Validity and reliability of the Swedish version of the Children's Sleep Habits Questionnaire (CSHQ-SWE).

BACKGROUND: To translate and culturally adapt the Children's Sleep Habits Questionnaire (CSHQ) to a Swedish version, CSHQ-SWE, and to assess its validity and reliability for use with children with attention deficit hyperactivity disorder (ADHD). METHODS: A total of 84 children with ADHD (51 boys and 33 girls; 6-12 years) and parents (7 men and 77 women; 28-51 years) were included in the study. CSHQ was translated and culturally adapted to Swedish, and assessed for concurrent validity with sleep actigraphy (analyzed by Kendall's Tau) and for reliability by internal consistency (analyzed by McDonald's Omega H). Face and content validity was evaluated by parents (n = 4) and healthcare professionals (n = 6) qualitatively (comprehensiveness, relevance, and comprehensibility assessed by interviews and analyzed by thematic analysis) and quantitatively (analyzed by content validity ratio and content validity index for 33 items and four non-scored inquiries). RESULTS: Parent-reported sleep problems (CSHQ-SWE total score) were moderately correlated with less "Sleep Efficiency" (Tau = -0.305; p < 0.001) measured by sleep actigraphy. Parent-reported problems with "Sleep Onset Delay" was moderately correlated with measured time for "Sleep Onset Latency" (Tau = 0.433; p < 0.001). Parent-reported problems with "Night Wakings" were weakly correlated with measured time for "Wake After Sleep Onset" (Tau = 0.282; p < 0.001). Parents estimation of "Total daily sleep duration" was moderately correlated with measured "Total Sleep Time" (Tau = 0.386; p < 0.001). Five of the seven subscales reached an acceptable level for internal consistency (McDonald's Omega H > 0.700). Comprehensiveness, relevance, and comprehensibility of CSHQ-SWE were satisfactory overall. Content validity ratio was 0.80 to 1.00 for six items, 0.00 to 0.60 for 22 items, and < 0.00 for nine items. Content validity index was 0.22. CONCLUSIONS: CSHQ-SWE demonstrated acceptable concurrent validity with objectively measured sleep and internal consistency, whereas the overall results of face and content validity assessment varied. The instrument needs to be further evaluated regarding construct validity, responsiveness, test-retest reliability, and its generalization to other populations.

A comprehensive overview of barriers and strategies for AI implementation in healthcare: Mixed-method design.

Implementation of artificial intelligence systems for healthcare is challenging. Understanding the barriers and implementation strategies can impact their adoption and allows for better anticipation and planning. This study's objective was to create a detailed inventory of barriers to and strategies for AI implementation in healthcare to support advancements in methods and implementation processes in healthcare. A sequential explanatory mixed method design was used. Firstly, scoping reviews and systematic literature reviews were identified using PubMed. Selected studies included empirical cases of AI implementation and use in clinical practice. As the reviews were deemed insufficient to fulfil the aim of the study, data collection shifted to the primary studies included in those reviews. The primary studies were screened by title and abstract, and thereafter read in full text. Then, data on barriers to and strategies for AI implementation were extracted from the included articles, thematically coded by inductive analysis, and summarized. Subsequently, a direct qualitative content analysis of 69 interviews with healthcare leaders and healthcare professionals confirmed and added results from the literature review. Thirty-eight empirical cases from the six identified scoping and literature reviews met the inclusion and exclusion criteria. Barriers to and strategies for AI implementation were grouped under three phases of implementation (planning, implementing, and sustaining the use) and were categorized into eleven concepts; Leadership, Buy-in, Change management, Engagement, Workflow, Finance and human resources, Legal, Training, Data, Evaluation and monitoring, Maintenance. Ethics emerged as a twelfth concept through qualitative analysis of the interviews. This study illustrates the inherent challenges and useful strategies in implementing AI in healthcare practice. Future research should explore various aspects of leadership, collaboration and contracts among key stakeholders, legal strategies surrounding clinicians' liability, solutions to ethical dilemmas, infrastructure for efficient integration of AI in workflows, and define decision points in the implementation process.

