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Journal of Affective Disorders Reports
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Research paper
Psychometric properties of the CES-D and four of its short-forms among South African primary care patients with a chronic condition
Lexy Staniland a , Katherine Sorsdahl b, Claire van der Westhuizen b, Lesley-Ann Erasmus-Claassen c , Petal Petersen Williams c,d,e, Bronwyn Myers a,c,f,*
a Curtin enAble Institute, Faculty of Health Sciences, Curtin University, Kent Street, Bentley, Western Australia, Australia
b Alan J. Flisher Centre for Public Mental Health, Department of Psychiatry & Mental Health, University of Cape Town, 46 Sawkins Road, Cape Town 7700, South Africa c Mental Health, Alcohol, Substance Use and Tobacco Research Unit, South African Medical Research Council, Francie Van Zijl Drive, Parow 7505, South Africa d Institute for Life Course Health Research, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Francie Van Zijl Drive, Parow 7505, South Africa
e Public Health Research Department, Faculty of Medicine & Health Sciences, University of East Anglia, United Kingdom

ABSTRACT

f National Drug Research Institute, Faculty of Health Sciences, Curtin University, Kent Street, Bentley, Western Australia, Australia

Keywords:
Depression screening
Chronic disease
Low-and middle-income country
Primary care

ARTICLE INFO
Background: To enhance practicality of routine depression screening in primary care, shorter versions of the 20- item CES-D have been created. However, providers lack evidence to guide their choice of short-form as their psychometric properties have not been systematically compared to the full scale. We compared the reliability, criterion validity, and dimensionality of four CES-D short-forms with the full CES-D in a South African primary care population.
Methods: Using the CES-D, we screened 4010 adults receiving HIV and/or diabetes treatment in primary care, of which 882 were rescreened prior to enrolment in a psychological intervention trial. We assessed the internal consistency and temporal stability, of the CES-D-12, -10, -9, and -8, and evaluated each short-form’s criterion validity. Exploratory and confirmatory factor analysis tested multiple factor solutions for the full CES-D and each short-form.
Results: All short-forms demonstrated high internal consistency (α > .85) and moderate temporal stability (intraclass correlations: .73-.75) comparable to the full CES-D. While all short-forms had excellent criterion validity (area under the receiver operator curve [AUROC] > .90), the CES-D-12 and CES-D-10 had superior criterion validity (AUROC = .99) and classification accuracy (93.1% and 93.7% respectively). The CES-D-12 emerged as the short-form with the closest conceptual alignment to the full scale, both optimally fitted by a three-factor model.
Conclusions: Our findings suggest that the CES-D-10 and -12 are the best alternatives to the full CES-D. While the CES-D-10 offers efficiency advantages for case detection, the CES-D-12 may provide more insight into depression symptom profiles.

* Corresponding author at: Curtin enAble Institute, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, Western Australia 6845, Australia.
E-mail address: bronwyn.myers-franchi@curtin.edu.au (B. Myers).
https://doi.org/10.1016/j.jadr.2026.101046
Received 16 September 2025; Received in revised form 8 February 2026; Accepted 17 February 2026
Available online 19 February 2026
2666-9153/© 2026 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

