Primary Image

Rehab Measures Database

Work Productivity & Activity Impairment Questionnaire - General Health

Last Updated

Purpose

The Work Productivity and Activity Impairment – General Health (WPAI-GH) Questionnaire is a 6-item instrument to measure impairments over the past 7 days in both paid work and unpaid work due to one’s health.

Link to Instrument

Acronym WPAI-GH

Area of Assessment

Occupational Performance
General Health
Quality of Life

Assessment Type

Patient Reported Outcomes

Administration Mode

Paper & Pencil

Cost

Free

CDE Status

Not a CDE -- last searched 10/11/2023. 

Key Descriptions

  • Respondents are asked questions about work and activity impairment due to health problems
  • There are interviewer and self-administered versions
  • Six questions measure absenteeism, presenteeism and the impairments in unpaid activity because of health problem during the past seven days
  • It consists of four metrics:
    1) Absenteeism (the percentage of work time missed)
    2) Presenteeism (the percentage of impairment experienced while at work)
    3) Overall work productivity loss (an estimate of combination of absenteeism and presenteeism)
    4) Activity impairment (the percentage of impairment in daily activities)
  • Only those being employed provided answer for absenteeism, presenteeism, and overall work impairment
  • Description of the items:
    > Item 1 = current employment status
    > Item 2 = hours missed due to health problems in last 7 days
    > item 3 = hours missed due to other reasons in last 7 days
    > Item 4 = hours actually worked in last 7 days
    > Item 5 = degree health affected productivity while working in last 7 days (using a 0 to 10 Visual Analogue Scale (VAS))
    > Item 6 = degree health affected productivity in regular unpaid activities (VAS) in last 7 days
  • Coding & Scoring:
    > WPAI scores are based on 1-item (presenteeism, activity impairment), 2-items (absenteeism) and multiple items (overall work productivity); a score cannot be calculated if there is a missing response to the corresponding item.
    > There are separate coding rules for interviewer and self-administration
    > WPAI outcomes are expressed as impairment percentages, with higher numbers indicating greater impairment and less productivity
  • WPAI-GH scores were positively correlated with other measurements of work productivity and activity impairment
  • Data generated by interviewer-administration of the WPAI had higher construct validity and fewer omissions than that obtained by self-administration of the instrument.
  • Two versions of WPAI are available:
    > WPAI-SHP is most appropriate for limited or local conditions (e.g. chronic hand dermatitis)
    > WPAI-GH can be utilized to assess diseases such as diabetes and multiple sclerosis
  • WPAI has been translated into over 80 languages

Number of Items

6

Equipment Required

  • pen or pencil

Time to Administer

Less than 10 minutes

Required Training

Reading an Article/Manual

Required Training Description

Reading an article regarding the development of WPAI-GH or Reviewing assessment manual. A clinician’s understanding of scoring information is needed--the Coding & Scoring Manual may be accessed here: http://www.reillyassociates.net/WPAI_Coding.html.

Age Ranges

Adult

18 - 64

years

Instrument Reviewers

Jay Kim, MA, University of Wisconsin-Madison

Yazmin Castruita Rios, MRC, University of Wisconsin-Madison

Susan Miller Smedema, PhD, CRC, LPC,   University of Wisconsin-Madison

Muneeb Ansari, BS, University of Illinois College of Medicine

Kevin Fearn, MS, Shirley Ryan 嫩B研究院

ICF Domain

Activity
Participation

Measurement Domain

Activities of Daily Living
General Health

Professional Association Recommendation

None found -- last searched 10/11/2023

Considerations

  • Some individuals with severe symptoms or problems do not consistently report their symptom impairment as a health impairment and this inconsistency of response affected the validity and reproducibility testing.
  • Different ethnic groups may respond to the term 'health' differently
  • It is not proven whether the subjects with lower schooling levels would have been able to answer the questionnaire in the self-administered form.  