Changed sleep according to weighted blanket adherence in a 16-week sleep intervention among children with attention-deficit/hyperactivity disorder.

STUDY OBJECTIVES: To examine differences in sample characteristics and longitudinal sleep outcomes according to weighted blanket adherence. METHODS: Children with attention-deficit/hyperactivity disorder (ADHD) (n =94), mean age 9.0 (sd 2.2, range 6-14) participated in a 16-week sleep intervention with weighted blankets (WB). Children were classified as WB adherent (use of WB ≥ 4 nights/week) or non-adherent (use of WB ≤ 3 nights/week). Changes in objectively measured sleep by actigraphy, parent-reported sleep problems (Children's Sleep Habits Questionnaire (CSHQ)) and child-reported Insomnia Severity Index (ISI) were evaluated according to adherence with mixed effect models. Gender, age, and ADHD subtype were examined as potential moderators. RESULTS: Children adherent to WBs (48/94) showed an early response in sleep outcomes and an acceptance of the WB after four weeks of use as well as a decrease in parent- (CSHQ) (-5.73, P = .000) and child-reported sleep problems (ISI) (-4.29, P = .005) after 16 weeks. The improvement in sleep was larger among WB adherent vs. non-adherent (between-group difference: CSHQ: -2.09, P = .038; ISI: -2.58, P =.007). Total sleep time was stable for children adherent to WB but decreased for non-adherent (between-group difference: +16.90, P = .019). CONCLUSIONS: An early response in sleep and acceptance of the WB predicted later adherence to WBs. Improvements in sleep were more likely among WB adherents vs. non-adherents. Children with ADHD may thus benefit from using WBs to handle their sleep problems.

Resilience in children of parents with mental illness, alcohol or substance misuse-An integrative review.

AIM: The aim of this integrative review was to investigate how resilience has been researched and explore experiences of resilience, in children of parents with mental illness or alcohol or substance misuse. DESIGN: An integrative review. METHOD: The search included three major electronic databases, PubMed, Scopus and PsycINFO with the aim of identifying peer-reviewed studies where the concept of resilience was explored as resilience, coping, adaptation or protective factors. RESULTS: Out of 4016 studies, 14 were included after meeting predetermined criteria and methodological quality evaluation. The findings are presented in five categories: characteristics of the studies, operationalization and interpretation of resilience, individual resources, family resources and resources outside the family. PATIENT OR PUBLIC CONTRIBUTION: Resilience in children of parents with mental illness or substance misuse refers to coping strategies, protective factors and absence of symptoms or risk behaviour despite being exposed to risk. We suggest a three-level approach for mapping of resilience resources in the target group: the individual level, family level and outside of the family that includes both non-professionals and professionals. The use of disengagement or avoidance strategies implies poor resilience but may be necessary in absence of support, as acts of self-preservation during chaotic periods or harmful situations.

Sex Differences in Children with Uncomplicated Attention Deficit/Hyperactivity Disorder and Sleep Problems.

BACKGROUND: Approximately 7.6% of children are diagnosed with attention deficit/hyperactivity disorder (ADHD), and sleep impairments affect 25-85%. There is a noticeable lack of research on girls and sex differences. The aim of this study was to examine sex differences in children with uncomplicated ADHD and sleep problems. METHODS: Cross-sectional baseline data were retrieved from a randomized controlled trial with weighted blankets (55 boys and 41 girls, 6-14 years) on a cohort recently diagnosed with uncomplicated ADHD and sleep problems. Differences between boys and girls in ADHD symptoms, objectively and subjectively measured sleep, anxiety, and functioning were examined via parent- or self-reported validated instruments. RESULTS: Girls reported significantly lower (worse) satisfaction with well-being, life overall, and school, but not for family. Parents reported more sleep anxiety and night-time wakings among boys, but no sex differences in other measures and also not in self-reported measures or objective sleep measures. Children who reported worry, sadness, or unhappiness had more sleep problems. CONCLUSIONS: Boys with ADHD and sleep problems may need support with sleep-related anxiety and night-time wakings, while girls may require support with overall functioning. Additionally, children who express feelings of worry, sadness, or unhappiness alongside their ADHD symptoms should have attention given to their sleep.

