Prevalence and associated factors of geriatric syndromes using an online self-administered screening tool based on the ICOPE framework in primary care

Abstract

Background

Geriatric syndromes (GSs) such as cognitive decline, malnutrition, and mobility impairment are common among older adults and associated with adverse health outcomes. Traditional paper-based assessments are often resource-intensive and difficult to implement in primary care. The World Health Organization’s Integrated Care for Older People (ICOPE) framework emphasizes early detection, yet evidence on the implementation of self-administered online screening in Southeast Asia is limited.

Objective

This study aimed to (1) determine the prevalence of GSs in primary care, (2) identify associated factors, and (3) evaluate preliminary process indicators of an online self-administered geriatric screening tool based on the ICOPE framework and Thai national guidelines.

Methods

A cross-sectional study was conducted between April and December 2024 across seven primary care units in Bangkok, Thailand. Older adults aged ≥ 60 years were randomly selected from daily clinic lists. Participants completed an online questionnaire covering demographics, comorbidities, health behaviors, and 10 geriatric screening questions. Those screening positive underwent in-depth assessments by trained nurses using validated tools (e.g., Mini-Cog, Snellen chart, Timed Up and Go test). Associations between participant characteristics and GSs were examined using multivariable logistic regression. Preliminary process indicators were assessed through completion rates, need for caregiver assistance, acceptability, and completion time.

Results

A total of 374 participants (mean age 76.4 years, 63.6% female) were included. Multimorbidity was present in 76.7% and polypharmacy in 58.6%. The most prevalent GSs were limited mobility (49.7%), vision impairment (43.6%), and undernutrition (34.8%). Significant risk factors for GSs included older age for hearing loss (adjusted odds ratio [OR] 2.37, 95% CI 1.19–4.72), low education for limited mobility (aOR 8.14, 95% CI 2.25–29.52) and urinary incontinence (aOR 3.48, 95% CI 1.36–8.89), multimorbidity for urinary incontinence (aOR 3.12, 95% CI 1.34–7.29), and polypharmacy for cognitive decline (aOR 2.70, 95% CI 1.25–5.81) and depressive symptoms (aOR 3.40, 95% CI 1.31–8.84). Protective factors included regular physical exercise and normal body mass index against multiple GSs. Regarding preliminary process indicators, 81.5% completed the online screening independently, the average completion time was 12.8 min, and 88.9% reported the system was easy to use.

Conclusions

A self-administered online geriatric screening tool adapted from the ICOPE framework is feasible, acceptable, and effective in detecting GSs in primary care. The high prevalence of GSs highlights the urgent need for scalable digital solutions. Integrating online screening into primary care workflows could facilitate early identification, optimize resource use, and promote healthy aging in resource-constrained settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-026-07590-9.

Introduction

Geriatric syndromes (GSs) represent a cluster of conditions arising from multifactorial causes, including medical, psychosocial, and environmental vulnerabilities. These syndromes cannot fit into discrete disease categories and are loosely defined [1]. Common GSs include vision and hearing impairment, urinary incontinence, falls, cognitive decline, and frailty [2]. These syndromes are strongly associated with re-hospitalization [3] and mortality [4]. Previous studies have reported the prevalence of GSs ranging from 44.7%–75.3% [5, 6]. Importantly, geriatric syndromes often co-occur and interact with one another, reflecting shared underlying vulnerabilities across multiple physiological systems [7].

To address these challenges, the World Health Organization introduced the Integrated Care for Older People (ICOPE) framework, which provides a roadmap for integrating care across the life course by optimizing the design, funding, and delivery of services. The ICOPE framework emphasizes screening in primary care through intrinsic capacity domains, including locomotor, vitality, visual, hearing, cognitive, and psychological capacity [8]. Although geriatric syndromes (GSs) and intrinsic capacity domains are conceptually distinct, they are closely interrelated. GSs represent multifactorial clinical conditions, whereas intrinsic capacity domains, as defined in the ICOPE framework, reflect functional reserves across key physiological and psychological systems. Impairments in intrinsic capacity domains can serve as early indicators or operational proxies for underlying geriatric syndromes [9]. Therefore, the ICOPE approach provides a practical framework for identifying individuals at risk of GSs through domain-based screening in primary care.