Non-Specific Patient Population

back to Populations

Normative Data

Non-specific patient population: (Ciconelli et al., 2006; n = 100; male = 18 (18%); mean age = 39.22 (11.17); Brazilian Portuguese version of WPAI-GH)

Work Productivity and Activity Impairment—General Health (WPAI-GH) questionnaire scaling test results

Scale

Mean

Standard deviation

Work time missed (%)

8.40

           15.33

Impairment at work (%)

43.30

           27.01

Overall work productivity loss (%)

 

47.46

 

           27.34

Activity impairment (%)

49.70

           31.28

Test/Retest Reliability

Non-specific patient population: (Ciconelli et al., 2006; Brazilian Portuguese version of WPAI-GH)

  • Acceptable test-retest reliability: (ICC = 0.78 ~ 0.90)  

Internal Consistency

Non-specific patient population: (Ciconelli et al., 2006; Brazilian Portuguese version of WPAI-GH)

  • Adequate: overall Cronbach’s alpha = 0.74

Construct Validity

Convergent Validity:

Non-specific patient population: (Ciconelli et al., 2006; Brazilian Portuguese version of WPAI-GH)

  • Poor (r <= 0.30) to Adequate (r = 0.31 - 0.59) convergent validity between SF-36 questionnaire scales and Work Productivity and Activity Impairment-General Health (WPAI-GH) questionnaire scales

Pearson's correlation coefficient between between SF-36 questionnaire scales and Work Productivity and Activity Impairment-General Health (WPAI-GH) questionnaire scales, r (p-value)* 

SF-36 Scale

WPAI-GH Work time missed 

WPAI-GH Impairment at work

WPAI-GH Overall productivity loss

WPAI-GH Activity impairment

Physical functioning

-0.079 (0.435)

-0.371 (0.000)a

-0.352 (0.000)a

-0.367 (0.000)a

Role limitations due to physical health

-0.035 (0.727)

-0.358 (0.000)a

-0.315 (0.000)a

-0.435 (0.000)a

 

Bodily pain

-0.055 (0.587)

-0.472 (0.000)a

-0.445 (0.000)a

-0.420 (0.000)a

General health perceptions

-0.052 (0.608)

-0.224 (0.025)b

-0.200 (0.046)b

-0.198 (0.049)b

Vitality

-0.067 (0.510)

-0.310 (0.002)c

-0.264 (0.008)c

-0.327 (0.000)a

Social functioning

-0.095 (0.348)

-0.406 (0.000)a

-0.377 (0.000)a

-0.243 (0.015)b

Role limitations due to emotional health 

-0.109 (0.278)

-0.206 (0.040)b

-0.181 (0.072)

-0.170 (0.091)

General mental health

-0.174 (0.084)

-0.343 (0.000)a

-0.317 (0.000)a

-0.172 (0.086)

*Comparisons show negative correlation coefficients because WPAI-GH scores range from lower to higher values according to the impairment or worsening of productivity, while SF-36 scores range from lower to higher value according to the improvement in the patient’s general health status.

a< 0.001; b< 0.05; c< 0.01

 

 

Arthritis

back to Populations

Normative Data

Rheumatoid arthritis: (Zhang et al., 2010; n = 150; mean age = 52.1 (10.0) years; disease duration since first clinic visit = 37.5 (18.3) months; disease duration since onset of symptom = 48.7 (23.2) months)

  • Mean of percent work time missed due to health for those with missed time > 0 (n = 26): 45.5 (41.2) 
    • Median (1st to 3rd quartile): 18 (12 to 100)
  • Mean of percent impairment while working due to health for those with % impairment while working > 0 (n = 88): 33.3 (20.1) 
    • Median (1st to 3rd quartile): 30 (20 to 50)
  • Mean of percent overall work impairment due to health (n = 135): 29.1 (29.8) 
    • Median (1st to 3rd quartile): 20 (0 to 46)
  • Mean of percent activity impairment due to health for those with % activity impairment > 0  (n = 123): 40.7 (25.1)
    • Median (1st to 3rd quartile): 30 (20 to 60)

Construct Validity

Convergent Validity

Rheumatoid arthritis: (Zhang et al., 2010)

  • Adequate to Excellent convergent validity between WPAI outcomes and health status outcomes (r = 0.36 – 0.77)

Spearman correlation between WPAI outcomes and health status outcomes

 

Function

Pain

Global assess. on health impact

Fatigue

Global assess. of disease activity

% work time missed

0.39

0.36

            0.36

0.37

            0.34

% impairment while working

0.69

0.75

            0.74

0.67

            0.76

% overall work impairment

0.67

0.73

            0.71

0.68

            0.73

% activity impairment

0.73

0.77

            0.77

0.68

            0.77

 

  • When the patients were divided into two groups according to the median of each health status outcome variable, each of WPAI productivity outcomes was significantly lower among patients with better health status than patient with worse health status.

