We agreed with Professor Brett D. Thombs for examining the impact of depression screening through meticulously designed clinical trials, emphasizing three key criteria: (1) random assignment prior to screening, (2) exclusion of patients already diagnosed with depression or undergoing treatment, and (3) equitable depression care to both screened and unscreened individuals.1 However, over the past two decades, only a few studies met these conditions, often with limited sample sizes and among specific groups.2
Our emulation target trial addressed the second and third criteria, albeit facing challenges inherent in observational studies.3 The Adult Preventive Health Checkup program, a free and optional service, requires active participation, influenced by socioeconomic factors. Screened individuals were more likely suburban/rural residents with middle-class income, visiting outpatient services more. Though differences between groups existed, they were minor (standardized mean differences < 0.15). Despite our efforts to mitigate discrepancies using propensity scores based on over 30 variables, the inherent limitations in observational studies, lacking random assignment, may compromise causal inferences regarding depression screening effects. Nonetheless, given the impracticality of conducting large clinical trials, emulation target trials represent a pragmatic approach.4
The intervention involves health checkups inclusive of depression screening, prompting scrutiny regarding intervention comparability. These checkups predominantly focused on physical assessments, indicating that if depression screening yields no benefits on depression outcomes, neither should the health checkups. Conversely, any observed benefits in depression outcomes would likely stem from the screening process itself. Concerns also arise regarding intervention comparability due to potentially repeated screenings in the screened group versus not in the unscreened group. If benefits in depression outcomes are influenced by higher healthcare utilization among screened individuals, we would expect a corresponding increase in psychiatric hospitalization rates instead of a decline. Hence, increased healthcare utilization cannot fully explain our findings.
The direct effect of depression screening is to identify undetected cases, potentially leading to improved symptoms with adequate treatment. The increase in newly treated depression cases among the screened group, notably with a younger age at initial treatment compared to the unscreened group, implies that screening facilitates early detection. While our study couldn't measure symptom severity directly, reduced psychiatric hospitalization rates indicated that the average symptom severity was improved, supporting the effectiveness of screening.
In conclusion, our study supports the association of depression screening with identifying undetected cases, initiating timely treatment, and potentially ameliorating symptoms. However, further large-scale, well-designed clinical trials are warranted to confirm its effects.
Declaration of interests
We declare no conflict of interest for this study.
Acknowledgements
Funding: This work was partly supported by the National Health Research Institutes, Taiwan (CG-111-GP-01 and CG-112-GP-01, PI: CSW). The funders had no role in study design, data collection, data analysis, interpretation, writing of the report.
References
- 1.Thombs B.D., Ziegelstein R.C., Roseman M., Kloda L.A., Ioannidis J.P.A. There are no randomized controlled trials that support the United States Preventive Services Task Force guideline on screening for depression in primary care: a systematic review. BMC Med. 2014;12:13. doi: 10.1186/1741-7015-12-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Thombs B.D., Markham S., Rice D.B., Ziegelstein R.C. Does depression screening in primary care improve mental health outcomes? BMJ. 2021;374 doi: 10.1136/bmj.n1661. [DOI] [PubMed] [Google Scholar]
- 3.Chen Y.-L., Wu M.-S., Wang S.-H., et al. Effectiveness of health checkup with depression screening on depression treatment and outcomes in middle-aged and older adults: a target trial emulation study. Lancet Reg Health Western Pac. 2024;43:100978. doi: 10.1016/j.lanwpc.2023.100978. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Hernán M.A., Robins J.M. Using big data to emulate a target trial when a randomized trial is not available. Am J Epidemiol. 2016;183(8):758–764. doi: 10.1093/aje/kwv254. [DOI] [PMC free article] [PubMed] [Google Scholar]