Despite the global expansion of digital health and the growing adoption of the ICOPE framework [10], evidence on self-administered online screening for older adults remains limited, particularly in low- and middle-income countries. In Southeast Asia, existing evidence is scarce; to date, only a pilot study from Malaysia has examined the feasibility of self-administered online surveys for geriatric syndrome screening in an urban community setting [11]. However, that study provided limited data on the prevalence of geriatric syndromes and their associated factors, and did not evaluate the integration of digital self-screening tools into routine primary care practice. This highlights a critical gap in the evidence base, particularly in resource-constrained settings, where scalable and efficient screening strategies are urgently needed.

Thailand, an upper middle–income country, is experiencing rapid population aging, with older adults (≥ 60 years) accounting for 20% of the population and projected to increase by 10% by 2050 [12]. Despite the introduction of national geriatric screening guidelines in 2020, which recommend standardized assessments across 15 health domains (e.g., Mini-Cog for dementia, finger rub test for hearing) [13], implementation remains difficult in practice. Primary care centers face high patient volumes and workforce shortages, making it challenging to screen all older adults as recommended, thereby creating a gap between policy and real-world practice.

The Outpatient Department and Division of Family Medicine at Phramongkutklao Hospital provide primary care to military communities across Bangkok, serving a large population of older adults. To strengthen geriatric care, the Primary Care Model for Keeping (PMK) Healthy Aging was developed, with a focus on geriatric syndrome assessment and management. However, detailed assessments remain constrained by limited time and staff resources. To address this, we developed an online self-administered screening approach, whereby older adults complete a digital questionnaire before further assessment by nurses and physicians. This tool was adapted from the ICOPE framework and the Thai national geriatric screening guideline.

To our knowledge, this research represents the first study in Thailand, and one of the few in Asia, to test online geriatric screening tools. The objectives of this study were to (1) determine the prevalence of GSs in primary care, (2) identify associated factors, and (3) evaluate preliminary process indicators of an online self-administered geriatric screening tool based on the ICOPE framework and Thai national guidelines.

Method

Study design and setting

This was a cross-sectional study conducted between April 1, 2024, and December 30, 2024, across seven primary care units under the Phramongkutklao Hospital network in Bangkok, Thailand. The study was part of the Primary Care Model for Keeping (PMK) Healthy Aging program.

Participants

Older adults aged ≥ 60 years attending the primary care units were invited to participate. Exclusion criteria were severe cognitive or communication impairment that prevented self-completion of the online questionnaire. Informed consent was obtained from all participants.

Sampling procedure

A simple random sampling method was applied. Each day, a list of eligible older adults attending the seven primary care units was compiled. Using a computer-generated random sequence, participants were randomly selected to be invited into the study. If a selected individual declined participation or did not meet the eligibility criteria, another eligible individual was randomly chosen from the same list. This approach ensured that all eligible older adults had an equal chance of selection.

On average, approximately 7 older adults attended each primary care unit per day during the study period. The number of individuals approached, those who declined participation, and those excluded after eligibility assessment were recorded to allow assessment of potential selection bias. A flow diagram illustrating participant recruitment, inclusion, and exclusion will be provided in the results section.

Sample size calculation

Sample size calculation was based on the primary objective of estimating the prevalence of geriatric syndromes among community-dwelling older adults in primary care. The estimated prevalence ranged from 20% to 58.3%, derived from previous studies [14, 15], with visual impairment having the highest reported prevalence (58.3%). The sample size was calculated using a single population proportion formula: n = Z²₁−α/2 × P(1 − P) / d². A 95% confidence level was applied (Z = 1.96), with a margin of error of 5% (d = 0.05). Based on these assumptions, the minimum required sample size was calculated to be 374 participants.

