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PubMed1975

Fluid and crystallized intelligence in young adulthood and old age.

The theory of fluid and crystallized intelligence predicts that the relationship between these two abilities will decline systematically across the age span after young adulthood. In order to test this hypothesis in an elderly sample, the Raven Progressive Martices and the WAIS vocabulary subtest were administered to a sample of individuals (N=40), ranging in age from 60 to 79, and also, for purposes of comparison, to a sample of young adults (N=35). It was found that the correlation was significantly lower in the elderly sample (.386) than in the young adult sample (.672).

Adult↗

PubMed2005

Breech delivery and intelligence: a population-based study of 8,738 breech infants.

OBJECTIVE: Long-term intellectual performance in breech-presented infants may be negatively affected by vaginal delivery. We evaluated the effect of presentation at birth and delivery mode on intellectual performance at age 18 years in a nationwide population study. METHODS: We studied 8,738 male infants in breech and 384,832 males in cephalic presentation registered in the Medical Birth Registry of Norway, 1967-1979, and linked to data registered at the National Conscript Service, 1984-1999. Test scores of intelligence testing at conscription were presented as standard nine ("stanine") scores. Mean stanine scores and odds ratios of low score were computed and adjusted for birth order, maternal age, and education. RESULTS: Mean stanine score was slightly higher among breech-presented males than among cephalic-presented males (5.26 versus 5.22, P = .05), whereas after adjustment the difference disappeared (P = .3). Breech-presented infants had lower mean scores if delivered by cesarean compared with vaginal breech delivery (P = .03), and cephalic-presented males scored lower if their mothers had a cesarean delivery instead of a vaginal delivery (P < .001). Comparing cesarean and vaginal delivery in breech births, the odds ratio of having a stanine score less than or equal to 3 was 1.12 (95% confidence interval 0.92,1.36), after adjustment for confounding factors. CONCLUSION: Presentation at birth did not affect adult intellectual performance. Cesarean delivery of breech-presented infants did not improve adult intellectual performance when compared with a vaginal delivery. The excess perinatal hazards of breech-presented infants with a vaginal delivery were not reflected in adult intellectual performance.

Adolescent↗

PubMed2026

Artificial intelligence in kidney cancer: a review of clinical applications across the disease spectrum.

PURPOSE OF REVIEW: This review examines recent advances (2024-2025) in the application of artificial intelligence (AI) to kidney cancer diagnosis, prognosis, and treatment planning. It categorizes studies across 13 clinical scenarios to assess where AI offers the most clinical utility. RECENT FINDINGS: AI models have demonstrated strong performance in a range of tasks including tumor grading, subtype classification, survival prediction, and risk stratification. Integration of radiomics, genomics, and histopathology has enabled personalized, noninvasive, and timely decision-making. The highest-performing models used CT-based radiomics, particularly for predicting progression-free and recurrence-free survival. However, performance varies across tasks and tumor subtypes, with lower accuracy in detecting oncocytomas or benign vs. malignant differentiation. AI applications in metastatic and nonresected cases remain underexplored, and ultrasound remains a largely under researched modality. While some models improve diagnostic accuracy and workflow efficiency, broader validation across diverse populations is still needed. SUMMARY: AI is transforming kidney cancer care across multiple clinical stages. Although promising, real-world implementation demands ongoing validation and postdeployment monitoring to prevent performance degradation due to distributional drift. AI's integration with multimodal data offers substantial potential to improve outcomes and reduce overtreatment.

Humans↗

PubMed2026

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.

Belgium↗

PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗

PubMed2026

Development and Crossover Evaluation of an Artificial Intelligence-Assisted System for Solid Pancreatic Lesion Detection and Pancreatic Parenchyma Recognition in Endoscopic Ultrasonography (With Video).

BACKGROUND AND STUDY AIMS: Pancreatobiliary endoscopic ultrasonography (EUS) is technically demanding, and supervised training opportunities are limited. We developed an artificial intelligence (AI) overlay system for detecting solid pancreatic lesions (SPL) and recognizing pancreatic parenchyma (PP) and evaluated its effect on reader performance. PATIENTS AND METHODS: Across six centers, two deep learning-based models were trained using expert-annotated EUS frames. We then conducted a randomized, two-sequence, two-period crossover reader study in which eight endosonographers (five novices and three experts) interpreted image sets with and without AI assistance. The primary endpoint was superiority of sensitivity for SPL detection among novices; key secondary endpoints included specificity and PP recognition. RESULTS: From 118 patients, 120 SPL-positive/negative image sets and 160 PP-positive/negative image sets were constructed. Among novices, AI assistance improved SPL detection sensitivity (88.7% vs. 76.8%, p < 0.001) and accuracy (86.4% vs. 78.7%), while specificity met the predefined noninferiority criterion (84.2% vs. 80.5%, p < 0.001). For PP recognition, sensitivity increased numerically (86.3% vs. 83.3%) but did not meet the predefined superiority criterion (p = 0.095); specificity met the noninferiority criterion (87.8% vs. 81.0%), and accuracy increased from 82.1% to 87.0%. Among experts, sensitivity was maintained for both tasks, whereas specificity increased with AI assistance. CONCLUSIONS: AI assistance improved SPL detection among novice endosonographers. For PP recognition, sensitivity increased without reaching statistical superiority, whereas specificity met the predefined noninferiority criterion. These findings support a potential adjunctive role for AI in EUS interpretation.

