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This study aims to assess psychometric properties of the Hungarian PROMIS-29+2 profile measure and provide general population reference values for Hungary.
Methods
An adult general population sample (n = 1700) completed PROMIS-29+2 v2.1 in an online survey. The following psychometric properties were assessed: floor and ceiling effect, convergent validity with SF-36v1 domains, internal consistency (McDonald’s omega), unidimensionality, local independence, monotonicity, graded response model (GRM) fit and differential item functioning (DIF). Age- and gender-specific reference values were established using the US item calibrations.
Results
Depending on scale orientation, high floor or ceiling effects were observed for all domains (25.2–60.7%) except for sleep disturbance. McDonald’s omega for domains ranged from 0.87–0.97. Unidimensionality, local independence and monotonicity were supported and the GRM adequately fitted for all but one domains. The sleep disturbance domain demonstrated item misfit, response level disordering and low discrimination ability, particularly for item Sleep116 (‘refreshing sleep’). Strong correlations were observed between PROMIS-29+2 and corresponding SF-36 domains (rs=│0.60│ to │0.78│). No DIF was detected for most sociodemographic characteristics. Problems with physical function, pain interference and social roles tended to increase, whereas problems with anxiety, depression, fatigue and cognitive function declined with age (p < 0.01). In all domains except for cognitive function, more health problems occurred in females than in males (p < 0.001).
Conclusion
The Hungarian PROMIS-29+2 shows satisfactory psychometric properties; however, the sleep disturbance domain substantially underperforms that requires further attention. Population reference values were generated that facilitate the interpretation of health outcomes in various patient populations.
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Introduction
In recent years, clinicians, health service providers, researchers, the pharmaceutical industry, reimbursement agencies and health policymakers have been increasingly recognizing the importance of measuring health-related-quality of life (HRQoL) [1, 2]. Some HRQoL instruments are referred to as ‘generic measures’ that describe health in a general way allowing the assessment of HRQoL and changes in HRQoL across a range of disease areas and patient populations, including members of the general public and patient groups. Such measures include the 36-Item Short Form Survey (SF-36), EQ-5D and Assessment of Quality of Life (AQoL) [3, 4]. More recently, the Patient-Reported Outcomes Measurement Information System (PROMIS) adult generic profiles (PROMIS-57, -43 and -29)[5] have been developed that represent a new generation of such measures by relying on item response theory (IRT) calibrated item banks there using a different approach than conventional measures [6].
The PROMIS initiative has so far developed item banks for over 100 key HRQoL domains, such as physical (e.g., pain, physical function, itch, sleep), mental (e.g., anxiety, depression) and social health (e.g., ability to participate in social roles and activities) [7]. Item banks enable computerized adaptive testing (CAT) tools for individual assessment of HRQoL. A major advantage of the three PROMIS generic profile measures is that they are able to produce comparable results to the complete item banks [5]. Although originating from the US, the item banks and the profile measures have been translated to several languages and have increasingly been used in European and Asian countries [8‐12]. As standardised HRQoL measures are required to maintain their psychometric performance in different languages, the robustness of measurement properties needs to be confirmed for all language versions.
Among the three PROMIS adult profile measures, PROMIS-29 is the most widely used as a standalone, concise HRQoL measure [13]. By extending it with two items of cognitive function (PROMIS-29+2), it allows the estimation of quality-adjusted life years (QALYs) to assess benefits of treatments in economic analyses [14]. Psychometric performance of PROMIS-29, including validity, reliability and responsiveness, has already been tested in a broad range of health conditions and populations, such as cancer [15, 16], inflammatory bowel diseases [17], chronic kidney disease [18], burn [19], haemophilia [20], musculoskeletal diseases [21‐23], systemic lupus erythematosus [24], aortic dissection [25], elderly with multiple chronic conditions [26] and general population [27‐30]. Moreover, PROMIS-29 population reference values have also been established in many countries [28, 29] supporting the interpretation of scores by evaluating the relative burden of health conditions compared with reference values. The psychometric performance of the Hungarian PROMIS profile measures has not yet been tested and no reference scores are available for Hungary. This study therefore aims to (1) assess psychometric properties of the Hungarian PROMIS-29+2 profile measure and (2) provide general population reference values from a large representative sample in Hungary.
Methods
Study design and data collection
The study was approved by the Research Ethics Committee of the Corvinus University of Budapest (No. KRH/343/2020). The validation of PROMIS-29+2 formed part of a larger survey on health and well-being of the Hungarian general population [31, 32]. In November 2020, a web-based cross-sectional survey was undertaken in Hungary. We engaged a survey research company to conduct the data collection among members of an online panel. By contract the company provided access to the dataset of those respondents’ responses that had fully completed the questionnaire. Providing access to partially completed questionnaires was not included in the contract. The survey company provided compensation to the respondents in the form of survey points redeemable for rewards. We set ‘soft’ target quotas for age, gender, education, type of settlement and region to achieve a sample that approximates the composition of the Hungarian adult general population. Inclusion criteria were being aged ≥ 18 years and providing informed consent prior to starting the survey.
Respondents completed the official Hungarian-language version PROMIS-29+2 v2.1 [33] as distributed by the PROMIS Health Organization. Other data collected included sociodemographic questions (age, gender, education, employment, marital status, income, household size, type of settlement, region), history of chronic health conditions and the 36-item Short Form Health Survey (SF-36v1). The order of the two instruments was fixed, respondents first completed the PROMIS-29+2 followed by the SF-36. There were no missing values in the data as we made it mandatory to respond to all questions in the online survey.
