shopping
16. do a full clothes wash
17. read newspapers or books
18. use the telephone
19. write letters
20. go out socially
21. plant in your garden or mange your own houseplants or garden
22. drive a car, ride a motor scooter, or ride a bike
Patients with stroke (n=188)
Independent t test with the Bonferroni adjustment
DIF: a difference >0.50 logits and statistically significant (Bonferroni’s correction: p=0.05/number of items)
Not mentioned
Baumeister et al. (2013)
IADL respectively physical functioning items, such as travelling with public transportation more than half an hour and getting groceries
* did not mention which item with gender-related DIF 
Patients with cardiovascular disease (n=720)
Not mentioned
Uniform DIF:
a significant main effect of gender (p<0.05)
Non-uniform DIF: a significant interaction effect (p<0.05)
Exclude items   with gender-related DIF 
Nair et al. (2011)
The same as those IADL items used in Chen et al. (2013)

Uniform DIF:  drive a car, ride a motor scooter, or ride a bike
Patients with acute stroke (first or recurrent) (n=210)
 ANOVA with  Bonferroni’s correction (RUMM2030 software was   used)
Not mentioned.
Retain the item if the removal of the item is not found to improve fit to Rasch model (person estimates derived before and after removal do not differ by less than 0.5 logits on average)
Niti et al. (2007)
Physical IADL
1. getting to places outside house
2. grocery shopping
3. preparing meals
4. doing housework
5. doing laundry
Cognitive IADL
1. using telephone
2. taking medications
3. managing money
Noninstitutionalized elderly subjects (n=1,072)
1. Modification index statistic 
2. Multiple -Indicator -Multiple-Cause model (MIMIC): to assess DIF with multiple latent variables (physical & cognitive IADL)
To estimate the percentage changes in beta weights between the DIF and non-DIF models 
Delete the item that shows large DIF or adjust it in a   statistical model
Fleishman et al. (2002)
1.      Shopping
2.      Doing light housework
3.      Doing heavy housework
4.      Preparing own meals
5.      Managing money
6.      Using the telephone
Adults respondents who received help or supervision with at least one of 11 ADL/IADL (n=5,750)
MIMIC: to assess DIF with multiple latent variables (ADL & IADL) 
(Mplus software was used)
To determine which model (DIF vs. non-DIF) had a better model fitting
1.      Statistical adjustment (to fit latent variable models)
2.      Reword questions that exist DIF
3.      Delete items with DIF (need to consider the impact on the content validity of the scale)
Spector & Fleishman (1998)
1. preparing meals
2. doing housework 
3. doing laundry 
4. shopping
5. managing money 
6. taking medicines
7. telephoning
8. going places outside of walking distance
9. getting around outside
Functionally disabled elderly (n=2,977)
A multiple-group IRT analysis to examine
the largest differences in location parameters for men and women
Not mentioned
Not mentioned










References:
Spector, W.D. and J.A. Fleishman, Combining activities of daily living with instrumental activities of daily living to measure functional disability. J Gerontol B Psychol Sci Soc Sci, 1998. 53(1): p. S46-57.
Fleishman, J.A., W.D. Spector, and B.M. Altman, Impact of differential item functioning on age and gender differences in functional disability. J Gerontol B Psychol Sci Soc Sci, 2002. 57(5): p. S275-84.
Niti, M., et al., Item response bias was present in instrumental activity of daily living scale in Asian older adults. J Clin Epidemiol, 2007. 60(4): p. 366-74.
das Nair, R., B.J. Moreton, and N.B. Lincoln, Rasch analysis of the Nottingham extended activities of daily living scale. J Rehabil Med, 2011. 43(10): p. 944-50.
Baumeister, H., et al., Development and calibration of an item bank for the assessment of activities of daily living in cardiovascular patients using Rasch analysis. Health Qual Life Outcomes, 2013. 11: p. 133.
Chen, H.F., et al., Rasch validation of a combined measure of basic and extended daily life functioning after stroke. Neurorehabil Neural Repair, 2013. 27(2): p. 125-32.
Darzins, S., et al., Evaluation of the internal construct validity of the Personal Care Participation Assessment and Resource Tool (PC-PART) using Rasch analysis. BMC Health Serv Res, 2014. 14: p. 543.
Forjaz, M.J., A. Ayala, and A. Abellan, Hierarchical nature of activities of daily living in the Spanish Disability Survey. Rheumatol Int, 2015. 35(9): p. 1581-9.
Hammond, A., et al., The reliability and validity of the English version of the Evaluation of Daily Activity Questionnaire for people with rheumatoid arthritis. Rheumatology (Oxford), 2015. 54(9): p. 1605-15.
Sousa, L.B., et al., The Adults and Older Adults Functional Assessment Inventory: A Rasch Model Analysis. Res Aging, 2015. 37(8): p. 787-814.
Lutomski, J.E., et al., Rasch analysis reveals comparative analyses of activities of daily living/instrumental activities of daily living summary scores from different residential settings is inappropriate. J Clin Epidemiol, 2016. 74: p. 207-17.

