Scale Problems Research Articles

Cognitive and Behavioral Outcomes of Snoring Among Adolescents

ImportanceSnoring is central to sleep-disordered breathing (SDB), which arises from nocturnal upper airway resistance. Habitual snoring is associated with cognitive and behavioral problems in young children, but less is known about these associations in adolescents.ObjectiveTo assess the longitudinal associations of snoring with cognition and problem behaviors among adolescents.Design, Setting, and ParticipantsThis cohort study was a secondary analysis of the Adolescent Brain Cognitive Development (ABCD) Study dataset (release 5.0), which enrolled 11 875 children and a parent or caregiver from June 1, 2016, to October 15, 2018, at 21 participating US research institutions and followed-up for 5 years. The analysis was performed between December 2023 and April 2024.ExposuresParent-reported snoring categorized as none, nonhabitual (<3 nights/week), and habitual (≥3 times/week).Main Outcomes and MeasuresCognition was assessed using 5 measures from the National Institutes of Health Toolbox (NIH-TB), and caregiver-reported problem behaviors were assessed using the Child Behavior Checklist (CBCL), including Total Problems, Internalizing Problems, and Externalizing Problems. Longitudinal associations of snoring with these assessment measures were analyzed using linear mixed-effects models stratified by obesity. Model fits were assessed after including the fixed-effects of age, sex at birth, race, family income, follow-up time, visit type, and the random-effects of site and identification number.ResultsThe study included data from 11 862 children at year 1 (mean age, 119.0 months [95% CI, 118.8 to 119.1 months]; 6164 male [52.2%]) and 11 198, 10 870, 10 064, and 4668 children at years 2 to 5, respectively. The proportion of habitual snorers decreased from 811 participants (6.8%) in year 1 to 150 participants (3.2%) in year 5. Snoring was not associated with any of the NIH-TB scores. A statistically significant association of snoring was identified with all CBCL scales. The largest-magnitude association was of snoring with the CBCL Total Problems scale among adolescents with obesity (β = 3.18; 95% CI, 2.59-3.77).Conclusions and RelevanceIn this cohort study analyzing associations of snoring with cognitive test scores and problem behaviors based on the ABCD dataset, the prevalence of snoring declined over time; snoring in adolescents was associated with problem behaviors but not cognitive deficits. These findings may aid shared decision-making regarding treatment options such as adenotonsillectomy for adolescents with SDB.

Challenges in measurement of adolescent mental health: how are gender patterns affected when level of symptoms is analysed simultaneously with impairment?

BackgroundAdolescent mental health surveys in public health are sometimes questioned because of their main focus on self-reported symptoms, lacking data on impairment, e.g. the consequences on everyday life of the mental health problems. While public health studies typically reveal higher prevalence rates of internalising problems for girls than boys, there are indications that the gender pattern may change when self-reported data on symptoms are analysed simultaneously with impairment. The purpose is to determine how gender patterns of adolescent mental health solely based on symptoms are affected when level of symptoms is analysed simultaneously with impairment.MethodsQuestionnaire data on adolescent mental health were collected in schools by Statistics Sweden in the autumn of 2009 as part of a national total population study in grades 6 and 9 in Sweden. In this study only data from grade 9 students are used (n = 91 627; response rate = 80 per cent). Psychosomatic symptoms were measured with the Psychosomatic Problems scale including eight items. Impairment was measured with four items included in the SDQ impact supplement. The associations between these key constructs were analysed with logistic regression and contingency tables.ResultsWhen analysing variables on psychosomatic symptoms and impairment independently, the results are consistent with typical findings of gender patterns in adolescent internalising mental health. Girls report both more psychosomatic symptoms, and more negative consequences in everyday life, than boys. The gender patterns are, however, strongly affected when impairment is conditioned on level of psychosomatic symptoms. Except for the Home Life setting, in the settings of Friendships, Classroom Learning and Leisure Activities, the previously reported gender pattern favoring higher disturbances among girls becomes partly reversed implying that boys report more negative consequences than girls. Hence, while girls report a higher prevalence of psychosomatic symptoms, boys appear to suffer from such symptoms more than, or as much as, girls in three out of four everyday life settings.ConclusionsThe study confirms the insufficiency of solely including data on symptoms in the measurement of adolescent mental health. Regardless of the causes of the complex gender pattern shown in this study, the results highlight the importance of simultaneous inclusion of indicators of impairment as well as symptom counts and frequency in the measurement of adolescent mental health.