PROMIS-29+2
PROMIS-29+2 v2.1 [33] was included in our survey that consists of PROMIS-29 and two items from Cognitive Function-Abilities v2.0 [34]. The PROMIS-29 profile comprises of 29 items relating to the following seven HRQoL domains [physical function, anxiety, depression, fatigue, sleep disturbance, ability to participate in social roles and activities (hereafter social roles) and pain interference] and an 11-point pain intensity numeric rating scale [5]. The Cognitive Function-Abilities items are measures of an eighth, cognitive function domain. Each PROMIS-29 domain has four five-level items. The five-point response scale varies across difficulty (i.e., ‘without any difficulty’ to ‘unable to do’), frequency (‘never’ to ‘always’), severity (‘not at all’ to ‘very much’) and global rating (‘very poor’ to ‘very good’) format scales. The recall period is unspecified for physical function and social roles; all other domains refer to the past seven days. A total raw score ranging from 4 to 20 (2–10 for cognitive function) may be computed for each domain by adding up the responses on each item of the domain. The US item calibrations were used to derive T-scores from raw domain scores, where a mean T-score of 50 with a SD of ten represents the US general population [7]. The only exception is the sleep disturbance domain, where a mixed general population and clinical sample was used for the calibration of T-scores with above-average sleep disturbance [35]. For scales of function (i.e., physical function, social roles and cognitive function) a higher score corresponds to a better HRQoL and for symptoms (i.e., anxiety, depression, fatigue, sleep disturbance and pain interference) a higher score corresponds to worse HRQoL [36].
36-item short form survey (SF-36)
SF-36 is one of the most extensively used and validated generic HRQoL instruments [37]. It assesses respondents’ HRQoL in 36 items covering eight domains with a four-week recall period: physical functioning (ten items), role limitations due to physical health problems (four items), bodily pain (two items), general health (five items), vitality (four items), social functioning (two items), role limitations due to emotional problems (three items) and mental health (five items). One item (2nd), which asks about health change, is not included in the scale or summary scores. Scores for items on each of the eight scales are summed up to give scale scores that are linearly transformed onto a 0–100 scale. Note that scores are not comparable across domains.
Psychometric analyses
Data analysis was carried out with R version 4.1.1 (Vienna, Austria). We followed classical test theory and IRT methods previously used in testing psychometric properties of PROMIS item banks and profile measures [6, 20, 21, 27, 38, 39]. For the analyses, we considered PROMIS-29 as the core measure and we tested measurement properties of the additional cognitive function domain separately, wherever possible. Psychometric analyses were performed on the unweighted sample; however, for estimating population reference values, the sample was weighted for age group and gender. All the statistical tests were two-sided, and p < 0.05 was considered statistically significant.
Floor and ceiling effect
Floor (proportion of responses at the lowest score) and ceiling (proportion of responses at the highest score) were computed for the eight PROMIS-29+2 domains. If > 15% of respondents scored the lowest or highest response level, we considered ceiling or floor effect to be present [40, 41].
Reliability analyses
Internal consistency reliability was assessed by computing Cronbach’s alpha and McDonald’s omega (total) for each domain (‘psych’ package [42]). For Cronbach’s alpha, a value > 0.70, while for McDonald’s omega total > 0.90 was considered as a sign of adequate internal consistency [43].
Item response theory assumptions
In accordance with previous PROMIS validation studies [6, 27, 30], the seven domains of PROMIS-29 were separately analysed with graded response models (GRM). Before modelling, the following three statistical assumptions were tested: unidimensionality, local independence and monotonicity. Unidimensionality was assessed using an exploratory bifactor model (‘psych’ package [42]) that allowed to extract explained common variance (ECV) and McDonald’s omega (hierarchical) values. The following cut-off values were used: ECV > 0.60 and omega > 0.70 [44]. IRT-based standardized Chen and Thissen’s index (χ2) was used to detect local dependence (‘mirt’ package [45]). A χ2 of > 0.3 implied possible local dependence and > 1 definite local dependence [46]. Any violations of local dependence were considered negligible if the ECV was ≥ 0.90 [46‐49]. Monotonicity was tested by examining the graphs of item mean scores conditional on the total raw scale score minus the item score [6].
Item response theory analyses
After confirming the IRT assumptions, we fitted a GRM (‘mirt’ package [45]). We examined each item’s discrimination (i.e., item slope, a) and item thresholds (i.e., item difficulty, b). Model fit was assessed by root mean square error of approximation (RMSEA), Standardized Root Mean Square Residual (SRMR), Comparative Fit Index (CFI) and Tucker–Lewis Index (TLI), and was considered acceptable if CFI > 0.95, TLI > 0.95, RMSEA < 0.06 and SRMR < 0.08 [50]. Item fit was assessed by computing the differences between observed and expected responses under the GRM using S-χ2 statistic, where a p-value < 0.001 was considered indicative of item misfit [51]. Item characteristic curves (ICCs) were generated using GRM.
Differential item functioning
To assess differential item functioning (DIF), a series of ordinal logistic regressions were fitted (‘lordif’ package [52]). In the first step, we performed an ordinal logistic regression without any anchor. The χ2 criterion was assessed looking for potential items with DIF. Once DIF was detected, we moved to the second step, where items within a domain that did not show any DIF were used as already-purified anchors. In this second step, three ordinal logistic regression models were estimated to compare the overall, uniform and non-uniform DIF for each item. Uniform DIF occurs when there is a constant systematic difference in item response between subgroups of respondents across the entire continuum of the latent trait, whereas non-uniform DIF occurs when the differences between groups vary across the continuum of the latent trait. Uniform, non-uniform and overall DIF were examined by comparing model 1 vs. model 2, model 2 vs. model 3, model 1 vs. model 3, respectively. Items were flagged for DIF when the McFadden’s pseudo R2 change was > 0.02 [33]. Test characteristic curves were used to visualize the aggregate impact of DIF on domain scores (i.e., differential test functioning). DIF was evaluated for age (median split at 47 years), gender (male vs. female), education (primary, secondary, university/college), employment (employed, retired, other), place of residence (capital, other town, village), geographical region (Central Hungary, Transdanubia, Great Plain and North), marital status (married or domestic partnership vs. any other) and household net monthly income per person (under or over the median of HUF 126,924 and do not know/want to answer).
