Aim The aim of this study is to gain more insight into child and environmental factors that influence gross motor development (GMD) of healthy infants from birth until reaching the milestone of independent walking, based on longitudinal research. Background A systematic search was conducted using Scopus, PsycINFO, MEDLINE and CINAHL to identify studies from inception to February 2020. Studies that investigated the association between child or environmental factors and infant GMD using longitudinal measurements of infant GMD were eligible. Two independent reviewers extracted key information and assessed risk of bias of the selected studies, using the Quality in Prognostic Studies tool (QUIPS). Strength of evidence (strong, moderate, limited, conflicting and no evidence) for the factors identified was described according to a previously established classification. Results In 36 studies, six children and 11 environmental factors were identified. Five studies were categorized as having low risk of bias. Strong evidence was found for the association between birthweight and GMD in healthy full-term and preterm infants. Moderate evidence was found for associations between gestational age and GMD, and sleeping position and GMD. There was conflicting evidence for associations between twinning and GMD, and breastfeeding and GMD. No evidence was found for an association between maternal postpartum depression and GMD. Evidence for the association of other factors with GMD was classified as ‘limited’ because each of these factors was examined in only one longitudinal study. Conclusion Infant GMD appears associated with two child factors (birthweight and gestational age) and one environmental factor (sleeping position). For the other factors identified in this review, insufficient evidence for an association with GMD was found. For those factors that were examined in only one longitudinal study, and are therefore classified as having limited evidence, more research would be needed to reach a conclusion.
BACKGROUND Seclusion is an intervention widely used in Dutch mental health care. The intervention can be effective in acute situations to avert (further) aggression or self-harm. However, seclusion is also a controversial intervention that may not have any positive effect with regard to symptom improvement. In general patients report negative effects after being secluded e.g. anxiety and having had a traumatic experience.The main reason for seclusion is not manageable aggressive behaviour of a patient. Earlier studies reported several risk factors that may contribute to seclusion, regarding patients’ characteristics, but also with regard to staff characteristics, working protocols and unit characteristics. Because of unequivocally results there is the need for a longitudinal prospective study to examine staff- and unit determinants in association with seclusion.AIMS The objective of this study is to determine which nursing staff and unit characteristics are associated with seclusion following aggression in hospitalized adult psychiatric patients. We hope to create a predictive model to estimate the risk of seclusion on an acute psychiatric ward.METHODS We will conduct a prospective observational study on a closed psychiatric ward of an academic hospital. Patients are aged 18 – 65 years and are admitted when their psychiatric condition leads to an immediate threat to the patient themselves or their surroundings.All nurses on the ward are all qualified nurses and registered in the Dutch registration of healthcare professionals. They are trained every six months in techniques of verbal de-escalation and safe physical restraint. For both nurses and the patients baseline characteristics are monitored. Every shift (day, evening, night) data are gathered on the patients, nurses and unit. Data are retrieved from the electronic patient chart, including information of the Brøset Violence Checklist. Furthermore, the exchange of information among nurses is measured using the Grid instrument. Data will be analysed using multilevel regression analysis. Data will be collected for a period of 2 years, which started January 2013.RESULTS The primary endpoint in our study is the incidence of seclusion. As a secondary endpoint, the duration of the seclusion is measured. These endpoints are measured using the Argus registration system and will be linked to predictors of seclusion, with special focus on the nursing staff- and unit determinants.
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Background The primary objective of this study is to identify which modifiable and non-modifiable factors are independent predictors of the development of chronic pain in patients with acute- or subacute nonspecific idiopathic, non-traumatic neck pain, and secondly, to combine these to develop and internally validate a prognostic prediction model. Methods A prospective cohort study will be conducted by physiotherapists in 30 primary physiotherapy practices between January 26, 2020, and August 31, 2022, with a 6-month follow-up until March 17, 2023. Patients who consult a physiotherapist with a new episode of acute- (0 to 3 weeks) or subacute neck pain (4 to 12 weeks) will complete a baseline questionnaire. After their first appointment, candidate prognostic variables will be collected from participants regarding their neck pain symptoms, prior conditions, work-related factors, general factors, psychological and behavioral factors. Follow-up assessments will be conducted at six weeks, three months, and six months after the initial assessment. The primary outcome measure is the Numeric Pain Rating Scale (NPRS) to examine the presence of chronic pain. If the pain is present at six weeks, three months, and six months with a score of NPRS �3, it is classified as chronic pain. An initial exploratory analysis will use univariate logistic regression to assess the relationship between candidate prognostic factors at baseline and outcome. Multiple logistic regression analyses will be conducted. The discriminative ability of the prognostic model will be determined based on the Area Under the receiver operating characteristic Curve (AUC), calibration will be assessed using a calibration plot and formally tested using the Hosmer and Lemeshow goodness-of-fit test, and model fit will be quantified as Nagelkerke’s R2. Internal validation will be performed using bootstrapping-resampling to yield a measure of overfitting and the optimism-corrected AUC. Discussion The results of this study will improve the understanding of prognostic and potential protective factors, which will help clinicians guide their clinical decision making, develop an individualized treatment approach, and predict chronic neck pain more accurately.
