Normalising sequence lengths using the relative duration of episodes: an application to doctoral trajectories in Germany.

To address significant variation of sequence lengths of doctoral trajectories, we propose sequence normalisation using the relative duration of episodes. We employ episode data from a panel study of doctorate holders in Germany where doctoral trajectories are measured in single months and differ in length up to several years. Utilising normalised sequences instead of absolute sequences, we are better able to identify typical trajectories. The graphical presentation of the cluster solutions more accurately depicts the underlying processes. Furthermore, it offers the possibility to define reference sequences without a fixed length. Normalising sequences instead of distances thus proves an easily implementable method to compare sequences of different lengths when the identification of patterns is a priority.

Identification and Economic Evaluation of Differentiated Thyroid Cancer Care Consumption Patterns Using Sequence Analysis.

Objectives: This study aims to assess the impact of care consumption patterns and individual characteristics on the cost of treating differentiated thyroid carcinoma (DTC), in France, with a specific emphasis on socioeconomic position. Methods: The methodology involved a net cost approach utilising cases from the EVATHYR cohort and controls from the French National Health Insurance database. Care consumption patterns were created using Optimal Matching and clustering techniques. The individual characteristics influence on patterns was assessed using multinomial logistic regression. The individual characteristics and patterns influence on care costs was assessed using generalised estimating equations. Results: The findings revealed an average cost of €13,753 per patient during the initial 3 years. Regression models suggested the main predictors of high DTC specific care consumption tended to include having a high risk of cancer recurrence (OR = 4.97), being a woman (OR = 2.00), and experiencing socio-economic deprivation (OR = 1.26), though not reaching statistical significance. Finally, high DTC-specific care consumers also incurred higher general care costs (RR = 1.35). Conclusion: The study underscores the increased costs of managing DTC, shaped by consumption habits and socioeconomic position, emphasising the need for more nuanced DTC management strategies.

A qualitative analysis and evaluation of social support received after experiencing a broken marriage engagement and impacts on holistic health.

This study provides new insights into the role of social support in the largely unexplored field of broken marriage engagements and an individual's wellbeing. The study extends the optimal matching theory (OMT) and the research surrounding helpful, unhelpful, and mixed social support. It uses constant comparison to examine the social support messages individuals received after telling others their engagement ended, as described in 43, in-depth, semi-structured interviews. Six types of helpful support messengers, six types of unhelpful support messengers, and four mixed messenger types were found. Receiver-centric messengers were found to be more helpful than messengers who centered on their own feelings and needs, sometimes to the detriment of the receiver's own wellbeing. Being present, thoughtful, and intentional with words, can have a positive impact on a person's holistic health, regardless of whether the relationship is a weak-tie or strong-tie. Using study findings, the broken engagement message stoplight is proposed, detailing messages that are generally helpful to a person's overall wellbeing, messages that should likely be avoided, and messages that should be said cautiously when interacting with someone experiencing a broken engagement.

Clinical care pathways of patients with biliary tract cancer: A French nationwide longitudinal cohort study.

BACKGROUND: Although the incidence of BTC is raising, national healthcare strategies to improve care lack. We aimed to explore patient clinical care pathways and strategies to improve biliary tract cancer (BTC) care. METHODS: We analysed the French National Healthcare database of all BTC inpatients between January 1, 2017 and December 31, 2021. Multinomial logistic regression adjusted odds ratios (aOR) were used to identify healthcare organisation factors that influenced access to curative care both overall and in a longitudinal sensibility analysis using optimal matching and hierarchical ascending classification to detect a subgroup of curative-care patients with a high survival over a two-year period. RESULTS: A total of 19,825 new BTC patients and three clinical care pathways (CCP) were identified: 'Palliative care' (PC-CCP), 'Non-curative Care' (NCC-CCP) and 'Curative Care' (CC-CCP) involving 7669 (38.7%), 7721 (38.9%) and 4435 (22.4%) patients respectively. Out of 1200 centers involved in BTC treatment, 84%, 11% and 5% were of low- (<15 patients/year), medium- (15-30 patients/year) and high-volume (>30 patients/year) respectively. Among patient, tumor and hospital factors, BTC management in academic (aOR: 2.32; 95%CI: 1.98-2.71), private (2.51; 2.22-2.83), semi-private (2.25; 1.91-2.65) and in high- (2.09; 1.81-2.42) or medium-volume (1.49; 1.33-1.68) centers increased probability to CC-CCP. These results were maintained in a longitudinal cluster of 2363 (53%) CC-CCP patients presenting a higher two-year survival compared with the rest [96.4% (95.1; 97.6) vs. 38.8% (36.3; 41.4), log-rank p < 0.001]. CONCLUSIONS: Among factors subject to healthcare policy improvement, the volume and type of centers managing BTC strongly influenced access to curative care.