Convergent validity
Convergent validity of PROMIS-29+2 was assessed against the SF-36v1 questionnaire. We used Spearman’s rank-order correlations to test the association between domains and summary scores of the two measures. Correlation coefficients were interpreted as very weak (< 0.20), weak (0.20–0.39), moderate (0.40–0.59), strong (0.60–0.79) and very strong (≥ 0.80) [53]. We hypothesized at least strong correlations between domains covering a similar construct (e.g., PROMIS physical function and SF-36 physical functioning). Weak or no correlations were assumed between the PROMIS cognitive function and SF-36 domains as this area of HRQoL is missing from the SF-36.
Population reference values and cross-country comparisons
In estimating population reference values, the sample was weighted for age group and gender to account for small deviations from the reference population in Hungary [54]. To accommodate the effect of weighting on variances, Taylor linearization was used to calculate appropriate standard errors. Mean (SD) dimension and summary T-scores and their 95%CIs were computed by gender and age groups (18–24, 25–34, 35–44, 45–54, 55–64 and 65 + years). Bivariate ordinary least squares regressions were used to test the association between domain T-scores and pain intensity scores with age groups and gender. Weighted domain T-scores were compared to those of the general population in the US, the UK, Germany and France [28].
Results
Characteristics of the sample
Overall, 2502 online panel members initiated the survey. Of these, 2079 consented and 379 dropped out during the questionnaire. A total of 1700 respondents finished the survey. The median completion time of PROMIS-29+2 was 2 min 59 s (Q1: 2 min 9 s, Q3: 4 min 8 s). Table 1 shows the sociodemographic and health-related characteristics of the respondents in comparison to the general population in Hungary. The sample was generally representative of the Hungarian general population for age, gender, employment and marital status, type of settlement and geographical region. Secondary educated respondents were underrepresented in the sample. Overall, 47.4% had a self-reported, physician diagnosed health condition. Descriptive statistics of PROMIS-29+2 and SF-36 domain scores are presented in Table 2.
Table 1
Characteristics of the study population (n = 1700)
Variables
Ref. populationa
Sample
%
n
%
Gender
Female
53.1
957
56.3
Male
46.9
743
43.7
Age (years)
18–24
10.0
148
8.7
25–34
15.2
293
17.2
35–44
19.5
309
18.2
45–54
16.0
304
17.9
55–64
16.8
296
17.4
65 +
22.5
350
20.6
Highest level of education
Primary school or less
23.8
468
27.5
Secondary school
55.0
682
40.1
College/university degree
21.2
550
32.4
Settlement
Capital
17.9
380
22.4
Other town
52.6
820
48.2
Village
29.5
500
29.4
Geographical region
Central Hungary
30.4
572
33.6
Transdanubia
30.2
493
29
Great Plain and North
39.5
635
37.4
Employment status
Employed
53.1
865
50.9
Retired
26.1
399
23.5
Disability pensioner
3.1
67
3.9
Student
4.7
74
4.4
Unemployed
3.1
129
7.6
Homemaker/housewife
1.0
99
5.8
Other
n/a
67
3.9
Per capita net monthly household income (HUF)
0–66,779
n/a
224
13.2
66,780–99,511
n/a
252
14.8
99,512–126,924
n/a
229
13.5
126,925–164,049
n/a
207
12.2
164,050 +
n/a
423
24.9
I do not know/refused to answer
n/a
365
21.5
Marital status
Married
45.6
718
42.2
Domestic partnership
13.4
360
21.2
Single
18.5
336
19.8
Widowed
11.4
98
5.8
Divorced
11.1
156
9.2
Other
n/a
32
1.9
Self-perceived health status (SF-36 question 1)
Excellent
n/a
139
8.2
Very good
n/a
401
23.6
Good
n/a
682
40.1
Fair
n/a
388
22.8
Poor
n/a
90
5.3
History of chronic illnessb
Yes
48.0
805
47.4
No
52.0
724
42.6
Do not know/refused to answer
–
171
10.1
n/a = not available
aHungarian Central Statistical Office: Microcensus 2016
bHungarian Central Statistical Office, Health at a Glance 2019
Percentages may not total 100% due to rounding
Table 2
Descriptive statistics of the outcome measures
Measures
Theoretical range
Observed range
Floor effect
Ceiling effect
Mean
SD
Median
Q1–Q3
n
%
n
%
PROMIS - 29+2
Physical functioning T-score
22.5–57
22.5–57
5
0.29
1032
60.71
51.55
7.56
57
45.5–57
Anxiety T-score
40.3–81.6
40.3–81.6
601
35.35
11
0.65
50.84
9.81
51.2
40.3–57.7
Depression T-score
41–79.4
41–79.4
749
44.06
13
0.76
49.94
9.54
49
41–55.7
Fatigue T-score
33.7–75.8
33.7–75.8
429
25.24
22
1.29
46.92
10.42
48.6
33.7–53.1
Sleep disturbance T-score
32–73.3
32–73.3
105
6.18
11
0.65
48.39
8.22
48.4
42.45–54.3
Social roles T-score
27.5–64.2
27.5–64.2
13
0.76
664
39.06
55.45
8.89
55.8
50–64.2
Pain interference T-score
41.6–75.6
