Introduction
Methods
Participants
Procedures
v1.2 PROMIS global health
Statistical analysis
Research questions from a users’ perspective | Research questions from a psychometric perspective | Psychometric property | Analyses per subscale | Statistic | Criteria | Reference | Software package with reference | Results | |
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GMH | GPH | ||||||||
1. Is it legitimate to calculate IRT-based score for this measure? | Do the items assess only one construct? | Unidimensionalitya | CFA | CFI | ≥ 0.95 | [44] | Mplus software (version 6.0) [45] | 0.98 | 0.99 |
TLI | ≥ 0.95 | [44] | 0.95 | 0.97 | |||||
RMSEA | ≤ 0.06 | [44] | 0.22 | 0.12 | |||||
SRMR | ≤ 0.08 | [44] | 0.04 | 0.03 | |||||
Exploratory Bifactor Analysis | ECV | > 0.70 | [46] | R package psych (version 1.7.8) [47] | 0.80 | 0.71 | |||
ωH | > 0.80 | [48] | 0.75 | 0.65 | |||||
Do the items relate to the construct being measured only? | Local independence | Residual correlation matrixb | r | ≤ 0.20 | [25] | Mplus software (version 6.0) [49] | all r < 0.20 | all r < 0.20 | |
Do the probabilities of higher responses to the items increase with increasing levels of the construct? | Monotonicity | Mokken scale analysis | Hi | ≥ 0.30 | [50] | R-package Mokken (version 2.8.4) [51] | See Table 3 | See Table 3 | |
H | > 0.50 | [50] | 0.60 | 0.54 | |||||
ICCsc | Graphic display | See Fig. 1a | See Fig. 1b | ||||||
Can the relationship between the items and the construct be described using an IRT-model? | IRT-model fit | Logistic GRM model fit | S-X2 and p of the items | p ≥ 0.001* | R-package mirt (version 3.3.2) [54] | See Table 3 | See Table 3 | ||
2. Is this measure able to discriminate between different levels of the construct/trait? | Do the items have the ability to discriminate between different levels of the construct/trait? | Range of item discrimination | IRT-modelling | αd | > 1.0 | [52] | R-package mirt (version 3.3.2) [54] | See Table 3 | See Table 3 |
3. Does this measure cover the relevant range of the construct/trait? | Do the items cover the relevant range of the construct/trait? | Range of item difficulties | IRT-modelling | βe | N/A | [52] | R-package mirt (version 3.3.2) [54] | See Table 3 | See Table 3 |
4. Is this measure reliable? | What is the overall precision of this measure in this sample? | Internal consistency | Internal consistency | Cronbach’s alpha | > 0.70 | [55] | SPSS software. Version 21 for Windows | 0.83 | 0.78 |
What is the contribution of the individual items to this overall precision? | Internal consistency | Internal consistency | Cronbach’s alpha if item deleted | Reduction of totalalpha | [56] | See Table 3 | See Table3 | ||
Corrected item-to-total correlation | rs | ≥ 0.40 | [57] | See Table 3 | See Table 3 | ||||
What is the precision of this measure at different levels of the construct/trait? | Precision | TIC and IIC | Graphic display | See Fig. 2a | See Fig. 2b | ||||
5/6. Does this measure function in the same way in different (sub)groups? | Can this measure be used to compare (sub)groups in terms of demographic variables? | Measurement invariance | DIFg | Change in Mcfadden R2 | > 0.02 | R-package lordif (version 0.3–3) [58] | See Table 3 | See Table 3 | |
