The relationship between public risk preference and the underuse or overuse of preventive health services in the information age.

The underuse or overuse of preventive health services by individuals is an outward behavioural reflection of their attitude towards disease risk, and they are strongly influenced by their information-acquisition ability. Therefore, we try to explore the relationship among the public risk preference, information-acquisition ability and underuse or overuse of preventive health services, in order to provide decision-making basis in the Information Age. The survey surveyed 2,211 respondents aged ≥ 18 in China from September to December 2019. Taking cancer screening as an example, the multiple price list (MPL) test and item response theory (IRT) model were used to measure individual risk preference and information-acquisition ability. The Logit model and Tobit model were used to estimate the relationship between risk preference, information-acquisition ability and underuse or overuse of preventive health services. Risk-seeking individuals were more likely to underuse preventive health services, while risk-averse individuals were more likely to overuse such services. Information-acquisition ability may improve the underuse of preventive health services in risk-seeking individuals but exacerbate the overuse of preventive health services in risk-averse individuals. Among the investigated information channels, the Internet is the most effective way for the public to obtain information. It is necessary to change the public's incorrect perception of disease risks and risks associated with preventive health services. In the rapid development of the Information Age, improving public information-acquisition ability is a practicable way to correct the negative relationship between risk preference and individuals' underuse or overuse of preventive health services.

Exclusive breastfeeding and its association with intimate partner violence during pregnancy: analysis from Pakistan demographic and health survey.

BACKGROUND: Intimate partner violence (IPV) is a global social issue and increasingly asks for the attention of policymakers. IPV is one of the main factors that affect the health of pregnant women and their infants during pregnancy and after childbirth; it will not only cause direct harm to women themselves but also reduce women's exclusive breastfeeding (EBF) behavior and pose a threat to newborn health. Existing facts on the association between IPV and EBF in the Pakistani context are negligible and incomplete to an enduring measure of IPV practice. To this effect, the present study aims to investigate the relationship between EBF and IPV practiced during the prenatal period and post-delivery. METHODS: The statistics study has drawn from the Pakistan Demographic and Health Survey (PDHS) 2018. A total of 1191 breastfeeding females aged 15-49 with children under 6 months were selected for the present study. T-test or chi-square test of Univariate test of hypothesis; Logistic regression model was utilized to explore the potential impact of IPV on female exclusive breastfeeding from three dimensions of physical, sexual and psychological violence, to provide data support for the Pakistani government to formulate policies to promote female EBF. All investigations have been performed in STATA software 16.0 (Stata Corp, College Station, TX, USA) at 95% confidence interval. RESULTS: Among the 1191 participants, 43.6% (520 / 1191) of the females were EBF, while the rates of physical, sexual, and emotional IPV were 47.44%, 30.23%, and 51.72%, respectively. Logistic regression analysis showed that females who have experienced physical IPV were 32% less likely to be exclusively breastfed (aOR = 0.68; 95% CI; 0.490, 0.980; P < 0.05), the chances of EBF were reduced by 22% in women who experienced IPV (aOR = 0.78; 95 CI; 0.55, 1.00; P < 0.05), females who experienced emotional IPV were 31% less probable to exclusively breastfed (aOR = 0.69; 95% CI; 0.47, 0.92; P < 0.05). CONCLUSIONS: This study determines the adverse effects of sexual and psychological violence on EBF practices in women. Policymakers in Pakistan should actively implement assistance programs to reduce IPV, emphasize monitoring women's experiences of IPV before and after giving birth, and encourage women to break the "culture of silence" when they experience IPV to maximize their access to assistance.

Stable n-Type Perylene Derivative Ladder Polymer with Antiambipolarity for Electrically Reconfigurable Organic Logic Gates.