Digestive Disorders

back to Populations

Normative Data

Crohn’s disease: (Reilly et al., 2008; n = 662; mean age = 37.4 (range: 18-77) years; male = 288 (43.5%); male = 288 (43.5%))

  • Mean of percent work time missed due to health (n = 351): 18.3 (29.3) 
    • Median: 2.0
  • Mean of percent impairment while working due to health (n = 359): 40.5 (25.2)  
    • Median: 40.0
  • Mean of percent overall work impairment due to health (n = 326): 45.9 (26.5)
    • Median: 43.1 
  • Mean of percent activity impairment due to health (n = 641): 52.0 (25.2)
    • Median: 50.0

Construct Validity

Discriminant Validity

Crohn’s disease: (Reilly et al., 2008; n = 662; mean age = 37.4 (range: 18-77) years, Groups are separated in the best health group (score of CDAI (Chron’s disease Activity Index) < median) and worst health group (score of CDAI (Chron’s disease Activity Index) > median).

  • Worst severity group showed significantly higher overall work impairment (+10.5%, p < 0.005)
  • Worst severity group showed significantly higher impairment in daily activities (+10.4%, < 0.005)

Responsiveness

Crohn’s disease: (Reilly et al., 2008)

  • Those who achieved a CDAI (Chron Disease Activity Index) remission at week 26 compared with those who did not showed: 
    • an 11.2% greater decrease in absenteeism (p = .028)
    • a 13.0% greater decrease in presenteeism (= .002)
    • a 15.2% greater decrease in overall work impairment (p = 0.002)
    • a 19.4% greater decrease in daily activity impairment (p < .001)

Caregivers

back to Populations

Normative Data

Caregiver of chronically ill older patients: (Giovannetti et al., 2009; n = 308; mean age = 61.8 (15.1) years; WPAI:CG for caregivers)

Baseline caregiver (CG) characteristics by employment status

Characteristic

Employed (=125) percentage/Mean (SD)

Nonemployed (=183) percentage/Mean (SD)

Total (=383) percentage/Mean (SD)

Age1

53.4 (12.0)

67.5 (14.1)

61.8 (15.1)

Female

71.2%

71.6%

71.4%

Married1

56.8%

71.6%

68.5%

Adult child CG1

70.4%

26.8%

44.5%

Spousal CG1

16.8%

66.0%

46.1%

>= 1 child in CG household1

27.2%

11.5%

17.9%

CG receives additional help from family/friends2

57.6%

42.1%

48.4%

CG receives additional paid help

8.8%

7.7%

8.1%

CG has at least a HS education1

97.6%

78.1%

86.0%

CG reports not enough money

9.6%

12.0%

11.0%

CG helps patient daily1

44.8%

72.7%

61.4%

Ave. hrs. of assistance/week1

16.6 (18.6)

30.0 (30.0)

24.7 (26.8)

Ave. # of ADL tasks CG assists with

.9 (1.5)

1.1 (1.5)

1.0 (1.5)

Ave. # of IADL tasks CG assists with

2.8 (1.9)

3.0 (2.1)

2.9 (2.0)

Care-Recipient HCC score

2.15 (1.32)

2.41 (1.28)

2.31 (2.16)

Baseline CG Depression (CESD)

6.3 (6.8)

7.5 (7.0)

7.1 (6.9)

Baseline CG Strain (CSI)

7.5 (5.7)

7.1 (6.0)

7.3 (5.9)

