Fear of Missing Out and Its Association with Respiratory Symptoms in Patients with Chronic Obstructive Pulmonary Disease Who Use Short-Video Platforms

Abstract

Purpose

The pervasive use of short-video platforms has raised concerns about their potential psychological impact, particularly the development of Fear of Missing Out (FoMO). This exploratory cross-sectional study aimed to investigate the association between general FoMO and respiratory symptoms in patients with Chronic Obstructive Pulmonary Disease (COPD) who use short-video platforms.

Patients and Methods

This exploratory cross-sectional study was conducted between January and April 2025 among 207 patients recruited from respiratory outpatient clinics, pulmonary function laboratories, and rehabilitation departments of three tertiary hospitals in Yinchuan City using convenience sampling. Participants were assessed using the general Chinese Fear of Missing Out Scale (FoMOs) and the Breathlessness, Cough, and Sputum Scale (BCSS). Multiple linear regression was used to evaluate the association between FoMO and respiratory symptoms while adjusting for covariates.

Results

Among the 207 patients included, average scores were 12.97 (±5.05) for FoMO and 7.86 (±2.24) for BCSS. In the multivariable model, FoMO (B = 0.079, p = 0.002), underweight BMI (<18.5 kg/m²; B = 1.191, p = 0.024), short-video exposure of 6–8 h/day (B = 1.507, p = 0.008), and anxiety (B = 0.321, p = 0.036) were significantly associated with higher BCSS scores. The model explained 24.2% of the variance in symptom severity (R² = 0.242; adjusted R² = 0.165).

Conclusion

Among patients with COPD who used short-form videos, FoMO showed a weak positive correlation with BCSS symptom scores. As this was a cross-sectional study, causal conclusions cannot be drawn, and further longitudinal studies are needed to validate these findings. Nevertheless, these results still suggest that incorporating psychosocial factors into the management of chronic obstructive pulmonary disease holds important potential value.

Introduction

Chronic Obstructive Pulmonary Disease (COPD) is characterized by persistent and progressively worsening respiratory symptoms such as dyspnea, cough, and sputum production. COPD is a leading cause of morbidity and mortality worldwide, accounting for approximately 3.2 million deaths annually.¹ In China, the prevalence of COPD is approximately 13.7% among adults aged 40 years and older, affecting about 99.9 million people,² and COPD imposes a substantial economic burden, with global costs estimated in the trillions of US dollars and projected to rise.³

COPD respiratory symptoms significantly contribute to disease progression and diminish patients’ quality of life.⁴ As a leading cause of morbidity and mortality worldwide, COPD places an increasing burden on both individuals and healthcare systems.⁵ The impact of respiratory symptoms on daily functioning and well-being is substantial, leading to frequent exacerbations and intensive medical management. Understanding the factors that influence the severity of these symptoms is critical for improving care and patient outcomes.

The exacerbation of respiratory symptoms in patients with COPD is influenced by multiple factors. Previous studies have highlighted several biophysical and psychosocial determinants, including smoking, frequent exacerbation phenotypes, and negative emotional states, which can exacerbate symptom severity and worsen disease trajectory.^6–9 However, these factors primarily focus on patients’ physical and emotional states without adequately addressing the broader spectrum of environmental and digital stressors that may also play a role in symptom exacerbation.

Recently, the widespread use of short-form video platforms has introduced a new set of digital stressors. One particularly relevant phenomenon is the Fear of Missing Out (FoMO), which is defined as “a pervasive apprehension that others might be having rewarding experiences from which one is absent”.¹⁰ Research has shown that FoMO is highly prevalent among individuals who engage frequently with social media, with a majority of frequent users reporting FoMO at least occasionally, and several studies indicate its detrimental effects on mental health, including increased anxiety, depression, and overall distress.^8–10 These findings suggest that constant exposure to curated social media content, which highlights idealized versions of life, can negatively impact emotional and psychological well-being.