41.6–75.6
858
50.47
18
1.06
49.35
8.9
41.6
41.6–55.6
Cognitive function T-score
29.5–61.2
29.5–61.2
98
5.76
620
36.47
52.66
8.73
54.7
50.5–61.2
Pain intensity NRS (0–10)
0–10
0–10
530
31.18
7
0.41
2.49
2.5
2
0–4
SF-36
Physical functioning
0–100
0–100
14
0.82
637
37.47
81.72
24.15
90
75–100
Role functioning
0–100
0–100
216
12.71
1007
59.24
74.74
36.12
100
50–100
Role emotional
0–100
0–100
207
12.18
1077
63.35
75.98
35.8
100
66.67–100
Vitality
0–100
0–100
11
0.65
113
6.65
62.13
23.88
65
45–80
Mental health
0–100
0–100
6
0.35
164
9.65
69.95
23.12
76
56–88
Social functioning
0–100
0–100
12
0.71
783
46.06
79.83
24.53
87.5
62.5–100
Bodily pain
0–100
0–100
9
0.53
574
33.76
76.16
24.3
80
57.5–100
General health
0–100
0–100
13
0.76
74
4.35
59.52
23.35
60
45–75
For PROMIS-29+2 scales of function (i.e., physical function, social roles and cognitive function) a higher score corresponds to a better HRQoL and for symptoms (i.e., anxiety, depression, fatigue, sleep disturbance and pain interference) a higher score corresponds to worse HRQoL. Higher score on pain intensity NRS indicates worst pain. For all SF-36 domains and summary scores, higher scores indicate better HRQoL. The observed range shows the range of domain scores observed in our sample, while the theoretical range refers to the possible range of the domains/items according to the PROMIS-29+2 and SF-36 instruments
HRQoL health-related quality of life, NRS numeric rating scale
Floor and ceiling effect
Among the eight PROMIS-29+2 domains, the highest floor effects were observed for pain interference (50.5%), followed by depression (44.1%), anxiety (35.4%) and fatigue (25.2%) (Table 2). Floors of the physical function, social roles, sleep and cognitive function domains were well below the threshold (0.3–6.2%). High ceiling effect was observed for physical function (60.7%), social roles (39.1%) and cognitive function (36.5%), while there were no apparent ceiling effects for the other domains (0.4–1.3%).
Reliability
Cronbach’s alpha and McDonald’s omega total values exceeded the thresholds of 0.70 and 0.90 for all PROMIS-29 domains with the exception of McDonald’s omega total (0.87) for the sleep disturbance domain (Table 3).
Table 3
Unidimensionality, IRT model fit and reliability estimates for the domains of the Hungarian PROMIS-29
Bifactor model (exploratory)
Graded response model
Reliability analyses
ECV
McDonald’s ω (hierarchial)
RMSEA
SRMR
CFI
TLI
Cronbach’s α
McDonald’s ω (total)
Physical function
0.80
0.87
0.103
0.025
0.993
0.979
0.91
0.96
Anxiety
0.93
0.91
0.032
0.012
0.999
0.998
0.92
0.94
Depression
0.92
0.92
0.056
0.013
0.998
0.995
0.93
0.94
Fatigue
0.91
0.92
0.126
0.020
0.992
0.975
0.94
0.96
Sleep disturbance
0.68
0.70
0.290
0.089
0.897
0.692
0.81
0.87
Social roles
0.93
0.92
0.035
0.017
0.999
0.998
0.93
0.94
Pain interference
0.94
0.94
0.067
0.010
0.998
0.994
0.96
0.97
CFI comparative fit index, ECV explained common variance, IRT item response theory, RMSEA root mean square error of approximation, SRMR Standardized Root Mean Square Residual, TLI Tucker–Lewis index
IRT assumptions
Using bifactor models, the unidimensionality assumption was confirmed for all PROMIS-29 domains. For sleep disturbance, ECV was met (0.68), however, McDonald’s omega hierarchical was exactly at the threshold (0.70) (Table 3). Chen and Thissen’s local dependence indices were below 1 for nearly all item pairs of each domain (Online Resource 1). The exceptions include Sleep109 (‘sleep quality’) vs. Sleep20 (‘problem with sleep’) and PAININ9 (‘pain interfering with day to day activities’) vs. PAININ22 (‘pain interfering with work around the home’). However, for the latter pair, the ECV from the bifactor model was very high (0.94), therefore the local dependence detected can be deemed negligible. In the sleep disturbance domain three item pairs showed a Chen and Thissen’s index of above 0.3 and one pair was above 1. Graph item mean scores conditional on total score minus item score supported the monotonicity assumption for all domains (Online Resource 2).
IRT analysis
For each of the seven PROMIS-29 domains, almost all three assumptions of IRT analysis were met. Several items misfitted the GRM as indicated by the p-values for the S–χ2 statistics (Table 4). Misfitting items included two items of the anxiety domain [EDANX01 (‘fearful’) and EDANX53 (‘uneasy’)], two items of the depression domain [EDDEP04 (‘worthless’), EDDEP41 (‘hopeless’)], all four items of the sleep disturbance domain and one item of the pain interference domain [PAININ31 (‘pain interfering with social activities’)].