1< 0.001; 2< 0.01

ADL = activities of daily living; CESD = Center for Epidemiological Studies Depression Index; CSI = Caregiver Strain Index; HCC = hierarchical condition category; IADL = instrumental activities of daily living; SD = standard deviation

 

 

Construct Validity

Convergent validity:

 

Caregiver of chronically ill older patients: (Giovannetti et al., 2009; WPAI:CG for caregivers)

Convergent validity between WPAI-CG and measures of caregiving intensity and health-related quality of life measures

Health-related quality of life measure

Work productivity loss
(n = 123)

Regular activity productivity loss (n = 308)

Caregiver strain (CSI score)

r = 0.45 (p < .001)

    r = 0.55 (p < .001)

Depression (CESD score)

r = 0.30 (p < .001)

    r = 0.31 (p < .001)

Hours spent caregiving per week

r = 0.32 (p < .001)

    r = 0.39 (p < .001)

Number of ADL (Activities of daily living) tasks

z = 2.18 (p =.029)

    z = 5.61 (p < .001)

HCC (Hierarchical Condition category) quartile

z = 2.21 (p =.027)

    z = 2.39 (p = .017)

r = Spearman’s rank correlation rho (p – value); z = Cuzick’s nonparametric test for trend. 

Pulmonary Diseases

back to Populations

Normative Data

Chronic Obstructive Pulmonary Disease (COPD): (Allen-Ramey et al., 2012; data from 2010 U.S. National Health and Wellness Survey (NHWS, n = 75,000, with self-reported COPD phenotypes of COPD only (n = 970), emphysema only (n = 399), or chronic bronchitis only (n = 2,071))

Unadjusted health outcome differences among COPD phenotypes

Metric

COPD only

Mean (SD)

Emphysema only

Mean (SD)

Chronic bronchitis only

Mean (SD)

Absenteeism (%)a

6.96 (19.37)

5.16 (15.43)

7.40 (19.17)

Presenteeism (%)b

28.96 (29.30)

25.29 (26.77)

25.50 (27.66)

Overall work impairment (%)a

32.23 (31.69)

27.41 (29.44)

28.95 (30.72)

Activity impairment (%)c,d

50.36 (31.29)

42.88 (31.19)

42.15 (32.14)

aResults are based on sample sizes of 227, 104, and 941 for COPD only, emphysema only, and chronic bronchitis only, respectively.

bResults are based on sample sizes of 222, 103, and 925 for COPD only, emphysema only, and chronic bronchitis only, respectively.

cResults are based on sample sizes of 970, 399, and 2,071 for COPD only, emphysema only, and chronic bronchitis only, respectively.

dp < 0.0001

Mental Health

back to Populations

Construct Validity

Convergent validity:

Workers With Diagnosed and Undiagnosed Depression: (Asami et al., 2015; n = 17,820 workers responding to the 2011 National Health & Wellness Survey in Japan; male = 62%; mean age = 44.19 (12.80); Absenteeism and overall work impairment analyses included 16,906 of the total workers, while presenteeism included 17,428; Japanese versions of the Work Productivity and Activity Impairment (WPAI) Questionnaire and Patient Health Questionnaire-9 (PHQ-9))

  • The interaction between PHQ-9 scores and depression diagnosis was not significant for absenteeism, but was significant for overall work impairment, presenteeism, and activity impairment (all p < 0.01).
  • Adjusted mean percentage impairments per subgroup indicate the effects of PHQ-9 on productivity were in all cases stronger in the undiagnosed than in the diagnosed group, respectively.
    • For overall work impairment, among the undiagnosed, the PHQ-9 score of 10 or more vs. less than 10 was associated with 33.3% vs. 14.8% (i.e., 2.25 times as much) impairment, respectively, while among the diagnosed, the difference was 51.9% vs. 33.0% (1.57 times as much.
    • For absenteeism, among those with undiagnosed depression, PHQ-9 scores of 10 or more vs. less than 10 were associated with 5.9% vs. 2.2% absenteeism (2.72 times as much), while among those with diagnosed depression, the difference was 16.0% vs. 8.0% (2.00 times as much), adjusting for covariates.
    • For presenteeism, among the undiagnosed, PHQ-9 scores of 10 or more vs. less than 10 were associated with 30.4% vs. 13.4% presenteeism (2.26 times as much), while among the diagnosed, the difference was 45.2% vs. 28.7% (1.58 times as much).
    • On average, the above results imply a greater burden of depression among the undiagnosed. 