Screening tool and assessment

We developed a 2-step geriatric screening approach adapted from the ICOPE framework and the Thai national guideline for geriatric health screening from the Ministry of Public Health of Thailand. Although the Thai national guidelines recommend assessment across 15 domains, the present study focused on 7 key domains that are most feasible for a 10-item self-administered online screening tool in primary care settings. In step 1, an online questionnaire was created using Google Forms (Google Inc) to collect demographic information, comorbidities, health behaviors, and 10 self-administered screening questions covering common geriatric syndromes. Participants who had difficulty using digital devices were assisted by caregivers or clinic staff. Assistance was limited to technical support, such as navigating the questionnaire interface or reading questions aloud when necessary, without influencing participants’ responses. In step 2, participants with positive responses underwent an in-depth assessment conducted by trained nurses using standardized tools (Table 1).

Table 1.

Ten screening questions and corresponding in-depth assessment tools for geriatric syndromes

Geriatric syndrome	Screening questions	In-dept assessment
Cognitive decline	1. Do you have problems with memory or orientation?	Mini-Cog
Vision impairment	2. Do you have any problems with your eyes (difficulties in seeing far or near, eye pain or discomfort)?	Snellen chart
Hearing loss	3. Do you have a hearing problem?	Finger rub test
Undernutrition	4. Have you unintentionally lost more than 3 kg over the last 3 months? 5. Have you experienced loss of appetite?	Mini nutritional assessment (MNA)
		Possible sarcopenia (calf circumference and 5-repetition chair stand test)
Depressive symptoms	Over the past 2 weeks, have you been bothered by either of the following: 6. Feeling down, depressed or hopeless? 7. little interest or pleasure in doing things?	Thai Geriatric Depression scale (TGDS)
Urinary incontinence	8. Have you lost urine and gotten wet that disturbed your daily life?	Three Incontinence Questions (3IQ)
Limited mobility	9. Have you fallen in the past year? 10. Do you feel unsteady when standing or walking?	Timed Up and Go test (TUGT)

Measures

• The tool assessed common GSs through in-depth assessments using validated instruments.

  • ◦ Cognitive decline: Cognition was assessed using the Mini-Cog test, which combines a 3-item recall task and a clock drawing test. The total score ranges from 0 to 5 points, with a cutoff score of < 3 indicating cognitive impairment [16].
  • ◦ Vision impairment: Visual acuity was assessed using the Snellen chart. Participants were allowed to use their usual corrective lenses, if any, during the assessment. Participants were classified as visually impaired if they could not read more than half of the optotypes at a distance of 6/12 meters [17].
  • ◦ Hearing loss: The finger rub test was conducted with participants using their usual hearing aids when applicable. Participants were asked whether they could hear the sound of fingers rubbed approximately 5 to 10 cm from the ear. Failure to perceive the sound was considered abnormal and suggestive of hearing impairment [18].
  • ◦ Undernutrition and sarcopenia: Nutritional status was assessed using the Mini Nutritional Assessment–Short Form (MNA-SF; score 0–14). Participants were classified as normal nutritional status (12–14 points), at risk of malnutrition (8–11 points), or malnourished (≤ 7 points) [19]. According to the Thai national guideline for geriatric health screening, participants diagnosed with malnutrition underwent further assessment for sarcopenia. Sarcopenia was identified using a two-step approach aligned with the AWGS 2019 “possible sarcopenia” algorithm: firstly, low muscle mass was screened using calf circumference (< 34 cm in men, < 33 cm in women); secondly, reduced physical performance was assessed using the 5-repetition chair stand test, with a threshold of > 12 s indicating impairment [20].
  • ◦ Depressive symptoms: Depressive symptoms were assessed using the Thai version of the Patient Health Questionnaire-9 (PHQ-9). The PHQ-9 consists of 9 items, each scored from 0 (not at all) to 3 (nearly every day), yielding a total score of 0–27. A cutoff score of > 7 was used to indicate clinically significant depressive symptoms [21].
  • ◦ Urinary incontinence: Urinary incontinence was screened using the 3-Incontinence Questions (3IQ). This brief self-administered tool consists of 3 items: (1) any involuntary urine leakage, (2) circumstances of leakage (such as with physical activity, urgency, or without obvious reason), and (3) frequency of leakage 22].
  • ◦ Limited mobility: Mobility was assessed using the Timed Up and Go Test (TUGT). Participants were instructed to rise from a standard chair, walk 3 m at a comfortable pace, turn around, return to the chair, and sit down. A completion time of ≥ 12 s was considered indicative of impaired mobility and increased fall risk [23].