1.		Introduction
Depression is a leading cause of the global burden of disease, accounting for 6.2% (5.0%-7.8%) of age-standardised years lived with disability in 2021 (Ferrari et al., 2024). The burden of depression is pronounced in low- and middle-income countries (LMICs), partly due to the social determinants of mental health (such as poverty, unemployment, and violence) being highly prevalent in these contexts coupled with under-resourced mental health treatment systems that impede access to care (Freeman, 2022; Sorsdahl et al., 2023). In South Africa, nationally representative surveys estimate that 9.8% of the general population will meet diagnostic criteria for a lifetime major depressive disorder (Herman et al., 2009) and 25.7% will screen positive for probable depression at any point in time (Craig et al., 2022). However, less than a quarter of South Africans with a diagnosis of depression access any form of mental health care (Docrat et al., 2019).
Beyond its impact on mental wellbeing, untreated depression is also strongly associated with poorer physical health (Machado et al., 2018). Depression frequently co-occurs with chronic non-communicable conditions such as diabetes mellitus (Al-Jabi, 2024; Alzoubi et al., 2018) and chronic infectious conditions like HIV (Fabrazzo et al., 2023). Further, untreated depression may compromise chronic disease treatment outcomes by reducing care engagement and self-management (Myers et al., 2018). Sub-optimal care engagement and self-management increases risk of treatment failure which accelerates disease progression (Al-Jabi, 2024; Derese et al., 2024; Mosha et al., 2024; Osler et al., 2018) and contributes to higher healthcare utilisation and costs (Mutyambizi-Mafunda et al., 2023). This is a major concern for LMICs like South Africa where the severely under-resourced public health system is struggling to respond to the high prevalence of HIV and a growing burden of non-communicable diseases like diabetes (Hazell et al., 2025).
Despite the potential impacts of untreated depression on HIV and diabetes treatment outcomes, persons receiving HIV and diabetes care from publicly funded primary healthcare clinics in South Africa are rarely screened for depressive symptoms (Bhana et al., 2015; Sorsdahl et al., 2021). Consequently, people who need or may benefit from psychological interventions often remain undetected and untreated (Bhana et al., 2015). There are several well-established and psychometrically sound measures that primary healthcare workers could use to screen patients for depression (Bhana et al., 2015; Stockton et al., 2024). One such scale is the 20-item Center for Epidemiological Studies – Depression (CES-D) scale (Radloff, 1977), with studies demonstrating robust psychometric properties across diverse populations and languages (Blodgett et al., 2021; Cosco et al., 2020; Park &Yu, 2021; Vilagut et al., 2016). For example, a meta-analysis of 22 studies with general and primary care populations reported that the CES-D had good diagnostic accuracy compared to gold standard diagnostic tools (such as the Composite International Diagnostic Interview (CIDI), and the Mini-International Neuropsychiatric Interview (MINI)), with a pooled sensitivity estimate of 0.87 (95% CI 0.82–0.91), and specificity of 0.70 (95% CI 0.65–0.75) when using a cut-off score of ≥16 (Vilagut et al., 2016). South African studies have also demonstrated acceptable diagnostic accuracy of the CES-D compared to gold standard diagnostic interviews (Kagee et al., 2020; Myer et al., 2008).
However, the length of the 20-item CES-D limits its practicality for routine depression screening in under-resourced primary healthcare settings, such as those in South Africa (Myers et al., 2019; Sorsdahl et al., 2021). In these settings, primary care staff are only likely to introduce routine screening for depression if measures are brief and generate clinically useful information (Brooke-Sumner et al., 2019). In response, the original CES-D has been shortened into 12-item (Assari & Moazen-Zadeh, 2016), 10-item (Andresen et al., 1994), 9-item (Santor & Coyne, 1997), and 8-item (Turvey et al., 1999) versions. While prior studies have shown that each of these short-forms have adequate psychometric properties (Adams et al., 2020; Adams et al., 2019; Briggs et al., 2018; James et al., 2020; Wang et al., 2017), only the CES-D-10 (Baron et al., 2017; Padmanabhanunni & Pretorius, 2024) and the CES-D-8 (Adams et al., 2020) have been evaluated in South African populations. Further, we are only aware of one study that has simultaneously compared the psychometric properties and screening performance of these short-forms against the full CES-D (Yang et al., 2018). As this prior study used data collected from Chinese adolescents (Yang et al., 2018), findings may not be generalizable to adult primary care populations in South Africa due to observed differences in the factor structure of the CES-D among Asian and other populations, and adolescent and adult populations (Blodgett et al., 2021; Vilagut et al., 2016). Consequently, the CES-D short-form that offers the most accurate alternative to the full scale for routine depression screening in adult primary care in LMICs like South Africa remains unknown.