Stressors and difficulties in early intervention programs in Jordan from the employee’s perspective

Early childhood is crucial in building and shaping the personalities of children with disabilities, where employees dealing with such children face a lot of challenges. This study aimed to identify problems and challenges faced during early intervention programs in Jordan from employees’ perspectives. We conducted a questionnaire-based study on 350 from a population of 4000 employees working in early intervention programs from Jordan’s North, Central, and South territories. Participants responded to the problem and challenges scale, containing 32 items distributed over five dimensions. The findings of this study showed that employees at special education centers in Jordan who work in early intervention programs said they typically faced moderate issues and difficulties. The most significant issues and difficulties that Jordan’s early intervention programs faced were the absence of interactive cooperation among employees and the flexibility of the programs. Factor analysis of the studied items showed that, apart from the social dimension, the items of all other dimensions of the research instrument were influenced by a diverse set of underlying factors. There were no statistically significant differences in the challenges and problems facing early intervention programs in Jordan due to the employees’ gender, academic qualification, and experience. Finally, this study offered suggestions and recommendations for enhancing early intervention services and programs, putting additional rehabilitation into place, and implementing ongoing training for professionals in this sector.

Rates of socio-emotional difficulties among deaf and hard of hearing children in Ireland

ABSTRACT Higher rates of socio-emotional difficulties for deaf and hard of hearing (DHH) children have been reported compared with their typical hearing (TH) peers. Nonetheless, there has to date been limited examination on this issue internationally and no such examination in the Republic of Ireland. In this study, data was collected from parents using an online survey which included the Strengths and Difficulties Questionnaire to examine the socio-emotional development of 113 DHH children aged 5–16 in the Republic of Ireland. The results were compared with data from typically hearing (TH) children obtained from a large longitudinal study of childhood in Ireland – the Growing Up in Ireland study. The findings demonstrate that the prevalence of socio-emotional difficulties among this cohort of children is over three times that of the general population of children in Ireland, with 42% of the sample demonstrating clinically significant problem scores. Furthermore, DHH children had elevated subscale scores for the four problem scales in the SDQ when compared against the TH sample. These differences were statistically significant and had a range of effect sizes from small to large. The subscale of most concern was the peer problems subscale where the DHH sample had mean scores that were roughly double those of the TH sample, with a large effect size found. Finally, bivariate analysis revealed that several background variables were associated with elevated difficulty scores for DHH children, namely male gender, poorer communicative competency, and presence of an additional educational need.

Optimizing resource utilization for large scale problems through architecture aware scheduling

Rapid development realms of parallel architectures and its heterogeneity have inspired researchers to invent new scheduling strategies to efficiently distribute workloads among these architectures in a way that may lead to better performance. This paper presents a comprehensive study on optimizing resource utilization for large-scale problems by employing architecture-aware scheduling techniques. We conducted a series of experiments to measure the execution times of various architectures with different problem sizes. These experiments have been conducted multiple times to minimize measurement variance. The findings from these experiments are utilized to develop a scheduling strategy that enables faster completion of larger data-parallel problems while maximizing resource utilization. The proposed approach makes performance enhancement with 16.7% for large data size. It has a significant impact on enhancing computational efficiency and reducing costs in high-performance computing environments.

Development and validation of a method for deriving MMPI-3 scores from MMPI-2/MMPI-2-RF item responses.

The Minnesota Multiphasic Personality Inventory-3 (MMPI-3; Ben-Porath & Tellegen, 2020a) was developed to expand the content coverage of the MMPI-2-Restructured Form (MMPI-2-RF; Ben-Porath & Tellegen, 2008/2011) and to update the test's norms to better represent the U.S. population. Because most MMPI-3 items were carried over from the MMPI-2-RF, most MMPI-3 scales can be either fully scored or prorated from the MMPI-2/MMPI-2-RF item pool. We describe development of a procedure for deriving MMPI-3 scores from MMPI-2/MMPI-2-RF protocols and examine the psychometric properties of prorated MMPI-3 scores across various samples. Following Tarescavage et al. (2016), who developed a method for prorating most MMPI-2-RF scores from the original MMPI, prorated MMPI-3 scales had to meet three criteria: (a) sufficient representation in the MMPI-2-RF item pool, (b) association with the full-length corresponding MMPI-3 scale at r ≥ .90 in multiple samples, and (c) comparable T score means and standard deviations in multiple samples. These criteria resulted in the exclusion of the three MMPI-3 non-content-based Validity Scales, as well as nine Specific Problems Scales, yielding 16 MMPI-3 scales that can be fully scored and 24 for which psychometrically comparable prorated score estimates can be derived from responses to the MMPI-2 or MMPI-2-RF item pools. Evidence of the psychometric functioning of the resulting scale scores and their comparability with the full versions of these scales across samples is presented and discussed. This procedure provides a means to study 40 of the 52 MMPI-3 scales using archival data obtained with older versions of the inventory. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Artificial Intelligence in public health: A case study