Organic electrochemical transistors (OECTs) are one of the promising building blocks to realize next-generation bioelectronics. To date, however, the performance and signal processing capabilities of these devices remain limited by their stability and speed. Herein, the authors demonstrate stable and fast n-type organic electrochemical transistors based on a side-chain-free ladder polymer, poly(benzimidazoanthradiisoquinolinedione). The device demonstrated fast normalized transient speed of 0.56 ± 0.17 ms um-2 and excellent long-term stability in aqueous electrolytes, with no significant drop in its doping current after 50 000 successive doping/dedoping cycles and 2-month storage at ambient conditions. These unique characteristics make this polymer especially suitable for bioelectronics, such as being used as a pull-down channel in a complementary inverter for long-term stable detection of electrophysiological signals. Moreover, the developed device shows a reversible anti-ambipolar behavior, enabling reconfigurable electronics to be realized using a single material. These results go beyond the conventional OECT and demonstrate the potential of OECTs to exhibit dynamically configurable functionalities for next-generation reconfigurable electronics.

The organization-level and physician-level factors associated with primary care physicians' confidence in pandemic response: A multilevel study in China.

Primary care physicians (PCPs) suffered from heavy workloads and health problems during COVID-19 pandemics, and building their confidence in pandemic response has great potential to improve their well-being and work performance. We identified the organizational factors associated with their confidence in pandemic response and proposed potential management levers to guide primary care response for the pandemic. We conducted a cross-sectional survey with 224 PCPs working in 38 community health centers in China. Guided by self-efficacy theory, organization-level factors (organizational structure and organizational culture) and physician-level factors (job skill variety, perceived organizational support, work-family conflict, and professional fulfillment) were selected, and two-level ordinal logit models were built to examine their association with PCPs' confidence in pandemic response. We found that hierarchical culture (OR = 3.51, P<0.05), perceived organizational support (OR = 2.36, P<0.05), job skill variety (OR = 1.86, P<0.05), and professional fulfillment (OR = 2.26, P<0.05) were positively associated with PCPs' confidence in pandemic response. However, the influence of organization structure and work-family conflict seemed limited. The study not only increases our understanding of the influence of organizational context on PCPs' pandemic response confidence, but also points out potential management levers for front-line primary care managers to enhance primary care pandemic response capacity.

Using explainable machine learning to uncover the kinase-substrate interaction landscape.

MOTIVATION: Phosphorylation, a post-translational modification regulated by protein kinase enzymes, plays an essential role in almost all cellular processes. Understanding how each of the nearly 500 human protein kinases selectively phosphorylates their substrates is a foundational challenge in bioinformatics and cell signaling. Although deep learning models have been a popular means to predict kinase-substrate relationships, existing models often lack interpretability and are trained on datasets skewed toward a subset of well-studied kinases. RESULTS: Here we leverage recent peptide library datasets generated to determine substrate specificity profiles of 300 serine/threonine kinases to develop an explainable Transformer model for kinase-peptide interaction prediction. The model, trained solely on primary sequences, achieved state-of-the-art performance. Its unique multitask learning paradigm built within the model enables predictions on virtually any kinase-peptide pair, including predictions on 139 kinases not used in peptide library screens. Furthermore, we employed explainable machine learning methods to elucidate the model's inner workings. Through analysis of learned embeddings at different training stages, we demonstrate that the model employs a unique strategy of substrate prediction considering both substrate motif patterns and kinase evolutionary features. SHapley Additive exPlanation (SHAP) analysis reveals key specificity determining residues in the peptide sequence. Finally, we provide a web interface for predicting kinase-substrate associations for user-defined sequences and a resource for visualizing the learned kinase-substrate associations. AVAILABILITY AND IMPLEMENTATION: All code and data are available at https://github.com/esbgkannan/Phosformer-ST. Web server is available at https://phosformer.netlify.app.

Informatic challenges and advances in illuminating the druggable proteome.

The understudied members of the druggable proteomes offer promising prospects for drug discovery efforts. While large-scale initiatives have generated valuable functional information on understudied members of the druggable gene families, translating this information into actionable knowledge for drug discovery requires specialized informatics tools and resources. Here, we review the unique informatics challenges and advances in annotating understudied members of the druggable proteome. We demonstrate the application of statistical evolutionary inference tools, knowledge graph mining approaches, and protein language models in illuminating understudied protein kinases, pseudokinases, and ion channels.

