Measurement Properties and Optimal Cutoff Point of the WHO-5 Among Chinese Healthcare Students

Abstract

Purpose

The World Health Organization-Five Well-Being Index (WHO-5) is widely used to assess subjective well-being. Nevertheless, measurement invariance and optimal cutoff point of the WHO-5 have not been examined in Chinese samples. We aimed to assess measurement properties of the Chinese version of the WHO-5 (WHO-5-C) among healthcare students.

Patients and Methods

A two-wave longitudinal assessment was conducted among 343 Chinese healthcare students from September to November 2022. Measurement properties of the WHO-5-C were assessed through structural validity using confirmatory factor analysis (CFA), measurement invariance using multigroup CFA (MGCFA) and longitudinal CFA (LCFA), convergent validity using correlation analysis with the Self-Rated Health Questionnaire (SRHQ) and Patient Health Questionnaire-4 (PHQ-4), reliability using internal consistency and test–retest reliability, and optimal cutoff point using receiver operating characteristic (ROC) analysis.

Results

The WHO-5-C demonstrated satisfactory structural validity with comparative fit index (CFI) of 0.968 at baseline and 0.980 at follow-up, and adequate measurement invariance in different sociodemographic variables at baseline (gender, age, major, home location, being only child, monthly household income, part-time job, physical exercise, hobby, frequency of visiting home, and stress coping strategy) (CFI changes [ΔCFI] = −0.009–0.003) and over a week (ΔCFI = −0.006–0.000). The WHO-5-C also had good internal consistency (Cronbach’s α = 0.907–0.934; McDonald’s ω = 0.908–0.935) and test–retest reliability (intraclass correlation coefficient [ICC] = 0.803). Convergent validity was supported by moderate correlations of the WHO-5-C with the SRHQ and PHQ-4. The optimal cutoff point of the WHO-5-C was found to be 50, with an area under the ROC curve of 0.882 at baseline data, with sensitivity of 0.803 and specificity of 0.762 at follow-up.

Conclusion

The WHO-5-C demonstrated adequate measurement properties, especially concerning cross-sectional and longitudinal measurement invariance, with a recommended optimal cutoff point of ≥ 50 for assessing adequate level of psychological well-being in healthcare students.

Keywords:

• WHO-5 Well-Being Index
• subjective well-being
• measurement properties
• diagnostic performance
• observational longitudinal design
• healthcare students

Introduction

Subjective well-being (SWB) refers to an individual’s ability to develop their potential, to work productively and creatively, to build strong and positive relationships with others, and to contribute to their community.¹ SWB involves multiple dimensions and its contribution to all aspects of human life, eg, optimistic attitude, positive affect, psychological resilience, and happiness.² Positive SWB is recognized as having crucial consequences for better physical outcomes in both healthy populations and patients suffering from various diseases, such as fewer self-perceived symptoms, fewer pain sensations, and longer survival.^3–5 As such, positive SWB has been regarded as a conducive health asset given its explicit associations with salutary outcomes of mental health,⁶ behaviors,⁷ and disease progression and rehabilitation.⁸ Therefore, identifying SWB carries clinical significance for public and psychosomatic health.

There has been increasing evidence showing that college students are exposed to excessive academic pressures that may affect their academic performance, lifestyle, physical health, and even psychosomatic disorders.^9–11 Healthcare students are expected to provide professional support in health services for individuals and societies in the future¹² and are at risk of physical and mental disorders.^13,14 Worldwide, approximately one-third of healthcare students suffer from negative emotions, which is notably higher than general population and non-healthcare students.^15,16 A meta-analysis of mental health problems among healthcare students in China showed that the prevalence of depression, anxiety, and suicidal ideation were 29%, 21%, and 11%, respectively, underlining the severity of the issue and urgency to understand their well-being more.¹⁷ Therefore, instruments with a positive focus can suggest to respondents that such programs are for individuals with pleased SWB and in this way support, rather than detract from, these initiatives.

There are numerous approaches in explaining and assessing well-being, and several instruments have been developed to monitor well-being.¹⁸ To date, the popular instruments for assessing SWB state are mostly symptom-based, eg, stress, anxiety, depression and bipolar disorders.^19–21 Existing instruments developed to evaluate well-being are mostly based on a single perspective.¹⁸ For instance, one of the most widely used for evaluating SWB is the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS), a 14-item instrument developed to assess hedonic and eudaimonic elements of mental health.²² Despite previous researches have endorsed the WEMWBS presented appropriate capacity for mental well-being in Chinese samples, it does not consider purpose in physical condition which is an essential component of overall well-being.^23,24 Likewise, other instruments introduced into China to determine SWB include the Personal Wellbeing Index (PWI),²⁵ Psychological Well-Being Scale (PWBS),²⁶ etc., and most only assess satisfaction level in terms of health-related quality of life. It is necessary to unearth an instrument that can capture a comprehensive conception of SWB, including affective-emotional aspects and physiological feelings.

The positively worded World Health Organization-Five Well-Being Index (WHO-5) is one of the measures from a positive perspective, aiming to measure overall wellness and cover healthy elements psychologically and physically.²⁷ As a multidimensional screening instrument, the WHO-5 initially comprised twenty-eight items and progressively shortened to five positive items to produce a brief and comprehensive scale of well-being.^27,28 To date, there are more than thirty official language versions of the WHO-5 that have been endorsed by the World Health Organization (WHO).²⁷ The scale has been adapted and validated across numerous cultures, including Arabic,²⁹ Brazilian,³⁰ Chinese,³¹ German,³² Icelandic,³³ Japanese,³⁴ Malay,³⁵ Polish,³⁶ Portuguese,³⁰ Sinhala,³⁷ Spanish,³⁸ Swahili,³⁹ Swedish,⁴⁰ and Turkish.⁴¹ The original English version of the WHO-5,⁴² as well as the Japanese³⁴ and Polish³⁶ versions, had a single-factor structure with excellent reliability and validity in adolescents with type 1 diabetes and a cutoff point below 50 was established to identify worsened well-being. Moreover, the WHO-5 has revealed correlations with adverse health conditions among different samples of diverse cultures, including Spanish, Swedish, and Turkish.^38,40,41 The WHO-5, overall, has sufficient validity to measure SWB in patients and general populations across study fields, and the scale has been extensively applied in endocrinology, psychiatry, and clinical as well as positive psychology.^28,37 Therefore, the WHO-5 demonstrated adequate effectiveness as both an outcome measure in clinical trials and a screening instrument in community settings.