Importantly, prior research suggests that social-media use and FoMO may have physiological correlates, although these pathways were not measured in the present study.¹⁰ Neurobiological studies indicate that the brain can respond to social exclusion and perceived threats to social status through activation of the amygdala and the hypothalamic-pituitary-adrenal (HPA) axis, with associated physiological stress responses.^11,12 Studies have also demonstrated that social-media use after acute stress can impair cortisol recovery, suggesting that digital engagement may sustain physiological arousal.^10,11 Furthermore, FoMO has been associated with sleep disturbances, which are known to exacerbate respiratory symptoms and impair immune function.^13,14 These mechanisms are presented as hypotheses derived from prior literature rather than as pathways demonstrated in this study.

The relationship between psychological stress and respiratory symptoms in COPD is well-established. Psychological distress, including anxiety and depression, has been shown to increase the perception of dyspnea, exacerbate respiratory symptoms, and contribute to more frequent disease exacerbations.^11,12 The cognitive-behavioral model of breathlessness suggests that anxious cognitions and fear of breathlessness can create a positive feedback loop, leading to heightened somatic awareness and worsening symptom perception.¹¹ Given that FoMO represents a form of chronic social stress characterized by persistent anxiety about missing rewarding experiences, it is plausible that FoMO may similarly influence respiratory symptom perception in COPD patients.

This exploratory cross-sectional study aimed to investigate the association between general FoMO and respiratory symptoms in patients with COPD who use short-video platforms. The research question was whether higher FoMO scores were associated with higher BCSS scores after adjustment for the covariates included in the specified model; because of the cross-sectional design, the study does not test causation.

Materials and Methods

Design and Participants

This exploratory cross-sectional study was conducted between January and April 2025. Convenience sampling was used to recruit participants from the respiratory outpatient clinics, pulmonary function laboratories, and rehabilitation departments of three tertiary hospitals in Yinchuan, Ningxia, China.

The recruitment process involved multiple strategies to ensure adequate participant enrollment. First, potential participants were identified through electronic medical records by reviewing scheduled appointments at respiratory outpatient clinics. Research assistants screened patients for eligibility based on age and COPD diagnosis. Eligible patients were approached during their clinic visits, provided with detailed information about the study, and invited to participate. For patients attending pulmonary function laboratories, research assistants coordinated with laboratory staff to identify eligible individuals awaiting or completing spirometry testing. In rehabilitation departments, patients enrolled in pulmonary rehabilitation programs were invited to participate during their routine sessions.

The inclusion criteria were: (1) a physician-diagnosed case of COPD or a post-bronchodilator FEV1/FVC ratio < 0.7. Patients diagnosed by physician had undergone three pulmonary function tests and diagnosed with COPD prior to the study, and had been receiving long-term symptom management in outpatient settings; (2) age ≥ 40 years; (3) daily use of short-video platforms (eg, Douyin, Kuaishou) for at least 30 minutes; and (4) ability to understand and complete questionnaires in Chinese. The exclusion criteria were: (1) language or hearing impairment that would prevent completion of questionnaires; (2) coexisting conditions with symptoms similar to COPD, such as active pneumonia, bronchiectasis, or lung cancer; and (3) acute exacerbation of COPD in the preceding four weeks. These criteria were established to ensure that participants had stable respiratory conditions and could provide reliable self-report data, while excluding conditions that might confound the assessment of respiratory symptoms.

Sample Size Calculation

The required sample size for this study was calculated based on the multiple linear regression model used to examine the relationship between general FoMO and respiratory symptoms. Following established methodological guidelines, 5–10 participants per predictor variable were considered sufficient for stable parameter estimates.^13,15 With twelve predictors in the final model (FoMO score, BMI, exacerbation phenotype, gender, marital status, education level, daily video exposure duration, smoking status, secondhand-smoke exposure, FCI score, anxiety, and depression), Accounting for the categorical levels, this resulted in a total of 27 variables, yielding a minimum required sample size of 135. Taking into account a 20% rate of incomplete or unusable response data, the target sample size was set to at least 162. A total of 207 subjects were included in the final analysis.

Ethics Approval

Ethical approval for this study was granted by the Institutional Review Board of Ningxia Medical University, China (Approval No. 2024–3747). All participants provided written informed consent for the use of their anonymized data for research purposes. The study was conducted in accordance with the Declaration of Helsinki principles for research involving human subjects.

