Tapio Nummi

Do ergonomically designed school workstations decrease musculoskeletal symptoms in children? A 26-month prospective follow-up study.

Workstations at school are among several factors that contribute to musculoskeletal symptoms among school-aged children. The aim of this study was to investigate the effects of ergonomically designed workstations on schoolchildrens musculoskeletal symptoms as compared to conventional workstations. In the first 14-month phase of the study (2002-2003, two schools), 42 from the intervention and 46 from the control school participated. In the total follow-up of 26 months (2002-2004), 23 in the intervention group and 20 in the control group participated. Anthropometrics and musculoskeletal symptoms were measured. In general, the ergonomically designed school workstations did not decrease present neck-shoulder, upper back, low back and lower limbs strain and pain, compared to conventional ones during follow-ups.

The Effect of Parenting Stress on Fathers’ Availability and Engagement

The present study was designed to shed light on the relation between parenting stress, fathers alcohol use, child characteristics and fathers engagement and availability. The study cohort comprised 821 fathers of preschool children in Finland. Parenting stress and childs mood, acceptability and demandingness were related to fathers engagement to the preschooler and to the extent of the fathers availability. Parenting stress began a cycle of alcohol abuse and child-negative characteristics, and eventually led to a decrease in joint father–child activities, fathers feeling of compulsory engagement, daily conflict situations, difficulty in including the child in everyday activities and a reduction in the amount of time spent directly or indirectly together.

Prediction in repeated-measures models with engineering applications

This article focuses on the problem of predicting future measurements on a statistical unit given past measurements on the same and other similar units. We introduce a conditional predictor that uses the information contained in previous measurements. The prediction technique is based on the iterative EM algorithm, but a noniterative variant is also provided. We use the sample-reuse methodology to select an appropriate predictor. The technique is illustrated in three engineering applications. The first considers prediction in the context of marketing for bucking in automatic forest harvesters. In fatigue-crack-growth data, the interest is in predicting the future crack-growth development of the test unit, and the third application concerns evaluation of pulp from the point of view of its papermaking potential.

Estimation in a random effects growth curve model

This paper considers estimation under the growth curve model of Potthoff and Roy (1964) with random effects. Estimation under a multivariate model is also considered. Estimation under incomplete data and estimation of random effects are also discussed. A numerical example of data on bulls is presented to illustrate these techniques.

Prediction in growth curve models using the EM algorithm

Abstract In this paper we suggest a predictor of future observations on a set of individuals. The predictor utilizes previous measurements taken both on individuals for whom a prediction is needed and also on a different set of individuals at various time points. Our approach is based on the method of maximum likelihood and computationally the prediction problem is solved by applying the EM algorithm. Under the model of Potthoff and Roy [8] we have derived an iterative EM predictor and corresponding onestep predictors. The relative performance of these predictors i assessed by crossvalidation in three different data sets and the results are compared with corresponding results reported by C.R. Rao [9]. When predicting only one future measurement, simple first degree polynomial models using observations at the immediate past few time points proved to be most efficient among EM predictors. These predictors also did very well in comparison with a number of various competing predictors investigated by C.R. Rao [9].

Evaluation of serum antibody response to a newly identified B-cell epitope in the minor nucleocapsid protein L2 of human papillomavirus type 16

The aim of this work was to identify B-cell epitopes in the minor nucleocapsid (L2) protein of human papillomavirus (HPV) type 16 and characterization of allied antibody response. Serum samples of 513 individuals (323 women with various degrees of cervical atypia, 150 men and 40 small children) were available for the study. Synthetic peptides overlapping the L2 protein of HPV 16 twice were applied in ELISA for epitope scanning and antibody determination. An HPV 16 L2 derived dodecamer SGYIPANTTIPF (amino acids 391-402) proved to be the major B-cell epitope. Both IgA antipeptide antibody positivity (range 7-28%) and mean IgA antibody levels (range 13.2 EIU to 42.4 EIU, P < 0.05) increased with the degree of cervical atypia, whereas antipeptide IgG antibodies showed an opposite trend. During a 2-years follow-up significantly (P < 0.0005) decreasing IgA antibody levels to the SGYIPANTTIPF peptide were associated with regression of koilocytotic atypia. Analysis of anti-peptide IgA antibodies of 118 women with known HPV type revealed that a majority of positives had HPV 16/18 DNA. It was concluded that antibody response to the newly discovered peptide was partially type- and disease-specific. Our results also suggest an impairment of the IgG but not IgA class antibody response to HPV 16 in patients with persistent cervical HPV infection.