The WHO-5 has been adapted and validated in Chinese university students⁴³ and medical educators.⁴⁴ Measurement properties of the Chinese version of the WHO-5 (WHO-5-C) were assessed in a recent multi-site study among a sample of university students and reported a stable one-factor structure and adequate internal consistency, factorial validity, construct validity and concurrent validity.⁴³ According to the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guideline,⁴⁵ it would be integral to further ascertain test–retest reliability, measurement invariance, measurement error, and recommended cutoff point of the WHO-5-C, intending to select the most appropriate outcome measurement instruments in research and clinical practice. This study aimed to achieve the goal of validating the WHO-5-C as a screening and monitoring instrument of SWB using data collected from healthcare students. This two-wave longitudinal study specifically assessed structural validity, measurement invariance, convergent validity and reliability; identified the optimal cutoff point by conducting receiver operating characteristic (ROC) analysis; and determined cross-sectional and longitudinal measurement invariance with respect to sociodemographic variables and approximately one-week interval, respectively. We hypothesized that the WHO-5 can serve as both an assessment and a screening instrument for routine monitoring of SWB in Chinese samples.

Materials and Methods

Participants and Procedures

This study was a two-wave longitudinal assessment and a convenience sample from a university in Hangzhou, China, participated in a paper-based survey in simplified Chinese from September to November 2022 upon informed consent. We recruited healthcare students who were enabled to read and write simplified Chinese and had the ability to conduct the response process freely. Respondents were excluded if they: 1) had difficulty understanding or writing Chinese; 2) were on leave or out of school; or 3) disagreed to participate in the study. The self-report paper-and-pencil survey was administered during breaks between classes or evening self-study and required about 10 minutes to complete the questionnaires. The trained investigators were responsible for implementing assessment and ensuring its onsite quality control. All participants were required to complete two-wave longitudinal measurements with an average interval of 7 days + 3 hours, given that 1) the appropriate interval varies from an hour to a year depending on the task, but generally speaking, a retest interval of 2 to 14 days is usual;⁴⁶ and 2) reproducibility of health status measures intended for longitudinal use may best be measured at intervals of 1 to 2 weeks.⁴⁷ Respondents were compensated with 2 CNY (1 CNY ≈ 0.150 US dollars) each. The valid questionnaires in this study (N = 343) reached recommended sample size for factor analyses: 1) the sample size of 300 is considered as good;⁴⁸ 2) the appropriate minimum for sample size include from 3 to 20 times the number of variables, and sample size above 200 is suggested when the variables-to-factors is six.⁴⁹

The current study was conducted in accordance with the Declaration of Helsinki⁵⁰ and approved by the Institutional Review Board of the School of Public Health, Hangzhou Normal University, China (Reference No. 20210014). All healthcare students freely consented to respond to the questionnaires and provided their informed consents before inclusion into the assessments. The authors confirmed full respect and protection of individual privacy rights before, during, and after the data collection and processing.

Measures

Sociodemographic Variables

We collected sociodemographic variables, including gender (male, female), age, major (clinical medicine, preventive medicine), home location (urban, rural, suburban), being only child (yes, no), monthly household income (< 10,000 CNY, ≥ 10,000 CNY), part-time job (yes, no), physical exercise [exercise goals to improve health (yes, no)], hobby (yes, no), frequency of visiting home [frequently (once per week, twice per week, and once per month); occasionally (once per quarter, once per semester, and once per academic year)], and self-reported preferred stress coping strategy (emotion-focused, solution-focused, avoidance coping).

World Health Organization-Five Well-Being Index (WHO-5)

The WHO-5 developed by the WHO is a brief self-report instrument used to assess SWB. The WHO-5 was translated into simplified Chinese in 2007 and is available on the WHO-5 official website.^27,51 Respondents were asked how well each of the five statements applies to them when considering the last two weeks. The five items of the scale cover positive emotions (in good spirits, feeling relaxed), vitality (feeling active, waking up refreshed and rested), and being interested in things.²⁷ Each item was scored on a six-point Likert scale, ranging from 0 (at no time) to 5 (all the time). Multiplying the original score by four is usually recommended because quality-of-life-related scales are often converted to a percentage scale.^27,28 The final score from 0 representing the worst imaginable well-being to 100 representing the best imaginable well-being. All items of the WHO-5-C are loaded on a potential factor with adequate reliability (Cronbach’s α = 0.810–0.850, McDonald’s ω = 0.820–0.860) and validity (comparative fit index [CFI] = 0.974, Tucker-Lewis index [TLI] = 0.947, and root mean square error of approximation [RMSEA] = 0.080).⁴³

Patient Health Questionnaire-4 (PHQ-4)