Measurements

Respiratory Symptoms

The Breathlessness, Cough, and Sputum Scale (BCSS) was used to assess respiratory symptoms.¹⁴ The scale consists of three items rating breathlessness, cough, and sputum on a five-point Likert scale ranging from 0 (no symptoms) to 4 (severe/constant symptoms). The total scores range from 0–12, with higher scores indicating greater symptom severity. The BCSS has demonstrated good psychometric properties, including internal consistency (Cronbach’s α = 0.70 for daily assessments), test-retest reliability (ICC = 0.77–0.88), and validity in COPD populations¹⁶ A BCSS sum score of ≥5.0 has been shown to identify COPD exacerbation with 83% sensitivity and 68% specificity.¹⁷ In the present study, participants rated their symptoms over the preceding four weeks, and questionnaires were interviewer-administered to participants with low educational attainment.

Fear of Missing Out

The Fear of Missing Out Scale (FoMOs) was used to assess patients’ fear of missing out related to short-video and social media use. We used the validated Chinese version of the 8-item FoMO scale,¹⁸ which was adapted from the original 10-item scale.¹⁹ The Chinese version comprises two factors: fear of missing novel information (4 items) and fear of missing social opportunities (4 items). Items are rated on a five-point Likert scale ranging from 1 (not at all true) to 5 (extremely true), with higher total scores indicating greater FoMO (range: 8–40). The Chinese version has demonstrated excellent psychometric properties, including internal consistency (Cronbach’s α = 0.91 for the full scale, 0.94 for fear of missing information, and 0.88 for fear of missing social situations), good construct validity, and measurement invariance across gender and age groups. The Chinese FoMO items were not modified to refer specifically to short-video use.

Short-Video Exposure Assessment

Participants were asked about their daily duration of short-form video viewing, including time spent on major platforms such as Douyin (TikTok) and Kuaishou. Duration was categorized into five groups: 0–2 hours, 2–4 hours, 4–6 hours, 6–8 hours, and ≥8 hours per day.

Covariates

Basic socio-demographic characteristics, including age, gender (male and female), race (Han and others), marital status (married and unmarried), and education level (no formal education, primary education, junior secondary education, and post-secondary education) were collected through structured interviews conducted by trained research staff. Body Mass Index (BMI) was calculated by dividing weight (in kilograms) by height (in meters squared) and categorized into three groups (<18.5 kg/m², 18.5–23.9 kg/m², and ≥24.0 kg/m²). Comorbidity was assessed using the Functional Comorbidity Index (FCI), which comprises 18 diseases with each condition scoring one point (total range: 0–18).²⁰ Frequent exacerbation was defined as an annual exacerbation rate of ≥2 episodes per year.²¹ Smoking status was categorized as never, ever, or current smoker, and secondhand-smoke (SHS) exposure was recorded as present or absent. Anxiety and depression were measured using the 2-item Generalized Anxiety Disorder (GAD-2)²² and the 2-item Patient Health Questionnaire (PHQ-2) scales,²³ respectively, both of which have shown good reliability and validity.

Statistical Analysis

Data analysis was performed using SPSS Statistics for Windows, version 26.0 (IBM Corp., Armonk, NY, USA). Categorical variables were presented as counts and percentages, whereas continuous variables with normal distribution were expressed as means and standard deviations (SD). The Kolmogorov–Smirnov test was used to assess normality of continuous variables. Chi-square tests were applied to categorical variables, and analysis of variance (ANOVA) or independent t-tests were used for continuous variables to assess group differences. Pearson correlation coefficients were calculated to examine bivariate relationships between continuous variables.

