Comparing three short questionnaires to detect psychosocial problems among 3 to 4-year olds

Background: Validated questionnaires help community pediatric services to identify psychosocial problems. Our aim was to assess which of three short questionnaires was most suitable for this identification among pre-school children. Methods: We included 1,650 children (response 64 %) aged 3-4 years undergoing routine well-child health assessments in 18 services across the Netherlands. Child healthcare professionals (CHPs) interviewed and examined children and parents. Parents were randomized regarding filling out the Strengths and Difficulties Questionnaire (SDQ) or the KIPPPI, a Dutch-origin questionnaire. In addition, all filled out the Ages and Stages Questionnaires: Social-Emotional (ASQ:SE) and the Child Behavior Checklist (CBCL). We assessed the internal consistency and validity of each questionnaire, with CBCL and treatment status as criteria, and the degree to which each questionnaire could improve identification based solely on clinical assessment. Results: The internal consistency of the total problems scale of each questionnaire was satisfactory, Cronbach's alphas varied between 0.75 and 0.98. Only the SDQ discriminated sufficiently between children with and without problems as measured by the CBCL (sensitivity = 0.76 at a cut-off point with specificity = 0.90), in contrast to the other two questionnaires (with sensitivity indices varying between 0.51-0.63). Similar results were found for the treatment status criterion, although sensitivity was lower for all questionnaires. The SDQ seemed to add most to the identification of psychosocial problems by CHPs, but the differences between the SDQ and the ASQ: SE were not statistically significant. Conclusions: The SDQ is the best tool for the identification of psychosocial problems in pre-school children by community paediatric services

Measuring determinants of implementation behavior: psychometric properties of a questionnaire based on the theoretical domains framework

BACKGROUND: To be able to design effective strategies to improve healthcare professionals’ implementation behaviors, a valid and reliable questionnaire is needed to assess potential implementation determinants. The present study describes the development of the Determinants of Implementation Behavior Questionnaire (DIBQ) and investigates the reliability and validity of this Theoretical Domains Framework (TDF)-based questionnaire. METHODS: The DIBQ was developed to measure the potential behavioral determinants of the 12-domain version of the TDF (Michie et al., 2005). We identified existing questionnaires including items assessing constructs within TDF domains and developed new items where needed. Confirmatory factor analysis was used to examine whether the predefined structure of the TDF-based questionnaire was supported by the data. Cronbach’s alpha was calculated to assess internal consistency reliability of the questionnaire, and domains’ discriminant validity was investigated. RESULTS: We developed an initial questionnaire containing 100 items assessing 12 domains. Results obtained from confirmatory factor analysis and Cronbach’s alpha resulted in the final questionnaire consisting of 93 items assessing 18 domains, explaining 63.3% of the variance, and internal consistency reliability values ranging from .68 to .93. Domains demonstrated good discriminant validity, although the domains ‘Knowledge’ and ‘Skills’ and the domains ‘Skills’ and ‘Social/professional role and identity’ were highly correlated. CONCLUSIONS: We have developed a valid and reliable questionnaire that can be used to assess potential determinants of healthcare professional implementation behavior following the theoretical domains of the TDF. The DIBQ can be used by researchers and practitioners who are interested in identifying determinants of implementation behaviors in order to be able to develop effective strategies to improve healthcare professionals’ implementation behaviors. Furthermore, the findings provide a novel validation of the TDF and indicate that the domain ‘Environmental context and resources’ might be divided into several environment-related domains

Quantitative and temporal approach to utilising electronic medical records from general practices in mental health prediction

This study proposes a framework for mining temporal patterns from Electronic Medical Records. A new scoring scheme based on the Wilson interval is provided to obtain frequent and predictive patterns, as well as to accelerate the mining process by reducing the number of patterns mined. This is combined with a case study using data from general practices in the Netherlands to identify children at risk of suffering from mental disorders. To develop an accurate model, feature engineering methods such as one hot encoding and frequency transformation are proposed, and the pattern selection is tailored to this type of clinical data. Six machine learning models are trained on five age groups, with XGBoost achieving the highest AUC values (0.75–0.79) with sensitivity and specificity above 0.7 and 0.6 respectively. An improvement is demonstrated by the models learning from patterns in addition to non-temporal features

Identification of children at risk for mental health problems in primary care—Development of a prediction model with routine health care data

Background: Despite being common and having long lasting effects, mental health problems in children are often under-recognised and under-treated. Improving early identification is important in order to provide adequate, timely treatment. We aimed to develop prediction models for the one-year risk of a first recorded mental health problem in children attending primary care. Methods: We carried out a population-based cohort study based on readily available routine healthcare data anonymously extracted from electronic medical records of 76 general practice centers in the Leiden area, the Netherlands. We included all patients aged 1–19 years on 31 December 2016 without prior mental health problems. Multilevel logistic regression analyses were used to predict the one-year risk of a first recorded mental health problem. Potential predictors were characteristics related to the child, family and healthcare use. Model performance was assessed by examining measures of discrimination and calibration. Findings: Data from 70,000 children were available. A mental health problem was recorded in 27•7% of patients during the period 2007–2017. Age independent predictors were somatic complaints, more than two GP visits in the previous year, one or more laboratory test and one or more referral/contact with other healthcare professional in the previous year. Other predictors and their effects differed between age groups. Model performance was moderate (c-statistic 0.62–0.63), while model calibration was good. Interpretation: This study is a first promising step towards developing prediction models for identifying children at risk of a first mental health problem to support primary care practice by using routine healthcare data. Data enrichment from other available sources regarding e.g. school performance and family history could improve model performance. Further research is needed to externally validate our models and to establish whether we are able to improve under-recognition of mental health problems