The PHQ was designed to facilitate recognition and diagnosis of the most common mental disorders in primary care patients.⁵² The PHQ-4 is a validated instrument for detecting anxiety and depression two weeks prior to assessment administration. The PHQ-4 consists of two ultra-short scales, one is the Generalized Anxiety Disorder-2 (GAD-2) for anxiety detection⁵³ and another is the PHQ-2 that reflects depression.⁵⁴ Each item of the PHQ-4 is scored on a four-point Likert scale, ranging from 0 (not at all) to 3 (nearly every day), with higher scores indicating more severe symptom levels.^55,56 The Chinese version of the PHQ-4 (PHQ-4-C) is publicly available and has shown good internal consistency and test–retest reliability (Cronbach’s α = 0.870–0.904, McDonald’s ω = 0.894–0.904, intraclass correlation coefficient [ICC] = 0.697).^57,58

Self-Rated Health Questionnaire (SRHQ)

A simple two-item questionnaire was applied to assess the self-perceived health of all participants, with one item estimating their physical health and one assessing their mental health. Each item was rated on a five-point Likert scale, from 1 (excellent) to 5 (extremely poor), with higher scores indicating worse overall health.^59,60 The SRHQ was demonstrated to have satisfactory internal consistency and test–retest reliability in our previous studies (Cronbach’s α = 0.706–0.857, ICC = 0.565–0.710).^59–61

Statistical Analysis

Data analysis was performed using R (version 4.1.3) and JASP (version 0.16.1). The R packages used in this analysis were “lavvan (0.6–11)”,⁶² “MBESS (4.9.2)”,⁶³ “irr (0.84.1)”,⁶⁴ “semTools (0.5–6)”,⁶⁵ and “pROC (1.18.2)”.⁶⁶ We matched data according to student ID, and missingness in the present study ranged from 0.29% to 1.46% (< 5%). We used mean imputation for continuous variables and median imputation for categorical variables.⁶⁷ Means, standard deviations (SDs), skewness, and kurtosis were used to assess multivariate normality. We selected maximum likelihood estimation (MLE) method to evaluate all confirmatory factor analysis (CFA) results given 1) data of the WHO-5-C is nonnormality (skew < 2, kurtosis < 7), and 2) the number of ordered categories is more than five.⁶⁸ All measurement properties of the WHO-5-C were assessed in accordance with the requirements of the COSMIN guideline.⁶⁹

Structural Validity

We assessed structural validity of the WHO-5-C by CFA to evaluate the extent to which the scores reflected underlying dimensions. Since the WHO-5 has been widely recognized as a single-factor scale, we evaluated structural validity of the scale based on a single-factor model. A satisfactory model fit was indicated for CFI and TLI ≥ 0.900, RMSEA ≤ 0.080, and standardized root mean square residual (SRMR) ≤ 0.080.^70,71

Measurement Invariance

To assess measurement invariance of the WHO-5-C with regard to demographic variables and time, we conducted a series of multi-group CFA (MGCFA) and longitudinal CFA (LCFA). This method involved progressively constraining parameters to be equal between subgroups (sociodemographic variables) and across time intervals, and then comparing changes in fit indices to determine whether the relationship between observed variables and underlying traits was equivalent.⁷² Herein, a series of nested models with increasing constraints were established, including the configural (same pattern of factors), metric (same pattern of factors and loadings), scalar (same pattern of factors, loadings, and item thresholds), and strict (same pattern of factors, loadings, item thresholds, and residual variances) models. Measurement invariance was defined as the fit statistic not significantly changing in an iterative procedure of progressively strict constraints. We considered the change in CFI (ΔCFI) to be an applicable metric for measurement invariance, with a change ≤ 0.010 indicating an appropriate measurement invariance.^73,74

Convergent Validity

To evaluate convergent validity of the WHO-5-C, we calculated Pearson correlation coefficients of the WHO-5-C with the SRHQ and PHQ-4-C, as these instruments are developed to assess an individual’s subjective feelings, considering mental and physical health often influence and accompany each other.⁷⁵ We additionally analyzed inter-item and item-total correlations. We hypothesized that the WHO-5-C would be moderately correlated with the PHQ-4-C and SRHQ in expected directions, given that these instruments measure interrelated constructs. The absolute magnitude of correlation coefficient was categorized as very strong correlation (r > 0.900), strong correlation (r = 0.700–0.900), moderate correlation (r = 0.400–0.700), and weak correlation (r < 0.400).⁷⁶

Reliability

We assessed internal consistency of the WHO-5-C using Cronbach’s α and McDonald’s ω coefficients, with coefficient ≥ 0.700 considered satisfactory.⁷⁷ To measure test–retest reliability, we used ICC between two separate times and coefficient below 0.400, between 0.400 and 0.590, between 0.600 and 0.740, and greater than 0.750 indicating poor, fair, good, and excellent reliability, respectively.⁷⁸ Moreover, standard error of measurement (SEM) was calculated as additional evidence to determine measurement accuracy when evaluating test–retest reliability.⁷⁹

Sensitivity and Specificity

To evaluate the WHO-5-C as a screening scale for SWB, area under the ROC curve (AUC), optimal cutoff point, sensitivity, and specificity were calculated using the ROC analysis. As the PHQ-2 was an ultra-brief and useful screening instrument in depression with excellent operating characteristics, the score ≥ 3 is used as a criterion to determine the optimal cutoff point of the WHO-5-C.⁵² The optimal cutoff point was obtained from the point closest to the top left-hand corner of ROC curve in baseline data and examined in follow-up data. The AUC value ranges from 0.500 to 1.000, with higher value indicating better prediction. A value greater than or equal to 0.800 was regarded as a good discrimination.^80,81

Results

Sociodemographic Variables

The sample consisted of 216 females (62.974%) with an average age of 19.650 (SD = 1.414) years, ranging from 17 to 23 years. Tables 1 and S1 summarized the participants’ sociodemographic variables and scores of the measured scales at baseline and follow-up.