Based on the analysis of the prerequisite assumptions, although there is a statistically significant linear relationship between BCSS and FOMOS (regression coefficient B = 0.061, p = 0.008), there are certain deviations from the model assumptions: Regarding independence, the Durbin-Watson (D-W) value is 1.709, which is close to 2, indicating that the residuals are largely free from severe autocorrelation, thus satisfying the independence assumption. In terms of normality, although the strict Shapiro–Wilk (S-W) test indicates that the data is non-normal (p < 0.001), the absolute values of skewness are less than 3 and kurtosis are less than 10, meaning the data can be approximately accepted as basically normally distributed; furthermore, linear regression exhibits robustness to normality under large sample sizes. However, concerning the homogeneity of variance, Levene’s test reveals significant heteroscedasticity (F = 2.052, p = 0.005), meaning that the fluctuation amplitude of BCSS residuals is inconsistent across different levels of FOMOS. This violates the homoscedasticity assumption, which directly affects the accuracy of the model’s standard errors and hypothesis testing. In summary, although a linear regression equation can be established between the two variables, given the presence of heteroscedasticity, this study employed the robust standard error method in OLS regression for correction to ensure the reliability of the linear relationship inference.

The OLS regression model included FoMO score as the independent variable and BCSS score as the dependent variable, with adjustment for BMI, exacerbation phenotype, gender, marital status, education level, daily short-video exposure duration, smoking status, secondhand-smoke exposure, comorbidity burden (FCI score), and symptoms of anxiety and depression. Multicategory variables (BMI, education level, smoking status, and daily short-video exposure duration) were entered as indicator (dummy) variables with explicit reference categories.

Results

A total of 207 patients were included in this study (74.7% of the screened participants). Among these, 107 were directly diagnosed by physicians. Figure 1 illustrates the screening and recruitment process.

Figure 1.

Flowchart of patient recruitment and exclusion.

Notes: Initially, 277 COPD patients were screened. After excluding 23 individuals with language or hearing impairments, 254 patients remained. Subsequently, 28 patients with pneumonia, bronchiectasis, or other pulmonary comorbidities were excluded, leaving 226 patients. Finally, 19 patients who experienced acute exacerbation within the past 4 weeks were excluded, yielding a final sample of 207 eligible participants for analysis.

Abbreviation: COPD, chronic obstructive pulmonary disease.

Table 1 presents the baseline characteristics of the 207 participants and the univariate associations with BCSS scores. Most participants were male (55.07%), of Han ethnicity (89.37%), married (66.67%), rural residents (68.60%), and never-smokers (69.08%); 72.95% reported no secondhand-smoke exposure. The most common education category was no formal education (51.21%). The univariate results are presented in Table 1. BMI was associated with BCSS score (F = 3.441, p = 0.034), whereas the exacerbation phenotype was not statistically significant in the univariate comparison (t = −1.772, p = 0.078).

Table 1.

Baseline Characteristics of Participants and Univariate Associations with BCSS (n=207)

Variables	N (%)	BCSS	F/t	p
Age/year
40–60	101 (48.79)	7.81±2.25	−0.311	0.756
61–81	106 (51.21)	7.91±2.23
Gender
Male	114 (55.07)	8.08±1.94	1.552	0.123
Female	93 (44.93)	7.58±2.56
BMI/(kg/m2)
<18.5	20 (9.66)	9.00±2.25	3.441*	0.034
18.5~23.9	105 (50.72)	7.59±2.27
≥24.0	82 (39.61)	7.91±2.14
Disease duration/year
<3	63 (30.43)	7.73±2.32	−0.529	0.598
≥3	144 (69.57)	7.91±2.22
Comorbidity
<2	107 (51.69)	7.98±2.22	0.836	0.404
≥2	100 (48.31)	7.72±2.27
Exacerbation phenotype
0~1	74 (35.75)	7.49±1.92	−1.772	0.078
≥2	133 (64.25)	8.06±2.39
Race
Han	185 (89.37)	7.90±2.21	0.784	0.434
Other	22 (10.63)	7.50±2.58
Residence
Rural	142 (68.60)	7.75±2.26	1.029	0.305
Urban	65 (31.40)	8.09±2.20
Marital status
Unmarried	69 (33.33)	7.96±2.32	0.459*	0.047
Married	138 (66.67)	7.80±2.21
Smoking
Never smoking	143 (69.08)	7.84±2.38	0.094	0.910
Ever smoking	41 (19.81)	7.80±2.09
Current smoking	23 (11.11)	8.04±1.58
Secondhand smoke (SHS) exposure
No	151 (72.95)	7.91±2.25	0.549	0.584
Yes	56 (27.05)	7.71±2.25
Education level
No formal education	106 (51.21)	7.55±2.37	2.299	0.079
Primary education	40 (19.32)	8.20±1.95
Junior secondary education	36 (17.39)	8.56±1.89
Post-secondary education	25 (12.08)	7.60±2.42
Daily duration of short-form video viewing/hours
0–2	110 (53.2)	7.55±2.17	2.811*	0.027
2–4	39 (18.8)	8.15±2.76
4–6	24 (11.6)	7.75±2.17
6–8	22 (10.6)	9.18±1.22
≥8	12 (5.8)	7.42±1.88

