Late-Life Depression (LLD) represents one of the most pressing public health challenges of the 21st century. As global populations age at unprecedented rates, the prevalence of depressive disorders among older adults has risen correspondingly, with estimates indicating that approximately 13 % to 18 % of community-dwelling older adults experience clinically significant depressive symptoms (Errazuriz et al., 2023; Zenebe et al., 2021). Unlike depression in younger populations, LLD presents unique diagnostic complexities, including atypical symptom presentation, high comorbidity with physical illness, cognitive impairment, and increased suicide risk (Alexopoulos, 2019; Kok & Reynolds, 2017).

The consequences of untreated LLD extend beyond individual suffering to include accelerated cognitive decline, increased healthcare utilization, elevated mortality risk, and substantial caregiver burden (Diniz et al., 2013). Despite its clinical significance, LLD remains underrecognized and undertreated in many healthcare systems, with fewer than 50% of affected older adults receiving adequate mental health services (Park & Unützer, 2011; Wang et al., 2007).

The Geriatric Depression Scale

The Geriatric Depression Scale (GDS), developed by Yesavage et al. (1983), has emerged as the most widely used screening instrument for LLD worldwide. Originally published as a 30-item scale (GDS-30), subsequent short forms including the 15-item (GDS-15), 10-item (GDS-10), and 5-item (GDS-5) versions have been developed to reduce respondent burden (van Marwijk et al., 1995; Yesavage & Sheikh, 1986). The GDS is distinguished from other depression measures by its dichotomous (yes/no) response format, which minimizes response bias, and its exclusion of somatic symptoms that may reflect normal aging rather than depression (Yesavage, 1988).

Despite its widespread use, questions remain regarding the GDS's psychometric performance across different cultural, linguistic, and clinical populations. Research has demonstrated variability in optimal cutoff scores, factor structure, and diagnostic accuracy across settings (Krishnamoorthy et al., 2020; Mitchell et al., 2010; Pocklington et al., 2016).

The Latin American Context for Late-Life Depression

Latin America is undergoing the most rapid demographic aging of any world region. The population of adults aged 60 years and older is projected to increase from approximately 80 million in 2020 to over 200 million by 2050 (United Nations, 2022). Prevalence estimates of late-life depression in Latin America range from 12 % to 34 % depending on country, with higher rates observed in women, individuals with low socioeconomic status, and those with chronic medical conditions (Gómez-Restrepo et al., 2021; Guerra et al., 2016; Salazar et al., 2015). A systematic review of Latin American studies reported pooled depression prevalence of 22.7 % among community-dwelling older adults, substantially higher than the 13 % to 18 % typically reported in high-income countries (Errazuriz et al., 2023).

Despite this burden, mental health services for older adults in Latin America remain severely limited. In this context, brief, validated screening instruments such as the GDS may provide useful tools for early identification of depressive symptoms and support task-sharing and decentralized mental health care.

However, the cross-cultural transferability of depression screening tools cannot be assumed. Latin America encompasses tremendous linguistic, cultural, and health system diversity. Measurement invariance—the statistical property ensuring that a scale measures the same construct across groups—has never been formally tested for the GDS across any Latin American countries.

Psychosocial Interventions for Late-Life Depression

Evidence-based psychosocial interventions for LLD include cognitive-behavioral therapy (CBT), problem-solving therapy, reminiscence and life review therapy, physical exercise programs, and multicomponent interventions (Cuijpers et al., 2026; Huang et al., 2015; Pinquart et al., 2007). Meta-analyses have established those psychosocial interventions produce small-to-moderate effect sizes for LLD compared to control conditions, with pooled effect sizes (Hedges' g) ranging from 0.32 to 0.68 (Cuijpers et al., 2026; Forsman et al., 2011; Gould et al., 2012).

The Present Systematic Review

The rationale for integrating measurement and intervention reviews warrants explicit justification. These two domains are conceptually and methodologically interdependent. First, intervention effect sizes are only interpretable to the extent that the outcome measure demonstrates validity and reliability in the population under study. A statistically significant intervention effect derived from a scale that lacks measurement invariance across cultural groups cannot be meaningfully compared with effects derived from a scale that does. Second, the GDS is the most frequently used outcome measure in psychosocial intervention trials for late-life depression—15 of the 16 intervention studies identified in this review used some version of the GDS as their primary outcome measure. Thus, the psychometric properties of the GDS directly affect the evidentiary basis for intervention recommendations. Third, by examining both domains within a single review, we can identify whether evidence gaps in one domain predict evidence gaps in the other. This integrated approach allows us to evaluate whether measurement quality moderates or confounds intervention conclusions—a question that would be obscured if the two literatures were reviewed separately.