New evidence on supplier-induced demand in China's public tertiary hospitals: is the cost of hospitalization higher in the off-season?

Supplier-induced demand (SID) is a long-standing concern in health economics and health system studies; however, empirical evidence on SID-critical to the development of health policy-is difficult to obtain, especially from China. This study, therefore, aims to add new evidence on SID in China's public tertiary hospitals and facilitates the development of evidence-based health policies in China and other countries with similar healthcare systems. For this study, we used patient-level electronic medical records (EMRs) collected from the information systems of tertiary hospitals in a western province in China. From 11 tertiary hospitals, we collected 274,811 hospitalization records dated between 15 February and 30 November 2019. Total expenditure on hospitalization and length of admission of each patient were the primary metrics for measuring SID. We constructed a character indicator to measure the high-season or off-season status of hospitals, and log-linear estimations were applied to estimate the "off-season effect" on hospitalized expenditures and length of admission. We find that the cost of hospitalization is indeed higher in the off-season in China's public tertiary hospitals; specifically, expenditures for patients admitted in the off-season increased by an average of 5.3-7.9% compared to patients admitted in the peak season, while the length of admission in the hospital increased by an average of 6.8% to 10.2%. We also checked the robustness of our findings by performing subgroup analyses of EMRs in the city-level hospitals and surgical group. We name this phenomenon the "hospital off-season effect" and suggest that the main reason for it is inappropriate financial incentives combined with a Fee-For-Services payment method. We suggest that China should work to reform inappropriate financial incentives in public hospitals to eliminate SID by changing its payment and financing compensation system.

Income loss and subsequent poor psychological well-being among the Chinese population during the early COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has had major ramifications for health and the economy at both the individual and collective levels. This study examined exogenous negative changes in household income and their implications on psychological well-being (PWB) among the Chinese population during the COVID-19 pandemic. METHODS: Data were drawn from the early China COVID-19 Survey, a cross-sectional anonymous online survey administered to the general population in China. Self-reported PWB was measured using a 5-point Likert scale with five questions related to the participants' recent psychological state. Hierarchical multiple linear regression was employed to examine whether income loss during the COVID-19 pandemic was associated with poor psychological health. RESULTS: This study included 8,428 adults, of which 90% had suffered from a moderate or severe loss of household income due to the early COVID-19 pandemic. Those who had experienced moderate or severe loss of income scored significantly lower on psychological well-being than those who did not experience income loss (19.96 or 18.07 vs. 21.46; P < 0.001); after controlling for confounders, income loss was negatively associated with PWB scores (moderate income loss: B = - 0.603, P < 0.001; severe income loss: B = - 1.261, P < 0.001). An interaction effect existed between the degree of income loss and pre-pandemic income groups. Specifically, participants in the middle-income group who had suffered severe income loss scored the lowest on PWB (B = - 1.529, P < 0.001). There was also a main effect on income loss, such that participants with varying degrees of income loss differed across five dimensions, including anhedonia, sleep problems, irritability or anger, difficulty with concentration, and repeated disturbing dreams related to COVID-19. CONCLUSIONS: Income loss during the pandemic has had detrimental consequences on psychological well-being, and the magnitude of the impact of income loss on psychological well-being varied according to previous income levels. Future policy efforts should be directed toward improving the psychological well-being of the economically vulnerable and helping them recover from lost income in the shortest time possible.

The Impact of Physician-Patient Gender Match on Healthcare Quality: An Experiment in China.