• Physical activity: Regular exercise was defined as engaging in moderate-intensity physical activity for at least 150 min per week, based on the World Health Organization recommendation [24]. Participants were categorized as engaging in regular physical exercise (yes) or not (no).

• Social participation: Social participation was assessed by asking whether participants engaged in any social, community, or group activities (e.g., religious gatherings, clubs, volunteer work) at least once per month [25]. Participants were categorized as having social participation (yes) or none (no).

Training and quality control

In each primary care unit, one nurse was designated to conduct the in-depth geriatric assessments. To ensure consistency, all nurses received standardized training provided by a geriatric family physician at Phramongkutklao Hospital, covering both the screening protocol and the administration of assessment tools. Continuous supervision was ensured by family physicians at each unit. Whenever uncertainties arose during screening or interpretation, family physicians were available for consultation and guidance. Inter-rater reliability was assessed and demonstrated good agreement across raters (e.g., intraclass correlation coefficient [ICC] = 0.85).

Outcomes

The primary outcome was the prevalence of geriatric syndromes. Secondary outcomes included factors associated with GSs and process indicators relevant to the implementation of online screening in primary care. These indicators were assessed using three measures: (1) the proportion of participants who completed the online screening independently versus those requiring caregiver assistance, (2) the acceptability of the tool, assessed by a yes/no question asking whether the online format was easy to use, and (3) the average time required to complete the questionnaire, measured automatically by the Google Forms timestamp.

Data collection and analysis

All responses from the self-administered online screening were automatically recorded in a secure, password-protected electronic database with restricted access limited to authorized research personnel. No personally identifiable information was disclosed during analysis. Data completeness and consistency were checked by trained research staff before analysis. A complete-case analysis approach was applied, whereby participants with missing data on key variables were excluded from the respective analyses.

Baseline characteristics were summarized as means with standard deviations for continuous variables and as frequencies with percentages for categorical variables. Univariable logistic regression was performed, and crude odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Variables with a P value < 0.20 in univariable analysis, along with those identified as clinically relevant from previous literature, were included in the multivariable logistic regression model. The final model included pre-specified variables: age, sex, education level, multimorbidity, polypharmacy, physical exercise, and body mass index (BMI).

Potential multicollinearity among independent variables was assessed using variance inflation factors (VIFs), with no evidence of significant multicollinearity observed. Adjusted odds ratios (aORs) with 95% CIs were reported, and P<.05 was considered statistically significant. Preliminary process indicators (proportion of participants completing the screening without assistance, acceptability, and average completion time) were analyzed descriptively using proportions and means, as appropriate. All statistical analyses were conducted using STATA/MP version 12 (StataCorp, College Station, TX, USA).

Ethics approval

This study was approved by the Institutional Review Board of Royal Thai Army Medical Department Ethics Committee as instituted (IRBRTA 736/2567) by the Declaration of Helsinski, and all participants were required to provide written informed consent before enrollment.

Results

A subset of 385 elderly individuals met the eligibility criteria out of the evaluated sample size of 400. A total of 9 (2.3%) individuals declined participation in the present study. Out of the 376 enrolled participants, 2 (0.5%) had missing data, leaving 374 participants’ data for the analysis (Fig. 1).

Fig. 1.