Table 1 Sociodemographic Variables (N = 343)

Variables	N (%)	Mean (SD)
		Baseline	Follow-Up
Gender
Male	127 (37.026)	57.732 (17.168)	57.827 (18.425)
Female	216 (62.974)	56.741 (17.873)	58.167 (18.578)
Age
< 20 years	150 (43.732)	58.800 (17.264)	60.773 (17.468)
≥ 20 years	193 (56.268)	55.793 (17.785)	55.917 (19.030)
Major
Clinical medicine	154 (44.898)	53.039 (17.232)	54.883 (19.518)
Preventive medicine	189 (55.102)	60.423 (17.234)	60.614 (17.246)
Home location
Urban	156 (45.481)	58.179 (17.885)	59.256 (19.050)
Rural	101 (29.446)	56.356 (18.401)	57.188 (17.786)
Suburban	86 (25.073)	56.047 (16.135)	56.837 (18.367)
Being only child
Yes	128 (37.318)	57.094 (16.864)	57.531 (19.246)
No	215 (62.682)	57.116 (18.058)	58.344 (18.072)
Monthly household income
< 10,000 CNY	141 (41.108)	55.489 (18.663)	57.135 (19.197)
≥ 10,000 CNY	202 (58.892)	58.238 (16.767)	58.673 (18.010)
Part-time job
Yes	33 (9.621)	56.364 (17.360)	57.333 (18.806)
No	310 (90.379)	57.187 (17.648)	58.116 (18.491)
Physical exercise
Yes	257 (74.927)	58.646 (17.513)	59.564 (18.532)
No	86 (25.073)	52.512 (17.134)	53.488 (17.720)
Hobby
Yes	244 (71.137)	58.639 (17.849)	59.770 (18.492)
No	99 (28.863)	53.333 (16.443)	53.778 (17.891)
Frequency of visiting home
Frequently	51 (14.869)	63.294 (17.283)	62.824 (17.386)
Occasionally	292 (85.131)	56.027 (17.456)	57.205 (18.584)
Stress coping strategy
Emotion-focused	189 (55.102)	58.455 (16.103)	59.111 (17.952)
Solution-focused	121 (35.277)	57.983 (18.656)	59.240 (18.757)
Avoidance coping	33 (9.621)	45.182 (18.550)	47.515 (17.798)

Abbreviations: SD, standard deviation; Mean (SD), mean scores and SDs of the Chinese World Health Organization-Five Well-Being Index.

Structural Validity

Structural validity of the WHO-5-C was explored using CFA based on a one-factor model. As shown in Table 2, the fit indices of both baseline (CFI = 0.968, TLI = 0.937, SRMR = 0.028) and follow-up (CFI = 0.980, TLI = 0.961, SRMR = 0.020) analyses indicated that the WHO-5-C had a satisfactory fit with a single-factor structure.

Table 2 Model Fit Indices of the Single-Factor Model for the WHO-5-C (N = 343)

	χ^2 (df)	P	CFI	TLI	RMSEA (90% CI)	SRMR
Baseline	42.372 (5)	< 0.001	0.968	0.937	0.148 (0.109, 0.190)	0.028
Follow-up	35.051 (5)	< 0.001	0.980	0.961	0.132 (0.093, 0.175)	0.020
Threshold	N/A	> 0.050	≥ 0.900	≥ 0.900	≤ 0.080	≤ 0.080

Abbreviations: WHO-5-C, Chinese World Health Organization-Five Well-Being Index; χ², chi-square; df, degrees of freedom; CFI, comparative fit index; TLI, Tucker-Lewis index; RMSEA, root mean square error of approximation; CI, confidence interval; SRMR, standardized root mean square residual; N/A, not applicable.

Measurement Invariance

Cross-sectional measurement invariance of the WHO-5-C was analyzed across healthcare students’ sociodemographic variables. Tables 3 and S2 showed that the WHO-5-C was well-fixed in four nested models among all subgroups, with all CFI and TLI values greater than 0.900 and SRMR values below 0.080. Meanwhile, MGCFA tests demonstrated that all ΔCFI values (ΔCFI = −0.009–0.003) were within the recommended range, indicating that the WHO-5-C had acceptable measurement invariance across different sociodemographic variables.

Table 3 Cross-Sectional Measurement Invariances of the WHO-5-C (N = 343)

