Sibling relationships in adolescence: Learning and growing together

fit this article, I discuss the reasons for my interest in sibling relationships, and showcase studies on sibling relationships in adolescence carried out with my colleagues and students, in the context of the broader literature on sibling relationships. Our studies have focused on a number of important issues concerned with sibling relationships. First, I report on the associations between sibling relationships and other family relationships and the ways that the various family relationships affect each other. Second, I report a study of sibling relationships in the context of parental separation and divorce and show that sibling relationships in these families are more likely to be high in both warmth and hostility than is true for relationships in 2-parent families. Third, I report on several data sets showing an association between the quality of sibling relationships and adolescent adjustment and the link between differential parenting, adolescent adjustment, and the quality of the sibling relationship. Fourth, I report on a study of comparison and competition in sibling relationships and the associations between sibling relationship quality and reactions to being outperformed by a sibling. Finally, I discuss possible future directions for research on sibling relationships, including the importance of multimethod studies and a longitudinal perspective.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup)

Mothers' mental illness and child behavior problems: Cause-effect association or observation bias

Objective: A number, of studies have consistently found that a mother's mental health (particularly her level of depression) is a strong predictor of mental health problems experienced by her child(ren). However, the validity of this finding is in doubt because the majority of these studies have relied on maternal reports as indicators of children's behavior. Method: This prospective, longitudinal study examines data an the mental health of the mother from prior to the birth of her child to when the child reaches 14 years of age. Child behavior is measured at 14 years of age using reports from mother and child. Mother and child responses are compared to provide an indication of the possible magnitude of maternal observation bias in the reporting of child behavior problems. Results: Anxious and/or depressed mothers tend to report more cases of child behavior problems than do their mentally healthy counterparts or children themselves. Differences between mothers and youths In reporting behavior problems appear to be related to the mothers' mental health. Conclusions: Current maternal mental health impairment appears to have a substantial effect on the reporting of child behavior problems by the mother, thereby raising questions about the validity of reports of child behavior by persons who are currently emotionally distressed.

Iron deficiency, general health and fatigue: Results from the Australian Longitudinal Study on Women's Health

Associations between self-reported 'low iron', general health and well-being, vitality and tiredness in women, were examined using physical (PCS) and mental (MCS) component summary and vitality (VT) scores from the MOS short-form survey (SF-36). 14,762 young (18-23 years) and 14,072 mid-age (45-50 years) women, randomly selected from the national health insurance commission (Medicare) database, completed a baseline mailed self-report questionnaire and 12,328 mid-age women completed a follow-up questionnaire 2 years later. Young and mid-age women who reported (ever) having had 'low iron' reported significantly lower mean PCS, MCS and VT scores, and greater prevalence of 'constant tiredness' at baseline than women with no history of iron deficiency [Differences: young PCS = -2.2, MCS = -4.8, VT = -8.7; constant tiredness: 67% vs. 45%; mid-age PCS = -1.4, MCS = -3.1, VT = -5.9; constant tiredness: 63% vs. 48%]. After adjusting for number of children, chronic conditions, symptoms and socio-demographic variables, mean PCS, MCS and VT scores for mid-age women at follow-up were significantly lower for women who reported recent iron deficiency (in the last 2 years) than for women who reported past iron deficiency or no history of iron deficiency [Means: PCS - recent = 46.6, past = 47.8, never = 47.7; MCS - recent = 45.4, past = 46.9, never = 47.4; VT - recent = 54.8, past = 57.6, never = 58.6]. The adjusted mean change in PCS, MCS and VT scores between baseline and follow-up were also significantly lower among mid-age women who reported iron deficiency only in the last 2 years (i.e. recent iron deficiency) [Mean change: PCS = -3.2; MCS = -2.1; VT = -4.2]. The results suggest that iron deficiency is associated with decreased general health and well-being and increased fatigue.

Dietary and supplement treatment of iron deficiency results in improvements in general health and fatigue in Australian women of childbearing age

Objective: To examine the effects of iron deficiency and its treatment by iron supplementation or a high iron diet on fatigue and general health measures in women of childbearing age. Design: Randomised controlled trial to compare supplement and dietary treatment of iron deficiency. Subjects: 44 iron deficient (serum ferritin < 15 mug/L or serum ferritin 15-20 mug/L, plus two of the following: serum iron < 10 mu mol/L, total iron binding capacity > 68 mu mol/L or transferrin saturation < 15%) and 22 iron replete (hemoglobin greater than or equal to 120 g/L and serum ferritin > 20 mug/L) women 18 to 50 years of age were matched for age and parity. Interventions: Iron deficient women were randomly allocated to either iron supplementation or a high iron diet for 12 weeks. Measures of Outcome: Iron deficient and iron replete participants had iron studies performed and completed the Piper Fatigue Scale (PFS) and the SF-36 general health and well-being questionnaire at baseline (TO), following the 12 week intervention (TI) and again after a six-month non-intervention phase (T2). The SF-36 includes measures of physical (PCS) and mental (MCS) health and vitality (VT). Results: MCS and VT scores were lower and PFS scores were higher for iron deficient women (diet and supplement groups) than iron replete women at baseline. Both intervention groups showed similar improvements in MCS, VT and PFS scores during the intervention phase, but mean increases in serum ferritin were greater in the supplement than the diet group. PCS scores were not related to iron status. Conclusions: Treatment of iron deficiency with either supplementation or a high iron diet results in improved mental health and decreased fatigue among women of childbearing age.

Enriched behavioral prediction equation and its impact on structured learning and the dynamic calculus

This theoretical note describes an expansion of the behavioral prediction equation, in line with the greater complexity encountered in models of structured learning theory (R. B. Cattell, 1996a). This presents learning theory with a vector substitute for the simpler scalar quantities by which traditional Pavlovian-Skinnerian models have hitherto been represented. Structured learning can be demonstrated by vector changes across a range of intrapersonal psychological variables (ability, personality, motivation, and state constructs). Its use with motivational dynamic trait measures (R. B. Cattell, 1985) should reveal new theoretical possibilities for scientifically monitoring change processes (dynamic calculus model; R. B. Cattell, 1996b), such as encountered within psycho therapeutic settings (R. B. Cattell, 1987). The enhanced behavioral prediction equation suggests that static conceptualizations of personality structure such as the Big Five model are less than optimal.