Flowchart of participants from eligibility to data analysis

Demographic characteristics

The mean age of participants was 76.4 (SD 8.9) years, and 238 (63.6%) were female. Most participants had attained a bachelor’s degree or higher (61.2%). The most common chronic conditions were dyslipidemia (77.0%) and hypertension (75.7%). Multimorbidity, defined as the presence of two or more chronic conditions, was observed in 76.7% of participants, and 58.6% reported polypharmacy (≥ 5 medications) (Table 2).

Table 2.

Characteristics of participants

Characteristic	n (%) or mean (SD)
Age, years (mean, SD)	76.4 (8.9)
Female	238 (63.6)
Education
Primary school or lower	54 (14.4)
Secondary school	40 (10.7)
Diploma/Associate degree	51 (13.6)
Bachelor’s or higher	229 (61.2)
Chronic conditions
Dyslipidemia	288 (77.0)
Hypertension	283 (75.7)
Diabetes	105 (28.1)
Osteoporosis	75 (20.1)
Cardiovascular disease	26 (7)
Multimorbidity	287 (76.7)
Polypharmacy	219 (58.6)
Smoking status: non-smoker	340 (90.9)
Alcohol consumption: non-drinker	339 (90.6)
Regular physical exercise	95 (25.4)
Body mass index
Underweight (< 18.5 kg/m²)	21 (5.6)
Normal (18.5–22.9 kg/m²)	176 (47.1)
overweight/obese (≥ 23 kg/m²)	177 (47.3)
Living arrangement: living alone	17 (4.6)
Social participation	206 (55.1)

Prevalence of geriatric syndromes

The most prevalent geriatric syndromes were limited mobility (49.7%), vision impairment (43.6%), and undernutrition (34.8%) (Fig. 2). A Venn diagram (Fig. 3) illustrates the overlap among three geriatric syndromes: limited mobility, undernutrition, and cognitive impairment. Approximately one-third of participants (35.5%) had at least two of these conditions, and nearly one-tenth (8.8%) were affected by all three conditions.

Fig. 2.

Percentage of overall prevalence of geriatric syndromes

Fig. 3.

The proportions of study participants affected by limited mobility, undernutrition, and/or cognitive impairment. The overlapping regions represent the coexistence of 2 or more conditions in the same individual

Factors associated with geriatric syndromes

Associations between participant characteristics and geriatric syndromes are presented in Table 3, and the results of univariable analysis are provided in Supplementary Table 1. In multivariable logistic regression analysis, older age (≥ 70 years) was significantly associated with hearing loss (adjusted odds ratio [aOR] 2.37, 95% CI 1.19–4.72; P=.014). Lower educational attainment was significantly associated with limited mobility (aOR 8.14, 95% CI 2.25–29.52; P=.001) and urinary incontinence (aOR 3.48, 95% CI 1.36–8.89; P=.009). Multimorbidity was also associated with limited mobility (aOR 5.03, 95% CI 1.25–20.24; P=.023) and urinary incontinence (aOR 3.12, 95% CI 1.34–7.29; P=.009).

Table 3.

