AIMC Topic: Self Efficacy

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Constructing a Predictive Model for Psychological Distress of Young- and Middle-Aged Gynaecological Cancer Patients.

Journal of evaluation in clinical practice Feb 1, 2025
BACKGROUND: Cancer patients experience substantial psychological distress which causes the reduction of the quality of life. However, the risk of psychological distress has not been well predicted especially in young- and middle-aged gynaecological c...
Stress, Psychological ROC Curve Quality of Life Self Efficacy Genital Neoplasms, Female Psychological Distress Logistic Models Age Factors Young Adult Adult Cross-Sectional Studies Middle Aged Female Risk Factors Humans Neural Networks, Computer
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Can the Use of Artificial Intelligence-Generated Content Bridge the Cancer Knowledge Gap? A Longitudinal Study With Health Self-Efficacy as a Mediator and Educational Level as a Moderator.

Cancer control : journal of the Moffitt Cancer Center Jan 1, 2025
OBJECTIVES: The cancer knowledge gap represents a significant disparity in awareness and understanding of cancer-related information across different demographic groups. Leveraging Artificial Intelligence-Generated Content (AIGC) offers a promising a...
China Surveys and Questionnaires Male Neoplasms Longitudinal Studies Health Education Self Efficacy Health Knowledge, Attitudes, Practice Female Educational Status Young Adult Adult Humans Artificial Intelligence
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Partnering a Compensatory Application with Activity-Aware Prompting to Improve Use in Individuals with Amnestic Mild Cognitive Impairment: A Randomized Controlled Pilot Clinical Trial.

Journal of Alzheimer's disease : JAD Jan 1, 2022
BACKGROUND: Compensatory aids can help mitigate the impact of progressive cognitive impairment on daily living.
Independent Living Reminder Systems Aged Male Middle Aged Quality of Life Humans Female Supervised Machine Learning Activities of Daily Living Self Efficacy Outcome Assessment, Health Care Pilot Projects Cognitive Dysfunction Technology Assessment, Biomedical Surveys and Questionnaires
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Factors Associated with HIV Testing Among Participants from Substance Use Disorder Treatment Programs in the US: A Machine Learning Approach.

AIDS and behavior Feb 1, 2017
HIV testing is the foundation for consolidated HIV treatment and prevention. In this study, we aim to discover the most relevant variables for predicting HIV testing uptake among substance users in substance use disorder treatment programs by applyin...
Condoms Male Comorbidity Safe Sex Mass Screening Substance-Related Disorders Self Efficacy Attitude to Health HIV Infections Logistic Models Drug Users Machine Learning Sexual Behavior United States Female Humans Counseling
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