In response to this gap, the present study compared four CES-D short forms by examining their psychometric properties, dimensionality, and criterion validity in South African primary care patients receiving HIV and diabetes treatment. This analysis aimed to identify which CES-D short-form can be recommended as a practical alternative to the full CES-D in these primary care settings. More specifically, we aimed to (i) identify and confirm the ideal factor structure, (ii) assess the reliability, and (iii) determine the optimal cut-off score of each short-form relative to the full CES-D.
2.		Methods
2.1.		Study design
This study analysed participant screening data from a three-armed cluster randomised control trial. This trial was designed to compare the effectiveness of different approaches to integrating community health worker-delivered counselling for depression and alcohol use disorder into chronic disease services offered through the Western Cape Provincial Department of Health’s primary care platform. Participants were recruited from 24 primary care clinics distributed across four of the Western Cape’s six health districts, with 15 of these clinics serving geographically distinct urban communities and nine serving rural communities. Full trial methods and outcomes are reported elsewhere (Myers et al., 2022; Myers et al., 2018).
2.2.		Measures
2.2.1.		. Demographics
Participants reported their age, sex (male or female), and whether they were living with HIV and/or diabetes. Measures were completed in the participants’ preferred language (isiXhosa, Afrikaans, or English, the main languages spoken in the region).
2.2.2.		Depression
Depression was measured using the 20-item CES-D (CES-D; Radloff, 1977). This screener assesses the frequency of depressive symptoms in the past week, with items examining negative affect (e.g., “I felt sad”), anhedonia (e.g., “I enjoyed life”), and somatic complaints (e.g., “I felt fidgety”). Participants rated each item on a four-point Likert scale, with responses ranging from 0 (rarely or none of the time) to 3 (most or all of the time). Item responses were summed to yield a composite score ranging from 0 to 60, with higher scores indicating a greater probability of depression and scores ≥ 16 indicating clinically significant symptoms (Radloff, 1977). This study also evaluated shorter versions of the 20-item CES-D, including the CES-D-12 (Assari & Moazen-Zadeh, 2016), CES-D-10 (Andresen et al., 1994), CES-D-9 (Santor & Coyne, 1997), and the CES-D-8 (Turvey et al., 1999). Each short-form comprises a subset of items from the original CES-D (see Table 1 for the items contained in each scale).
2.3.		Participants and procedure
Ethical approval for this study was granted by the South African Medical Research Council (EC 004–2/2015), the University of Cape Town (089/2015), and Oxford University (OxTREC 2–17). The Western Cape Department of Health also approved all procedures (WC2016_RP6_9). The trial was registered with the Pan African Clinical Trials Registry (PACTR201610001825403).
Between 1 May 2017 and 31 March 2019, providers at participating clinics asked patients presenting for HIV or diabetes care about their alcohol use and mood. Patients who reported recent alcohol use and low mood were referred to a study assessor who explained the purpose of the trial. Patients who were interested in participating were asked to consent to eligibility screening. Eligibility screening included administration of the CES-D in English, isiXhosa or Afrikaans (the official languages of the province). The study used previously cross-culturally adapted and validated Afrikaans and isiXhosa language versions of the CES-D (Baron et al., 2017; Myer et al., 2008; Pretorius, 1991). Patients who were (i) ≥18 years old, (ii) on medication for HIV or diabetes, (iii) not receiving
Table 1
Items included in each CES-D short-form.
CES-D Short-Form
CES-D 20 Items	CES-D 12	CES-D 10	CES-
D 9	CES-
D 8	
1)		I was bothered by things that usually don’t bother me.
2)		I did not feel like eating; my appetite was		X	X		
poor.					
3) I felt that I could not shake off the blues, even with the help from family or friends.			X		
4) I felt that I was just as good as other	X				
people.					
5) I had trouble keeping my mind on what I	X	X	X		
was doing.					
6) I felt depressed.	X	X	X	X	
7) I felt that everything I did was an effort.	X	X	X	X	
8) I felt hopeful about the future.	X	X			
9) I thought my life had been a failure.					
10) I felt fearful.		X			
11) My sleep was restless.	X	X	X	X	
12) I was happy.	X	X	X	X	
13) I talked less than usual.					
14) I felt lonely.		X		X	
15) People were unfriendly.	X				
16) I enjoyed life.	X		X	X	
17) I had crying spells.	X				
18) I felt sad.			X	X	
19) I felt that people dislike me.	X				
20) I could not get “going”.	X	X		X	
Composite score range (Min - Max)	0 - 36	0 - 30	0 - 27	0 - 24	