Optimal plastic recycling system and technology development could accelerate decarbonization: A case study from Japan.

This study provided a geographic and technical matching approach supporting low-carbon style recycling systems, demonstrated using polyvinyl chloride waste (PVCW) generated in 2018 in Mie Prefecture, Japan. From a carbon dioxide (CO2) emission basis, mechanical/material recycling (MR) and energy recovery facilities were all allocated full capacity; however, parts of chemical recycling facilities were excluded in the optimal solutions. From the spatial distribution of the allocated result, we confirmed a trend that to achieve the minimum total emissions, the matchings from pretreatment to recycling facilities were done based on a nearby priority rule. From an emission reduction basis, MR accounted for the major proportion of total reductions which was similar to that accessed from an emission basis. Thus, the promotion of MR should be prioritized at the current technical level when optimizing emissions of the whole lifecycle. The number of facilities allocated were substantially reduced; meanwhile, the averaged emission reductions per ton of PVCW disposed were increased from the current level (2.93) to the near-future level (4.99 t-CO2 t-1). Thus, we concluded that this optimization under a higher technical level was effective to make the current recycling system with more emission reductions (low-carbon environmental effect) and require fewer disposal facilities (cost-saving economic effect). Meanwhile, certain long-distance routes found in solutions implied that technical parameters were more important than geolocation parameters to achieve maximum emission reductions.

Applying sequence analysis to uncover 'real-world' clinical pathways from routinely collected data: a systematic review.

OBJECTIVES: This systematic review aims to elucidate the methodological practices and reporting standards associated with sequence analysis (SA) for the identification of clinical pathways in real-world scenarios, using routinely collected data. STUDY DESIGN AND SETTING: We conducted a methodological systematic review, searching five medical and health databases: MEDLINE, PsycINFO, CINAHL, EMBASE and Web of Science. The search encompassed articles from the inception of these databases up to February 28, 2023. The search strategy comprised two distinctive sets of search terms, specifically focused on sequence analysis and clinical pathways. RESULTS: 19 studies met the eligibility criteria for this systematic review. Nearly 60% of the included studies were published in or after 2021, with a significant proportion originating from Canada (n = 7) and France (n = 5). 90% of the studies adhered to the fundamental SA steps. The optimal matching (OM) method emerged as the most frequently employed dissimilarity measure (63%), while agglomerative hierarchical clustering using Ward's linkage was the preferred clustering algorithm (53%). However, it is imperative to underline that a majority of the studies inadequately reported key methodological decisions pertaining to SA. CONCLUSION: This review underscores the necessity for enhanced transparency in reporting both data management procedures and key methodological choices within SA processes. The development of reporting guidelines and a robust appraisal tool tailored to assess the quality of SA would be invaluable for researchers in this field.

Matching One Sample According to Two Criteria in Observational Studies.

Multivariate matching has two goals: (i) to construct treated and control groups that have similar distributions of observed covariates, and (ii) to produce matched pairs or sets that are homogeneous in a few key covariates. When there are only a few binary covariates, both goals may be achieved by matching exactly for these few covariates. Commonly, however, there are many covariates, so goals (i) and (ii) come apart, and must be achieved by different means. As is also true in a randomized experiment, similar distributions can be achieved for a high-dimensional covariate, but close pairs can be achieved for only a few covariates. We introduce a new polynomial-time method for achieving both goals that substantially generalizes several existing methods; in particular, it can minimize the earthmover distance between two marginal distributions. The method involves minimum cost flow optimization in a network built around a tripartite graph, unlike the usual network built around a bipartite graph. In the tripartite graph, treated subjects appear twice, on the far left and the far right, with controls sandwiched between them, and efforts to balance covariates are represented on the right, while efforts to find close individual pairs are represented on the left. In this way, the two efforts may be pursued simultaneously without conflict. The method is applied to our on-going study in the Medicare population of the relationship between superior nursing and sepsis mortality. The match2C package in R implements the method.

Impact of event encoding and dissimilarity measures on traffic crash characterization based on sequence of events.