Factors associated with geriatric syndrome by multivariable logistic regression

Factor	Limited mobility a OR (95% CI)	P value	Vision impairment aOR (95% CI)	P value	Undernutrition aOR (95% CI)	P value	Urinary incontinence aOR (95% CI)	P value	Hearing loss aOR (95% CI)	P value	Possible sarcopenia aOR (95% CI)	P value	Cognitive decline aOR (95% CI)	P value	Depressive symptoms aOR (95% CI)	P value
Age ≥ 70 years	0.76 (0.33–1.77)	0.525	1.34 (0.78–2.30)	0.293	1.55 (0.83–2.90)	0.172	1.20 (0.63–2.29)	0.588	2.37 (1.19–4.72)	0.014	0.96 (0.44–2.06)	0.909	0.92 (0.45–1.87)	0.808	1.10 (0.49–2.49)	0.817
Female	0.62 (0.32–1.17)	0.141	0.61 (0.39–0.97)	0.037	0.72 (0.43–1.21)	0.213	0.90 (0.54–1.51)	0.689	0.67 (0.40–1.12)	0.124	0.64 (0.35–1.17)	0.144	0.73 (0.41–1.32)	0.300	0.86 (0.43–1.74)	0.680
Low education	8.14 (2.25–29.52)	0.001	1.44 (0.64–3.26)	0.381	0.17 (0.07–0.42)	< 0.001	3.48 (1.36–8.89)	0.009	0.21 (0.08–0.56)	0.002	0.41 (0.15–1.10)	0.077	1.38 (0.56–3.37)	0.485	0.47 (0.13–1.73)	0.256
Multimorbidity	5.03 (1.25–20.24)	0.023	0.85 (0.45–1.61)	0.623	0.85 (0.41–1.76)	0.665	3.12 (1.34–7.29)	0.009	1.17 (0.55–2.46)	0.683	1.33 (0.55–3.21)	0.525	1.44 (0.57–3.62)	0.443	0.72 (0.25–2.04)	0.531
Polypharmacy	2.19 (0.94–5.09)	0.070	1.65 (0.94–2.89)	0.084	1.34 (0.70–2.54)	0.374	1.61 (0.86–3.00)	0.138	1.45 (0.77–2.74)	0.255	0.95 (0.45–2.01)	0.886	2.70 (1.25–5.81)	0.011	3.40 (1.31–8.84)	0.012
Physical exercise	0.97 (0.49–1.90)	0.921	0.58 (0.36–0.94)	0.027	0.30 (0.18–0.52)	< 0.001	0.72 (0.42–1.23)	0.226	0.83 (0.48–1.42)	0.487	0.16 (0.08–0.31)	< 0.001	0.34 (0.19–0.62)	< 0.001	1.72 (0.81–3.64)	0.158
Normal body mass index	0.69 (0.61–0.79)	< 0.001	0.94 (0.89–0.99)	0.031	0.88 (0.82–0.94)	< 0.001	0.86 (0.79–0.92)	< 0.001	1.01 (0.95–1.07)	0.847	0.79 (0.72–0.87)	< 0.001	1.05 (0.98–1.12)	0.171	1.08 (1.00–1.16)	0.061

Polypharmacy was significantly associated with cognitive decline (aOR 2.70, 95% CI 1.25–5.81; P=.011) and depressive symptoms (aOR 3.40, 95% CI 1.31–8.84; P=.012). Female sex was associated with lower odds of vision impairment (aOR 0.61, 95% CI 0.39–0.97; P=.037).Regular physical exercise was inversely associated with vision impairment, undernutrition, possible sarcopenia, and cognitive decline (all P<.05). In addition, normal body mass index was associated with lower odds of limited mobility, vision impairment, undernutrition, urinary incontinence, and possible sarcopenia (all P<.05).

Preliminary process indicators of online self-administered screening

Regarding the preliminary process indicators, 81.5% of participants completed the online screening independently, whereas 18.5% required assistance from a caregiver or clinic staff. The mean completion time was 12.8 (SD 4.7) minutes. Overall, 88.9% of participants reported that the online format was easy to use.

Discussion

This study provides new evidence on the preliminary process indicators and utility of a two-step screening process for GSs in primary care. The process consisted of an initial self-administered online screening, followed by detailed assessments conducted by trained health professionals, adapted from the ICOPE framework and the Thai national guideline. It is important to note that the findings should be interpreted as reflecting a screening approach rather than definitive diagnoses. The online tool was intended to identify older adults who may be at risk of geriatric syndromes, and positive results should be considered as an indication for further clinical assessment.

Nearly half of community-dwelling older adults screened positive for at least one geriatric syndrome, underscoring the high burden of these conditions in primary care. Limited mobility, visual impairment, and undernutrition were the most common syndromes identified. Furthermore, older age, lower education, polypharmacy, and multimorbidity were independently associated with multiple geriatric syndromes, whereas regular physical exercise and normal BMI were protective against these conditions. Importantly, preliminary process indicators were encouraging: most participants were able to complete the screening independently, with high acceptability reported. These findings suggest that digital tools may help overcome workforce shortages and time constraints commonly faced in primary care.