mental health treatment, and who (iv) screened positive for unhealthy alcohol use with a score ≥8 on the Alcohol Use Disorders Identification Test (Morojele et al., 2017) or possible depression (CES-D score ≥16) were eligible for trial participation.
Study assessors invited eligible patients to a study enrolment appointment. If these appointments occurred more than one week after initial screening (the first timepoint of CES-D administration), the CES-D was re-administered. This second timepoint enabled us to assess temporal stability. We selected a test-retest interval of at least one week as the CES-D assesses past-week depressive symptoms and we wanted to verify that patients remained eligible for trial enrolment. In this trial, the test-retest interval ranged between one and two weeks. Test-retest intervals within this range are generally considered suitable for evaluating the temporal stability of psychiatric symptom-based measures (Streiner et al., 2024). Prior studies of the CES-D have also used test-retest intervals within a one-to-two-week range (Andresen et al., 1994; Miller et al., 2008; Radloff, 1977).
2.4.		Data analyses
Analyses were conducted in SPSS (Version 27; 2020) and JASP (Version 0.15.4; 2022). First, exploratory factor analysis (EFA) was performed to examine the latent dimensionality of each CES-D form, followed by confirmatory factor analysis (CFA) to confirm the identified factor structures. To facilitate this, we first checked the factorability of the data using Bartlett’s (1954) test of sphericity (BTS) and the Kaiser-Meyer-Olkin (KMO; Kaiser, 1974) measure of sample adequacy (values > .60 required). Next, we split the initial screening data (n = 4010) into two groups using the select cases function in SPSS to randomly allocate cases to each group. EFA was conducted on the first half (n = 1963) and CFA on the second (n = 2047).
For the EFAs, principal axis factoring with oblique (Promax) rotation was used to explore the latent factor structure of the data (Cudeck, 2000). We tested the established three-factor structure in our sample before examining alternative (two and one-factor) structures reported in the literature (Vilagut et al., 2016). Factor loadings (values ≥ .40 acceptable) and communalities (values ≥ .30 acceptable; Comrey & Lee, 1992) were used to evaluate item performance, and factor performance was evaluated according to parsimony (cross-loading values ≤ .32; Tabachnick & Fidell, 2019). CFAs were estimated using Satorra-Bentler-corrected Maximum Likelihood, with 95% confidence intervals calculated using bias-corrected percentile bootstrapping on 1000 sample re-draws (Nevitt & Hancock, 2001). Brown’s (2015) conventions were used to assess EFA and CFA model fit, with ideal fit represented by non-significant chi-square (χ2) values, Root Mean Error of Approximation (RMSEA), Standardised Root Mean Square Residual (SRMR) values ≥ .08, Comparative Fit Index (CFI), and Tucker-Lewis Index (TLI) values ≥ .90. Cronbach’s alpha and McDonald’s omega coefficients were calculated to assess the internal consistency (values ≥ 0.7 acceptable; Terwee et al., 2007) of each CES-D short-form’s best performing model.
Next, using the full screening sample, we estimated the test-retest reliability of each CES-D form. Two-way mixed effects models were used to calculate the intraclass correlation coefficients (ICC) between initial screening and rescreening scores; ICC values < .50 were considered poor, .50 –.75 moderate, .75 – .90 good, and > .90 excellent (Koo & Li, 2016). Then, we used receiver operating characteristic (ROC) curves to examine each short-form’s criterion validity against the CES-D-20. For each CES-D short-form, we evaluated the sensitivity, specificity, positive predictive value (PPV), negative value (NPV), and proportion of cases correctly classified for the recommended and other potential cut-off points, with a view to identifying an optimal cut-off point that balanced sensitivity and specificity (Streiner et al., 2024). We also compared the area under the ROC curve (AUROC) using DeLong et al.’s (1988) nonparametric approach.
3.		Results
3.1.		Sample description
In total, 4010 patients between 18 and 88 years old (M = 46.3, SD = 13.3) were initially screened for trial eligibility, of whom 70.9% were female (n = 2844). Almost half (n = 1989; 46.9%) reported HIV, 1792 (44.7%) reported diabetes, and 229 (5.7%) reported co-occurring HIV and diabetes. Among those screened, 48.3% (n = 1935) had CES-D scores ≥ 16, indicating clinically significant symptoms of depression. Of these patients, 28.2% (n = 882) were re-screened, of whom 82.2% (n = 725) had CES-D scores ≥ 16.
3.2.		Dimensionality of the CES-D and its short-forms
3.2.1.		Exploratory factor analyses
In the initial EFA (n = 1963), three factors with eigenvalues ≥ 1 were extracted for the CES-D-20 and CES-D-12, and two factors were extracted for the CES-D-10, CES-D-9, and CES-D-8 respectively. For the CES-D-20 and CES-D-12, factor one comprised somatic and affective items, factor two comprised anhedonia items, and factor three contained items referring to interpersonal symptoms including social isolation. For the CES-D short-forms where only two factors were extracted, factor one comprised items relating to somatic and affective symptoms and factor two comprised items referring to anhedonia.
For the CES-D-20 and CES-D-12, we examined alternatives to a three- factor solution, by forcing a two-factor and one-factor solution. Model fit was superior for the three-factor model compared to both alternatives. Similarly, we forced a one-factor solution for the CES-D-10, CES-D-9, and CES-D-8. For each of these CES-D short-forms, model fit was superior for the two-factor solution. Model fit indices for the CES-D-20 and various short-forms are presented in Table 2. Factor loadings for each factor solution are shown in Supplementary file 1.
3.2.2.		Confirmatory factor analyses
For the CES-D-20 and each of its short-forms, CFA confirmed the factor structures identified in the EFAs (see Table 3). For the CES-D-20