Note: * p<0.05.

Table 2 presents the descriptive statistics (mean ± standard deviation) of continuous variables and their Pearson correlation coefficients with BCSS. The mean BCSS score was 7.86 ± 2.24, and the mean FoMO score was 12.97 ± 5.05. FoMO was significantly and positively correlated with BCSS (r = 0.185, P < 0.01), as were anxiety (r = 0.287, P < 0.01) and depression (r = 0.238, P < 0.01), while the FCI score (2.54 ± 1.31) showed no significant correlation with BCSS (r = −0.021). Overall, among the psychological variables, FoMO, anxiety, and depression were all significantly and positively associated with BCSS, with anxiety exhibiting the strongest correlation, whereas the FCI score did not demonstrate a significant.

Table 2.

Pearson Correlation Coefficients Between BCSS and Other Continuous Variables

Variables	M±SD	BCSS
BCSS	7.86±2.24	1
Fear of missing out	12.97±5.05	0.185**
FCI score	2.54±1.31	−0.021
Anxiety	1.81±1.26	0.287**
Depression	1.61±1.20	0.238**

Note: ** p<0.01.

Table 3 presents the result of OLS model. The results showed that the overall model was statistically significant (F(19, 187) = 4.108, p < 0.001), with an R-squared value of 0.242, indicating that the independent and control variables explained 24.2% of the variance in BCSS. Furthermore, the omitted variable test (Ramsey reset test, p = 0.240) indicated that the model did not omit any important explanatory variables. After controlling for other confounding factors, the core independent variable FOMOS had a significant positive effect on BCSS (B = 0.079, Beta = 0.239, t = 3.057, p = 0.002 < 0.01); that is, for every one-unit increase in the FOMOS score, the BCSS score increased by an average of 0.079 units. Among the control variables, Anxiety (B = 0.321, p = 0.036 < 0.05), daily short-form video usage duration of 6–8 hours (B = 1.507, p = 0.008 < 0.01), and BMI < 18.5 (B = 1.191, p = 0.024 < 0.05) also exerted a significant positive impact on BCSS; whereas the remaining control variables, including FCI score, Depression, education level, exacerbation phenotype, marital status, gender, smoking and passive smoking status, and BMI ≥ 24.0, did not show a statistically significant effect on BCSS. Additionally, this analysis employed the robust standard error method to effectively address potential heteroscedasticity issues, thereby ensuring the reliability of the model’s inferences.

Table 3.

OLS Regression Analysis of the Association Between FoMO and Respiratory Symptoms (n=207)