Effect of early working alliance on retention in outpatient substance abuse treatment

This study examined the client–therapist early working alliance effect on retention in outpatient substance abuse treatment. The study was implemented on naturalistic principles adopting a prospective design. Data were collected in southern and western Finland in a multisite clinical trial including outpatient treatment units (N = 7). The sample consisted of clients (N = 327, 111 women, 216 men) starting a new treatment period. Clients were assigned randomly to therapists (N = 33). Both clients and therapists’ ratings of the working alliance were measured. Generalised linear mixed model was used in the analyses. The covariate was clients per cent days abstinent before treatment. Therapists rating of the alliance of the first therapy session and the clients percentage of days abstinent predicted treatment retention. The therapists’ ratings were better for clients whose treatment continued than for those whose treatment was discontinued. There was considerable between-therapist variation in retention and this became wider as treatment progressed. Lower per cent days abstinent at baseline negatively predicted retention. Since the therapists evaluation of the working alliance has proved to be a predictor of retention in treatment and differences between the therapists exist in this particular and also in earlier studies, future research should be directed more towards the therapists and their characteristics associated with good treatment results.

Prediction of Stem Measurements of Scots Pine

The aim of this study was to investigate prediction of stem measurements of Scots pine(Pinus sylvestris L.) for a modern computerized forest harvester. We are interested in the prediction of stem curve measurements when measurements of stems already processed and a short section of the stem under process are known. The techniques presented here are based on cubic smoothing splines and on multivariate regression models. One advantage of these methods is that they do not assume any special functional form of the stem curve. They can also be applied to the prediction of branch limits and stem height of pine stems.

Testing for cubic smoothing splines under dependent data

In most research on smoothing splines the focus has been on estimation, while inference, especially hypothesis testing, has received less attention. By defining design matrices for fixed and random effects and the structure of the covariance matrices of random errors in an appropriate way, the cubic smoothing spline admits a mixed model formulation, which places this nonparametric smoother firmly in a parametric setting. Thus nonlinear curves can be included with random effects and random coefficients. The smoothing parameter is the ratio of the random-coefficient and error variances and tests for linear regression reduce to tests for zero random-coefficient variances. We propose an exact F-test for the situation and investigate its performance in a real pine stem data set and by simulation experiments. Under certain conditions the suggested methods can also be applied when the data are dependent.

A trajectory analysis of body mass index for Finnish children

The aim of this study is to investigate the early development of body mass index (BMI), a standard tool for assessing the body shape and average level of adiposity for children and adults. The main aim of the study is to identify the primary trajectories of BMI development and to investigate the changes of certain growth characteristics over time. Based on our longitudinal data of 4223 Finnish children, we took anthropometric measurements from birth up to 15 years of age for birth years 1974, 1981, 1991 and 1995, but only up to 11 years of age for the birth year 2001. As a statistical method, we utilized trajectory analysis with the methods of nonparametric regression. We identified four main trajectories of BMI growth. Two of these trajectories do not seem to follow the normal growth pattern. The highest growth track appears to yield to a track that may yield to overweight and the low birth BMI track shows that the girls’ track differs that of boys on the same track, and on the normal tracks. The so-called adiposity rebound time decreased over time and started earlier for those on the overweight track. According to our study, this kind of acceleration of growth might be more of a general phenomenon that also relates to the other phases of BMI development. The major change seems to occur especially for those children on high growth tracks.