Table 2
Model fit indices for exploratory factor analyses for N = 1963 participants.
CES-D
Form	χ2 (df)	RMSEA [CI]	SRMR	TLI	CFI	BIC	
CES-D 20
Three	655.38	0.045	0.022	0.954	0.968	-353.05	
factorsa
Two	(133)
1335.41	[0.041, 0.048]
0.063 [0.060,	0.036	0.909	0.928	190.49	
factorsb One	(151)
2598.93	0.066]
0.085 [0.082,	0.060	0.834	0.852	1309.96	
factorb
CES-D 12
Three	(170)
125.88	0.088]
0.038	0.015	0.976	0.988	-124.33	
factorsa
Two	(33)
674.04	[0.031, 0.045]
0.086 [0.081,	0.043	0.874	0.918	348.00	
factorsb One	(43) 1847.85	0.092]
0.130 [0.125,	0.086	0.715	0.767	1438.41	
factorb
CES-D 10
Two	(54)
138.25	0.135]
0.047	0.019	0.970	0.982	-58.89	
factorsa
One	(26)
362.29	[0.039, 0.055]
0.069 [0.063,	0.040	0.934	0.949	97.41	
factorb
CES-D 9
Two	(35)
109.79	0.076]
0.049	0.018	0.974	0.986	-34.27	
factorsa
One	(19)
760.20	[0.041, 0.058]
0.118 [0.111,	0.061	0.853	0.890	555.480	
factorb
CES-D 8
Two	(27)
90.86	0.125]
0.055	0.019	0.970	0.986	-7.71	
factorsa
One	(13)
660.99	[0.045, 0.066]
0.128 [0.120,	0.062	0.838	0.885	509.34	
factorb	(20)	0.136]					
Note.
a = Factors extracted based on Eigenvalues ≥ 1.00;
b = Factors extracted based on stipulation.
All χ2 values significant at p < .001.
RMSEA = Root Mean Square Error of Approximation; SRMR = Standardised Root Mean Square Residual; TLI = Tucker-Lewis Indicator; CFI = Comparative Fit Index; BIC = Bayesian Information Criterion.
Optimal fit is indicated in bold.
and the CES-D-12, the three-factor solution was superior to the two- and one-factor solutions. For the CES-D-10, CES-D-9, and CES-D-8, model fit was superior for the two-factor solution.
3.3.		Reliability
Internal consistency was adequate for the CES-D-20 and all shortforms, with Cronbach’s alpha and McDonald’s omega coefficients in the acceptable range (> .70; see Table 4). The CES-D and each of its short-forms exceeded the recommended threshold (ICC ≥ .70 for adequate test-retest reliability (Koo & Li, 2016; Streiner et al., 2024) with the full CES-D and most short-forms demonstrating good temporal stability (ICCs ≥ .75). The CES-D-8 had moderate temporal stability (ICC = .73). Table 4 presents the ICCs with 95% confidence intervals for the test-retest sample.
3.4.		Criterion validity
The ROC curves for each CES-D short-form are presented in Fig. 1. Each CES-D short-form had excellent criterion validity (AUROC > .90). Compared to the CES-D-20, the best performing short-forms were the CES-D-12 (AUROC=.99, 95% CI [98, .99]) and CES-D-10 (AUROC =99, 95% CI [.98, .99]). These AUROCs were significantly lower than the CES-D-20 (CES-D-12: z = 11.38, AUC D = .02, p < .001; CES-D-10: z = 11.15, AUC D = .02, p < .001). The AUROC of the CES-D-12 was not significantly different from the AUROC of the CES-D-10, z = -.26, AUC D = .00, p = .792; however, it was significantly higher than the CES-D-9, z = 2.28, AUC D =.00, p < .05, and the CES-D-8, z = 5.73, AUC D = .01, p < .001. The AUROC of the CES-D-10 was significantly higher than the CES-D-9, z = 3.67, AUC D = .01, p < .001, and the CES-D-8, z = 6.79, AUC D =.01, p < .001. The CES-D-9 and CES-D-8 also had AUROCs that were significantly lower than the CES-D-20. The CES-D-9 had an AUROC of .98, 95% CI [.98, .98], z = 11.57, AUC D =.02, p <.001 and the CES- D-8 had an AUROC of .98, 95% CI [.97, .98], z = 12.64, AUC D =.03, p < .001. The AUROC of the CES-D-9 was significantly higher than the CES- D-8, z = 2.86, AUC D = .01, p < .01.