2016年10月4日 星期二

募集與思覺失調症患者配對的一般成人參與認知測驗的可能方式 (10/4 renew)

1. 預計收集人數:60位
2. 配對條件:
(1) 性別配對
(2) 年齡(相差一年內)配對
如:23歲0個月可與23歲11個月成配對
(3) 教育程度:學歷 或 受教育年數配對
- 嚴謹一點的話是要以受教育年數做配對,但如果實在太難配對的話,就以學歷配對,如:高中肄業和高中畢業 算同等學歷

3. 募集步驟及方式:
(1) 先收集思覺失調症患者的資料。收集30人左右,可確定受試者大致年齡範圍及學歷,之後再收集配對的一般成人資料。
(2) 募集方式
- 到高中及大學進修部收案 (可收集到國中及高中學歷,且比較可能是年輕的受試者)
- 張貼宣傳廣告在松德/桃療,募集符合條件的醫院員工/志工
- 口耳相傳,請認識的人幫忙介紹
- 請自己或認識的人居住社區裡的里長幫忙宣傳/介紹

4. 可能遇到的困難:
由於思覺失調症患者發病大多較早,蠻多數只有高中或國中學歷,而其年齡是40~50歲。但目前高中學歷的一般成人大多是5,60歲,所以不見得容易配對。

5. 目前作法:先收集思覺失調症個案資料,再思考符合條件的一般成人個案大多在哪裡 (高中及大學進修部)

2016年10月3日 星期一

iSAT擺位

找了許久,終於找到進行iSAT施測時放置iPad的適當架子。
這個架子的好處是:
1. 底部高起,讓刺激物接近個案眼睛的位置
2. 傾斜角度可進行微調 (有些架子的傾斜角度只有幾種,不能進行微調)

參考Ariel (2016)的論文,傾斜角度60度能讓受試者頭部和頸部flexion的角度減少,較接近neutral position,所以若是長時間使用tablet,不適感則較少。

所以目前先把傾斜角度定為60度,然後找正常人施測(field testing),以確定這個角度是OK的。



參考文獻:
Chiang, H. Y., & Liu, C. H. (2016). Exploration of the associations of touch-screen tablet computer usage and musculoskeletal discomfort. Work, 53, 917-925.

2016年9月29日 星期四

募集一般成人參與認知測驗的可能方式 (0930-renew)

募集與思覺失調症患者配對的一般成人參與認知測驗的可能方式:
1. 預計收集人數:60位
2. 配對條件:
(1) 性別配對
(2) 年齡(相差一年內)配對
如:23歲0個月可與23歲11個月成配對
(3) 教育程度:學歷 或 受教育年數配對
- 嚴謹一點的話是要以受教育年數做配對,但如果實在太難配對的話,就以學歷配對,如:高中肄業和高中畢業 算同等學歷

3. 募集步驟及方式:
(1) 先收集思覺失調症患者的資料。收集30人左右後,可確定大致年齡範圍及學歷
(2) 募集方式
- 張貼宣傳廣告在松德/桃療,募集符合條件的醫院員工/志工
- 口耳相傳,請認識的人幫忙介紹
- 請自己或認識的人居住社區裡的里長幫忙宣傳/介紹

4. 可能遇到的困難:
由於思覺失調症患者發病大多較早,蠻多數只有高中或國中學歷,而其年齡是40~50歲。但目前高中學歷的一般成人大多是5,60歲,所以不見得容易配對。

5. 目前作法:先收集思覺失調症個案資料,再思考符合條件的一般成人個案大多在哪裡。

2016年9月5日 星期一

桃療106年院內計畫內容-0910renew

計畫名稱:驗證iPad版選擇性注意力測驗於思覺失調症患者之心理計量特性
研究方法:本計畫包含二個子研究。研究一將募集60位慢性思覺失調症患者及60位一般成人(60位患者之年齡、教育程度配對)之方便樣本比較iSAT羅夫27選擇性注意力測驗 (Ruff 2 & 7 Selective Attention Test, Ruff 2 & 7 Test)之再測信度、收斂效度及區辨效度。每位受試者皆接受二次評估,每次間隔二週。
研究二將徵求60位思覺失調症住院患者比較i-SATRuff 2 & 7 Test之反應性、預測效度及生態效度。每位受試者將於入院一週內和出院前一週接受PANSS、個人與社會功能量表(Personal and Social Performance scale, PSP)MoCAiSAT和Ruff 2 &7 Test之評估。

研究一流程圖


研究二流程圖

d2注意力測驗之介紹

d2注意力測驗 (d2 test of attention)
歐洲很常用,可評估選擇性注意力,也評估到持續性注意力和視覺搜尋速度。
測驗一套的費用為137美金,折合台幣約4341元。












測驗內容:共有14列,每列含有47個符號(共有16種不同類型)。
測驗方式: 紙筆測驗,受試者要找出所有含有2條短線的字母d(二條短線在上或下或二者皆有)並劃掉。受試者於測驗前先進行練習列的練習,再進行正式測驗。正式測驗需計時,每一列計時20秒鐘。
計分包括完成數、錯誤數(含漏劃和誤劃)及正確數(完成數減錯誤數)。
完成測驗大約需8分鐘。
常模:主要為德國(6,000人),美國為大學生常模