Despite growing evidence of gender disparities in healthcare utilization and health outcomes, there is a lack of understanding of what may drive such differences. Designing and implementing an experiment using the standardized patients' approach, we present novel evidence on the impact of physician-patient gender match on healthcare quality in a primary care setting in China. We find that, compared with female physicians treating female patients, the combination of female physicians treating male patients resulted in a 23.0 percentage-point increase in correct diagnosis and a 19.4 percentage-point increase in correct drug prescriptions. Despite these substantial gains in healthcare quality, there was no significant increase in medical costs and time investment. Our analyses suggest that the gains in healthcare quality were mainly attributed to better physician-patient communications, but not the presence of more clinical information. This paper has policy implications in that improving patient centeredness and incentivizing physicians' efforts in consultation (as opposed to treatment) can lead to significant gains in the quality of healthcare with modest costs, while reducing gender differences in care.

Can digital finance mitigate trust issues for chronically ill patients because of relative deprivation of income?

Objective: The relative deprivation of income among chronically ill patients may create a perception of inequity in their access to quality healthcare, which may lead to a decline in patients' trust and further increases the burden of chronic diseases. Digital finance could be the antidote. To promote equity in healthcare delivery, this study explores the mitigating effect of digital finance by elucidating the relationship between relative deprivation of income and chronically ill patients' trust. Methods: Using data from the China Family Panel Study, a Poisson regression model was applied to assess the effect of relative deprivation of income on chronically ill patients' trust. A marginal effect analysis was used to verify the effect and a two-stage least squares method was used to test robustness. Results: Chronically ill patients' trust was at a medium level (5.98 ± 2.05). Relative deprivation of income significantly reduced patients' trust (ß=-0.056, p < 0.1). The digital finance had a positive effect on patients' trust (ß=0.035, p < 0.01) and alleviated the negative effect of relative deprivation of income on patients' trust (ß=0.105, p < 0.01). The instrumental variable estimation results confirmed the robustness of the benchmark regression results. Conclusions: The inequity resulting from relative deprivation of income undermines patients' trust. Digital finance has a long-term effect on alleviating perception of inequity among chronically ill patients. The government should promote the integration of digital finance and smart healthcare to enhance patients' trust and contribute to equality in healthcare delivery. Limitations include self-reported data and an insufficient correlation between selected indicators and healthcare services.

The role of pet attachment in alleviating the negative effects of loneliness on a health-promoting lifestyle: An empirical study based on threshold effects for pet owners.

BACKGROUND: A health-promoting lifestyle is acknowledged as a 'positive ageing' strategy for older people. The inevitable decline in their social networks may lead to loneliness and subsequently damage their health-promoting lifestyle. Therefore, pet owning has become a popular way for them to alleviate loneliness. However, the attachment resulting from pet ownership may either facilitate or impede older people's ability to counteract the negative effect of loneliness on health-promoting lifestyles, and this effect may only be observed when pet owners have limited human confidants. OBJECTIVES: To identify the role of pet attachment in alleviating the negative impact of loneliness on a health-promoting lifestyle and its supplementary role in the deficiency of social relationships by analysing the correlation mechanism between pet attachment, loneliness and a health-promoting lifestyle. METHODS: Self-report questionnaires were sent to 879 older people (aged ≥60) with pets in China by using a multistage stratified random sampling method. Cross-sectional threshold regression models were established to analyse the nonlinear effects of loneliness on a health-promoting lifestyle and the different threshold effects among different social relationship levels. RESULTS: A single threshold value (0.444) was drawn to determine the action mode of pet attachment on the negative relationship between loneliness and a health-promoting lifestyle. When the level of pet attachment exceeded 0.444, the inhibition of loneliness on a health-promoting lifestyle decreased significantly. Additionally, this threshold effect was evident among older people at different levels of social relationships. CONCLUSIONS: The negative effect of loneliness on a health-promoting lifestyle is alleviated by the single threshold effect of pet attachment. Pet-owner relationships can compensate for a lack of social relationships to some extent and alleviate both an individual's loneliness and its negative effect on a health-promoting lifestyle. IMPLICATIONS FOR PRACTICE: To alleviate loneliness and promote healthy ageing in older people who lack social relationships, the tailored pet intervention strategies that prioritize 'one health' at the animal-ecosystem interface that consider their different individual levels of social relationship should be developed.

Catastrophic health expenditure of households with hypertension: a comparative study in China.