CES-D Form	χ2 (df)	Δχ2 (df)	RMSEA [CI]	SRMR	TLI	CFI	BIC	
CES-D 20
Three factors	679.03 (167)		0.046 [0.043, 0.049]	0.031	0.953	0.959	99090.23	
Two factors	1448.01 (169)	284.76 (2)	0.061 [0.058, 0.064]	0.039	0.920	0.929	99621.22	
One factor	2780.58 (170)	53575.27 (1)	0.087 [0.084, 0.089]	0.061	0.837	0.854	100946.16	
CES-D 12
Three factors	207.99 (51)		0.039 [0.033, 0.044]	0.022	0.976	0.982	61711.95	
Two factors	740.14 (53)	532.14 (2)	0.080 [0.075, 0.085]	0.043	0.901	0.920	62228.84	
One factor	2051.74 (54)	1311.61 (1)	0.134 [0.129, 0.139]	0.082	0.717	0.768	63532.82	
CES-D 10
Two factors	177.23 (34)		0.045 [0.039, 0.052]	0.022	0.972	0.979	52760.18	
One factor	482.62 (35)	310.92 (1)	0.079 [0.073, 0.085]	0.047	0.916	0.935	52981.71	
CES-D 9
Two factors	159.00 (26)		0.050 [0.043, 0.058]	0.024	0.975	0.982	46970.25	
One factor	947.34 (35)	606.35 (9)	0.113 [0.107, 0.119]	0.059	0.862	0.892	52392.84	
CES-D 8
Two factors	102.18 (19)		0.046 [0.038, 0.055]	0.022	0.979	0.986	41570.30	
One factor	784.76 (20)	559.40 (1)	0.137 [0.129, 0.145]	0.066	0.820	0.871	42245.26	

Table 3
Fit indices for confirmatory factor analyses.