Variables	Unstandardized	Standardized	S.E	t	p	95% CI
Constant	5.456	–	0.816	6.686	< 0.001**	3.846 ~ 7.066
Fear of missing out	0.079	0.239	0.026	3.057	0.002**	0.028 ~ 0.129
BMI (Kg/m2)
18.5–23.9 (Reference)
<18.5	1.191	0.157	0.528	2.255	0.024*	0.149 ~ 2.233
≥24.0	0.411	0.090	0.303	1.357	0.175	−0.187 ~ 1.008
Exacerbation phenotype
0–1 (Reference)
≥2	0.577	0.124	0.313	1.845	0.065	−0.040 ~ 1.195
Gender
Male (Reference)
Female	−0.290	−0.064	0.312	−0.929	0.353	−0.905 ~ 0.325
Marital status
Unmarried (Reference)
Married	−0.627	−0.132	0.353	−1.775	0.076	−1.324 ~ 0.070
Education level
No formal (Reference)
Primary	0.184	0.032	0.473	0.389	0.698	−0.749 ~ 1.117
Junior	0.605	0.102	0.505	1.197	0.231	−0.392 ~ 1.601
Post	−0.799	−0.116	0.638	−1.252	0.210	−2.057 ~ 0.459
Daily duration of short-form video exposure
0–2 (Reference)
2–4	0.347	0.061	0.495	0.701	0.483	−0.630 ~ 1.325
4–6	0.332	0.047	0.590	0.563	0.574	−0.832 ~ 1.496
6–8	1.507	0.207	0.568	2.654	0.008**	0.387 ~ 2.627
≥8	−0.478	−0.050	0.660	−0.724	0.469	−1.780 ~ 0.824
Smoking status
Never (Reference)
Ever	−0.375	−0.067	0.409	−0.916	0.359	−1.182 ~ 0.432
Current	−0.281	−0.039	0.460	−0.612	0.541	−1.188 ~ 0.626
Passive smoking
No (Reference)
Yes	0.210	0.042	0.396	0.530	0.596	−0.572 ~ 0.992
FCI score	0.146	0.085	0.163	0.897	0.370	−0.175 ~ 0.467
Anxiety	0.321	0.180	0.153	2.103	0.036*	0.020 ~ 0.622
Depression	0.196	0.105	0.169	1.155	0.248	−0.138 ~ 0.530
R 2	0.242
Adjusted R 2	0.165
F	F (19,187)=4.108, p < 0.001
D-W value	1.709

Note: Dependent variable = BCSS, * p<0.05 ** p<0.01;

Figure 2 shows the regression coefficients and their 95% confidence intervals for the multivariable model, with reference categories defined in the figure note. The confidence intervals of four predictors did not cross the null line: daily short-form video viewing of 6–8 h (β = 1.507, 95% CI: 0.387 to 2.627), BMI < 18.5 (β = 1.191, 95% CI: 0.149 to 2.233), anxiety (β = 0.321, 95% CI: 0.020 to 0.622), and FoMO (β = 0.079, 95% CI: 0.028 to 0.129, p = 0.002); the intervals for all other predictors crossed zero.

Figure 2.

Forest plot of the adjusted association between FOMOS and respiratory symptoms.

Notes: Estimates and 95% confidence intervals were derived from a multivariable regression model after adjusting for BMI, exacerbation phenotype, sex, marital status, education level, daily short-form video exposure duration, smoking status, passive smoking, FCI score, anxiety, and depression. Reference groups for categorical variables are indicated in the figure.

Abbreviations: FOMOS, fear of missing out scale; BMI, body mass index; FCI, functional comorbidity index; CI, confidence interval.

Discussion

The present study identified a significant positive association between FoMO and respiratory symptom burden in patients with COPD, even after adjusting for frequent exacerbation phenotypes and sociodemographic factors. This finding suggests that psychological factors, particularly general FoMO, may play an important role in symptom perception and reporting in this population.

Our results are consistent with emerging evidence indicating that psychological traits and digital behaviors can influence symptom experience in chronic respiratory diseases. The theoretical framework linking FoMO to respiratory symptoms can be understood through multiple pathways.

First, FoMO may represent a form of chronic social stress characterized by persistent anxiety about missing rewarding experiences. Although these mediators were not measured in the present study, prior literature suggests that such chronic stress may activate the HPA axis and sustain physiological arousal,^11,24 potentially exacerbating respiratory symptoms through elevated cortisol and sympathetic nervous system activation. These pathways are therefore presented as hypotheses derived from prior literature rather than as mechanisms demonstrated by this study.

Second, the cognitive-behavioral model of breathlessness suggests that anxiety and catastrophic cognitions about symptoms can create a positive feedback loop, leading to heightened somatic awareness and increased symptom perception;^25,26 FoMO, as a form of social anxiety, may similarly amplify symptom perception, although this mechanism was not measured in the present study.