Existing systematic reviews have typically addressed either measurement or intervention, but rarely both. This fragmentation limits our understanding of how measurement properties affect intervention conclusions. Furthermore, previous reviews have primarily synthesized evidence from high-income countries, limiting generalizability to low- and middle-income settings (Guerra et al., 2016; Reynolds et al., 2014).

The rationale for integrating measurement and intervention reviews warrants explicit justification. These two domains are conceptually and methodologically interdependent. First, intervention effect sizes are only interpretable to the extent that the outcome measure demonstrates validity and reliability in the population under study. A statistically significant intervention effect derived from a scale that lacks measurement invariance across cultural groups cannot be meaningfully compared with effects derived from a scale that does. Second, the GDS is the most frequently used outcome measure in psychosocial intervention trials for late-life depression—15 of the 16 intervention studies identified in this review used some version of the GDS as their primary outcome measure. Thus, the psychometric properties of the GDS directly affect the evidentiary basis for intervention recommendations. Third, by examining both domains within a single review, we can identify whether evidence gaps in one domain predict evidence gaps in the other. This integrated approach allows us to evaluate whether measurement quality moderates or confounds intervention conclusions—a question that would be obscured if the two literatures were reviewed separately.

Therefore, this systematic review had two primary aims: (1) to synthesize the psychometric properties of the Geriatric Depression Scale in community-dwelling older adult populations, and (2) to evaluate the efficacy of psychosocial interventions for reducing depressive symptoms in older adults compared to control conditions.

Conceptual Framework

This review is guided by three interconnected premises. First, depression is a culturally shaped construct; the GDS, developed in North America, assumes similar symptom manifestation across populations. Second, measurement invariance has never been tested for the GDS across Latin American countries. Third, intervention efficacy assumes measurement validity; if the GDS does not measure depression equivalently, effect sizes may be biased.

Method

Registration and Protocol

This systematic review followed PRISMA 2020 guidelines (Page et al., 2021). The review was not registered, and no protocol was prepared.

Eligibility Criteria

Studies were included based on the following criteria: (1) community-dwelling older adults (mean age ≥60 years); (2) administration of GDS (any version) or psychosocial intervention; (3) gold standard clinical interview for diagnostic accuracy studies or control condition for intervention studies; (4) psychometric properties or depressive symptom outcomes; (5) peer-reviewed journal articles or dissertations; (6) English, Portuguese, or Spanish; (7) database inception to April 2026.

Exclusion criteria: institutional settings; younger adults; qualitative studies; pharmacological interventions only; studies without original data; non-validated outcome measures.

Information Sources and Search Strategy

A comprehensive and systematic literature search was conducted on April 1, 2026, across eight electronic databases: PubMed (MEDLINE), PsycINFO (EBSCOhost), SciELO, LILACS, Redalyc, Dialnet, Web of Science, and ProQuest Dissertations & Theses Global. No publication date restrictions were applied to any of the searches.

The search strategies were developed by combining controlled vocabulary terms (e.g., Medical Subject Headings [MeSH] in PubMed and LILACS, and Thesaurus terms in PsycINFO) with free-text keywords using the Boolean operators AND and OR. The search strategy encompassed three principal conceptual domains.

Target Instrument and Population.

Terms related to the Geriatric Depression Scale ("Geriatric Depression Scale," "GDS," "Yesavage") were combined with descriptors referring to older adults ("aged," "older adults," "elderly," "geriatric," "late-life," "idosos," "adultos mayores," and "ancianos").

Clinical Condition and Interventions. Descriptors for depressive disorders ("depression," "depressive symptoms," "depressive disorder," and "depressão") were combined with terms referring to psychosocial interventions, including "psychosocial intervention," "psychotherapy," "cognitive behavioral therapy," "CBT," "exercise," "behavioral activation," "problem solving," "terapia," and "intervención psicosocial."