Comparison with previous studies

In ICOPE Step 1 community screenings, limited mobility was reported in approximately one-quarter of older adults, including 30.4% in a China [26] and 24.3% in a Singapore [27]. These figures are lower than the prevalence observed in our study (49.7%), may be explained by differences in assessment methods (performance-based Timed Up and Go Test vs. self-reported ICOPE screening) as well as the older age and higher burden of chronic disease in our population. Our findings are also comparable to the nationwide prevalence of high fall risk in Thailand (38.5%) [28]. Visual impairment affected 43.6% of participants, consistent with a previous Thai survey (34.6%) [29] and study from China (42%). Similarly, undernutrition (34.8%) in our study was close to the pooled prevalence of older adults at risk of malnutrition in Thailand (37.8%) [30] and to that reported in Singapore (27%) [31].

Older age, lower education, multimorbidity, and polypharmacy were independently associated with multiple GSs in our study, consistent with previous findings. In a large community-based study from China, advancing age and poor self-rated health were strong predictors of coexisting geriatric syndromes [32]. Similarly, a cohort study of older homeless adults in the United States found that having less than a high school education was significantly associated with a higher total number of geriatric syndromes, including falls and urinary incontinence [33]. Moreover, multimorbidity was found to increase the risk of urinary incontinence in the English Longitudinal Study of Ageing over a 10-year follow-up [34]. In addition, evidence from the China Health and Retirement Longitudinal Study demonstrated that multimorbidity was associated with a higher prevalence of functional and mobility limitations [35]. Polypharmacy was associated with an increased risk of cognitive decline and depression in our study. This finding is consistent with a cross-sectional community-based study in the United States, which reported that polypharmacy increased the odds of cognitive impairment [36]. Moreover, a longitudinal observational study from the Netherlands Study of Depression in Older Persons demonstrated that polypharmacy was associated with depression, with a higher number of medications linked to a worse course of late-life depression. These findings suggest that depression may moderate the relationship between polypharmacy and adverse outcomes through shared risk factors, including motivational problems, anxiety, and pain [37].

These associations may be explained by several underlying mechanisms. Ageing is associated with a progressive decline in physiological reserve, increased inflammatory burden, and reduced resilience to stressors, which contribute to the development of geriatric syndromes [38]. Lower educational attainment may reflect limited health literacy and reduced access to healthcare resources, leading to poorer disease management [39]. In addition, multimorbidity contributes to cumulative physiological burden and functional decline [40], while polypharmacy increases the risk of adverse drug reactions, drug–drug interactions, and medication-related cognitive and functional impairment [41]. Furthermore, depression may act as both a consequence and a mediator, exacerbating functional decline through reduced motivation, physical inactivity, and poor treatment adherence [42].

In contrast, regular physical exercise and maintaining a normal BMI emerged as protective factors against several geriatric syndromes. These findings are consistent with systematic reviews and meta-analyses showing that physical activity including multicomponent exercise preserves mobility, muscle strength, and cognition [43] while reducing risks of sarcopenia and malnutrition [44]. Maintaining a normal BMI appears to reduce the risks of falls, malnutrition, urinary incontinence, and sarcopenia. Systematic reviews and meta-analyses report a U-shaped association between BMI and risk of falls [45]. In addition, BMI is closely associated with malnutrition and sarcopenia in older adults. Underweight status reflects poor nutritional reserves and is strongly linked to muscle mass loss, and increased risk of sarcopenia [46]. Conversely, higher BMI may mask sarcopenia as sarcopenic obesity, in which increased fat mass coexists with reduced muscle strength and function [47]. Although evidence directly linking normal BMI to lower urinary incontinence risk is limited, meta-analytic data demonstrate that overweight and obesity are significant risk factors for urinary incontinence. Women who maintain a normal BMI have a notably lower risk of stress and severe incontinence compared to those who have been overweight or obese [48]. Moreover, female gender was associated with a lower likelihood of vision impairment. This may be partly explained by differences in health-seeking behavior, as women are more likely to access healthcare services, including cataract surgery [49]. However, this finding should be interpreted with caution, as it may reflect residual confounding or characteristics specific to our study population.