Towards evidence-based practice 2.0: leveraging artificial intelligence in healthcare.

Background: Evidence-based practice (EBP) involves making clinical decisions based on three sources of information: evidence, clinical experience and patient preferences. Despite popularization of EBP, research has shown that there are many barriers to achieving the goals of the EBP model. The use of artificial intelligence (AI) in healthcare has been proposed as a means to improve clinical decision-making. The aim of this paper was to pinpoint key challenges pertaining to the three pillars of EBP and to investigate the potential of AI in surmounting these challenges and contributing to a more evidence-based healthcare practice. We conducted a selective review of the literature on EBP and the integration of AI in healthcare to achieve this. Challenges with the three components of EBP: Clinical decision-making in line with the EBP model presents several challenges. The availability and existence of robust evidence sometimes pose limitations due to slow generation and dissemination processes, as well as the scarcity of high-quality evidence. Direct application of evidence is not always viable because studies often involve patient groups distinct from those encountered in routine healthcare. Clinicians need to rely on their clinical experience to interpret the relevance of evidence and contextualize it within the unique needs of their patients. Moreover, clinical decision-making might be influenced by cognitive and implicit biases. Achieving patient involvement and shared decision-making between clinicians and patients remains challenging in routine healthcare practice due to factors such as low levels of health literacy among patients and their reluctance to actively participate, barriers rooted in clinicians' attitudes, scepticism towards patient knowledge and ineffective communication strategies, busy healthcare environments and limited resources. AI assistance for the three components of EBP: AI presents a promising solution to address several challenges inherent in the research process, from conducting studies, generating evidence, synthesizing findings, and disseminating crucial information to clinicians to implementing these findings into routine practice. AI systems have a distinct advantage over human clinicians in processing specific types of data and information. The use of AI has shown great promise in areas such as image analysis. AI presents promising avenues to enhance patient engagement by saving time for clinicians and has the potential to increase patient autonomy although there is a lack of research on this issue. Conclusion: This review underscores AI's potential to augment evidence-based healthcare practices, potentially marking the emergence of EBP 2.0. However, there are also uncertainties regarding how AI will contribute to a more evidence-based healthcare. Hence, empirical research is essential to validate and substantiate various aspects of AI use in healthcare.

SoCap YMH - youth mental health, social capital and help-seeking: a study protocol.

Background: The increase in adolescents reporting mental health problems presents a major public health challenge. The complex association between mental health and social capital motivates further investigation of social capital as a crucial aspect in shaping adolescents' help-seeking knowledge, attitudes, and behaviours. Aim: This protocol presents a project that aims to investigate social capital in relation to help-seeking and mental health in close collaboration with adolescents and key stakeholders in the school setting, in the southern part of Sweden. Methods: A mixed-method design with three interconnected work packages (WP) will be undertaken with an emphasis on co-production where adolescents are involved throughout the process. WP1 is a development and validation of two questionnaire instruments for assessing social capital and help-seeking in adolescence. WP2 is a longitudinal quantitative study involving 1,500 adolescents from two regions representing rural and suburban/urban settings. Adolescents aged 15 will be asked to complete questionnaires concerning social capital, mental health, and help-seeking in a baseline and one-year follow-up, allowing for investigation of the role of social capital for help-seeking. WP3 is designed to elucidate experiences and knowledge of adolescents and key stakeholders via collaborative World Café workshops. These will be held along the project to evolve the generated knowledge and maximize it's applicability during and after the project is finalized. Conclusion: The results are expected to further the understanding of the relationship between adolescents' social capital, mental health, and help-seeking, to contribute to a deeper understanding of the mechanisms behind the paradoxical help-seeking patterns among adolescents today and to narrow the gap between research and practice to produce sustainable and efficient strategies, which may facilitate help-seeking and improve the mental health of adolescents within existing organizational structures.