Crash sequence analysis has been shown in prior studies to be useful for characterizing crashes and identifying safety countermeasures. Sequence analysis is highly domain-specific, but its various techniques have not been evaluated for adaptation to crash sequences. This paper evaluates the impact of encoding and dissimilarity measures on crash sequence analysis and clustering. Sequence data of interstate highway, single-vehicle crashes in the United States, from 2016 to 2018, were studied. Two encoding schemes and five optimal matching based dissimilarity measures were compared by evaluating the sequence clustering results. The five dissimilarity measures were categorized into two groups based on correlations between dissimilarity matrices. The optimal dissimilarity measure and encoding scheme were identified based on the agreements with a benchmark crash categorization. The transition-rate-based, localized optimal matching dissimilarity and consolidated encoding scheme had the highest agreement with the benchmark. Evaluation results indicate that the selection of dissimilarity measure and encoding scheme determines the results of sequence clustering and crash characterization. A dissimilarity measure that considers the relationships between events and domain context tends to perform well in crash sequence clustering. An encoding scheme that consolidates similar events naturally takes domain context into consideration.

Couple Formation is Prolonged not Postponed. New Paths to Union Formation in Contemporary France.

In France, as in other European countries, the age at first cohabiting union has risen over the past decades, as a result of longer school enrolment, structural economic changes, and new family norms. While the median age at first co-resident couple was 23.8 for men born in France in the beginning of the 1950s, it was 26.0 among the generation born in the beginning of the 1970s. This tendency is often referred to as a postponement of couple formation and as a part of a broader delay in the transition to adulthood. This article argues, on the contrary, that couple formation has not been postponed but prolonged. In fact, age at first couple formation has remained stable across generations born since the mid-twentieth century in France. Starting from there, we take on a biographical approach to examine the nature, duration, and articulation of the successive stages that make up young people's conjugal trajectories in France. What are the different pathways into couple life, and how have these changed over time? In order to answer these questions, we use optimal matching methods to identify ideal typical trajectories and then logistic regressions in order to see how these relate to generational differences as well as sociodemographic characteristics. We observe three traditional, three timeless and five new paths to couple life. The main historical change is the increasingly gradual nature of union formation, a trend that reflects a dual pattern. First, unions are progressively institutionalized: the time laps between different relationship stages, such as "going out," "settling in," and eventually marrying, have expanded. Second, young people increasingly experience several relationships during youth: the different steps of couple formation are taken with different partners. We conclude that couple formation is not delayed per se; it is rather the material and institutional formalization of unions that is put off for the future. We discuss the scientific and methodological implications of this finding. Supplementary Information: The online version contains supplementary material available at 10.1007/s10680-022-09629-0.

Who is absent from school when? An optimal matching analysis of within-year variation in the timing of school absences.

Although school absenteeism trajectories can be studied through various parameters and dimensions, such as the amount of school absenteeism, sequence, and timing, most studies have only focused on changes in the amount of school absenteeism. However, when investigating the nature of school absenteeism, an analysis cannot be restricted to just changes in the amount of school absenteeism. In this article, I show how applying optimal matching on time-stamped half days of missed school (n = 6260) enables researchers, policy makers, and school professionals to uncover socio-temporal regularities in trajectories of non-attendance (i.e., the degree to which groups of pupils are absent at the same time and in the same rhythm within a given school year). Results indicated that students fall into five types of trajectories, and that these are highly predictive of student's examination results at the end of the school year. In the Discussion, I elaborate on the implications of these findings.

Dissecting the structure-property relationship of ceramic membrane with asymmetric multilayer structures for maximizing permselectivity.

Robust ceramic membranes presented attractive features of easy cleaning and excellent stability compared to polymeric membranes. Nevertheless, their inherent relationships between the membrane microstructures and separation properties are not completely clear. In this work, we established a quantitative structure-property model using α-Al2O3 membrane on account of the theory of filtrated cake to predict the effects of membrane structure-controlled factors (i.e., α-Al2O3 particle size and layer thickness) on separation performances (i.e., solute rejection and water permeance). The simulation results show that membrane pore size mainly depends upon α-Al2O3 particle size rather than the layer thickness. When the microstructure of top layer in a double-layer asymmetric ceramic membrane is fixed, there exists optimum particle size and layer thickness that constitute the support layer to achieve maximum water permeance. For a triple-layer ceramic membrane, a similar matching relationship exists between top layer and intermediate layer, indicating that the intermediate layer has a vital role in determining water permeance. While the bottom layer has little effect on overall separation property. Finally, the upper-bound tradeoff relationship between permeance and selectivity is further established for the α-Al2O3 membrane. This study reveals the structure-property relationship of ceramic membrane and provides insights into performance enhancement.