Artificial Intelligence technology has become an innovative tool in global healthcare that helps to manage various problems of scale and complexity. Its use in public health is multifaceted and multivariate extending across early outbreak detection, risk modeling and prediction, efficient vaccine logistics and administration, reducing health disparities, aiding assist in diagnosis, everyday monitoring of chronic diseases, telemedicine and virtual chatbots especially for elderly care, mental health and oncology patients, and community engagement. Despite these huge generational advantages, multiple challenges exist in data quality, security and misuse, individual privacy, contextual application, accountability and oversight and remain primary concerns for universal adoption of artificial intelligence. There is a need for safeguards and a global regulatory framework to responsibly harvest the benefits of artificial intelligence for the advancement of public and community health.

A gentle introduction to gradient-based optimization and variational inequalities for machine learning

Abstract The rapid progress in machine learning in recent years has been based on a highly productive connection to gradient-based optimization. Further progress hinges in part on a shift in focus from pattern recognition to decision-making and multi-agent problems. In these broader settings, new mathematical challenges emerge that involve equilibria and game theory instead of optima. Gradient-based methods remain essential—given the high dimensionality and large scale of machine-learning problems—but simple gradient descent is no longer the point of departure for algorithm design. We provide a gentle introduction to a broader framework for gradient-based algorithms in machine learning, beginning with saddle points and monotone games, and proceeding to general variational inequalities. While we provide convergence proofs for several of the algorithms that we present, our main focus is that of providing motivation and intuition.

Analyzing the Characteristic of Simplex Algorithm

Simplex algorithm is a kind of iterated algorithm which is used to solve linear programming problems. It is raised by George Dantzig in 1974 and is still a valid tool especially when the scale of problem is relatively small or secondary. Simplex algorithm starts at an initializing feasible solution, and constantly approach to the optimal solution until the optimal solution is found or unbounded. Serving as a classical algorithm solving linear programming problem, it plays an important role in both theoretical. With the continuous development of computing technology, the simplex method and its varieties will continue in optimization. This research aims to help people make better decisions in optimization problems by summarizing the formula, characteristics and problem solutions of simplex algorithm. The summary is come from existing literature and including the condition of using simplex algorithm, all kind of different solutions, an example of simplex tableau method and the future of simplex algorithm.

Feasibility of a Home-Based Developmental Behavioral Intervention for Children With Autism Spectrum Disorder in Underserved Taiwanese Families

Purpose: This study aims to investigate the feasibility of the home-based parent- mediated intervention Naturalistic developmental behavioral intervention (HB-NDBI) in underserved Taiwanese families of children with Autism spectrum disorder (ASD) and explore its effects on children’s developmental skills and parents’ parenting stress. Method: 24 underserved Taiwanese families of children with ASD (mean age = 46.5 months) received 12-week HB-NDBI programs. Social Responsiveness Scale, Second Edition (SRS-2), Mullen Scales of Early Learning (MSEL), Child Behavior Checklist (CBCL/1.5-5), and Parenting Stress Index (PSI) were administered before and after the HB-NDBI programs. Results: Following the HB-NDBI programs, significant improvements in social cognition, social communication subscales, receptive language subscale, internalizing, externalizing, and total behavioral problems scales of children, and release of parenting stress were observed. Conclusion: This study demonstrated the feasibility of home-based parent-mediated intervention for underserved families in Taiwan. These promising results might facilitate the development of such interventions for underserved families.

Insomnia treatment effects on negative emotionality among veterans in treatment for alcohol use disorder.