Hypothesis	Baseline							Follow-up
	χ^2 (df)	P	Δχ^2 (Δdf)	CFI	ΔCFI	TLI	SRMR	χ^2 (df)	P	Δχ^2 (Δdf)	CFI	ΔCFI	TLI	SRMR
Gender (male vs female)
Configural	52.934 (10)	< 0.001		0.964		0.929	0.027	41.874 (10)	< 0.001		0.979		0.959	0.018
Metric	55.992 (14)	< 0.001	3.058 (4)	0.965	0.001	0.950	0.037	51.370 (14)	< 0.001	9.496 (4)	0.976	−0.003	0.965	0.044
Scalar	63.280 (18)	< 0.001	7.288 (4)	0.962	−0.003	0.958	0.042	55.458 (18)	< 0.001	4.088 (4)	0.976	0.000	0.973	0.046
Strict	79.479 (23)	< 0.001	16.200 (5)*	0.953	−0.009	0.959	0.041	65.966 (23)	< 0.001	10.508 (5)	0.972	−0.004	0.976	0.046
Age (< 20 years vs ≥ 20 years)
Configural	49.244 (10)	< 0.001		0.967		0.934	0.025	41.665 (10)	< 0.001		0.979		0.958	0.018
Metric	57.824 (14)	< 0.001	8.580 (4)	0.963	−0.004	0.947	0.051	49.650 (14)	< 0.001	7.985 (4)	0.976	−0.003	0.966	0.043
Scalar	70.454 (18)	< 0.001	12.630 (4)*	0.956	−0.007	0.951	0.058	54.244 (18)	< 0.001	4.594 (4)	0.976	0.000	0.973	0.046
Strict	74.182 (23)	< 0.001	3.728 (5)	0.957	0.001	0.963	0.054	59.088 (23)	< 0.001	4.844 (5)	0.976	0.000	0.979	0.046
Major (clinical medicine vs preventive medicine)
Configural	46.837 (10)	< 0.001		0.968		0.936	0.026	42.164 (10)	< 0.001		0.979		0.958	0.019
Metric	57.528 (14)	< 0.001	10.691 (4)*	0.962	−0.006	0.946	0.060	58.085 (14)	< 0.001	15.921 (4)	0.971	−0.008	0.958	0.056
Scalar	63.445 (18)	< 0.001	5.917 (4)	0.961	−0.001	0.956	0.064	70.981 (18)	< 0.001	12.895 (4)	0.965	−0.006	0.961	0.063
Strict	69.586 (23)	< 0.001	6.140 (5)	0.960	−0.001	0.965	0.062	78.824 (23)	< 0.001	7.844 (5)	0.963	−0.002	0.968	0.059
Home location (urban vs rural vs suburban)
Configural	52.121 (15)	< 0.001		0.969		0.938	0.028	47.354 (15)	< 0.001		0.979		0.958	0.020
Metric	56.444 (23)	< 0.001	4.323 (8)	0.972	0.003	0.963	0.042	50.249 (23)	0.001	2.895 (8)	0.982	0.003	0.977	0.031
Scalar	71.353 (31)	< 0.001	14.909 (8)	0.966	−0.006	0.967	0.051	57.660 (31)	0.003	7.411 (8)	0.983	0.001	0.983	0.037
Strict	85.508 (41)	< 0.001	14.155 (10)	0.963	−0.003	0.973	0.056	69.440 (41)	0.004	11.780 (10)	0.981	−0.002	0.986	0.036
Threshold	N/A	> 0.050	N/A	≥ 0.900	≤ 0.010	≥ 0.900	≤ 0.080	N/A	> 0.050	N/A	≥ 0.900	≤ 0.010	≥ 0.900	≤ 0.080
Being only child (yes vs no)
Configural	55.642 (10)	< 0.001		0.962		0.923	0.027	45.525 (10)	< 0.001		0.977		0.954	0.019
Metric	57.227 (14)	< 0.001	1.585 (4)	0.964	0.002	0.948	0.031	55.883 (14)	< 0.001	10.358 (4)	0.973	−0.004	0.961	0.051
Scalar	58.106 (18)	< 0.001	0.879 (4)	0.966	0.002	0.962	0.032	58.072 (18)	< 0.001	2.189 (4)	0.974	0.001	0.971	0.052
Strict	59.867 (23)	< 0.001	1.760 (5)	0.969	0.003	0.973	0.032	63.610 (23)	< 0.001	5.539 (5)	0.974	0.000	0.977	0.048
Monthly household income (<10,000 CNY vs ≥10,000 CNY)
Configural	52.339 (10)	< 0.001		0.964		0.928	0.028	42.364 (10)	< 0.001		0.979		0.958	0.019
Metric	54.249 (14)	< 0.001	1.911 (4)	0.966	0.002	0.951	0.035	46.149 (14)	< 0.001	3.785 (4)	0.979	0.000	0.970	0.036
Scalar	59.468 (18)	< 0.001	5.219 (4)	0.965	−0.001	0.961	0.038	49.460 (18)	< 0.001	3.311 (4)	0.979	0.000	0.977	0.038
Strict	60.943 (23)	< 0.001	1.475 (5)	0.968	0.003	0.972	0.037	52.133 (23)	< 0.001	2.673 (5)	0.981	0.002	0.983	0.038
Part-time job (yes vs no)
Configural	47.502 (10)	< 0.001		0.968		0.937	0.026	37.583 (10)	< 0.001		0.982		0.964	0.018
Metric	53.590 (14)	< 0.001	6.088 (4)	0.966	−0.002	0.952	0.038	39.405 (14)	< 0.001	1.822 (4)	0.983	0.001	0.976	0.022
Scalar	54.664 (18)	< 0.001	1.075 (4)	0.969	0.003	0.966	0.038	39.965 (18)	0.002	0.559 (4)	0.986	0.003	0.984	0.023
Strict	56.380 (23)	< 0.001	1.716 (5)	0.972	0.003	0.975	0.037	43.980 (23)	0.005	4.015 (5)	0.986	0.000	0.988	0.023
Physical exercise (yes vs no)
Configural	48.218 (10)	< 0.001		0.967		0.934	0.027	45.160 (10)	< 0.001		0.977		0.953	0.018
Metric	49.586 (14)	< 0.001	1.368 (4)	0.969	0.002	0.956	0.031	46.897 (14)	< 0.001	1.737 (4)	0.978	0.001	0.969	0.023
Scalar	55.063 (18)	< 0.001	5.477 (4)	0.968	−0.001	0.965	0.034	50.420 (18)	< 0.001	3.523 (4)	0.979	0.001	0.976	0.025
Strict	58.785 (23)	< 0.001	3.722 (5)	0.969	0.001	0.973	0.036	55.071 (23)	< 0.001	4.651 (5)	0.979	0.000	0.982	0.028
Threshold	N/A	> 0.050	N/A	≥ 0.900	≤ 0.010	≥ 0.900	≤ 0.080	N/A	> 0.050	N/A	≥ 0.900	≤ 0.010	≥ 0.900	≤ 0.080
Hobby (yes vs no)
Configural	45.443 (10)	< 0.001		0.970		0.939	0.025	41.634 (10)	< 0.001		0.979		0.958	0.018
Metric	54.322 (14)	< 0.001	8.879 (4)	0.966	−0.004	0.951	0.047	45.428 (14)	< 0.001	3.794 (4)	0.979	0.000	0.970	0.030
Scalar	60.352 (18)	< 0.001	6.030 (4)	0.964	−0.002	0.960	0.051	50.697 (18)	< 0.001	5.269 (4)	0.978	−0.001	0.976	0.033
Strict	64.862 (23)	< 0.001	4.511 (5)	0.964	0.000	0.969	0.049	58.747 (23)	< 0.001	8.050 (5)	0.976	−0.002	0.979	0.033
Frequency of visiting home (frequently vs occasionally)
Configural	59.381 (10)	< 0.001		0.958		0.916	0.030	44.238 (10)	< 0.001		0.978		0.955	0.020
Metric	60.465 (14)	< 0.001	1.084 (4)	0.961	0.003	0.944	0.033	55.843 (14)	< 0.001	11.604 (4)	0.973	−0.005	0.961	0.034
Scalar	67.474 (18)	< 0.001	7.010 (4)	0.958	−0.003	0.953	0.037	63.186 (18)	< 0.001	7.343 (4)	0.970	−0.003	0.967	0.036
Strict	74.911 (23)	< 0.001	7.437 (5)	0.956	−0.002	0.962	0.037	64.914 (23)	< 0.001	1.728 (5)	0.972	0.002	0.976	0.038
Stress coping strategy (emotion-focused vs solution-focused vs avoidance coping)
Configural	64.714 (15)	< 0.001		0.957		0.914	0.030	56.192 (15)	< 0.001		0.973		0.945	0.021
Metric	72.264 (23)	< 0.001	7.550 (8)	0.958	0.001	0.945	0.047	61.663 (23)	< 0.001	5.471 (8)	0.974	0.001	0.967	0.040
Scalar	84.429 (31)	< 0.001	12.165 (8)	0.954	−0.004	0.955	0.052	72.893 (31)	< 0.001	11.230 (8)	0.972	−0.002	0.973	0.044
Strict	97.831 (41)	< 0.001	13.402 (10)	0.951	−0.003	0.964	0.060	86.189 (41)	< 0.001	13.296 (10)	0.970	−0.002	0.978	0.044
Threshold	N/A	> 0.050	N/A	≥ 0.900	≤ 0.010	≥ 0.900	≤ 0.080	N/A	> 0.050	N/A	≥ 0.900	≤ 0.010	≥ 0.900	≤ 0.080