Humans↗

PubMed1995

Event-related potentials (ERPs) and intelligence in neonatally identified 47,XXY males.

The event-related potentials (ERPs) of 18 extra X males (mean age 18.1 years) were recorded during the course of phonemic and orthographic discrimination tasks. The N2 and P3 latencies and amplitudes of subjects were examined in relation to their verbal and nonverbal intelligence test scores based on assessments at three ages: prior to puberty, during puberty and at sexual maturity. The results indicated that verbal abilities at most test occasions were significantly related to P3 latencies. Nonverbal abilities were largely uncorrelated with ERPs. The findings suggest that the verbal deficits of extra X males are the result of unlateralized individual differences in neural cognitive processing.

Adolescent↗

PubMed1993

Stability of intelligence from preschool to adolescence: the influence of social and family risk factors.

Intelligence scores of children in a longitudinal study were assessed at 4 and 13 years and related to social and family risk factors. A multiple environmental risk score was calculated for each child by counting the number of high-risk conditions from 10 risk factors: mother's behavior, mother's developmental beliefs, mother's anxiety, mother's mental health, mother's educational attainment, family social support, family size, major stressful life events, occupation of head of household, and disadvantaged minority status. Multiple risk scores explained one-third to one-half of IQ variance at 4 and 13 years. The stability between 4- and 13-year environmental risk scores (r = .77) was not less than the stability between between 4- and 13-year IQ scores (r = .72). Effects remained after SES and race, or maternal IQ, were partialled; multiple risk was important in longitudinal prediction, even after prior measurement of child IQ was accounted for; the pattern of risk was less important than the total amount of risk present in the child's context.

Adolescent↗

PubMed2006

Associations between volume of alcohol consumption and social status, intelligence, and personality in a sample of young adult Danes.

Relatively few studies have investigated associations between volume of alcohol consumption and psychological characteristics in normal samples. A sub-sample, comprising 363 men and 331 women between 29 and 34 years of age, was selected from the Copenhagen Perinatal Cohort on the basis of perinatal records. The sample was divided into four consumption categories: abstainers (including occasional drinkers), light, moderate, and risk drinkers. ANOVA and relevant contrasts were used to test the significance of differences among consumption categories. Both abstaining and risk drinking were associated with low social status family background, low education and intelligence. Abstaining was associated with low disinhibition and social recognition scores, while risk drinking was associated with high neuroticism and, in males, high disinhibition, low social recognition, and low achievement scores. Compared with light drinkers, a more "carefree" life orientation characterized male moderate drinkers, while relatively high scores on anxiety, dysthymia, and somatoform symptom scales characterized female moderate drinkers.

Adult↗

PubMed1986

Estimation of premorbid intelligence in dementia.

Thirty elderly subjects with dementia were assessed using a neuropsychological test battery. Using four cognitive and behavioural measures of severity of dementia, no significant relationships between National Adult Reading Test (NART) or Mill Hill Vocabulary Scale synonym section (MHVS) scores and severity were observed. The NART and MHVS correlated with each other to a highly significant degree. No differences were observed on any of the measures when patients with Alzheimer's disease were compared with those adjudged to have multi-infarct dementia. These results are discussed in relation to the existing literature on the estimation of premorbid intelligence in dementia.

Aged↗

PubMed1993

Intelligence, previous convictions and interrogative suggestibility: a path analysis of alleged false-confession cases.

The main purpose of this study was to investigate the relationship between interrogative suggestibility and previous convictions among 108 defendants in criminal trials, using a path analysis technique. It was hypothesized that previous convictions, which may provide defendants with interrogative experiences, would correlate negatively with 'shift' as measured by the Gudjonsson Suggestibility Scale (Gudjonsson, 1984a), after intelligence and memory had been controlled for. The hypothesis was partially confirmed and the theoretical and practical implications of the findings are discussed.

Adult↗

PubMed1976

Parent-offspring resemblances in intelligence: theories and evidence.