Note. N = 2,047.
All χ2 values significant at p < .001 except those marked with †.
RMSEA = Root Mean Square Error of Approximation; SRMR = Standardised Root Mean Square Residual; TLI = Tucker-Lewis Indicator; CFI = Comparative Fit Index;
BIC = Bayesian Information Criterion.
Optimal fit is indicated in bold.

As shown in Table 5, the sensitivity of each CES-D short-form decreased while specificity improved with every one-point increase in the proposed cut-off score. A cut-off score of 10 on the CES-D-12, 9 on the CES-D-10, and 7 on the CES-D-9 and CES-D-8 led to the best balance between sensitivity and specificity and optimised the correct classification of participants in this sample. For each of these cut-off scores, the positive predictive value (PPV) was very high, suggesting that more than

CES-D Form	Internal consistency (N = 4010)	Test-retest reliability (n = 882)
M (SD)	Cronbach’s α	McDonald’s ω	Average Inter-item r	M (SD)	ΔM	ICC [CI]	
CES-D-20
Factor 1
Factor 2
Factor 3
CES-D-12
Factor 1
Factor 2
Factor 3
CES-D-10
Factor 1
Factor 2
CES-D-9
Factor 1
Factor 2
CES-D-8
Factor 1
Factor 2	17.20 (12.68)	.920	.921	0.37	26.88 (12.22)	1.49	0.77 [0.75, 0.80]
.918	.918	0.45
.757	.762	0.44
.763	.763	0.62
10.31 (7.51)	.853	.855	0.33	14.99	(7.13)	0.71	0.75	[0.72,	0.78]
.834	.835	0.46
.757	.762	0.44
.763	.763	0.62
9.36 (6.90)	.860	.863	0.38	13.60	(6.49)	0.94	0.75	[0.72,	0.77]
.863	.864	0.45
.604	.617	0.43
9.08 (6.61)	.867	.868	0.42	13.78	(6.33)	1.43	0.75	[0.72,	0.78]
.861	.862	0.47
.784	.787	0.64
7.63 (5.75)	.848	.849	0.42	11.21	(5.54)	0.59	0.73	[0.69,	0.76]
.834	.834	0.46
.784	.787	0.64	

Table 4
Internal consistency and test-retest reliability for the CES-D-20 and each CES-D short form.

Note. ΔM = change in mean score, ICC = intraclass correlation coefficient, CI = 95% confidence interval.

Fig. 1. Receiver operating characteristic curves for each CES-D short-form (N = 4010).

90% of participants who scored on or above the cut-off-point were also classified as having clinically significant symptoms of depression on the CES-D-20. Compared to the CES-D-20, 93.1% of participants were correctly classified by the CES-D-12, 93.7% by the CES-D-10, 92.6% by the CES-D-9, and 91.6% by the CES-D-8 when using these respective cutoff scores.
4.		Discussion
This study compared the psychometric properties of four CES-D short-forms to identify the best alternative to the full CES-D for depression screening in South African primary care populations. Findings indicate that (1) each short-form demonstrated reliability comparable to that of the full CES-D, with high internal consistency and good temporal stability; (2) the CES-D-12 and CES-D-10 had significantly stronger criterion validity and classification accuracy than the other short-forms; and (3) the CES-D-12 was the only short-form with a latent structure that aligned with that of the full CES-D.
First, we found that the internal consistency of each short-form was comparable with the full CES-D. Consistent with prior systematic reviews (Park & Yu, 2021), the full CES-D had excellent internal consistency (α = .92). The CES-D short-forms also demonstrated high internal consistency (α > .85), as reported by earlier evaluations of the CES-D-12 (Adams et al., 2019; Torres, 2012), CES-D-10, (Baron et al., 2017; James et al., 2020), CES-D-9 (Santor & Coyne, 1997; Yang et al., 2018) and CES-D-8 (Briggs et al., 2018; O’Halloran et al., 2014). Our findings further indicate that the test-retest reliability of each short-form is comparable to that of the full CES-D, with all ICCs exceeding the threshold for adequate temporal stability (ICC >.70). These findings are consistent with previous reports of acceptable test-retest reliability for the full scale and the CES-D-10 (Andresen et al., 1994; Miller et al., 2008; Ohno et al., 2017; Radloff, 1977). Overall, these findings suggest that all four short-forms are highly reliable alternatives to the full CES-D for South African populations.
Table 5
Classification statistics for each CES-D short form.
Cut off-points for each form	Sensitivity	Specificity	PPV	NPV	Correctly classified	
CESD-12						
≥7	.993	.740	.780	.991	.862	
≥8	.983	.823	.837	.981	.900	
≥9	.961	.892	.892	.961	.925	
≥ 10	.925	.936	.931	.931	.931	
≥ 11	.875	.973	.967	.893	.925	
≥ 12	.804	.988	.984	.844	.899	
CESD-10						
≥6	.993	.711	.762	.991	.847	
≥7	.981	.811	.829	.979	.893	
≥8	.960	.895	.894	.961	.926	
≥9	.931	.943	.938	.936	.937	
≥ 10	.880	.972	.967	.897	.927	
≥ 11	.804	.990	.987	.845	.901	
CESD-9						
≥4	.996	.560	.678	.993	.770	
≥5	.991	.681	.743	.988	.831	
≥6	.983	.785	.809	.980	.880	
≥7	.959	.871	.874	.958	.914	
≥8	.915	.936	.930	.922	.926	
≥9	.859	.974	.968	.881	.918	
CESD-8						
≥2	.998	.284	.565	.995	.628	
≥3	.995	.418	.614	.990	.696	
≥4	.992	.569	.681	.987	.773	
≥5	.983	.705	.756	.978	.839	
≥6	.960	.820	.832	.957	.888	
≥7	.923	.910	.905	.927	.916	
Note. N = 4010
PPV = positive predictive values NPV = negative predictive value Optimal cut-off scores are in bold