Objectives: The aim of this study was to understand the impact of multimorbidity on catastrophic health expenditures for people with hypertension. Methods: Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) in 2018, 8,342 adults were included in our analysis. Propensity score matching method was used to compare the risk of catastrophic health expenditures between the hypertension patients (treatment group) and those without any chronic disease (control group) in middle-aged and older adults. Patients with hypertension were also divided into two groups: only hypertension and multimorbidity. Results: Hypertension increased the likelihood of CHE by 11.3% in older adults. Further analysis showed that hypertension alone does not increase the risk of CHE, and the risk of CHE in hypertension patients with multimorbidity was 12.9% higher than those without chronic disease. Conclusion: Our study highlights the importance of healthy management of patients with only hypertension and preventing them from developing multimorbidity.

Evaluating the Impact of COVID-19 on Hospital Profit Compensation Activities: A Difference-in-Differences Event Study Analysis in China.

The impact of the 2019 coronavirus disease (COVID-19) pandemic is still being revealed, and little is known about the effect of COVID-19-induced outpatient and inpatient losses on hospital operations in many counties. Hence, we aimed to explore whether hospitals adopted profit compensation activities after the 2020 first-wave outbreak of COVID-19 in China. A total of 2,616,589 hospitalization records from 2018, 2019, and 2020 were extracted from 36 tertiary hospitals in a western province in China; we applied a difference-in-differences event study design to estimate the dynamic effect of COVID-19 on hospitalized patients' total expenses before and after the last confirmed case. We found that average total expenses for each patient increased by 8.7% to 16.7% in the first 25 weeks after the city reopened and hospital admissions returned to normal. Our findings emphasize that the increase in total inpatient expenses was mainly covered by claiming expenses from health insurance and was largely driven by an increase in the expenses for laboratory tests and medical consumables. Our study documents that there were profit compensation activities in hospitals after the 2020 first-wave outbreak of COVID-19 in China, which was driven by the loss of hospitalization admissions during this wave outbreak.

Association Between Multiple Chronic Conditions and Depressive Symptoms Among Older Adults in China: Evidence From the China Health and Retirement Longitudinal Study (CHARLS).

Objectives: The purpose of this study was to explore the association between multiple chronic conditions (MCCs) and depressive symptoms among older adults in China. Methods: We used the fourth round of data from the China Health and Retirement Longitudinal Study, and included 9789 older adults aged 60 years old and above. Results: Compared with the older adults without chronic disease, older adults with MCCs and those with one chronic disease had a high risk of depression (MCCs: OR-adjusted: 1.55, 95% CI: 1.37 to 1.75; one chronic disease: OR-adjusted: 1.20, 95% CI: 1.05-1.37). In urban areas, the prevalence among older adults with MCCs was 2.01 times higher than that among older adults without chronic disease (OR-adjusted: 2.01, 95% CI: 1.56-2.60), while it was 1.44 times higher in rural areas (OR-adjusted:1.44, 95% CI: 1.25-1.65). Self-reported health, duration of sleep, social activities, and type of medical insurance were the influencing factors of depressive symptoms in older adults. Conclusion: This study contributed to enriching the research on the relationship between MCCs and depressive symptoms in older adults in China.

Phosformer: an explainable transformer model for protein kinase-specific phosphorylation predictions.