After adjustment for the covariates included in the specified model, FoMO remained associated with BCSS scores; however, we do not claim that this association is independent of unmeasured confounders or that it provides additive value.

Daily short-form video exposure duration did not show a monotonic association with BCSS score in the multivariable model, although the 6–8 h/day category was significantly associated with higher BCSS (B = 1.507, 95% CI: 0.387–2.627, p = 0.008). This pattern was also observed in the univariate analysis, in which the 6–8 h group reported the highest BCSS scores (9.18 ± 1.22). The absence of a monotonic dose–response relationship — with the ≥8 h category showing no elevation (B = −0.478, p = 0.469) — suggests that the association between exposure duration and symptom severity is not linear, and may reflect reverse causation (patients with more severe symptoms curtailing their viewing), the sedentary context of prolonged viewing, or imprecision in the extreme category, which contained only 11 participants.

Most sociodemographic variables were not significantly associated with BCSS in the multivariable model. The statistically significant predictors in the multivariable model were the underweight BMI (<18.5 kg/m²; B = 1.191, 95% CI: 0.149–2.233, p = 0.024) and anxiety (B = 0.321, 95% CI: 0.020–0.622, p = 0.036). Of note, the underweight category, which had the highest crude BCSS scores (9.00 ± 2.25, univariate p = 0.034), remained significantly associated with higher BCSS after adjustment, indicating an independent effect beyond covariates. In contrast, the overweight/obese category (≥24.0 kg/m²), despite showing a modest crude mean (7.91 ± 2.14), was not significant in the multivariable model (B = 0.411, p = 0.175), suggesting that its crude association was largely explained by other covariates such as exacerbation phenotype and psychosocial factors. Similarly, depression, which correlated with BCSS in the bivariate analysis (r = 0.238, p < 0.01), did not retain significance in the multivariable model (B = 0.196, p = 0.248), indicating substantial overlap between the variance of depression and that of anxiety and FoMO. The sample was predominantly composed of never-smokers (69.08%), and the BCSS measures subjective symptom experience, which may be influenced by psychological as well as physiological factors.

Finally, the modest explanatory power of the model (adjusted R² = 0.165) implies that other unmeasured factors — such as physiological parameters (eg, lung function, oxygenation), social support, coping strategies, and the specific types of short-form video content viewed — may contribute substantially to symptom burden. Future studies should incorporate these variables, preferably with longitudinal designs capable of establishing temporal precedence, to build a more comprehensive model.

Conclusion

This exploratory cross-sectional study examined the association between general FoMO and respiratory symptoms among patients with COPD who use short-video platforms, using validated scales and adjusting for multiple covariates. Among the selected patients, higher general FoMO scores were weakly associated with higher self-reported BCSS scores after adjustment for the covariates included in the specified model. Temporality, causality, clinical significance, and independence from major unmeasured confounders remain unresolved.

The findings are preliminary and do not support routine integration of FoMO assessment into COPD management at this time. Longitudinal studies are needed to establish temporal direction, and intervention studies are needed to determine whether reducing FoMO improves respiratory symptoms or quality of life.

Despite these contributions, this study had several limitations. The cross-sectional design inherently restricts causal interpretation, while convenience sampling from a single geographic region may affect generalizability. The use of convenience sampling — necessitated by the absence of a comprehensive sampling frame across the three participating hospitals — may limit the generalizability of the findings to other COPD populations or geographic regions. Although clinically relevant covariates were included, the use of self-reported measures for both exposure and outcome may have introduced bias, and the modest explanatory power of the model suggests that important predictors remain unaccounted for. The study did not analyze short-video content and thus cannot adequately explain the specific mechanisms by which FoMO affects respiratory symptoms. Future studies should prioritize longitudinal designs to elucidate the temporal and causal relationships between FoMO and symptom progression, and incorporate objective measures of both respiratory function and digital engagement.

Funding Statement

This work was supported by the Special Talent Launch Project of Ningxia Medical University [Grant Number: XT2024008].

Data Sharing Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Author Contributions

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

Disclosure

The author(s) report no conflicts of interest in this work.