Minimally invasive versus open lumbar spinal fusion: a matched study investigating patient-reported and surgical outcomes.

OBJECTIVE: With the expanding indications for and increasing popularity of minimally invasive surgery (MIS) for lumbar spinal fusion, large-scale outcomes analysis to compare MIS approaches with open procedures is warranted. METHODS: The authors queried the Quality Outcomes Database for patients who underwent elective lumbar fusion for degenerative spine disease. They performed optimal matching, at a 1:2 ratio between patients who underwent MIS and those who underwent open lumbar fusion, to create two highly homogeneous groups in terms of 33 baseline variables (including demographic characteristics, comorbidities, symptoms, patient-reported scores, indications, and operative details). The outcomes of interest were overall satisfaction, decrease in Oswestry Disability Index (ODI), and back and leg pain, as well as hospital length of stay (LOS), operative time, reoperations, and incidental durotomy rate. Satisfaction was defined as a score of 1 or 2 on the North American Spine Society scale. Minimal clinically important difference (MCID) in ODI was defined as ≥ 30% decrease from baseline. Outcomes were assessed at the 3- and 12-month follow-up evaluations. RESULTS: After the groups were matched, the MIS and open groups consisted of 1483 and 2966 patients, respectively. Patients who underwent MIS fusion had higher odds of satisfaction at 3 months (OR 1.4, p = 0.004); no difference was demonstrated at 12 months (OR 1.04, p = 0.67). Lumbar stenosis, single-level fusion, higher American Society of Anesthesiologists Physical Status Classification System grade, and absence of spondylolisthesis were most prominently associated with higher odds of satisfaction with MIS compared with open surgery. Patients in the MIS group had slightly lower ODI scores at 3 months (mean difference 1.61, p = 0.006; MCID OR 1.14, p = 0.0495) and 12 months (mean difference 2.35, p < 0.001; MCID OR 1.29, p < 0.001). MIS was also associated with a greater decrease in leg and back pain at both follow-up time points. The two groups did not differ in operative time and incidental durotomy rate; however, LOS was shorter for the MIS group. Revision surgery at 12 months was less likely for patients who underwent MIS (4.1% vs 5.6%, p = 0.032). CONCLUSIONS: In patients who underwent lumbar fusion for degenerative spinal disease, MIS was associated with higher odds of satisfaction at 3 months postoperatively. No difference was demonstrated at the 12-month follow-up. MIS maintained a small, yet consistent, superiority in decreasing ODI and back and leg pain, and MIS was associated with a lower reoperation rate.

Fast and optimal algorithm for case-control matching using registry data: application on the antibiotics use of colorectal cancer patients.

BACKGROUND: In case-control studies most algorithms allow the controls to be sampled several times, which is not always optimal. If many controls are available and adjustment for several covariates is necessary, matching without replacement might increase statistical efficiency. Comparing similar units when having observational data is of utter importance, since confounding and selection bias is present. The aim was twofold, firstly to create a method that accommodates the option that a control is not resampled, and second, to display several scenarios that identify changes of Odds Ratios (ORs) while increasing the balance of the matched sample. METHODS: The algorithm was derived in an iterative way starting from the pre-processing steps to derive the data until its application in a study to investigate the risk of antibiotics on colorectal cancer in the INTEGO registry (Flanders, Belgium). Different scenarios were developed to investigate the fluctuation of ORs using the combination of exact and varying variables with or without replacement of controls. To achieve balance in the population, we introduced the Comorbidity Index (CI) variable, which is the sum of chronic diseases as a means to have comparable units for drawing valid associations. RESULTS: This algorithm is fast and optimal. We simulated data and demonstrated that the run-time of matching even with millions of patients is minimal. Optimal, since the closest controls is always captured (using the appropriate ordering and by creating some auxiliary variables), and in the scenario that a case has only one control, we assure that this control will be matched to this case, thus maximizing the cases to be used in the analysis. In total, 72 different scenarios were displayed indicating the fluctuation of ORs, and revealing patterns, especially a drop when balancing the population. CONCLUSIONS: We created an optimal and computationally efficient algorithm to derive a matched case-control sample with and without replacement of controls. The code and the functions are publicly available as an open source in an R package. Finally, we emphasize the importance of displaying several scenarios and assess the difference of ORs while using an index to balance population in observational data.

More robust estimation of average treatment effects using kernel optimal matching in an observational study of spine surgical interventions.