Table 4
IRT parameters for the Hungarian PROMIS-29
Item code
Graded response model
a
b1
b2
b3
b4
Average b
Index-S-χ2
df
p-value
Physical function
PFA11
3.689
−2.529
−2.014
−1.503
−0.841
−1.72
29.897
18
0.038
PFA21
4.083
−2.423
−1.696
−1.111
−0.422
−1.41
25.186
14
0.033
PFA23
5.856
−2.32
−1.91
−1.466
−1.005
−1.68
17.187
11
0.102
PFA53
4.628
−2.571
−2.038
−1.615
−1.073
−1.82
20.957
14
0.103
Anxiety
EDANX01
3.926
0.114
0.858
1.608
2.394
1.24
39.719
15
< 0.001
EDANX40
5.348
0.51
1.134
1.721
2.41
1.44
30.455
12
0.002
EDANX41
4.802
0.198
0.898
1.431
2.08
1.15
36.039
15
0.002
EDANX53
3.714
−0.248
0.664
1.349
2.138
0.98
52.853
17
< 0.001
Depression
EDDEP04
3.819
0.396
0.957
1.592
2.235
1.3
47.713
18
< 0.001
EDDEP06
3.986
0.058
0.701
1.38
2.206
1.09
28.28
16
0.029
EDDEP29
4.191
0.501
0.989
1.604
2.304
1.35
29.28
16
0.022
EDDEP41
6.718
0.294
0.853
1.369
1.941
1.11
69.464
13
< 0.001
Fatigue
HI7
4.656
−0.422
0.565
1.165
1.984
0.82
35.657
14
0.001
AN3
4.29
−0.142
0.708
1.334
1.963
0.97
30.747
15
0.009
FATEXP41
3.928
−0.233
0.686
1.372
2.134
0.99
15.433
14
0.349
FATEXP40
6.941
−0.401
0.589
1.188
1.873
0.81
17.222
10
0.07
Sleep disturbance
Sleep109
2.644
−1.145
0.125
1.334
2.3
0.65
110.436
21
< 0.001
Sleep116
1.346
−1.972
−0.244
0.863
1.591
0.06
303.663
27
< 0.001
Sleep20
4.166
−0.199
0.559
1.317
1.955
0.91
95.558
19
< 0.001
Sleep44
2.29
−0.213
0.653
1.333
2.12
0.97
143.605
25
< 0.001
Ability to participate in social roles and activities
SRPPER11_CaPS
4.413
−2.043
−1.449
−0.766
−0.037
−1.07
18.222
15
0.251
SRPPER18_CaPS
4.948
−2.085
−1.509
−0.93
−0.302
−1.21
16.555
15
0.346
SRPPER23_CaPS
3.556
−2.4
−1.546
−0.872
−0.03
−1.21
16.67
17
0.477
SRPPER46_CaPS
5.4
−1.914
−1.333
−0.783
−0.167
−1.05
29.008
15
0.016
Pain interference
PAININ9
6.934
0.167
0.914
1.488
2.174
1.19
15.058
8
0.058
PAININ22
8.397
0.252
0.923
1.448
1.952
1.14
10.056
7
0.185
PAININ31
5.904
0.459
1.012
1.499
2.088
1.26
41.178
12
< 0.001
PAININ34
8.177
0.278
0.982
1.474
2.019
1.19
5.093
7
0.649
a = item’s discrimination (item slope), b = item threshold (item difficulty), IRT = item response theory
For all domains but sleep disturbance, the GRM models’ fit indices met the established criteria for SRMR, CFI and TLI. However, out of the seven PROMIS-29 domains, only anxiety, depression and social roles met the RMSEA cut-off value. The sleep disturbance (0.06–0.97) and fatigue (0.81–0.99) domains had the lowest average item difficulty (b), while physical function (1.41–1.82) had the highest in absolute values. The following items produced the highest discriminative ability (a): PAININ22 (‘pain interfering with work around the home’), PAININ34 (‘pain interfering with household chores’), FATEXP40 (‘fatigue on average’) and PAININ9 (‘pain interfering with day to day activities’). Three items of the sleep disturbance domain [Sleep116 (‘refreshing sleep’), Sleep44 (‘difficulty falling asleep’), Sleep109 (‘sleep quality’)] had the lowest item discrimination.
The ICC plots shown in Online Resource 3 indicated that for most items, the five response options were monotonically ordered. The only exception was item Sleep116 (‘refreshing sleep’) (Fig. 1).
Fig. 1
Item characteristic curves for PROMIS-29+2 Sleep disturbance domain
×
Differential item functioning
No DIF was identified for any of the domains for the following sociodemographic characteristics: gender, education, employment, place of residence, geographical region, marital status and income. However, PFA21 (‘go up and down stairs at a normal pace’) and PFA53 (‘run errands at shop’) of the physical function domain showed uniform DIF for age (McFadden’s pseudo R2 changes between model 1 and 2: 0.030 and 0.023, respectively). The test characteristic curves for these two items showed a small overall impact of DIF (Online Resource 4).
Convergent validity
Table 5 presents the results of the convergent validity analyses. In line with our hypotheses, evidence of strong convergence between corresponding PROMIS-29+2 and SF-36 domains were identified. The strongest correlations were observed between PROMIS-29+2 physical function and SF-36 physical function domains (rs = 0.78), PROMIS-29+2 fatigue and SF-36 vitality (rs = −0.76), PROMIS-29+2 pain interference and SF-36 bodily pain (rs = −0.74) and PROMIS-29+2 depression and SF-36 mental health (rs = −0.70). The PROMIS-29+2 sleep disturbance domain correlated weakly or moderately with SF-36 domains and showed the strongest association with vitality (rs = −0.57). As expected, the PROMIS-29+2 cognitive function domain correlated moderately or weakly with all SF-36 domains (rs = 0.18–0.42). The correlations between the domains within the two questionnaires are presented in Online Resources 5 and 6.
Table 5
Spearman’s correlation matrix between PROMIS-29+2 and SF-36 domains
PROMIS-29+2
SF-36
PF
RP
RE
VT
MH
SF
BP
GH
Physical function
0.78
0.60
0.42
0.38
0.31
0.39
0.56
0.59
Anxiety
−0.27
−0.36
−0.49
−0.60
−0.66
−0.53
−0.39
−0.38
Depression
−0.30
−0.38
−0.50
−0.63
−0.70
−0.58
−0.40
−0.40
Fatigue
−0.40
−0.49
−0.53
−0.76
−0.61
−0.53
−0.53
−0.46
Sleep disturbance
−0.29
−0.32
−0.34
−0.57
−0.54
−0.43
−0.37
−0.39
Ability to participate in social roles and activities
0.55
0.56
0.53
0.61
0.53
0.60
0.54
0.55
Pain interference
−0.64
−0.62
−0.45
−0.48
−0.39
−0.51
−0.74
−0.56
Cognitive function
0.18
0.19
0.26
0.41
0.42
0.39
0.24
0.26
Pain intensity (0–10)
−0.54
−0.53
−0.39
−0.48
−0.40
−0.46
−0.79
−0.54
For PROMIS-29+2 scales of function (i.e., physical function, social roles and cognitive function) a higher score corresponds to a better HRQoL and for symptoms (i.e., anxiety, depression, fatigue, sleep disturbance and pain interference) a higher score corresponds to worse HRQoL
BP bodily pain; GH general health; HRQoL health-related quality of life; MH mental health; PF physical functioning; RE role limitations due to emotional problems; RP role limitations due to physical health; SF social functioning; VT vitality
p < 0.05 for all correlation coefficients
Population reference values and cross-country comparisons
Mean domain T-scores tended to worsen with age for physical function, pain interference and social roles, whereas improved with age for depression, anxiety, fatigue and cognitive function (p < 0.01) (Table 6). The age gradient was not present for sleep disturbance (p = 0.155). Self-reported HRQoL problems were generally higher for females in all domains (p < 0.001), except for cognitive function (p = 0.348). Higher mean pain intensity scores were reported by older and female respondents (p < 0.001).