Nurses

back to Populations

Normative Data

Work Productivity and Intent to Stay In Nursing: (Letvak & Buck, 2008; n = 332; mean age = 40.15 (10.9) years, range = 22-71; female = 91.6%; mean years in nursing = 12.29 (10.2) years, range = 4-50; Registered Nurses (RNs) employed at the bedside at three hospitals: a 1,000-bed tertiary care medical center which employed approximately 1,700 RNs (187 responses), and two community-based hospitals with approximately 200 beds and 400 RNs (136 responses from the first and 100 from the second)

  • Mean work activity impairment as measured by the WPAI-GH was 12.71% (SD = 18.56, range = 0-90%)
    • Predictor variables determined by linear regression explained 26.8% of the variance (F = 16.73, < 0.001)

Predictor

S Beta

t

Significance

Age

-0.202

-2.445

0.15

Total years as RN

 

0.188

 

2.194

 

0.029

Quality of care

-0.172

-2.676

0.008

Job stress score

 

0.151

 

2.430

 

0.016

Job injury

-0.172

-3.009

0.003

Health problem

-0.323

-5.966

0.000

Skin Disorders

back to Populations

Minimally Clinically Important Difference (MCID)

Psoriasis patients:  (Wu et al., 2018; n = 3,126 patients 18 years of age or older with moderate-to-sever plaque psoriasis (diagnosed at least 6 months prior to randomization, 10% or more of their body area affected by psoriasis, a static physician global assessment score of 3 or higher, and a Psoriasis Area and Severity Index of 12 or higher (placebo = 792, ixekizumab = 2,334); Workplace Productivity and Activity Impairment Questionnaire—Psoriasis (WPAI-PsO).

  • MCID = 20% improvement for work productivity
  • MCID = 20% improvement for activity impairment

 

Neurological Disorders

back to Populations

Minimally Clinically Important Difference (MCID)

Episodic or Chronic Migraine: (Ford et al., 2023; n = 444 migraine patients (Episodic migraine = 261, Chronic migraine = 183); mean age = 45.9 (11.81); female = 381 (85.8%)

  • MCID = -20-unit change from baseline to month 3 for all three WPAI domain scores (presenteeism, overall work productivity, and non-work-related activity impairment

 

Normative Data

Episodic or Chronic Migraine: (Ford et al., 2023; n = 444 migraine patients (Episodic migraine = 261, Chronic migraine = 183); mean age = 45.9 (11.81); female = 381 (85.8%)

 

Patient baseline demographics and clinical characteristics

 

Characteristic

Overall

(n = 444)

EMa

(n = 261)

CMb

(n = 261)

Age (years)

45.89 (11.81)

46.34 (11.35)

45.23 (12.44)

Gender (women)

381 (85.8%)

222 (85.1%)

159 (86.9%)

Years since migraine diagnosis

23.34 (13.58)

22.52 (12.92)

24.52 (14.43)

Monthly migraine headache days

13.12 (5.90)

9.30 (2.84)

18.58 (4.72)

WPAI absenteeism score*

9.37 (17.85)

8.22 (15.65)

11.03 (20.57)

WPAI presenteeism score*

42.75 (23.24)

38.70 (24.65)

48.70 (19.62)

WPAI overall work productivity loss score*

46.86 (25.69)

42.42 (26.92)

53.29 (22.39)

WPAI non-work-related activity impairment score

50.97 (23.91)

48.01 (24.96)

55.19 (21.71)

MSQ-RFRc score

45.05 (17.16)

48.05 (15.79)

40.77 (18.15)

MSQ-RFPd score

63.78 (19.15)

65.38 (18.78)

61.50 (1949)

*Scores were computed only for employed individuals.