Inverse probability of treatment weighting (IPTW), which has been used to estimate average treatment effects (ATE) using observational data, tenuously relies on the positivity assumption and the correct specification of the treatment assignment model, both of which are problematic assumptions in many observational studies. Various methods have been proposed to overcome these challenges, including truncation, covariate-balancing propensity scores, and stable balancing weights. Motivated by an observational study in spine surgery, in which positivity is violated and the true treatment assignment model is unknown, we present the use of optimal balancing by kernel optimal matching (KOM) to estimate ATE. By uniformly controlling the conditional mean squared error of a weighted estimator over a class of models, KOM simultaneously mitigates issues of possible misspecification of the treatment assignment model and is able to handle practical violations of the positivity assumption, as shown in our simulation study. Using data from a clinical registry, we apply KOM to compare two spine surgical interventions and demonstrate how the result matches the conclusions of clinical trials that IPTW estimates spuriously refute.

The vulnerability of shellfish farmers to HAB events: An optimal matching analysis of closure decrees.

Harmful Algal Blooms (HAB) events may have serious economic consequences for shellfish farmers. When toxic algae blooms threaten human health, public authorities may decide to shut down the farming business for a while, i.e. ranging from a few days to several weeks or months, according to the severity of risks. The impact of closures being temporally and spatially distributed, shellfish farmers can avoid the risky zones or develop adaptive strategies to mitigate the economic consequences and therefore reduce significantly their business sensitivity to HABs. A sequential approach by optimal matching analysis is applied to an original data set of shellfish area closure decrees between April 2004 and December 2018 in Southern Brittany and Pays de la Loire (France) to build a typology of 79 aquaculture zones affected by various HAB and microbiological hazards (ASP, DSP, Norovirus, E. Coli, oil spills). The hypothesis is that the degree of exposure to the HAB hazard assessed by zonal closures may not be correlated to the level of sensitivity revealed by the economic results of the shellfish farming industry which can develop avoidance strategies.

Citizenship and education trajectories among children of immigrants: A transition-oriented sequence analysis.

During recent decades, the educational outcomes of the children of immigrants have been extensively studied, with a growing emphasis on the heterogeneity of the so-called second generation. Yet, the impact of host country citizenship on children's educational outcomes has only received limited attention so far, although children of immigrants do not get automatic birthright citizenship in most European countries. Focusing on the Netherlands, this paper compares educational trajectories among citizen and non-citizen children of immigrants. Register data and sequence analysis are used to map and cluster the trajectories of a full cohort of second-generation students from the start of secondary school. We apply a variant of optimal matching focusing on sequences of transitions, which enables us to uncover different patterns of (im)mobility within a stratified school system better than the standard approach. Multinomial logistic regressions show that students who acquire Dutch citizenship are significantly more likely to follow upward trajectories, taking advantage of the system's flexibility and "back doors". Conversely, not having Dutch citizenship is associated with a higher risk of dropout and school interruptions. These findings are in line with our theoretical expectation that, during the naturalisation process, parents acquire or further develop important resources for navigating a complex educational system such as the Dutch one.

Protocol - Evaluating the Effect of ACA Medicaid Expansion on Mortality During the COVID-19 Pandemic Using County-level Matching.

States are able to choose whether to expand Medicaid as part of the Affordable Care Act (ACA); thus it is of interest to understand the impact of this policy choice. In this protocol, we outline a study on the impact of Medicaid expansion as part of the ACA on mortality during the COVID-19 pandemic in the United States. County-level matching using full, optimal matching with a propensity score model is used to estimate causal effects in this observational study. Due to the provisional nature of mortality data in 2020 as reported by the CDC, we outline a modified aligned rank test to account for censored data as well as reporting lags for different states. We aim to make connections between statistical and ethnographic methodologies by particularly examining adjacent counties and similar counties that are in the same region of the US and in vastly different regions of the US. Finally, we aim to add to the growing literature about the effect of ACA Medicaid expansion on mortality by calculating effects, disaggregating by race.

A hierarchical algorithm for multicentric matched cohort study designs.