Methodological and Psychometric Indicators. Keywords related to psychometric evaluation included "psychometric," "reliability," "validity," "sensitivity," "specificity," "factor analysis," "ROC curve," "cutoff," "confiabilidad," "validación," "validação," and "fiabilidad." These were complemented with study design descriptors such as "randomized controlled trial," "controlled clinical trial," "RCT," and "ensayo clínico."

Database-Specific Adaptations.

In PubMed (MEDLINE), controlled MeSH terms and title/abstract keywords ([tiab]) were combined with publication type filters ([pt]). Searches were restricted to human studies published in English, Spanish, or Portuguese involving populations aged 65 years and older.

In PsycINFO (EBSCOhost), controlled descriptors (DE) and free-text terms were used to retrieve peer-reviewed journal articles published in English, Spanish, and Portuguese, focusing on adults aged 60 years and older.

For SciELO, Redalyc, and Dialnet, multilingual search terms in English, Spanish, and Portuguese were searched within titles, abstracts, and keywords to identify regional Ibero-American literature.

In LILACS, text words (tw:) and DeCS/MeSH descriptors (mh:) were combined in Spanish and Portuguese to retrieve relevant health sciences literature from Latin America and the Caribbean.

In Web of Science, topic searches (TS=) were conducted for articles and reviews published in English, Spanish, and Portuguese involving adults aged 60 years and older.

For ProQuest Dissertations & Theses Global, broad keyword combinations focusing on depression, psychometric validation, and older adults were used to identify relevant grey literature, including doctoral dissertations and master's theses.

Across all databases, the search was restricted to records published in English, Spanish, or Portuguese, consistent with the review's eligibility criteria. The complete search strategies for each database, including the exact Boolean syntax, are documented in Appendix B to ensure methodological transparency and reproducibility.

Date of all searches: April 1, 2026. No date limits applied

Selection Process

Two independent reviewers screened all records using Rayyan software (Ouzzani et al., 2016). Inter-rater agreement was excellent (title/abstract: κ = 0.87; full-text: κ = 0.92).

Data Extraction

A standardized data extraction form was developed in Microsoft Excel. Two reviewers independently extracted data, with discrepancies resolved by consensus. Extracted variables included study characteristics, sample characteristics, GDS version or intervention type, psychometric properties or effect size data, and risk of bias information.

Risk of Bias Assessment

Part A (psychometric studies): COSMIN Risk of Bias checklist (Mokkink et al., 2018). Part B (intervention studies): Cochrane Risk of Bias 2 (RoB2) tool (Sterne et al., 2019). Two reviewers independently assessed risk of bias (COSMIN: κ = 0.84; RoB2: κ = 0.81).

Justification of Methodological Assessment Tools: PRISMA was applied as the overarching reporting guideline. COSMIN was selected for psychometric studies as it provides domain-specific ratings for each psychometric property. RoB2 was selected for RCTs as it addresses key sources of bias relevant to psychosocial interventions (randomization, deviations from interventions, missing outcome data). For included meta-analyses, AMSTAR-2 (Shea et al., 2017) was used to assess methodological quality (results in Appendix B).

Data Synthesis

A narrative synthesis was conducted following SWiM guidelines (Campbell et al., 2020). For intervention studies, Hedges' g was calculated as the standardized mean difference between intervention and control groups at post-treatment. Random-effects models using the DerSimonian-Laird estimator were employed for pooled effect sizes (DerSimonian & Laird, 1986), conducted in R version 4.2.1 (R Core Team, 2022) with the meta package (Schwarzer et al., 2026). Heterogeneity was assessed using I ^² (Higgins et al., 2003). Sensitivity analyses excluded high-risk studies and those with >20% attrition, a threshold commonly used to identify studies with concerning attrition levels. Publication bias was assessed via funnel plots, Egger's test (Egger et al., 1997), and trim-and-fill procedures (Duval & Tweedie, 2000a, 2000b).

A hierarchical approach was adopted to avoid duplication when both meta-analyses and primary studies were included: meta-analyses provided pooled estimates, while primary studies provided unique data not captured in meta-analyses. Specifically, Cuijpers et al. (2026), Gould et al. (2012), and Mitchell et al. (2010) were included as meta-analyses, with their constituent studies included only when providing additional moderator or subgroup data.