aEM = episodic migraine—defined as 4 to 14 migraine headache days and <15 headache days per 30-day period in the prospective baseline period. Patients with 4 to <8 migraine headache days and 15-29 headache days per 30-day period in the prospective baseline period were considered to have episodic migraine.

bCM = chronic migraine—defined as 15-29 headache days per 30-day period in the prospective baseline period, of which at least 8 are migraine.

cMSQ-RFR = Migraine-Specific Quality of Life Questionnaire—Role Function-Restrictive

dMSQ-RFP = Migraine-Specific Quality of Life Questionnaire—Role Function-Preventive

 

Patient baseline demographics and clinical characteristics for employed patients*

 

Characteristic

Overall

(n = 289)

EMa

(n = 171)

CMb

(n = 118)

Age (years)

43.60 (10.04)

43.82 (10.00)

43.28 (10.15)

Gender (women)

245 (84.8%)

143 (83.6%)

102 (86.4%)

Years since migraine diagnosis

22.11 (12.45)

21.72 (12.55)

22.67 (12.33)

Monthly migraine headache days

13.17 (5.73)

9.57 (2.82)

18.40 (4.78)

WPAI absenteeism score*

9.37 (17.85)

8.22 (15.65)

11.03 (20.57)

WPAI presenteeism score*

42.75 (23.24)

38.70 (24.65)

48.70 (19.62)

WPAI overall work productivity loss score*

46.86 (25.69)

42.42 (26.92)

53.29 (22.39)

WPAI non-work-related activity impairment score

49.24 (23.22)

46.90 (24.31)

52.63 (21.18)

MSQ-RFRc score

46.21 (16.01)

48.29 (14.82)

43.20 (17.22)

MSQ-RFPd score

66.51 (16.93)

67.11 (17.27)

65.64 (16.47)

*Mean scores and standard deviations were calculated based on non-missing values.

aEM = episodic migraine—defined as 4 to 14 migraine headache days and <15 headache days per 30-day period in the prospective baseline period. Patients with 4 to <8 migraine headache days and 15-29 headache days per 30-day period in the prospective baseline period were considered to have episodic migraine.

bCM = chronic migraine—defined as 15-29 headache days per 30-day period in the prospective baseline period, of which at least 8 are migraine.

cMSQ-RFR = Migraine-Specific Quality of Life Questionnaire—Role Function-Restrictive

dMSQ-RFP = Migraine-Specific Quality of Life Questionnaire—Role Function-Preventive

Test/Retest Reliability

Episodic or Chronic Migraine: (Ford et al., 2023)

  • Poor test-retest reliability (estimated in stable patients treated with placebo) for all patients for WPAI presenteeism (ICC = 0.438)
    • Poor test-retest reliability for episodic migrainel patients for WPAI presenteeism (ICC = 0.227)
    • Adequate test-retest reliability for chronic migraine patients for WPAI presenteeism (ICC = 0.893)
  • Poor test-retest reliability (estimated in stable patients treated with placebo) for all patients for WPAI non-work-related Activity Impairment  (ICC = 0.446)
    • Poor test-retest reliability for episodic migrainel patients for WPAI non-work-related Activity Impairment (ICC = 0.272)
    • Poor test-retest reliability for chronic migraine patients for WPAI non-work-related Activity Impairment (ICC = 0.653)
  • Poor test-retest reliability (estimated in stable patients treated with placebo) for all patients for WPAI overall work productivity loss (ICC = 0.360)
    • Poor test-retest reliability for episodic migrainel patients for WPAI overall work productivity loss (ICC = 0.158)
    • Adequate test-retest reliability for chronic migraine patients for WPAI overall work productivity loss (ICC = 0.885)

Construct Validity

Convergent validity:

 

Episodic or Chronic Migraine: (Ford et al., 2023)

  • Adequate convergent validity between WPAI Overall, WPAI Presenteeism, and WPAI Non-Work-Related Activity Impairment scores (WPAI-Activity) and Migraine-Specific Quality of Life Questionnaire--Role Function-Restrictive (MSQ-RFR) and Role-Function-Preventive (MSQ-RFP) scales for all patients, episodic migraine (EM) patients, and chronic migraine (CM) patients