Note: *P < 0.05.

Abbreviations: WHO-5-C, Chinese World Health Organization-Five Well-Being Index; χ², chi-square; df, degrees of freedom; CFI, comparative fit index; TLI, Tucker-Lewis index; SRMR, standardized root mean square residual; Δ, change in χ², df, and CFI; N/A, not applicable.

In LCFA tests of the WHO-5-C, all fit indices were in line with the proposed thresholds (CFI = 0.974–0.980, TLI = 0.968–0.976, REMSA = 0.070–0.081, SRMR = 0.022–0.027), and there were no substantial CFI changes in each nested model (ΔCFI = −0.006–0.000), supporting that the WHO-5-C had good longitudinal measurement invariance (Table 4).

Table 4 Longitudinal Measurement Invariances of the WHO-5-C (N = 343)

Hypothesis	χ^2 (df)	P	Scaled Chi-Square Difference Test Statistics		CFI	ΔCFI	TLI	ΔTLI	RMSEA (90% CI)	ΔRMSEA	SRMR	ΔSRMR
			Δχ^2 (Δdf)	P
Configural	94.419 (29)	< 0.001			0.980		0.968		0.081 (0.063, 0.100)		0.022
Metric	95.342 (33)	< 0.001	0.923 (4)	0.921	0.980	0.000	0.973	0.005	0.074 (0.057, 0.092)	−0.007	0.024	0.002
Scalar	99.464 (37)	< 0.001	4.122 (4)	0.390	0.980	0.000	0.976	0.003	0.070 (0.054, 0.087)	−0.004	0.025	0.001
Strict	125.095 (42)	< 0.001	25.631 (5)	< 0.001	0.974	−0.006	0.972	−0.004	0.076 (0.061, 0.091)	0.006	0.027	0.002
Threshold	N/A	> 0.050	N/A	> 0.050	≥ 0.900	≤ 0.010	≥ 0.900	≤ 0.010	≤ 0.080	≤ 0.015	≤ 0.080	≤ 0.030

Abbreviations: WHO-5-C, Chinese World Health Organization-Five Well-Being Index; χ², chi-square; df, degrees of freedom; CFI, comparative fit index; TLI, Tucker-Lewis index; RMSEA, root mean square error of approximation; CI, confidence interval; SRMR, standardized root mean square residual; Δ, change in χ², df, CFI, TLI, RMSEA, and SRMR; N/A, not applicable.

Convergent Validity

As shown in Figure 1, inter-item coefficients of the WHO-5-C ranged from 0.535 to 0.844 and item-total coefficients ranged from 0.806 to 0.935, indicating moderate to super strong correlations. Moderate correlations were observed between the WHO-5-C and SRHQ (Time 1: r = −0.561, Time 2: r = −0.573), as well as the PHQ-4-C (Time 1: r = −0.691, Time 2: r = −0.675), demonstrating adequate convergent validity.

Figure 1 Inter-item and item-total correlations between the Chinese WHO-5, PHQ-4, and SRHQ (N=343).

Abbreviations: WHO-5, World Health Organization-Five Well-Being Index; WHO01-05, item 01–05 of the WHO-5; PHQ-2, Patient Health Questionnaire-2; GAD-2, Generalized Anxiety Disorder-2; PHQ-4, Patient Health Questionnaire-4; SRHQ, Self-Rated Health Questionnaire; T1, Time 1; T2, Time 2.