Can this measure be used to compare the scores of English-speaking persons (who responded to its English original version) and Dutch-speaking persons (who responded to its Dutch-Flemish translation)? | Cross-cultural validity | DIFg | Change in Mcfadden R2 | > 0.02 | R-package lordif (version 0.3–3) [58] | See Table 3 | See Table 3 |
Results
Participants
Variable | Dutch generalpopulation studytotal sample (N = 4370) | Dutch general population study sample 1 (N = 1052) | Dutch general population study sample 2 (N = 1006) | Dutch general population study sample 3 (N = 1002) | Dutch general population study sample 4 (N = 1310) | Dutch general population 2016a (N = 13,562,539) | |
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Mean ± SD | Percentage | Percentage | Percentage | Percentage | Percentage | Percentage | |
Age (years): | 51.2 ± 16.6 | ||||||
18–39 | 32.9 | 31.7 | 31.3 | 31.5 | 35.1 | 33.7 | |
40–65 | 44.1 | 45.0 | 45.1 | 45.6 | 42.4 | 43.6 | |
> 65 | 23.1 | 23.3 | 23.6 | 22.9 | 22.5 | 22.7 | |
Gender: | |||||||
Male | 47.3 | 47.4 | 47.5 | 47.6 | 47.4 | 49.2 | |
Female | 52.7 | 52.6 | 52.5 | 52.4 | 52.6 | 50.8 | |
Educational level: | |||||||
Low | 29.1 | 27.8 | 27.9 | 29.3 | 31.0 | 30.2 | |
Middle | 40.9 | 40.2 | 42.3 | 42.6 | 39.8 | 40.2 | |
High | 30.0 | 32.0 | 29.8 | 28.0 | 29.2 | 29.6 | |
Region: | |||||||
North | 10.2 | 9.9 | 10.9 | 10.2 | 9.4 | 10.2 | |
East | 20.5 | 21.4 | 19.8 | 19.9 | 20.8 | 20.8 | |
South | 21.2 | 21.1 | 21.9 | 20.1 | 20.5 | 21.6 | |
West | 47.9 | 47.1 | 47.1 | 49.6 | 49.2 | 47.4 | |
Missing | 0.3 | 0.5 | 0.3 | 0.3 | 0.2 | - | |
Ethnicity: | |||||||
Native | 78.2 | 76.7 | 79.1 | 77.2 | 79.5 | 78.6 | |
First and second generation western immigrant | 11.8 | 11.7 | 11.9 | 12.7 | 11.8 | 10.3 | |
First and second generation non-western immigrant | 10.0 | 11.6 | 9.0 | 10.1 | 8.7 | 11.2 | |
Global Mental Health (GMH) T-scoreb | 44.7 ± 8.0 | ||||||
Global Physical Health (GPH) T-Scoreb | 45.2 ± 9.2 |
Items
Items description | Descriptives | Mokken scalability | GRM model fit | Range of item discrimination and difficulties* | Internal consistency | Measurement invariance | Cross cultural validity | |||||||||||||
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Mean (SD) | Range (Min–Max) | Skewness (SE) | Kurtosis (SE) | Hi (SE) | S-X2 | p | α | β1 | β2 | β3 | β4 | IIT | αIID | Sex | Age | Region | Educ. level | Ethnicity | ||
Global Mental Health | ||||||||||||||||||||
Global02: quality of life | 3.0 (0.9) | 1–5 | 0.08 (0.04) | − 0.17 (0.07) | 0.633 (0.009) | 94.550 | < 0.001 | 3.507 | − 1.935 | − 0.603 | 0.710 | 1.893 | 0.72 | 0.76 | 0.0025 | 0.0065 | 0.0005 | 0.0014 | 0.0001 | 0.0041 |
Global04: mental health, including mood and ability to think | 3.1 (1.0) | 1–5 | 0.01 (0.04) | − 0.32 (0.07) | 0.654 (0.009) | 160.820 | < 0.001 | 2.757 | − 2.047 | − 0.783 | 0.529 | 1.648 | 0.73 | 0.75 | 0.0007 | 0.0031 | 0.0001 | 0.0006 | 0.0011 | 0.0028 |
Global05: satisfaction with social activities and relationships | 3.0 (0.9) | 1–5 | 0.03 (0.04) | − 0.15 (0.07) | 0.603 (0.010) | 87.731 | < 0.001 | 2.849 | − 1.855 | − 0.644 | 0.739 | 1.916 | 0.68 | 0.78 | 0.0017 | 0.0031 | 0.0003 | 0.0012 | 0.0018 | 0.0032 |
Global10: bothered by emotional problems | 3.7 (1.0) | 1–5 | − 0.31 (0.04) | − 0.64 (0.07) | 0.518 (0.012) | 323.387 | < 0.001 | 1.321 | − 3.717 | − 1.779 | − 0.220 | 1.181 | 0.52 | 0.85 | 0.0070 | 0.0165 | 0.0017 | 0.0034 | 0.0020 | 0.0136 |
Global physical health | ||||||||||||||||||||