Table 6
Population reference values for Hungarian PROMIS-29+2 domain T-scores and pain intensity scale
Age groups (years)
Female
Male
Total
n
Mean
SD
95%CI lower
95%CI upper
n
Mean
SD
95%CI lower
95%CI upper
n
Mean
SD
95%CI lower
95%CI upper
Physical function
18–24
82
53.63
6.90
52.56
54.7
87
55.71
2.66
54.21
57.21
169
54.7
4.88
53.77
55.63
25–34
126
53.05
8.78
52.1
54
133
54.57
4.52
53.42
55.72
259
53.83
6.68
53.08
54.58
35–44
164
52.23
7.34
51.13
53.32
167
54.45
5.24
53.5
55.4
331
53.35
6.38
52.62
54.07
45–54
137
50.3
8.94
48.98
51.61
135
53.66
6.12
52.71
54.62
272
51.97
7.85
51.15
52.78
55–64
154
49.69
8.28
48.41
50.97
132
50.3
8.74
48.87
51.73
286
49.97
8.50
49.02
50.92
65 +
239
46.73
6.23
45.51
47.95
144
49.66
8.80
48.6
50.73
383
47.84
7.46
46.97
48.7
Total
902
50.29
8.20
49.78
50.8
798
52.92
6.62
52.45
53.39
1700
51.53
7.58
51.18
51.87
Anxiety
18–24
82
54.4
12.08
52.52
56.28
87
49.17
5.25
46.22
52.12
169
51.72
9.11
49.95
53.49
25–34
126
54.33
13.58
52.86
55.79
133
49.78
7.43
47.89
51.68
259
52
10.79
50.79
53.2
35–44
164
52.06
9.60
50.62
53.5
167
49.23
8.84
47.63
50.83
331
50.63
9.33
49.55
51.71
45–54
137
52.77
11.06
51.15
54.4
135
48.74
9.44
47.27
50.21
272
50.77
10.49
49.68
51.87
55–64
154
51.51
10.29
49.92
53.09
132
47.77
8.83
46.33
49.22
286
49.79
9.83
48.7
50.87
65 +
239
51.21
7.68
49.7
52.71
144
47.33
8.86
46.25
48.4
383
49.75
8.66
48.72
50.77
Total
902
52.38
10.36
51.72
53.04
798
48.65
8.55
47.96
49.33
1700
50.63
9.69
50.15
51.1
Depression
18–24
82
53.43
11.79
51.6
55.27
87
49.52
5.41
46.48
52.56
169
51.43
8.96
49.63
53.23
25–34
126
52.87
13.52
51.41
54.33
133
49.78
7.77
47.8
51.77
259
51.29
10.83
50.05
52.53
35–44
164
51.09
10.34
49.54
52.64
167
49.6
8.51
48.06
51.13
331
50.34
9.44
49.24
51.43
45–54
137
51.27
9.92
49.81
52.72
135
48.16
9.70
46.65
49.67
272
49.73
9.95
48.68
50.78
55–64
154
50.06
9.59
48.57
51.54
132
46.99
8.87
45.54
48.44
286
48.64
9.40
47.6
49.69
65 +
239
49.43
6.80
48.09
50.76
144
46.87
8.71
45.81
47.92
383
48.46
7.83
47.54
49.38
Total
902
50.96
9.93
50.34
51.59
798
48.45
8.64
47.76
49.15
1700
49.79
9.41
49.32
50.25
Fatigue
18–24
82
50.34
12.42
48.41
52.27
87
46.51
7.02
42.57
50.46
169
48.38
10.41
46.14
50.61
25–34
126
50.53
13.63
49.06
52
133
46.08
8.60
43.89
48.28
259
48.25
11.53
46.91
49.58
35–44
164
48.41
10.30
46.87
49.96
167
46.24
9.77
44.48
48.01
331
47.32
10.11
46.14
48.49
45–54
137
48.4
10.81
46.82
49.99
135
45.11
9.87
43.57
46.64
272
46.77
10.49
45.66
47.87
55–64
154
46.88
10.60
45.24
48.52
132
44.69
10.41
42.99
46.39
286
45.87
10.58
44.69
47.05
65 +
239
46.06
8.18
44.45
47.66
144
43.22
10.40
41.96
44.47
383
44.99
9.38
43.88
46.09
Total
902
48
10.76
47.31
48.68
798
45.25
9.85
44.44
46.06
1700
46.71
10.42
46.18
47.23
Sleep disturbance
18–24
82
49.25
10.68
47.59
50.91
87
48.63
4.32
46.2
51.06
169
48.93
7.54
47.45
50.42
25–34
126
50.7
10.31
49.58
51.81
133
47.16
6.26
45.56
48.76
259
48.88
8.59
47.9
49.87
35–44
164
48.69
8.24
47.45
49.92
167
48.1
7.00
46.84
49.37
331
48.39
7.62
47.51
49.28
45–54
137
49.7
8.42
48.47
50.94
135
46.13
8.33
44.84
47.43
272
47.93
8.59
47.04
48.83
55–64
154
49.48
8.92
48.1
50.85
132
47.44
8.10
46.11
48.76
286
48.54
8.62
47.57
49.5
65 +
239
49.17
6.98
47.81
50.54
144
45.75
8.40
44.73
46.77
383
47.89
7.95
46.95
48.82
Total
902
49.44
8.71
48.87
50
798
47.13
7.34
46.55
47.72
1700
48.36
8.18
47.95
48.76
Ability to participate in social roles and activities
18–24
82
56.35
9.75