Reliability

Cronbach’s α and McDonald’s ω coefficients of the WHO-5-C at baseline were 0.907 (range of α-if-item-deleted = 0.865–0.905) and 0.908 (range of α-if-item-deleted = 0.865–0.905), respectively; and at follow-up were 0.934 (range of α-if-item-deleted = 0.906–0.930) and 0.935 (range of α-if-item-deleted = 0.904–0.931), respectively. The WHO-5-C demonstrated excellent test–retest reliability, with an ICC of 0.803 (range of ICC-if-item-deleted = 0.785–0.799), and stability of the scale was also demonstrated by SEM indices. No significant increase in indices was observed when any item was deleted. Similarly, the SRHQ and PHQ-4-C showed good internal consistencies and test–retest reliabilities (Table 5).

Table 5 Internal Consistency and Test–Retest Reliability of the WHO-5-C, SRHQ, and PHQ-4-C (N = 343)

Scales	Cronbach’s α		McDonald’s ω		ICC (95% CI)	SEM
	Baseline	Follow-Up	Baseline	Follow-Up		Baseline	Follow-Up
WHO-5-C	0.907 (0.891, 0.922)	0.934 (0.923, 0.945)	0.908 (0.893, 0.924)	0.935 (0.924, 0.946)	0.803 (0.762, 0.838)	7.810	8.209
WHO-5-C01	0.883 (0.863, 0.903)	0.915 (0.900, 0.929)	0.885 (0.865, 0.905)	0.915 (0.900, 0.930)	0.796 (0.754, 0.832)	6.578	6.875
WHO-5-C02	0.877 (0.857, 0.898)	0.914 (0.899, 0.929)	0.881 (0.860, 0.901)	0.915 (0.901, 0.930)	0.799 (0.757, 0.834)	6.394	6.682
WHO-5-C03	0.865 (0.843, 0.888)	0.906 (0.890, 0.921)	0.865 (0.841, 0.888)	0.904 (0.887, 0.921)	0.785 (0.741, 0.822)	6.484	6.820
WHO-5-C04	0.905 (0.889, 0.921)	0.930 (0.918, 0.942)	0.905 (0.889, 0.922)	0.931 (0.918, 0.943)	0.791 (0.748, 0.828)	6.521	6.772
WHO-5-C05	0.898 (0.881, 0.916)	0.930 (0.918, 0.942)	0.900 (0.883, 0.918)	0.931 (0.919, 0.943)	0.798 (0.756, 0.833)	6.347	6.712
SRHQ	0.727	0.805	N/A	N/A	0.749 (0.697, 0.793)	0.637	0.675
PHQ-4-C	0.818 (0.786, 0.849)	0.846 (0.820, 0.872)	0.820 (0.789, 0.851)	0.849 (0.823, 0.875)	0.681 (0.620, 0.734)	1.234	1.263

Note: The McDonald’s ω and the 95% CI of Cronbach’s α cannot be calculated due to the SRHQ containing only 2 items.

Abbreviations: WHO-5-C, Chinese World Health Organization-Five Well-Being Index; WHO-5-C_01-05, item 01–05 of the WHO-5-C was deleted; SRHQ, Self-Rated Health Questionnaire; PHQ-4-C, Chinese Patient Health Questionnaire-4; ICC, intraclass correlation coefficient; CI, confidence interval; SEM, standard error of measurement, calculated as “SD × sqrt (1-ICC)”.

Sensitivity and Specificity

Based on baseline data, ROC curve analysis indicated that the WHO-5-C had an AUC value of 0.882, and the optimal cutoff point of ≥ 50 had sensitivity of 0.782 and specificity of 0.857 for screening satisfactory SWB in healthcare students (Figure 2). Sensitivity and specificity of the WHO-5-C were 0.803 and 0.762, respectively, in follow-up data when the cutoff point of 50 was applied as the threshold for predicting SWB (Table 6).

Table 6 Sensitivity and Specificity of the WHO-5-C for Identifying Well-Being in Healthcare Students (N = 343)

WHO-5-C	PHQ-2-C		Total	Sensitivity	Specificity
	< 3	≥ 3
≥ 50	211	13	224	0.803	0.762
< 50	66	53	119
Total	277	66	343

Abbreviations: WHO-5-C, Chinese World Health Organization-Five Well-Being Index; PHQ-2-C, Chinese Patient Health Questionnaire-2.

Figure 2 ROC curve of the Chinese WHO-5 for well-being (N=343).

Abbreviations: WHO-5, World Health Organization-Five Well-Being Index; ROC, receiver operating characteristic; AUC, area under the curve.

Discussion

The adaptation of existing well-being instruments in Chinese populations mostly focuses on construct validity and reliability, but rarely responds to measurement invariance and clinical diagnostic capability. As an example, the WEMWBS is an instrument of well-being considering positive aspects of mental health, and despite the Chinese version representing stable factor structure and reliability across populations, its measurement invariance and truncation value are not available.^23,82,83 Herein, the current study comprehensively evaluated measurement properties of the WHO-5-C in healthcare students, intending to introduce a well-being measuring tool with all-round persuasiveness. To our knowledge, this is the first study to explore measurement invariance of the WHO-5-C and determine a cutoff point for SWB identification in healthcare students. We provide strong evidence of a one-factor model with adequate validity and reliability, as well as measurement invariance, explaining its stability across different sociodemographic variables and time intervals. ROC analysis supports the WHO-5-C as a sensitive and specific instrument in assessing positive mental and physical well-being, with a recommended cutoff point of ≥ 50 indicating adequate SWB for Chinese healthcare students. Overall, our findings highlight effectiveness of the WHO-5-C and its validity in assessing SWB among healthcare students.