Global03: physical health | 2.7 (0.9) | 1–5 | 0.24 (0.04) | − 0.23 (0.07) | 0.565 (0.010) | 145.562 | < 0.001 | 2.266 | − 1.792 | − 0.239 | 1.094 | 2.248 | 0.62 | 0.71 | 0.0010 | 0.0022 | 0.0019 | 0.0021 | 0.0041 | 0.0046 |
Global06: carry out every day physical activities | 4.1 (1.2) | 1–5 | − 0.91 (0.04) | − 0.32 (0.07) | 0.525 (0.013) | 184.359 | < 0.001 | 1.943 | − 2.668 | − 1.619 | − 0.705 | − 0.055 | 0.55 | 0.74 | 0.0018 | 0.0013 | 0.0005 | 0.0030 | 0.0003 | 0.0006 |
Global07: pain on average | 3.1 (2.7) | 1–5 | 0.41 (0.04) | − 1.16 (0.07) | 0.547 (0.010) | 82.367 | < 0.001 | 2.063 | − 3.641 | − 1.306 | − 0.279 | 0.916 | 0.62 | 0.71 | 0.0013 | 0.0047 | 0.0002 | 0.0013 | 0.0011 | 0.0048 |
Global08: fatigue on average | 3.4 (1.0) | 1–5 | − 0.16 (0.04) | − 0.50 (0.07) | 0.513 (0.011) | 64.189 | < 0.001 | 1.705 | − 2.844 | − 1.291 | 0.144 | 1.548 | 0.56 | 0.74 | 0.0029 | 0.0458 | 0.0018 | 0.0049 | 0.0034 | 0.0002 |
Items not contributing to the subscale scores | ||||||||||||||||||||
Global01: general health | 2.8 (0.9) | 1–5 | 0.20 (0.04) | − 0.16 (0.07) | – | – | – | – | – | – | – | – | – | – | – | – | – | – | – | – |
Global09: usual social activities and roles | 3.0 (0.9) | 1–5 | 0.07 (0.04) | − 0.12 (0.07) | – | – | – | – | – | – | – | – | – | – | – | – | – | – | – | – |
Recommended values | N/A | N/A | N/A | N/A | > 0.30 | N/A | ≥ 0.001 | > 1.0 | N/A | N/A | N/A | N/A | ≥ 0.40 | < α | < 0.02 | < 0.02 | < 0.02 | < 0.02 | < 0.02 | < 0.02 |
Is it legitimate to calculate IRT-based scores for PROMIS-GH?
Items | Sample 1 | Sample 2 | Sample 3 | Sample 4 | Sample 5 | Sample 6 | Sample 7 | Sample 8 | Sample 9 | Sample 10 | ||||||||||
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S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | S-X2 | p.S-X2 | |
Global mental health | ||||||||||||||||||||
Global02 | 12.559 | 0.084 | 13.954 | 0.083 | 6.435 | 0.696 | 6.796 | 0.658 | 42.118 | 0.000 | 10.239 | 0.509 | 22.968 | 0.003 | 8.201 | 0.414 | 14.972 | 0.133 | 8.879 | 0.449 |
Global04 | 14.218 | 0.115 | 21.793 | 0.040 | 17.267 | 0.100 | 18.825 | 0.043 | 34.371 | 0.001 | 30.387 | 0.007 | 24.238 | 0.007 | 39.123 | 0.000 | 23.835 | 0.021 | 18.996 | 0.089 |
Global05 | 18.809 | 0.027 | 12.457 | 0.189 | 30.303 | 0.000 | 11.846 | 0.540 | 8.327 | 0.684 | 17.109 | 0.105 | 4.854 | 0.847 | 25.040 | 0.015 | 19.845 | 0.031 | 14.416 | 0.155 |
Global10 | 63.991 | 0.000 | 39.085 | 0.007 | 43.508 | 0.000 | 35.477 | 0.003 | 42.483 | 0.001 | 56.640 | 0.000 | 47.465 | 0.000 | 73.273 | 0.000 | 47.167 | 0.000 | 19.519 | 0.191 |
Global physical health | ||||||||||||||||||||
Global03 | 23.068 | 0.041 | 30.304 | 0.003 | 17.584 | 0.092 | 28.022 | 0.009 | 25.689 | 0.019 | 24.152 | 0.030 | 9.089 | 0.614 | 19.221 | 0.057 | 14.474 | 0.341 | 25.292 | 0.046 |
Global06 | 23.940 | 0.121 | 25.469 | 0.085 | 16.071 | 0.519 | 22.376 | 0.171 | 27.245 | 0.099 | 15.739 | 0.471 | 17.621 | 0.347 | 28.619 | 0.038 | 26.008 | 0.074 | 22.647 | 0.123 |
Global07 | 19.943 | 0.174 | 15.422 | 0.350 | 13.859 | 0.460 | 16.168 | 0.303 | 38.288 | 0.000 | 11.051 | 0.854 | 24.764 | 0.053 | 39.554 | 0.001 | 12.297 | 0.503 | 14.859 | 0.388 |
Global08 | 7.800 | 0.856 | 17.086 | 0.449 | 18.065 | 0.204 | 20.637 | 0.193 | 13.724 | 0.687 | 20.874 | 0.141 | 16.816 | 0.536 | 32.616 | 0.019 | 19.606 | 0.143 | 27.718 | 0.048 |
Recommended values | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC | N/S | ≥ p-BC |