MOTIVATION: The human genome encodes over 500 distinct protein kinases which regulate nearly all cellular processes by the specific phosphorylation of protein substrates. While advances in mass spectrometry and proteomics studies have identified thousands of phosphorylation sites across species, information on the specific kinases that phosphorylate these sites is currently lacking for the vast majority of phosphosites. Recently, there has been a major focus on the development of computational models for predicting kinase-substrate associations. However, most current models only allow predictions on a subset of well-studied kinases. Furthermore, the utilization of hand-curated features and imbalances in training and testing datasets pose unique challenges in the development of accurate predictive models for kinase-specific phosphorylation prediction. Motivated by the recent development of universal protein language models which automatically generate context-aware features from primary sequence information, we sought to develop a unified framework for kinase-specific phosphosite prediction, allowing for greater investigative utility and enabling substrate predictions at the whole kinome level. RESULTS: We present a deep learning model for kinase-specific phosphosite prediction, termed Phosformer, which predicts the probability of phosphorylation given an arbitrary pair of unaligned kinase and substrate peptide sequences. We demonstrate that Phosformer implicitly learns evolutionary and functional features during training, removing the need for feature curation and engineering. Further analyses reveal that Phosformer also learns substrate specificity motifs and is able to distinguish between functionally distinct kinase families. Benchmarks indicate that Phosformer exhibits significant improvements compared to the state-of-the-art models, while also presenting a more generalized, unified, and interpretable predictive framework. AVAILABILITY AND IMPLEMENTATION: Code and data are available at https://github.com/esbgkannan/phosformer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tree visualizations of protein sequence embedding space enable improved functional clustering of diverse protein superfamilies.

Protein language models, trained on millions of biologically observed sequences, generate feature-rich numerical representations of protein sequences. These representations, called sequence embeddings, can infer structure-functional properties, despite protein language models being trained on primary sequence alone. While sequence embeddings have been applied toward tasks such as structure and function prediction, applications toward alignment-free sequence classification have been hindered by the lack of studies to derive, quantify and evaluate relationships between protein sequence embeddings. Here, we develop workflows and visualization methods for the classification of protein families using sequence embedding derived from protein language models. A benchmark of manifold visualization methods reveals that Neighbor Joining (NJ) embedding trees are highly effective in capturing global structure while achieving similar performance in capturing local structure compared with popular dimensionality reduction techniques such as t-SNE and UMAP. The statistical significance of hierarchical clusters on a tree is evaluated by resampling embeddings using a variational autoencoder (VAE). We demonstrate the application of our methods in the classification of two well-studied enzyme superfamilies, phosphatases and protein kinases. Our embedding-based classifications remain consistent with and extend upon previously published sequence alignment-based classifications. We also propose a new hierarchical classification for the S-Adenosyl-L-Methionine (SAM) enzyme superfamily which has been difficult to classify using traditional alignment-based approaches. Beyond applications in sequence classification, our results further suggest NJ trees are a promising general method for visualizing high-dimensional data sets.

Alignment-free estimation of sequence conservation for identifying functional sites using protein sequence embeddings.

Protein language modeling is a fast-emerging deep learning method in bioinformatics with diverse applications such as structure prediction and protein design. However, application toward estimating sequence conservation for functional site prediction has not been systematically explored. Here, we present a method for the alignment-free estimation of sequence conservation using sequence embeddings generated from protein language models. Comprehensive benchmarks across publicly available protein language models reveal that ESM2 models provide the best performance to computational cost ratio for conservation estimation. Applying our method to full-length protein sequences, we demonstrate that embedding-based methods are not sensitive to the order of conserved elements-conservation scores can be calculated for multidomain proteins in a single run, without the need to separate individual domains. Our method can also identify conserved functional sites within fast-evolving sequence regions (such as domain inserts), which we demonstrate through the identification of conserved phosphorylation motifs in variable insert segments in protein kinases. Overall, embedding-based conservation analysis is a broadly applicable method for identifying potential functional sites in any full-length protein sequence and estimating conservation in an alignment-free manner. To run this on your protein sequence of interest, try our scripts at https://github.com/esbgkannan/kibby.

Quantifying the financial impact of overuse in primary care in China: A standardised patient study.