54.83
57.86
87
57.89
5.09
55.03
60.76
169
57.14
7.75
55.5
58.78
25–34
126
55
11.46
53.76
56.24
133
57.57
6.42
55.93
59.21
259
56.32
9.07
55.28
57.35
35–44
164
55.78
9.06
54.42
57.13
167
57.22
7.68
55.83
58.6
331
56.5
8.39
55.53
57.48
45–54
137
53.88
9.53
52.48
55.28
135
57.56
8.89
56.17
58.94
272
55.71
9.42
54.72
56.69
55–64
154
53.26
9.78
51.75
54.77
132
55.99
9.28
54.47
57.51
286
54.52
9.65
53.44
55.59
65 +
239
52.92
7.09
51.53
54.31
144
55.53
9.76
54.35
56.71
383
53.9
8.36
52.93
54.88
Total
902
54.25
9.33
53.65
54.84
798
56.9
8.17
56.25
57.55
1700
55.49
8.89
55.05
55.93
Pain interference
18–24
82
47.73
9.14
46.3
49.15
87
45.14
3.52
43.16
47.12
169
46.4
6.45
45.17
47.63
25–34
126
48.76
11.72
47.5
50.03
133
46.54
6.26
44.95
48.14
259
47.63
9.07
46.6
48.65
35–44
164
49.29
9.04
47.93
50.64
167
47.45
7.09
46.17
48.73
331
48.36
8.11
47.43
49.29
45–54
137
52.15
10.49
50.61
53.69
135
47.28
8.02
46.03
48.53
272
49.74
9.66
48.74
50.73
55–64
154
51.18
9.71
49.68
52.68
132
49.14
8.93
47.68
50.6
286
50.24
9.42
49.18
51.29
65 +
239
52.74
7.26
51.32
54.17
144
49.62
10.03
48.4
50.83
383
51.57
8.60
50.57
52.57
Total
902
50.74
9.59
50.14
51.35
798
47.69
7.71
47.11
48.27
1700
49.31
8.85
48.89
49.73
Cognitive function
18–24
82
49.67
9.87
48.13
51.2
87
48.57
7.10
44.58
52.56
169
49.1
9.46
46.93
51.28
25–34
126
51.66
10.76
50.49
52.82
133
51.29
7.84
49.29
53.28
259
51.47
9.63
50.3
52.64
35–44
164
51.84
9.81
50.37
53.31
167
51.27
8.98
49.65
52.89
331
51.55
9.41
50.46
52.65
45–54
137
52.33
10.08
50.85
53.81
135
54.18
8.29
52.89
55.47
272
53.24
9.27
52.26
54.23
55–64
154
54.57
7.54
53.4
55.73
132
53.91
7.79
52.64
55.19
286
54.27
7.66
53.41
55.12
65 +
239
54.36
5.97
53.19
55.53
144
53.89
9.35
52.76
55.02
383
54.18
7.32
53.33
55.02
Total
902
52.82
8.82
52.27
53.37
798
52.38
8.90
51.64
53.12
1700
52.61
8.88
52.16
53.07
Pain intensity (0–10 NRS)
18–24
82
2.65
3.11
2.17
3.14
87
1.21
0.95
0.68
1.74
169
1.91
2.11
1.55
2.27
25–34
126
2.67
3.29
2.32
3.03
133
1.79
1.77
1.34
2.24
259
2.22
2.57
1.93
2.51
35–44
164
2.62
2.52
2.24
3
167
1.99
1.96
1.64
2.35
331
2.3
2.26
2.04
2.56
45–54
137
3.01
2.86
2.59
3.43
135
2.13
2.42
1.75
2.51
272
2.57
2.69
2.29
2.86
55–64
154
2.69
2.70
2.27
3.11
132
2.37
2.55
1.95
2.79
286
2.54
2.64
2.25
2.84
65 +
239
3.34
2.20
2.91
3.77
144
2.11
2.43
1.81
2.4
383
2.88
2.47
2.59
3.17
Total
902
2.89
2.73
2.72
3.07
798
1.98
2.12
1.82
2.14
1700
2.46
2.49
2.34
2.58
For PROMIS-29+2 scales of function (i.e. physical function, social roles and cognitive function) a higher score corresponds to a better HRQoL and for symptoms (i.e. anxiety, depression, fatigue, sleep disturbance and pain interference) a higher score corresponds to worse HRQoL. Higher score on pain intensity NRS indicate worst pain
HRQoL health-related quality of life, NRS numeric rating scale
Compared to the US calibration sample with a mean of 50 and the three European countries with existing reference values, mean PROMIS-29+2 domain T-scores in the Hungarian general population indicated similar or better HRQoL with the largest difference being seen for social roles (> 5 points from the US calibration sample) (Fig. 2). The lowest level of anxiety and sleep disturbance was found in Hungary, while for physical function it was similar to Germany and the UK and for depression, fatigue and pain interference to France. Cognitive function in Hungary was better compared to the US calibration sample.