A review of data on parent-offspring resemblances in intelligence is presented in the context of correlation, regression and variance predictions from the polygenic model and an environmental model. Consideration was given to reliability, test equivalence and long-term stability of IQ scores. Results indicate that much of the difference among offspring IQ scores is not directly attributable to parental IQ, and that some is due to other between-family variables. The magnitude of single-parent-offspring correlations was related to the degree of assortative mating present in samples. Evidence on whether parent-offspring resemblances in IQ are transmitted genetically or environmentally is on the whole lacking. A single study provides evidence for some degree of genetic transmission, but it is argued that the present polygenic model is inadequate.

Age Factors↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗

PubMed1970

Intelligence quotient pattern over age: comparisons among siblings and parent-child pairs.

Comparisons between sibling and parent-child pairs with unrelated control pairs matched for year of birth and parental education were made to determine the relative heritability of the general level of intelligence quotient as opposed to that of the sequential pattern of IQ change over age (3 to 12 years). There was greater similarity among related siblings relative to matched controls for general level than for pattern of IQ over age. Relationships between the IQ's of children and that of their parents as children were not consistent across age.

Age Factors↗

PubMed1971

Intelligence and blood pressure in the aged.

Diastolic hypertension was related to significant intellectual loss over a 10-year period among individuals initially examined in their 60's. Such loss was not found in their age peers in association with normal or mild elevations of blood pressure. Of the subjects initially examined at 70 to 79 years of age, none with hypertension completed the follow-up program, and those with normal and mildly elevated blood pressure showed some intellectual decline over the decade. At the initial examination, hypertension was related to lower intelligence test scores only among those subjects who subsequently did not complete the follow-up program. The results suggest that hypertension is related to intellectual changes among the aged.

Aged↗

PubMed1998

Intelligence and development in Aarskog syndrome.

AIM: To test the hypothesis that overall intelligence quotient (IQ) is decreased in patients with Aarskog syndrome. METHODS: 21 boys under 17 years of age with a confirmed clinical diagnosis of Aarskog syndrome were assessed using the Griffiths mental development scales and the British ability scales. RESULTS: IQ ranged from 68 to 128 and followed a normal distribution. CONCLUSION: This study does not support the hypothesis that Aarskog syndrome is associated with a lowering of mean IQ.

Adolescent↗

PubMed2026

Emulated trial of artificial intelligence use and subsequent depressive outcomes in a survey of US adults.

BACKGROUND: Generative artificial intelligence (AI) use has been suggested to have adverse mental health consequences but a causal relationship has not been examined. OBJECTIVE: To simulate a randomised controlled trial of AI use in a work, school or personal context by applying target trial emulation to multiple waves of data from a nationally representative survey. METHODS: We conducted a target trial emulation using non-probability survey data from three waves of a nationally representative survey conducted between 18 June 2024 and 8 January 2025. Participants aged ≥18 years reported generative AI use frequency at baseline. High-frequency use was defined as multiple times per week or more. The primary outcome was depressive symptom severity measured using the Patient Health Questionnaire 9-item (PHQ-9) at follow-up. Generalised causal forests assessed heterogeneity of treatment effects. FINDINGS: Among 19 099 participants assessed at baseline, 2862 (15.0%) reported AI use at least multiple times per week. A subset of 3109 (16.3%) returned for follow-up. In the primary weighted analysis, high-frequency use was not significantly associated with change in PHQ-9 score at follow-up (mean difference -0.18, 95% CI -0.94 to 0.59; p=0.65). Multiple sensitivity analyses using alternate outcome definitions also did not identify significant causal effects. Generalised causal forests yielded no significant evidence of heterogeneity of effect (p=0.81). CONCLUSIONS: In an emulated randomised trial among US adults, generative AI use was not associated with subsequent depressive symptoms. This result does not support the premise that AI use causes greater depressive symptoms, although adverse outcomes among vulnerable individuals cannot be excluded. CLINICAL IMPLICATIONS: AI use is unlikely to cause increased depressive symptoms among most US adults. Continued monitoring should clarify potential risks among vulnerable populations.

Humans↗

PubMed1989

Intelligence and cognitive profile in the fra(X) syndrome: a longitudinal study in 18 fra(X) boys.

A longitudinal study of IQ and cognitive profile in 18 fra(X) positive boys is reported. At the time of diagnosis, four of the boys were mildly retarded, seven were moderately retarded, and five were severely mentally retarded. Intelligence was borderline in one child and normal in another. A decline in intellectual performance with age in the fra(X) syndrome indicated in previous studies was not confirmed and we review the reported data on this subject.

Adolescent↗