Results

Study Selection

The systematic search identified 1,847 records across seven databases. After removing 438 duplicates, 1,409 records proceeded to screening. Of these, 1,281 were excluded, leaving 128 full-text articles assessed for eligibility. Of these, 100 were excluded, yielding a final sample of 28 studies (12 psychometric, 16 intervention).

Figure 1 presents the PRISMA 2020 flow diagram. After removing 438 duplicates, 1,409 records were screened. Following title/abstract screening (1,281 excluded), 128 full-text articles were assessed, of which 100 were excluded for reasons listed in the figure. The final sample included 28 studies (12 psychometric, 16 intervention).

Study Characteristics

The 28 included studies spanned 1983 to 2026. Psychometric studies included 5 diagnostic accuracy studies, 4 validation studies, 2 factor analysis studies, and 1 meta-analysis. Intervention studies included 9 individual RCTs and 7 meta-analyses. The most common GDS version was GDS-15 (10/12 psychometric studies). CBT was the most frequently tested intervention (6/16 intervention studies). Of the 28 included studies, only 3 (10.7 %) came from Latin America, all from Brazil.

Part A: Psychometric Properties of the Geriatric Depression Scale

Internal Consistency

All 12 psychometric studies reported internal consistency. For the GDS-30, Cronbach's alpha ranged from 0.92 to 0.95. For the GDS-15, alpha coefficients ranged from 0.79 to 0.91 (median α = 0.85). For the GDS-5, alpha ranged from 0.72 to 0.78. McDonald's omega showed comparable values (ω = 0.83 – 0.92).

Test-Retest Reliability

Six studies reported test-retest reliability. For the GDS-15, ICC ranged from 0.82 to 0.90 over intervals of 1 to 4 weeks. For the GDS-30, Pearson correlations ranged from r = 0.85 to 0.92 over 2-week intervals.

Diagnostic Accuracy and Optimal Cutoff Scores

The GDS-15 demonstrated good-to-excellent diagnostic accuracy across validation studies (see Table 1 for detailed values). Optimal cutoff varied by population: ≥5 in European/Canadian samples, ≥6 in Brazilian samples, and ≥7 in the Indian sample, consistent with Mitchell et al. (2010).

Latin American GDS Validation Studies

Across the three Brazilian validation studies, optimal cutoff was consistently ≥6. Sensitivity ranged from 0.86 to 0.92, specificity from 0.75 to 0.79, and Cronbach's . from 0.86 to 0.91 (see Table 2).

Factor Structure

Seven studies examined factor structure. A one-factor solution was supported in four studies (CFI = 0.92 – 0.96), while three studies reported better fit for a three-factor solution (dysphoric mood, withdrawal/apathy, cognitive concerns; CFI = 0.94, RMSEA = 0.06). No studies examined measurement invariance across Latin American cultural groups.

The three-factor solution may better capture how older adults—particularly those with mild cognitive impairment—experience depression as a multidimensional phenomenon rather than a unitary mood disorder.

Part B: Efficacy of Psychosocial Interventions

Overview of Included Interventions

The 16 intervention studies examined CBT (6 studies), exercise (2), reminiscence/life review (1), multicomponent (3), and other psychosocial approaches (4). No psychosocial intervention RCTs have been conducted in any Latin American country.

All pooled effect sizes were estimated, and all moderator and sensitivity analyses were conducted, using random-effects models with the DerSimonian–Laird estimator (DerSimonian & Laird, 1986) in R version 4.2.1 (R Core Team, 2022), using version 7.0-0 of the meta package (Schwarzer et al., 2015).

Effect Sizes by Intervention Type

All interventions demonstrated significant small-to-moderate effect sizes (see Table 3). Behavioral Activation produced the largest effect (g = 0.62), followed by CBT (g = 0.56) and multicomponent interventions (g = 0.51). Pooled effect was g = 0.48 [0.40, 0.56], with substantial heterogeneity (I^² = 72 %).

Behavioral Activation (BA; g = 0.62) outperformed Reminiscence (g = 0.38), suggesting behavioral mechanisms may be more central to LLD than cognitive or autobiographical mechanisms

Effect Sizes by Control Condition Type

Effect sizes varied by control type: waitlist controls (g = 0.62; k = 8), treatment as usual (g = 0.44; k = 5), active controls (g = 0.32; k = 3).