Structural Validity

CFA results corroborated general consensus of previous studies that the WHO-5 had a stable single-factor structure, which has also been found in most language versions: Brazilian,³⁰ Japanese,³⁴ Polish,³⁶ Sinhala,³⁷ Spanish,³⁸ Swedish,⁴⁰ and Turkish.⁴¹ The WHO-5-C had adequate structural validity, and these findings were also found in another study in multiple samples.⁴³ In summary, our study adds to the growing body of evidence supporting structural validity of the WHO-5.

Measurement Invariance

Our study has validated cross-cultural validity of the WHO-5-C by demonstrating adequate measurement invariance across sociodemographic variables and time intervals. Adequate measurement invariance ensured that the scale had consistent measurement properties in a heterogeneous group and that targeted measurement was stably assessed by the scale.⁸⁴ While partial fitting indices of MGCFA tests were contradictory to expectations, likely due to a small degree of freedom,^85,86 all CFI changes among the four progressive nested models were consistently within adequate range, which is recognized as the most pivotal indicator to assess measurement invariance of a scale.⁷⁴ Only limited evidence for the WHO-5 measurement invariance was found in extant literature. The Sinhala version supported measurement invariance across gender in all four nested models.³⁷ Our findings extend previous ones in supporting satisfactory measurement invariance of the WHO-5-C in healthcare students both by different sociodemographic variables and over time.

Convergent Validity

Our findings demonstrated that the WHO-5-C demonstrated moderate negative correlations with both the SRHQ and PHQ-4-C, showing the WHO-5-C had sufficient convergent validity. Associations of comparable strengths with its related constructs of mental and physical health have been reported in community and patient samples,^33,87,88 and special populations like healthcare workers in multi-national studies.⁸⁹ Our evidence for construct validity of the WHO-5 in Chinese population adds support to its cross-cultural applicability as a valid instrument for measuring SWB in diverse domains and groups.

Reliability

Similar and consistent with previous studies of other language versions of the WHO-5,^{29,30,33,37–39,41,90} Cronbach’s α, McDonald’s ω and ICC of the WHO-5-C across two separate time points were greater than 0.800 in our study, illustrating its high internal consistency and test–retest reliability. Despite the brevity of the WHO-5-C, our data further support coherence across items and stability over time in Chinese.

Sensitivity and Specificity

Our study showed that the WHO-5-C had a reasonable ability to distinguish those who had psychological positive components when the cutoff point was ≥ 50 (AUC = 0.882), suggesting that the scale is a suitable screening instrument for measuring adequate SWB in Chinese healthcare students. Consistent with other studies in Asia, a standard cutoff point of ≥ 13 had an excellent sensitivity/specificity trade-off in the Arabic and Japanese versions, which meant that respondents with positive mindset can be detected by this cutoff criterion.^29,34 Along the same vein, a reduction of 50% indicates reduced wellness in the Brazilian version and recommends that further clinical diagnosis for depression should be undertaken.³⁰ Other cutoff points for different purposes and samples have been identified in other language versions of the WHO-5. The German version of the WHO-5 was applied to screen depression in an elderly population (AUC = 0.886), and a standard cutoff point of ≥ 16 was sufficiently sensitive and specific in predicting a status of optimal well-being.³² The fact that the definition and feeling of wellness are notably discrepant in different stages of life due to the gains and losses in health assets, social networks, economic resources and family structures.^91,92 A systematic review of the WHO-5, thoroughly, drew a conclusion that the scale had been applied successfully as a generic scale for well-being across numerous fields, and a point below 50 was defined as an obvious reduction in well-being.²⁸ The WHO-5, briefly, has appropriate validity both as a screening instrument for subjective psychosomatic well-being and as an outcome measurement in clinical trials.

Strengths and Limitations

The present study contributes to literature on utilization of the WHO-5 in Chinese healthcare students by providing empirical findings on its measurement properties and diagnostic performance. The study supports the application of the WHO-5-C in young adults with adequate validity and reliability, laying a solid foundation for its utilization in China. To our knowledge, our study is the first to verify cutoff point and to comprehensively examine measurement invariance of the WHO-5-C among healthcare students in terms of sociological characteristics and measurement times. As such, we provide a precise threshold for evaluating SWB state for clinical and research purposes in young adults, a vulnerable group for onset of psychosomatic health problems and developmental challenges.

This study is admittedly limited in that participants involved were all young healthcare students, rendering it difficult to generalize the findings to other age groups or disciplines. Given the promising findings this study offers, it would be highly valuable to further investigate psychometric properties of the WHO-5-C in various samples or a nationally representative and to validate the optimal cutoff point in different purposes and external samples. Despite widespread utilization of the PHQ-4-C, an instrument of positive SWB should be considered as a complementary measure to capture the comprehensive and multidimensional construct of wellness.¹ Moreover, despite the WHO-5-C is freely available, it is essential to examine its content validity with a view to providing credible evidence for the sustainable implementation of the scale in China.

Conclusion

In conclusion, this study supports the WHO-5-C as a reliable and valid instrument for capturing SWB in healthcare students, with satisfactory measurement invariance in different sociodemographic variables and over time, and a cutoff point of ≥ 50 for identifying significantly adequate SWB state. Together with the family of studies on the WHO-5 worldwide, our evidence enables research and clinical communities to apply the scale for screening well-being in public health and primary care settings.

Data Sharing Statement

Not available.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

Acknowledgments

The authors thank the study participants and the research assistants for their time. The authors are indebted to three anonymous reviewers and a handling editor for their insightful views and constructive comments.

Additional information

Funding

This study was supported by the Medical Research Fund of Zhejiang Province, Grant No. 2023RC073 and the Research Initiation Fund of Hangzhou Normal University, Grant No. RWSK20201003.