Insomnia symptoms are pervasive and persistent in alcohol use disorder (AUD), though little is known about the mechanisms that underlie this association. We previously found that cognitive behavioral therapy for insomnia (CBT-I) reduced alcohol-related problems among veterans by improving insomnia severity (NCT03806491). In this planned secondary analysis of the same clinical trial data, we tested negative emotionality as one potential mechanism to explain this effect. Specifically, we tested the change in negative emotionality as a mediator of the association between change in insomnia symptoms and alcohol-related outcomes (craving, heavy drinking frequency, and alcohol-related problems). Participants were 67 veterans in treatment for AUD who also met the criteria for insomnia disorder (91% male, 84% White, average age = 46.3 years). Participants were randomized to five sessions of CBT-I or a single-session sleep hygiene control. Assessments occurred at baseline, immediately posttreatment (~6 weeks after baseline), and at 6-week follow-up. Measures included the Insomnia Severity Index, Penn Alcohol Craving Scale, Timeline Followback, and Short Inventory of Problems. We created a latent negative emotionality indicator based on five validated and reliable measures of negative emotionality. Contrary to hypotheses, CBT-I did not improve negative emotionality relative to sleep hygiene control. However, across both treatment conditions, decreases in insomnia symptoms from baseline to posttreatment were associated with concurrent decreases in negative emotionality, which in turn predicted reductions in alcohol craving and heavy drinking. Negative emotionality may help explain links between insomnia symptoms and alcohol-related outcomes.

Sleep pattern, behavior, duration and incident hypertension: results from two large prospective cohorts

Abstract Background Poor sleep quality pose significant public health challenges globally. The objective of this study is to investigate the association between sleep quality, duration and the risk of hypertension. Methods 284,250 adults from the UK Biobank (UKB) and 6,104 participants from the English Longitudinal Study of Ageing (ELSA) were analyzed. The exposures of interest were sleep quality and duration. Sleep quality was evaluated based on the number of healthy sleep behaviors (UKB cohort) or questionnaire adapted from the Jenkins Sleep Problems Scale (ELSA cohort). Participants were divided into three groups based on the assessment of sleep quality. Long sleep is characterized by a duration exceeding 8 hours, medium sleep ranges from 7 to 8 hours and short sleep denotes less than 7 hours of sleep. The primary endpoint was incident hypertension. Results In UKB cohort, participants with poor sleep quality showed significantly higher risk of hypertension compared those with healthy sleep quality (hazard ratio [HR] 1.276, confidence interval [CI] 1.21, 1.346). Short sleep duration (≤7h) was associated with an elevated hypertension risk in participants regardless of different sleep quality, and both short(≤7h) and prolonged sleep time (≥9h) were associated with an increased hypertension risk in the poor sleep quality group. Several factors were independently associated with a lower risk of hypertension, including appropriate sleep duration (7-8 hours per day), absence of frequent insomnia, no self-reported snoring(P<0.001). Associations between sleep quality and an increased risk of hypertension remained significant regardless of genetic susceptibility to hypertension (P for interaction= 0.067). Conclusions Poor sleep quality is associated with an elevated risk of hypertension. Adjusting sleep behavior to enhance sleep quality within a recommended range could be a promising strategy for mitigating the risk of hypertension.

Nonlinear Optimization and Adaptive Heuristics for Solving Irregular Object Packing Problems

We review and present several challenging model classes arising in the context of finding optimized object packings (OP). Except for the smallest and/or simplest general OP model instances, it is not possible to find their exact (closed-form) solution. Most OP problem instances become increasingly difficult to handle even numerically, as the number of packed objects increases. Specifically, here we consider classes of general OP problems that can be formulated in the framework of nonlinear optimization. Research experience demonstrates that—in addition to utilizing general-purpose nonlinear optimization solver engines—the insightful exploitation of problem-specific heuristics can improve the quality of numerical solutions. We discuss scalable OP problem classes aimed at packing general circles, spheres, ellipses, and ovals, with numerical (conjectured) solutions of non-trivial model instances. In addition to their practical relevance, these models and their various extensions can also serve as constrained global optimization test challenges.

Reliability and Validity of the Diagnostic Interview Trauma and Stressors- Intellectual Disability in Adults with Mild Intellectual Disabilities or Borderline Intellectual Functioning

ABSTRACT Objective To assess the reliability and construct validity of the Diagnostic Interview Trauma and Stressors- Intellectual Disability – Adult version (DITS-ID-adults) in adults with mild intellectual disabilities or borderline intellectual functioning (MID-BIF). Method The DITS-ID-adults, Brief Symptom Inventory–18 (BSI–18), and Impact of Event Scale-Intellectual Disability (IES – ID) were administered to 97 participants with MID-BIF who lived in supported housing. The Anxiety, Depression, and Mood Scale (ADESS) and Behavior Problems Inventory (BPI) were administered to their relatives. Results The interrater reliability of the DITS-ID-adults was good to excellent. The construct validity of the DITS-ID-adults was good, based on positive correlations between the BSI–18, IES-ID, ADESS and DITS-ID-adults, and mainly positive correlations between the BPI and DITS-ID-adults (r = .21 to r = .75). Reporting potentially traumatic events listed under the A criterium for PTSD was associated with fulfilling PTSD symptom criteria. In this sample, 58% were classified with post-traumatic stress disorder (PTSD) according to the DITS-ID-adults, while PTSD diagnosis on file was low (7%). Conclusion The present findings support the DITS-ID-adults as a reliable and valid basis for classifying PTSD in individuals with MID-BIF.