Factors associated with the identification of child mental health problems in primary care—a systematic review

Background: Although common and often with long-lasting effects, child mental health problems (MHPs) are still under-recognized and under-treated. A better understanding of the factors associated with the identification of MHPs in primary care may improve the recognition of MHPs. Objectives: To review studies on factors associated with the identification of child MHPs in primary care. Methods: Six leading databases were systematically searched until 1 October 2018. Two independent researchers selected articles and extracted data on study characteristics and factors associated with MHP identification. Inclusion criteria were the investigation of factors associated with MHP identification by primary care professionals (PCPs) in children aged 0–18 years. Results: Of the 6215 articles identified, 26 were included. Prevalence rates of PCP-identified MHPs varied between 7 and 30%. PCPs identified 26–60% of children with an increased risk of MHPs as indicated by MHP assessment tools, but associated factors were investigated in relatively few studies. MHPs were more often identified in children with a family composition other than married parents, with worse mental health symptoms, prior MHPs, among boys in elementary school, when contact with PCPs was related to parental psychosocial concerns or routine health check-ups, when PCPs were recently trained in MHPs or when PCPs felt less burdened treating MHPs. Conclusion: MHP identification varied substantially between studies and PCPs and was related to several child, family and practice factors. Future studies should systematically investigate factors associated with MHP identification by PCPs and specifically in children with an increased risk of MHPs according to mental health assessment tools

Smoking cessation strategy in the national cervical cancer screening program (SUCCESS): study protocol for a pragmatic cluster randomised trial and process evaluation in Dutch general practice

INTRODUCTION: Cervical cancer screening in general practice could be a routine moment to provide female smokers with stop smoking advice and support. The aim of this study is to assess the effect of a stop smoking strategy delivered by trained practice assistants after the cervical smear, and to evaluate the implementation process. METHODS AND ANALYSIS: The study is a two-arm, pragmatic cluster randomised trial, in Dutch general practice. Randomisation takes place 1:1 at the level of the general practice. Practices either deliver the SUCCESS stop smoking strategy or the usual care condition. The strategy consists of brief stop smoking advice based on the Ask-Advise-Connect method and is conducted by trained practice assistants after routine cervical cancer screening. The primary outcome is the performance of a serious quit attempt in the 6 months after screening. Secondary outcomes are 7-day point prevalence abstinence, reduction in the number of cigarettes per day and transition in motivation to quit smoking. Follow-up for these measurements takes place after 6 months. Analysis on the primary outcome aims to detect a 10% difference between treatment arms (0.80 power, p=0.05, using a one-sided test), and will be performed according to the intention to treat principle. The process evaluation will assess feasibility, acceptability and barriers or enablers to the strategy's implementation. For this purpose, both qualitative and quantitative data will be collected via questionnaires and in-depth interviews, respectively, in both individual study participants and involved staff. ETHICS AND DISSEMINATION: The Dutch Ministry of Health, Welfare and Sport approved of the trial after an advisory report from the Health Council (Nr. 2018/17). A licence was provided to conduct the study under the Population Screening Act. Study results will be disseminated through publications in peer-reviewed journals and conference presentations. TRIAL REGISTRATION NUMBER: NL5052 (NTR7451)

A stitch in time saves nine? A repeated cross-sectional case study on the implementation of the intersectoral community approach Youth at a Healthy Weight Health behavior, health promotion and society

Background: The implementation of programs complex in design, such as the intersectoral community approach Youth At a Healthy Weight (JOGG), often deviates from their application as intended. There is limited knowledge of their implementation processes, making it difficult to formulate sound implementation strategies. Methods: For two years, we performed a repeated cross-sectional case study on the implementation of a JOGG fruit and water campaign targeting children age 0-12. Semi-structured observations, interviews, field notes and professionals' logs entries were used to evaluate implementation process. Data was analyzed via a framework approach; within-case and cross-case displays were formulated and key determinants identified. Principles from Qualitative Comparative Analysis (QCA) were used to identify causal configurations of determinants per sector and implementation phase. Results: Implementation completeness differed, but was highest in the educational and health care sector, and higher for key than additional activities. Determinants and causal configurations of determinants were mostly sector- and implementation phase specific. High campaign ownership and possibilities for campaign adaptation were most frequently mentioned as facilitators. A lack of reinforcement strategies, low priority for campaign use and incompatibility of own goals with campaign goals were most often indicated as barriers. Discussion: We advise multiple 'stitches in time'; tailoring implementation strategies to specific implementation phases and sectors using both t