Overuse of health care is a potential factor in explaining the rapid increase in health care expenditure in many countries; however, it is difficult to measure overuse. This study employed the novel method of using unannounced standardised patients (SPs) to identify overuse, document its patterns and quantify its financial impact on patients in primary care in China. We trained 18 SPs to present consistent cases of two common chronic diseases and recorded 492 physician-patient interactions in 63 public and private primary hospitals in a capital city in western China in 2017 and 2018. Overuse, defined as the provision of unnecessary medical tests and drugs, was identified by a panel of medical experts based on national clinical guidelines. We estimated linear regression models to investigate how hospital, physician and patient characteristics were associated with overuse and to quantify the financial impact of overuse after controlling for a series of fixed effects. We found overuse in 72.15% of the SP visits. The high prevalence of overuse was similar among public and private hospitals, low-competence and high-competence physicians, male and female physicians, junior and senior physicians and male and female patients, but it varied between patients presenting different diseases. Compared to the non-overuse group, overuse significantly increased the total cost by 117.8%, the test cost by 58.8% and the drug cost by 100.3%. The financial impact of overuse was consistent across the aforementioned hospital, physician and patient characteristics. We suggest that the overuse observed in this study is unlikely to be attributable to physician incompetence but rather to the financing framework for primary care in China. These findings illuminate the cost escalation of primary care in China, which is a form of medical inefficiency that should be urgently addressed.

Comparison of Health Care Utilization in Different Usual Sources of Care Among Older People With Cardiovascular Disease in China: Evidence From the Study on Global Ageing and Adult Health.

Objectives: To compare the health care utilization in different usual sources of care (USCs) among the elderly population with cardiovascular disease in China. Methods: Cross-sectional data for 3,340 participants aged ≥50 years with cardiovascular disease from Global AGEing and Adult Health (2010)-China were used. Using the inverse probability of treatment weighting on the propensity score with survey weighting, combined with negative binomial regression and logistic regression models, the correlation between USCs and health care utilization was assessed. Results: Patients using primary care facilities as their USC had fewer hospital admissions (IRR = 0.507, 95% CI = 0.413, 0.623) but more unmet health needs (OR = 1.657, 95% CI = 1.108, 2.478) than those using public hospitals. Patients using public clinics as their USC had higher outpatient visits (IRR = 2.188, 95% CI = 1.630, 2.939) than the private clinics' group. Conclusion: The difference in inpatient care utilization and unmet health care needs between public hospitals and primary care facilities, and the difference in outpatient care utilization between public and private clinics were significant. Using primary care facilities as USCs, particularly public ones, appeared to increase care accessibility, but it still should be strengthened to better address patients' health care needs.

Impacts of Internet Use on Chinese Patients' Trust-Related Primary Healthcare Utilization.

Background: The internet has greatly improved the availability of medical knowledge and may be an important avenue to improve patients' trust in physicians and promote primary healthcare seeking by reducing information asymmetry. However, very few studies have addressed the interactive impacts of both patients' internet use and trust on primary healthcare-seeking decisions. Objective: To explore the impact of internet use on the relationship between patients' trust in physicians and primary healthcare seeking among Chinese adults 18 years of age and older to understand the varieties of effects in different cities. Methods: Generalized linear mixed models were applied to investigate the interactive impacts of internet use and patients' trust in physicians on primary healthcare seeking using pooled data from the China Family Panel Study of 2014 to 2018. We also compared these effects based on different levels of urbanization, ages, and PHC services. Results: Overall, a higher degree of patients' trust (p < 0.001) was able to directly predict better primary healthcare seeking, and internet use significantly increased the positive effect of patients' trust on primary healthcare seeking (p < 0.001). However, the marginal effect analysis showed that this effect was related to the level of patients' trust and that internet use could reduce the positive effect of patients' trust on primary healthcare seeking when the individual had a low level of trust (≤ 3 units). Further, the heterogeneity analysis indicated that the benefits from internet use were higher in cities with high urbanization, high aging, and high PHC service levels compared to cities with low levels of these factors. Conclusions: The internet use may enhance patients' trust-related PHC utilization. However, this impact is effective only if patients' benchmark trust remains at a relatively high level. Comparatively, the role of internet use is more effective in areas with high urbanization, high aging and high PHC level. Thus, with increasing accessibility to the internet, the internet should be regulated to disseminate correct healthcare information. Moreover, in-depth integration of the internet and PHC should be promoted to provide excellent opportunities for patient participation, and different strategies should be set according to each city's characteristics.