Sequential Memetic Algorithm Optimization for Allocation Planning in Hostelry Establishments

Hostelry establishments face the challenge of devising a table and chair allocation for accommodating their customers on a daily basis. This problem scales significantly with the introduction of constraints, such as scenario obstacles or the requirement of a minimum distance separation. The TLP (Table Location Problem) and the CLP (Chair Location Problem) are NP-Hard complexity problems that aim to attain the optimal table and chair distribution for certain applications. Existing approaches to this problem fail to address both the TLP and CLP simultaneously, thus resulting in suboptimal solutions achieved by imposing optimization constraints. Therefore, in this paper, a sequential optimization methodology based on a GBLS MA (Gradient-Based Local Search Memetic Algorithm) optimizations is proposed for optimizing the table and chair disposition simultaneously while also considering scenario and distancing restrictions. The proposed methodology is then implemented into a realistic establishment, where different optimization strategies within the CLP are compared. Results prove the viability and flexibility of the proposed sequential optimization for complex hostelry scenarios.

Functional network disruptions in youth with concussion using the Adolescent Brain Cognitive Development study

ABSTRACT Objective This study aimed to compare psychosocial outcomes and functional neuroimaging among youth with concussion, youth with anxiety, and age- and sex-matched controls. Methods Using archival data from the Adolescent Brain Cognitive DevelopmentSM Study, we analyzed between-group differences in psychosocial outcomes measured by the Child Behavior Checklist’s internalizing and externalizing problem scales, and assessed brain function using resting-state fMRI network-region connectivity (specifically frontoparietal network (FPN) and default mode network (DMN) connectivity with the amygdala). Results Significant differences in psychosocial outcomes were found across all groups, with the anxiety group reporting the most internalizing problems, followed by the concussion group which significantly differed from controls. Additionally, FPN-amygdala connectivity was significantly reduced in the concussion group only; this reduced connectivity did not predict psychosocial outcomes across groups. Conclusion This study provided preliminary findings that brain connectivity is reduced exclusively in individuals with concussion. Although disruptions were observed in the concussion group, further investigation is warranted to understand how disruptions may be associated with concussion symptoms. Studies that utilize well-defined control and study groups, and comprehensive cognitive and mental health measures will offer a deeper understanding of the relationship between brain function and psychosocial outcomes.

Beyond the Bite: Exploring Mental Health of Dental Faculty in Pakistan– a multi-institutional study

IntroductionMental health issues are being reported increasingly amongst healthcare staff and students globally. The aim of this study was to investigate the frequency of common mental health issues amongst dental faculty members at multiple institutions in Pakistan.MethodsFollowing approval from the institutional ethics review board, dental faculty members at 14 dental institutions were invited to participate in an online survey based on globally validated scales for mental health problems including the Patient Health Questionnaire (PHQ-9), and the Depression, Anxiety, and Stress Scale (DASS-21). Two open-ended questions were included in the survey to identify perceived factors contributing to poor mental health and recommendations for improving institutional support.ResultsA total of 200 faculty members out of provided their responses to the survey questionnaire but complete responses were provided by 183 participants which included 120 (65.57%) females, and 63 (34.43%) males. The total number of faculty members at the participating institutions was 426 and 183 responses translated into an overall response rate of 43%. Most participants were in the 31–40 years age-group (n = 81, 44.26%) followed by 25–30 year (n = 51, 22.87%) and 41–50 years (n = 40, 21.86%). The mean score on PHQ-9 was 6.51 (SD ± 5.4) while the mean DASS-21 score was 13.04 (SD ± 10.95). PHQ-9 Depression, and DASS-21 Depression, Anxiety, and Stress scores were all significantly positively correlated for the whole sample, and within each subgroup of each demographic factor. Job-related workload, lack of institutional support, financial limitations, and poor work life balance were identified as the main factors contributing adversely to the mental health of the participants.DiscussionThis study provides useful insights into the scale of mental health status amongst dental faculty members at 14 institutions in Pakistan. Underlying factors affecting the mental health of faculty members adversely were identified and recommendations are provided to address these challenges.