 

Spearman correlations of baseline WPAI scores with MSQ-RFR and MSQ-RFP scores for all patients

 

Scale

 

WPAI-Overall

 

WPAI-Presenteeism

 

WPAI-Activity

MSQ-RFR

-0.486

-0.478

-0.573

MSQ-RFP

-0.453

-0.423

-0.517

 

 

Spearman correlations of baseline WPAI scores with MSQ-RFR and MSQ-RFP scores for EM patients

 

Scale

 

WPAI-Overall

 

WPAI-Presenteeism

 

WPAI-Activity

MSQ-RFR

-0.446

-0.421

-0.606

MSQ-RFP

-0.443

-0.398

-0.540

 

 

Spearman correlations of baseline WPAI scores with MSQ-RFR and MSQ-RFP scores for CM patients

 

Scale

 

WPAI-Overall

 

WPAI-Presenteeism

 

WPAI-Activity

MSQ-RFR

-0.515

-0.531

-0.505

MSQ-RFP

-0.457

-0.450

-0.476

Responsiveness

Episodic or Chronic Migraine: (Ford et al., 2023)

  • Significant overall improvements in WPAI domain scores for patients who achieved the pre-specified responsiveness thresholds for monthly migraine headache days and MSQ-RFP, MSQ-RFR from baseline to month 3 compared to non-responders (p < 0.001)
    • Similar significant results were observed in patients with EM and CM (p < 0.05)

 

Bibliography

Allen-Ramey FC, Gupta S, Dibonaventura MD. (2012). Patient characteristics, treatment patterns, and health outcomes among COPD phenotypes. Int J Chron Obstruct Pulmon Dis., 7, 779-787.

Asami Y, Goren A, Okumura Y. (January 2015). Work productivity loss with depression, diagnosed and undiagnosed, among workers in an internet-based survey conducted in Japan. J Occup Environ Med., 57(1):105-110.

Ciconelli RM, Soarez PC, Kowalski CC, Ferraz MB. (2006). The Brazilian Portuguese version of the Work Productivity and Activity Impairment--General Health (WPAI-GH) Questionnaire. Sao Paulo Medicine Journal, 124(6):325-332.

Ford, JH, Ye, W., Ayer, DW, Mi, X, Bhandari, S., Buse, DC, & Lipton, RB. (2023), Validation and meaningful within-patient change in work productivity and activity impairment questionnaire (WPAI) for episodic or chronic migraine. Journal of Patient-Reported Outcomes, 7:34-48.

Giovannetti ER, Wolff JL, Frick KD, Boult C. (2009). Construct validity of the Work Productivity and Activity Impairment questionnaire across informal caregivers of chronically ill older patients. Value in Health, 12(6):1011-1017.

Lenneman J, Schwartz S, Giuseffi DL, Wang C. (2011). Productivity and health: An application of three perspectives to measuring productivity. Journal of Occupational and Environmental Medicine, 53(1):55-61.

Letvak S, Buck R. (May-June, 2008). Factors influencing work productivity and intent to stay in nursing. Nursing Economics, 26(3): 159-165.

Reilly MC, Gerlier L, Brabant Y, Brown M. (2008). Validity, reliability, and responsiveness of the work productivity and activity impairment questionnaire in Crohn's disease. Clinical therapeutics, 30(2):393-404.

Reilly MC, Zbrozek AS, Dukes EM. (1993). The validity and reproducibility of a work productivity and activity impairment instrument. PharmacoEconomics, 4(5):353-365.

Wu, JJ, Lin, C., Sun, L., Goldblum, O., Zbrozek, A., Burge, R., Augustine, M., & Feldman, SR. (2019). Minimal clinically important difference (MCID) for work productivity and activity impairment (WPAI) questionnaire for psoriasis patients. Journal of the European Academy of Dermatology and Venereology, 33: 318-324.

Zhang W, Bansback N, Boonen A, Young A, Singh A, Anis AH. (2010). Validity of the work productivity and activity impairment questionnaire-general health version in patients with rheumatoid arthritis. Arthritis research & therapy, 12:R177.