Evaluation of an experience-based program to understand the concept of recovery among hospital-based psychiatric nurses

This study aimed to implement an experience-based program to promote the understanding of the concept of recovery, which is defined as a meaningful life and valued sense of integrity based on subjective and individual viewpoints, among psychiatric nurses working in hospitals in Japan and to evaluate this program. Methods: We conducted a preliminary survey of nurses at six facilities with psychiatric wards. The experience-based program was conducted for 12 nurses who expressed a wish to participate. The program spanned three days and consisted of lectures, assertive community treatment (ACT) staff visits for recovery orientation, and group work. Results: The mean Recovery Knowledge Inventory of nine participants ultimately included was 3.41 points (SD, 0.28) before the program and 3.69 points (SD, 0.24) after the program, indicating a significant difference (p = .004). Categories obtained from ACT support experiences included the following: “Continuing to attend to the need to live in one’s community/home regardless of how bad psychiatric symptoms become without the use of medicines,” “Viewing the person living their life in a place where they belong and in their own individual style,” “Valuing the patient’s wishes is the slow but sure way to a fruitful relationship,” and “Become familiar to the patient and their family’s lifestyle by carefully listening to the family’s feelings”. Discussion: We believe that this program can help establish the concept of recovery in hospital, which tend to rely on the medical model, and enable daily nursing practice to be implemented from a strength-based viewpoint.     

Fourier analysis of irregularly spaced data on Rd

Summary.  The purpose of the paper is to propose a frequency domain approach for irregularly spaced data on R ^d . We extend the original definition of a periodogram for time series to that for irregularly spaced data and define non-parametric and parametric spectral density estimators in a way that is similar to the classical approach. Introduction of the mixed asymptotics, which are one of the asymptotics for irregularly spaced data, makes it possible to provide asymptotic theories to the spectral estimators. The asymptotic result for the parametric estimator is regarded as a natural extension of the classical result for regularly spaced data to that for irregularly spaced data. Empirical studies are also included to illustrate the frequency domain approach in comparisons with the existing spatial and frequency domain approaches.     

A Comparative Study of Homelessness in the United Kingdom and Japan

This article describes the problem of homelessness in Japan, and contrasts the status of the problem between the United Kingdom and Japan. Demographic characteristics of the homeless, including age and gender, vary across the two countries (for example, there are very few homeless women in Japan). Factors contributing to the development of homelessness in each country are discussed and contrasted. Differences in social welfare systems may be the primary contributor to differences in the apparent rates of homelessness and the conditions that the homeless must endure across the two nations. Housing and homeless policy in Japan are discussed in depth.     

An Ecological Assessment of Drug-Related Problem Situations for American Indian Adolescents of the Southwest

This study examined difficult situations related to drug and alcohol use as identified by American Indian youth in the South-west. Sixty-two contextually based items were developed from focus group data, and were administered to 71 American Indian youth. The items measured the frequency in which youth experienced specific drug-related situations, as well as the perceived difficulty in resisting drug use offers in those situations: The results indicated that the most frequent and difficult drug and alcohol situations occurred primarily with friends or cousins at their homes or after school. Implications for culturally specific assessment, prevention, and treatment are discussed.     

Analysis of changes of insect-plant ratio-improvement of key-factor analysis for evaluating bottom-up effects in insect population dynamics

A revised key-factor analysis was presented for analyzing the temporal changes in the ratio of insect absolute number to plant resource. Ten data sets for 5 insect species were then analyzed. In this key-factor analysis, the key factor is defined as the factor contributing highly to between-year variation inR _r , the log rate of the inter-year change of the insect-plant ratio. The yearly change of plant resource was handled as a separate factor, expressed byr _pl , log ratio of plant resource in yearn to plant resource in yearn+1. The following was revealed: 1) In 7 of the 10 data sets examined,r _pl influenced variations ofR _r ; in particular in 3 casesr _pl was the main key factor. 2) Generation-to-generation fluctuations of absolute insect densities showed density dependence in 4 cases, while those of insect-plant ratios, in 8 cases. 3) The Royama model or a linear model, explained well the relationship between log insect-plant ratio (X _r ) andR _r and the relationship betweenX _r and log yearly change rate of absolute insect density (R _abs ). However, in the 7 cases in whichr _pl was a critical factor for variations ofR _r , with, increase ofX _r ,R _r showed a steeper, decrease around the equilibrium point (the point for whichR _r is 0) thanR _abs . This occurred becauser _pl tended to be negatively correlated withX _r . Consequently, in two casesX _r fluctuated cyclicly or chaotically although without the changes in plant resource, fluctuations ofX _r would be damped oscillations approaching equilibrium.     

"I No Like Get Caught Using Drugs": Explanations for Refusal as a Drug Resistance Strategy for Rural Native Hawaiian Youth

This exploratory study examined the use of explanations for refusal as a drug resistance strategy for rural Native Hawaiian youth. Fourteen gender-specific focus groups were conducted within seven middle or intermediate schools on the Island of Hawai'i (N = 64). Participants were asked to describe drug resistance strategies in response to 15 hypothetical culturally specific drug-related problem scenarios developed from earlier research. The findings indicate that variations in the types of explanations used for refusal were based on the type of drug offerer in the associated scenario (i.e., peer/friend, cousin, or parent). Participants also described the rationales for the use of different explanations with different drug offerers. The findings suggest that culturally grounded drug prevention programs for Hawaiian youth should incorporate the use of specific types of explanations for refusal, depending on the youths' relationship to the drug offerer.     

The Social Construction of Deviant Behavior in Homeless and Runaway Youth: Implications for Practice

This study examined the social construction of deviance in a sample of homeless and/or runaway youth in metropolitan Phoenix. In depth semi-structured interviews with 14 youth were conducted, and the data were transcribed and analyzed using a qualitative research computer program. The findings from the study point to an emerging theory, which suggests that ambiguous local policies relevant to homeless youth (e.g., trespassing, loitering) resulted in their selective enforcement by local security and police. Respondents described the ways that they adapted their behaviors to the environmental stressors resulting from these policies. Implications for practice are discussed.

Edge selection based on the geometry of dually flat spaces for Gaussian graphical models

We propose a method for selecting edges in undirected Gaussian graphical models. Our algorithm takes after our previous work, an extension of Least Angle Regression (LARS), and it is based on the information geometry of dually flat spaces. Non-diagonal elements of the inverse of the covariance matrix, the concentration matrix, play an important role in edge selection. Our iterative method estimates these elements and selects covariance models simultaneously. A sequence of pairs of estimates of the concentration matrix and an independence graph is generated, whose length is the same as the number of non-diagonal elements of the matrix. In our algorithm, the next estimate of the graph is the nearest graph to the latest estimate of the concentration matrix. The next estimate of the concentration matrix is not just the projection of the latest estimate, and it is shrunk to the origin. We describe the algorithm and show results for some datasets. Furthermore, we give some remarks on model identification and prediction.