This pattern suggests that approximately half of the observed treatment effect may be attributable to non-specific factors rather than intervention-specific mechanisms.

Moderators of Intervention Efficacy

Group interventions showed slightly smaller effects (g = 0.44) than individual interventions (g = 0.54; p = 0.18). Studies requiring minimum depression scores showed larger effects (g = 0.58 vs. g = 0.39; p = 0.04). In-person interventions showed g = 0.50; telephone/online showed g = 0.42 (p = 0.24).

Risk of Bias Assessment

Overall, 31 % of RCTs were low risk, 44 % had some concerns, and 25 % were high risk (see Table 4). For psychometric studies (COSMIN), 42 % were rated "very good," 33 % "adequate," 17% "doubtful," and 8 % "inadequate."

Discussion

Summary of Findings

This systematic review found that the GDS-15 demonstrates adequate psychometric properties in populations where it has been studied, with internal consistency (α = 0.79 – 0.91) and diagnostic accuracy (sensitivity 0.80 – 0.92; specificity 0.75 – 0.88) meeting conventional thresholds. Psychosocial interventions, particularly Behavioral Activation (g = 0.62) and CBT (g = 0.56), produced clinically meaningful reductions in depressive symptoms (pooled g = 0.48). However, these conclusions are geographically limited, as the evidence base for the GDS excludes all Spanish-speaking Latin American countries, and no psychosocial intervention RCT has been conducted with older adults in any Latin American country.

The Latin American Evidence Gap

This review's most striking finding is the near-complete absence of Latin American research. Of 28 included studies, only 3 (10.7 %) came from Latin America, all from Brazil. No studies from Spanish-speaking Latin American countries met inclusion criteria. This gap is consequential for several reasons. First, without local validation studies, clinicians lack evidence-based cutoff scores. Using cutoffs derived from European or North American samples may produce high false positive rates. Second, without intervention RCTs, clinicians have no evidence on whether psychosocial interventions are effective in Latin American settings. Third, this absence represents a failure of research equity.

Conceptual Implications of GDS Performance Variability

The variability in optimal GDS-15 cutoffs across settings (≥5 to ≥7) raises three conceptual questions that extend beyond methodology.

First, does the GDS measure the same latent construct across populations? The factor analytic evidence is mixed: four studies support a one-factor solution, while three support a three-factor solution (dysphoric mood, withdrawal/apathy, cognitive concerns). The three-factor solution may better capture how older adults—particularly those with mild cognitive impairment—experience depression as a multidimensional phenomenon rather than a unitary mood disorder. For Latin America, where cognitive screening is not routine in primary care, a three-factor interpretation could lead to different clinical decisions depending on which domain is elevated.

Second, why does the optimal cutoff increase from Europe (≥5) to Brazil (≥6) to India (≥7)? Three non-mutually exclusive explanations exist: (a) true prevalence differences (higher prevalence requires higher cutoffs to maintain specificity), (b) differential item functioning (certain items are endorsed more or less frequently due to cultural norms about emotional expression), or (c) reference group effects (the gold standard clinical interview itself may have variable cross-cultural validity). The current literature cannot adjudicate among these explanations because no study has simultaneously tested measurement invariance and diagnostic accuracy in a Latin American sample.

The variability in optimal GDS-15 cutoffs across settings may reflect meaningful differences in how late-life depression is experienced across cultural contexts. However, alternative explanations—including differences in study methodology or sampling strategies—cannot be ruled out. The available evidence is insufficient to confirm cultural differences as the primary explanation.

Third, what does the exclusion of somatic symptoms imply for Latin American populations? The GDS deliberately omits somatic items (fatigue, appetite change, sleep disturbance) to avoid confounding depression with physical illness or normal aging. However, in many Latin American cultural contexts, older adults may express psychological distress primarily through somatic complaints—a phenomenon documented in Mexican, Colombian, and Central American populations (Arrieta et al., 2017). If somatic presentations are common, the GDS may systematically under-identify depression in Spanish-speaking Latin America relative to populations where cognitive-affective symptoms are more readily endorsed.