OBJECTIVE: Lack of structural equality is a major issue to be addressed in observational studies. Their major disadvantage of these studies compared to randomized controlled trials is the vulnerability towards confounding, but they often better mirror real world patients and, therefore, entail an increased external validity. Numerous approaches have been developed to account for confounding in observational research, including multiple regression, subgroup analysis and matched cohort designs. The latter has been often described as a useful tool if large control data sets are available. METHODS: In this paper we present a hierarchical matching algorithm entailing two stages which enables a multicentric matched cohort study to be conducted. In particular, the algorithm defines the matching strategy as a combination of exact matching and a subsequent consideration of further matching variables to be controlled using a distance measure (e.g. the propensity score). RESULTS: The algorithm is applied to a study in interventional cardiology and demonstrates high flexibility and usefulness with regard to the aim of finding comparable cases of exposed and non-exposed patients from observational data. The algorithm increased structural equality by balancing the most important covariates which might be of different importance for the matching process. CONCLUSION: The implementation of the algorithm in the statistical software SAS offers high flexibility regarding an application to various data analysis projects. Specifically, it provides a broader range of features (e.g. diverse distance measures) when compared to other existing solutions for conducting matched cohort analyses.

Healthcare utilization after a first hospitalization for COPD: a new approach of State Sequence Analysis based on the '6W' multidimensional model of care trajectories.

BACKGROUND: Published methods to describe and visualize Care Trajectories (CTs) as patterns of healthcare use are very sparse, often incomplete, and not intuitive for non-experts. Our objectives are to propose a typology of CTs one year after a first hospitalization for Chronic Obstructive Pulmonary Disease (COPD), and describe CT types and compare patients' characteristics for each CT type. METHODS: This is an observational cohort study extracted from Quebec's medico-administrative data of patients aged 40 to 84 years hospitalized for COPD in 2013 (index date). The cohort included patients hospitalized for the first time over a 3-year period before the index date and who survived over the follow-up period. The CTs consisted of sequences of healthcare use (e.g. ED-hospital-home-GP-respiratory therapists, etc.) over a one-year period. The main variable was a CT typology, which was generated by a 'tailored' multidimensional State Sequence Analysis, based on the "6W" model of Care Trajectories. Three dimensions were considered: the care setting ("where"), the reason for consultation ("why"), and the speciality of care providers ("which"). Patients were grouped into specific CT types, which were compared in terms of care use attributes and patients' characteristics using the usual descriptive statistics. RESULTS: The 2581 patients were grouped into five distinct and homogeneous CT types: Type 1 (n = 1351, 52.3%) and Type 2 (n = 748, 29.0%) with low healthcare and moderate healthcare use respectively; Type 3 (n = 216, 8.4%) with high healthcare use, mainly for respiratory reasons, with the highest number of urgent in-hospital days, seen by pulmonologists and respiratory therapists at primary care settings; Type 4 (n = 100, 3.9%) with high healthcare use, mainly cardiovascular, high ED visits, and mostly seen by nurses in community-based primary care; Type 5 (n = 166, 6.4%) with high healthcare use, high ED visits and non-urgent hospitalisations, and with consultations at outpatient clinics and primary care settings, mainly for other reasons than respiratory or cardiovascular. Patients in the 3 highest utilization CT types were older, and had more comorbidities and more severe condition at index hospitalization. CONCLUSIONS: The proposed method allows for a better representation of the sequences of healthcare use in the real world, supporting data-driven decision making.

Synthesis of P-Doped and NiCo-Hybridized Graphene-Based Fibers for Flexible Asymmetrical Solid-State Micro-Energy Storage Device.

Fiber supercapacitors (FSCs) are promising energy storage devices in portable and wearable smart electronics. Currently, a major challenge for FSCs is simultaneously achieving high volumetric energy and power densities. Herein, the microscale fiber electrode is designed by using carbon fibers as substrates and capillary channels as microreactors to space-confined hydrothermal assembling. As P-doped graphene oxide/carbon fiber (PGO/CF) and NiCo2 O4 -based graphene oxide/carbon fiber (NCGO/CF) electrodes are successfully prepared, their unique hybrid structures exhibit a satisfactory electrochemical performance. An all-solid-state PGO/CF//NCGO/CF flexible asymmetric fiber supercapacitor (AFSC) based on the PGO/CF as the negative electrode, NCGO/CF hybrid electrode as the positive electrode, and poly(vinyl alcohol)/potassium hydroxide as the electrolyte is successfully assembled. The AFSC device delivers a higher volumetric energy density of 36.77 mW h cm-3 at a power density of 142.5 mW cm-3 . In addition, a double reference electrode system is adopted to analyze and reduce the IR drop, as well as effectively matching negative and positive electrodes, which is conducive for the optimization and improvement of energy density. For the AFSC device, its better flexibility and electrochemical properties create a promising potential for high-performance micro-supercapacitors. Furthermore, the introduction of the double reference electrode system provides an interesting method for the study on the electrochemical performances of two-electrode systems.