Eating Problems in Young Adults: The Role of Unbalanced Family Cohesion and Difficulties in Emotion Regulation

Strong emotional bonds with the family often result in many positive consequences for human functioning, including emotional regulation and eating patterns. The study aimed to determine the relationship between unbalanced family cohesion, emotion regulation, and eating problems in young adults. A correlation research design was used with a non-probability purposive sampling technique to recruit a sample consisting of 300 university students, 50% men and 50% women, with an age range from 18 to 25 years ( M = 21.60, SD = 1.95) from the four universities of Lahore. Demographic performa, Family Cohesion Scale (FCS), Difficulties in Emotion Regulation Scale (DERS), and Eating Problem Scale (EPS) were used to explore the study variables. Data was analyzed using SPSS 21. Pearson product-moment correlation indicated a significant positive relationship between unbalanced family cohesion, difficulties in emotion regulation, and eating problems. It also revealed that a positive relationship was found among unbalanced family cohesion, difficulties in emotion regulation, and eating problems in young adults. Mediation analysis shows that emotion regulation fully mediates the relationship between unbalanced family cohesion and eating problems in young adults. The findings will help students and family counselors identify risk factors of eating problems and its impact on their transition into marriage life. They will contribute to a deeper understanding of unbalanced family dynamics, difficulties in emotion regulation, and eating problems.

학교폭력 가해자에 대한 경찰다이버전 정책 기반 다중체계치료 사례연구

Objectives This purpose of the study was conducted to explore the effectiveness of Multisystemic Therapy for school violence perpetrators as part of the police diversion policy. Methods The subject of the study was a 14-year-old male student who was reported to have school violence, which is extortion and intimidation, and was released on the condition of participating MST. In accordance with the multisystemic therapy manual, five key goals were derived by analyzing risk factors for adolescents' problematic behaviors through evaluation of various systems surrounding him. An intervention strategies were established to achieve the core goals(i.e., stop smoking and alcohol, controlled use of SNS, making pro-social friends, stay away from delinquents, promoting positive parenting skills of parents). The essential parts of MST as like the therapy team, the visiting service, and weekly supervision were implemented. In order to measure pre-post changes, Children Behavior Checklist 6-18, the Parenting Stress Index, the Parenting Attitude Test, and the MMPI-A were conducted. The package of scales was implemented at 3 points as pre-time, post-time, and 8 months follow-up. Results First of all, the level of the externalization problem scale of CBCL 6-18, which was at the clinical range at the pre-test, recovered to the level of the normal range in the post-test, and these results were maintained even at the 8 months follow-up. Regarding MMPI-A, the score was lowered by nearly 2 standard deviations in the scale of Pd compared to pre-test. Then, parenting stress decreased and positive parenting attitudes of parents increased. In addition, all the five core goals were achieved. Conclusions The results of this study showed that multisystemic therapy for school violence perpetrator can help decrease adolescents’ problematic behaviors including school violence.

Derivative dynamic time warping algorithm with introduced correction for varying load fault diagnosis of nuclear power system steam turbine units

The Derivative Dynamic Time Warping (DDTW) algorithm is improved to address the multi-parameters time series classification problem faced by nuclear power system steam turbine units varying load fault diagnosis. Firstly, the entire load changing process is treated as a single sample rather than multiple time-step-samples. This ensures the complete information on the load changing processes, while avoiding interference from normal data fluctuations during faults. Secondly, Time Series Position Coefficient and Time Series Length Coefficient are proposed to correct the DDTW algorithm from two perspectives: the sequences lengths and the data positions in the sequences. This solves the singularities and timeline scaling problems, thereby preventing interference introduced by data sequences' lengths differences and ''similar data appearing at different times'' problem. The nuclear power system steam turbine unit simulation model was built to obtain load changing processes data under normal and faults statuses. In the varying load fault diagnosis test based on these data, the improved DDTW algorithm achieved an accuracy of 1.38%–12.06% higher than other methods, reaching 87.50%. Finally, The Deep Convolutional Generative Adversarial Networks (DCGAN) model was used to generate data to supplement the limited samples of complete load changing processes, and the accuracy of the novel method increased to 95.51% with the increase of data used to support the comparison.