Compared to traditional paper-based assessments, the online format in our study demonstrated favorable process indicators, with nearly 90% of participants reporting that the system was easy to use. This finding is consistent with recent reports of growing digital health literacy among older adults [50]. The mean completion time was 12.8 min, similar to a study in Malaysia where older adults required 16.9 min to complete an online geriatric screening tool [11]. However, nearly one-fifth of participants required caregiver assistance, underscoring the persistent digital divide, particularly among the oldest-old and those with lower education [51].

Strengths and limitations

This study has several notable strengths. First, it applied practical tools for primary care, combining self-administered online screening with in-depth assessments, and was based on internationally endorsed frameworks (ICOPE) and national Thai guidelines. These validated instruments, which follow international standards and established cutoffs, can be readily replicated in other primary care settings, both in Thailand and globally, owing to the availability of translations and standardized protocols. Second, the random selection of participants from clinic lists across seven primary care units strengthen the representativeness of the study population. This design enhances the generalizability of our findings and provides robust evidence on the utility of self-administered online assessments for detecting common yet often underrecognized GSs in primary care. Third, the study examined multiple determinants of geriatric syndromes, encompassing physical factors (e.g., chronic diseases, polypharmacy), lifestyle factors (e.g., exercise, smoking, alcohol use), and social aspects (e.g., social participation), offering a holistic perspective on contributors to geriatric syndromes. Finally, process indicators such as completion time and acceptability were systematically evaluated, providing valuable insights for the integration of digital health tools into primary care.

Nevertheless, certain limitations should be acknowledged. First, recall bias or social desirability bias may have affected the accuracy of self-reported responses. Second, the study focused on screening and assessment of GSs rather than definitive diagnoses; causal relationships could not be established. Third, older adults with severe cognitive or communication impairment who were unable to complete the questionnaire independently were excluded. This may have introduced selection bias, potentially underrepresenting individuals with more severe cognitive impairment or communication. Moreover, social participation was assessed using a single-item yes/no question, which may not fully capture the frequency, intensity, or quality of social engagement. In addition, the study population had a relatively high educational level, which may limit the generalizability of the findings to the broader older adult population, particularly those with lower educational attainment.

Finally, although the sample size was adequate overall, confidence intervals for some risk factors were wide, suggesting limited statistical power for subgroup analyses. Future studies with larger and more diverse primary care populations are needed to improve precision, confirm these associations, and enhance generalizability. In addition, further research should explore practical implementation challenges, including digital literacy, caregiver support, and resource availability in real-world settings.

Conclusions

This study showed that a self-administered online geriatric health screening tool, adapted from the ICOPE framework and national guidelines, is feasible and acceptable in primary care. The prevalence of GSs was high, with limited mobility, visual impairment, and malnutrition being the most common. Older age, lower education, multimorbidity, and polypharmacy were significant risk factors, whereas regular physical exercise and maintaining a normal BMI were protective. By integrating digital self-screening into primary care workflows, this approach provides a scalable and resource-efficient method for the early identification of at-risk older adults. Wider implementation, with particular attention to digital accessibility, could support healthy aging and help bridge gaps in geriatric care in resource-constrained settings.

Authors’ contributions

PS, KK, SK, and KM contributed to conceptualization. PS, and KM contributed to the methodology. PS, IK and PL contributed to the investigation. PS, IK, and KM contributed to data curation. PS, KK, SK, and KM contributed to formal analysis. PS and KM contributed to writing. All authors read and agreed to the version of the manuscript intended for publication.

Funding

No funding was received.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Institutional Review Board of Royal Thai Army Medical Department Ethics Committee as instituted (IRBRTA 736/2567) by the Declaration of Helsinski, and all participants were required to provide written informed consent before enrollment.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.