Comparison with Previous Systematic Reviews

Our findings are broadly consistent with prior reviews: similar pooled sensitivity (0.82 vs. 0.80 in Mitchell et al., 2010), specificity (0.81 vs. 0.81), and effect sizes for CBT (g = 0.56 vs. g = 0.52 in Cuijpers et al., 2026). However, our review extends previous work by explicitly examining the intersection of measurement and intervention literatures, revealing that while each literature is robust in high-income countries, the combined evidence base for Latin America is essentially absent.

We also identified a graded pattern of optimal cutoffs (Europe ≥5, Brazil ≥6, India ≥7) that diverges from Pocklington et al. (2016), who concluded a single cutoff (≥5) is appropriate across populations. This discrepancy may reflect differences in inclusion criteria (primary care vs. community samples) or may indicate genuine cross-cultural differences in depression presentation. Additionally, our finding that Behavioral Activation (g = 0.62) showed the largest effect among intervention types extends the work of Cuijpers et al. (2026), who did not separately analyze BA from CBT interventions. This suggests that behavioral mechanisms may warrant greater attention in future intervention development.

Theoretical Implications

The finding that effect sizes varied by control condition type suggests that approximately half of the observed treatment effect may be attributable to non-specific factors (therapist attention, expectation of improvement, structured routine) rather than intervention-specific mechanisms. This pattern has implications for intervention design in Latin America, where culturally adapted interventions maximizing therapeutic alliance and credibility may be as important as specific techniques.

Behavioral Activation (g = 0.62) outperformed Reminiscence (g = 0.38), suggesting behavioral mechanisms may be more central to LLD than cognitive or autobiographical mechanisms. For Latin America, culturally adapted interventions should prioritize BA with consideration of collectivist values (e.g., family-centered activities rather than individual walks).

Practical Guidance for Clinicians

In the absence of local validation studies, clinicians in Spanish-speaking Latin America may consider adopting a provisional cutoff of ≥6, while recognizing this recommendation is based on Brazilian data and international literature, and that local validation is needed to confirm its appropriateness.

Clinicians should: (1) use GDS-15 with provisional cutoff ≥6, (2) supplement positive screens with clinical interview, (3) document local performance, and (4) consider PHQ-9 as alternative (Arrieta et al., 2017; Diez-Quevedo et al., 2001).

Recommendations for Latin American Research

Immediate priority (0-2 years): GDS-15 validation studies in Mexico, Colombia, and Argentina. Short-term (2-4 years): Measurement invariance testing across Latin American countries. Medium-term (4-6 years): Culturally adapted psychosocial intervention trials.

Limitations

Methodological limitations include: only three Latin American studies identified (all Brazil), substantial heterogeneity (I^² = 72 %), and 69 % of intervention studies with high risk/some concerns. Scope limitations: community-dwelling older adults only; findings may not generalize to institutional settings. The review was not prospectively registered, and no protocol was prepared; therefore, adherence to prespecified methods and the possibility of selective reporting could not be independently assessed.

Conclusion

This systematic review demonstrates that the GDS is psychometrically adequate in studied populations (α = 0.79 – 0.91; sensitivity 0.80 – 0.92; specificity 0.75 – 0.88), and psychosocial interventions produce clinically meaningful reductions in depressive symptoms (pooled g = 0.48). However, these conclusions are geographically contingent. The evidence base excludes all Spanish-speaking Latin American countries. No psychosocial intervention RCT has been conducted in any Latin American country.

The variability in optimal GDS cutoffs (≥5 Europe, ≥6 Brazil, ≥7 India) cannot be dismissed as sampling error. Without measurement invariance testing, we cannot know whether a GDS score of 6 in Mexico means the same as in Brazil. For geropsychology to advance equitably in Latin America, we propose: (1) immediate country-specific validation studies; (2) short-term measurement invariance testing; and (3) medium-term culturally adapted intervention trials. The question is not whether imported tools "work" in Latin America, but for whom, in which contexts, and with what adaptations they serve older adults' interests.

References

Notes

^* Original Review/Systematic Review.

Author notes

^a Correspondence author. Email: gautam_makwana@hotmail.com

Additional information

How to cite: Makwana, G. S. (2026). Geriatric Depression Scale and Psychosocial Interventions for Late-Life Depression: A Systematic Review Focusing on Latin America. Universitas Psychologica, 25, 1-14. https://doi.org/10.11144/Javeriana.upsy25.gdsp

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