Second, while all short-forms demonstrated excellent criterion validity and correctly classified over 90% of cases identified by the full CES- D, the CES-D-10 and CES-D-12 achieved significantly higher classification accuracy than the other short-forms. This finding suggests that the CES-D-10 and CES-D-12 may offer a more psychometrically robust alternative to the full CES-D than the other CES-D short-forms. While the optimal cut-off scores were slightly lower for this study than those reported in previous community samples (Adams et al., 2019; Andresen et al., 1994; Briggs et al., 2018). This likely reflects our inclusion criteria, which required participants to report recent low mood to qualify for screening. By pre-selecting individuals with self-reported mood concerns, we likely filtered out potential false positives, allowing for lower cut-offs without compromising specificity.
Third, this study confirmed that a three-factor structure—comprising somatic and affective symptoms, anhedonia, and interpersonal symp- toms—was the most appropriate for the full CES-D in this setting. Systematic reviews examining the latent structure of the CES-D in nonWestern populations have also recommended three-factor solutions (Blodgett et al., 2021; Carleton et al., 2013; Kim et al., 2011). However, these factors typically consist of depressed affect, anhedonia, and somatic symptoms, with interpersonal items distributed across factors. Our findings likely reflect how depression is understood and expressed in Sub-Saharan Africa. In this context, negative affect and somatic symptoms are often closely linked, with somatic symptoms serving as culturally accepted expressions of psychological distress. This distress is communicated through idioms such as “pain in the heart”, “heaviness in the body”, and “thinking too much” (Backe et al., 2021; Magidson et al., 2020; Mayston et al., 2020). It is also unsurprising that interpersonal symptoms emerged as a distinct factor, given that social disconnection and disrupted relationships are widely recognised as both causes and consequences of psychological distress in this cultural context (Mayston et al., 2020). Notably, the CES-D-12 was the only short-form to mirror the full CES-D’s three-factor structure. Prior research also found that the CES-D-12 had a three-factor structure characterised by somatic/affective, anhedonia, and interpersonal factors (Assari & Moazen-Zadeh, 2016). The remaining short-forms each exhibited a two-factor structure, capturing somatic symptoms/negative affect and anhedonia, but excluding the interpersonal factor. This two-factor model is consistent with earlier findings for the CES-D-10 (James et al., 2020), CES-D-9 and CES-D-8 (Adams et al., 2020; Briggs et al., 2018).
Although factorially-derived subscale scores are rarely calculated due to population-specific variations in the CES-D’s latent structure (Blodgett et al., 2021; Vilagut, 2016), they may provide information about individual symptom profiles that could facilitate treatment personalisation (Li et al., 2024; Nye et al., 2023). Except for the CES-D-10 anhedonia subscale, all CES-D subscales and those of its short-forms demonstrated good internal consistency. Nonetheless, our findings indicate that the CES-D-12 may be the most appropriate short-form for personalised treatment planning as its factorially-derived subscales reflect the range of depressive symptoms (including interpersonal symptoms). However, caution should be exercised when interpreting subscale scores, as both the CES-D and CES-D-12 require further research to confirm the stability of their factor structures and establish the criterion validity of their subscales.
4.1.		Strengths and limitations
Study strengths include the large sample of South African adults receiving chronic disease care and the inclusion of multiple screening time-points. However, some limitations warrant consideration when interpreting findings. Our sample comprised patients interested in participating in a psychological intervention trial, which likely resulted in a skewed sample comprised of individuals with higher CES-D scores. While this selection bias commonly occurs in mental health research (Kaz´mierczak et al., 2023), it may limit the generalizability of our findings. Future studies could limit selection bias by using random sampling methods to recruit participants representative of the broader primary care population, rather than restricting recruitment to treatment-seeking individuals.
Similarly, there are methodological limitations to the test-retest analysis as we relied on data collected through rescreening for the purposes of confirming trial eligibility. Consequently, participants who underwent retesting were not randomly selected from the pool of initially screened participants, and the test-retest interval was not standardised. While our findings still offer insights into the temporal stability of the CES-D and its short-forms, these should be considered preliminary and require replication.
Further, our use of the full CES-D as the reference standard prevented us from drawing definitive conclusions about the diagnostic accuracy of the short-forms. Although previous South African studies have validated the full CES-D against structured clinical interviews—reporting sensitivity of 79% (95% CI: 76%–83%) and specificity of 61% (95% CI: 56%– 85%) using the standard cut-off of 16 (Myer et al., 2008) —further validation of both the full CES-D and its short-forms against diagnostic gold standards is needed. Such research would help determine the most appropriate cut-off scores for the South African population to maximise case detection accuracy.
This study also did not assess convergent and discriminant validity of the CES-D and its short-forms against other depression screeners widely recommended for use in LMICs, such as the Patient Health Questionnaire (Bhana et al., 2015) or related constructs such as psychological distress. Future studies should include comparisons with other established measures of depression and related constructs to confirm that these CES-D short-forms can accurately identify depression and differentiate it from other related but distinct mental health conditions.
In addition, we could not compare the psychometric properties of the Afrikaans, isiXhosa and English language versions of the CES-D as the MIND trial did not record the language in which screening was conducted. We acknowledge that the use of multiple language versions of the CES-D may have influenced our overall results. We sought to minimise this risk by using Afrikaans and isiXhosa language versions that had been carefully translated and cross-culturally validated. There is evidence to suggest that these language versions perform comparably to the English CES-D in South African populations (Baron et al., 2017). Nonetheless, the lack of language information meant we were unable to assess cross-language measurement equivalence of the CES-D and its short-forms. Further research is needed to establish measurement equivalence of these different language versions so that these tools can confidently be used for depression screening in diverse patient populations.
Similarly, future studies should assess whether the CES-D functions equivalently for patients with different chronic conditions. Available evidence on the performance of the CES-D for populations with a chronic condition remains limited to populations with HIV, suggesting some CES-D items function differently between populations with and without HIV (Adams et al., 2018; Bagheri et al., 2021; Radusky et al., 2021). Future validation studies should assess whether item responses systematically vary between populations with HIV, diabetes and other conditions, and whether cut-off scores require adjustment to improve depression case detection accuracy for specific patient groups.
5.		Conclusion
Findings from this study suggest that the CES-D-10 and CES-D-12 are the most psychometrically robust alternatives to the full CES-D for depression screening in South African primary care populations. When choosing between these two short-forms, clinicians should consider the specific needs and constraints of their practice setting. The CES-D-10 may be a more efficient option for routine screening in resourcelimited care environments when the primary goal is potential case detection. However, as the latent structure of the CES-D-12 aligns with that of the full CES-D, it may offer greater insights into patients’ symptom profiles and better support clinical decision-making. Regardless of the CES-D short-form used for depression screening, elevated scores should always prompt further diagnostic assessment before initiating treatment.
Funding
This study was funded jointly by the British Medical Research Council, Wellcome Trust, Department for International Development, the Economic and Social Research Council, and the Global Challenges Research Fund (MR/M014290/1). Bronwyn Myers’ time was supported by the Stan Perron Charitable Foundation (People Grant 2023054). Study funders were not involved in data collection, analysis, or interpretation.
Data availability
A data dictionary and de-identified participant data is available after approval of a proposal and a signed data access agreement (bmyers@mrc.ac.za; bronwyn.myers-franchi@curtin.edu.au).
CRediT authorship contribution statement
Lexy Staniland: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Conceptualization. Katherine Sorsdahl: Writing – review & editing, Methodology, Investigation, Conceptualization. Claire van der Westhuizen: Writing – review & editing, Investigation, Data curation. Lesley-Ann Erasmus-Claassen: Writing – review & editing, Project administration, Investigation, Data curation. Petal Petersen Williams: Writing – review & editing, Project administration, Investigation, Data curation. Bronwyn Myers: Writing – review & editing, Supervision, Methodology, Investigation, Funding acquisition, Conceptualization.
Declaration of competing interest
The authors declare that this research was conducted in the absence of any commercial or financial relationships that could have been perceived as a potential conflict of interest.
Acknowledgements
We wish to thank the Western Cape Department of Health and all patients who agreed to participate in this trial. We also want to thank our stakeholder advisory group (that comprised representatives from the Western Cape Department of Health, community organisations, and service users) and our trial steering committee for their governance, guidance, and support throughout the trial. We also acknowledge the contribution of Dr Nozibele Gcora who provided data management support during the MIND trial and cleaned the screening data.
Supplementary materials
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jadr.2026.101046.
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