Fig. 2
Comparison of domain T-scores in the general population across Hungary, the US, France, Germany and the UK. Note that the cognitive function domain is not presented in the figure due to the lack of data from general population samples in any of the Western European countries. For PROMIS-29+2 scales of function (i.e., physical function, social roles and cognitive function) a higher score corresponds to a better HRQoL and for symptoms (i.e., anxiety, depression, fatigue, sleep disturbance and pain interference) a higher score corresponds to worse HRQoL. HRQoL health-related quality of life
×
Discussion
This study assessed the psychometric properties of the Hungarian version of PROMIS-29+2 and provided reference values in a large representative sample of the adult general population in Hungary. Our findings provide evidence of a satisfactory measurement performance of the Hungarian PROMIS-29+2. Floor and ceiling effects were observed for nearly all domains depending on the scale orientation that is comparable to the findings of previous studies in various patient samples [18, 20, 21, 25]. An acceptable reliability was confirmed for all domains. Favourable psychometric properties of the scale include an excellent convergent validity with SF-36 and no or minor DIF for main sociodemographic characteristics. Nevertheless, few potential weaknesses of PROMIS-29+2 have also been identified, particularly the poor performance of the sleep disturbance domain.
While the GRM produced an acceptable fit for six PROMIS-29+2 domains, sleep disturbance failed to meet any fit indices and showed item misfit for all four items of the domain and very low item discrimination ability. Sleep109 (‘sleep quality’) vs. Sleep20 (‘problem with sleep’) showed local dependence suggesting redundancy between the two items. Furthermore, response categories of item Sleep116 (‘refreshing sleep’) were disordered and its discriminatory ability was also substantially lower than that of any other item. Similarly to our findings, the Norwegian and Dutch PROMIS-29 validation studies also reported problems with the performance of the sleep disturbance domain and item characteristics curves of Sleep116 [27, 30]. The sleep disturbance domain of PROMIS-29 is unique in the sense that it includes two positively phrased, reverse coded items (Sleep109 and Sleep116). In questionnaires, reverse-worded items are typically intended to reduce response bias (e.g., pattern answering), disrupt nonsubstantive responding or provide a better coverage of the domain studied [55]. Yet, several studies reported that such items can lead to measurement problems, including low reliability and poor model fit and some argue that they would prevent respondents from inattentive or acquiescent answering [56]. The further exploration of the issues with the sleep disturbance domain as well as testing alternative combinations of items could be subject of future research that administer the full PROMIS sleep item bank.
HRQoL decreased with age for physical and social health domains, but not for the cognitive or mental ones. This finding corresponds to the general population reference values in neighbouring Slovenia that reported worse mental health among young adult respondents using the EQ-5D-5L [57] and to the European reference values for the European Organisation for Research and Treatment of Cancer (EORTC) CAT Core that reported an improving trend for cognitive and emotional functions with age [58]. The better HRQoL of the Hungarian population in some domains compared to Western Europe is an unexpected finding as the average health status in Hungary was found to be below the EU average [59]. Comparisons across countries using different health status measures also reported mixed evidence. Using the EQ-5D-3L, the Hungarian general population was in a substantially worse HRQoL compared to other European countries [60]; however, the EQ-5D lacks domains for fatigue, sleep problems and social roles. By contrast, the EORTC CAT showed that in some HRQoL domains (e.g., physical functioning, social functioning, sleep problems), the Hungarian population, in fact, had a better health status than what was found in Germany or the UK [58].
In this study, we used the official US item parameters to compute T-scores. However, multiple approaches exist to score PROMIS items with each offering their own advantages and disadvantages [61]. Using the US item calibrations follows the PROMIS convention and has the advantage that it represents a common metric, which directly allows for international comparisons. On the other hand, if any item within a domain shows language-DIF, the parameter estimates may not be valid for the local population. Another option is using country-specific item calibrations that enable improved accuracy for comparisons with local patient groups and country-specific interpretation of scores. To benefit from the advantages of both methods, a hybrid approach may also be recommended that uses US item calibrations for items without language-DIF and country-specific item parameters for items with language-DIF [62].
There are a number of limitations to this study. First, the online mode of administration might be responsible for selection bias, and the quota sampling lacks known sampling probability. Second, data were collected during the second wave of the COVID-19 pandemic in Hungary that could have an effect on self-reported health, particularly on young adults’ mental health [62‐67]. However, responses on self-perceived health status (SF-36 first question) were roughly identical to those reported in a similar large-scale general population survey in Hungary before the pandemic (2019) [68]. The third limitation is that we had no information on the total number of potential respondents contacted by the survey company or access to the data from partially completed questionnaires. Fourth, the reference values for the 65 + age group might not be fully representative to the general population as there were relatively few respondents in the 75 + age group (3.4%). Fifth, it was not possible to fit a GRM for cognitive function because the domain has only two items in PROMIS-29+2. Finally, for each PROMIS-29 domain we fitted a GRM, as this modelling approach was used to develop the PROMIS item banks and this is suggested in the PROMIS analytical recommendations [6]. However, it is possible that certain traits measured by PROMIS-29+2 domains do not have an a priori normal distribution in the population, e.g., physical functioning, pain, fatigue, anxiety and depression because many respondents reporting no problems [69]. A few alternative model types exist that could be useful for future analyses, for example, to alleviate the skewness in data, e.g., zero-inflated mixture IRT models or Davidian Curve IRT [70, 71].
In summary, our results provide support for the satisfactory psychometric properties of the Hungarian version of PROMIS-29+2, including internal consistency reliability, good convergent validity with SF-36 and no DIF. However, the large ceiling and floor effect may detract from the usefulness of the measure when the aim is to differentiate between HRQoL levels at the mild end of the scale. Measurement problems were found with regard to the sleep disturbance domain that would require further refinement. Age and gender-specific reference values were generated for the Hungarian PROMIS-29+2 that facilitate the interpretation of HRQoL outcomes in various patient populations.
Acknowledgements
The authors wish to thank Istvan Mucsi for supporting this study.
Declarations
Conflict of interest
The authors have not disclosed any competing interests.
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