In order to study the temporal variations of correlations between two time series,a running correlation coefficient(RCC)could be used.An RCC is calculated for a given time window,and the window is then moved sequentia...In order to study the temporal variations of correlations between two time series,a running correlation coefficient(RCC)could be used.An RCC is calculated for a given time window,and the window is then moved sequentially through time.The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient,calculated with the data within the time window,which we call the local running correlation coefficient(LRCC).The LRCC is calculated via the two anomalies corresponding to the two local means,meanwhile,the local means also vary.It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means.To address this problem,two unchanged means obtained from all available data are adopted to calculate an RCC,which is called the synthetic running correlation coefficient(SRCC).When the anomaly variations are dominant,the two RCCs are similar.However,when the variations of the means are dominant,the difference between the two RCCs becomes obvious.The SRCC reflects the correlations of both the anomaly variations and the variations of the means.Therefore,the SRCCs from different time points are intercomparable.A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data.The SRCC always meets this criterion,while the LRCC sometimes fails.Therefore,the SRCC is better than the LRCC for running correlations.We suggest using the SRCC to calculate the RCCs.展开更多
The activism of patients associations, in decision making, about health and social services, is an expanding phenomenon in Italy and elsewhere. But the civic roles of these patients associations, in health care settin...The activism of patients associations, in decision making, about health and social services, is an expanding phenomenon in Italy and elsewhere. But the civic roles of these patients associations, in health care settings, remain largely unexplored, especially in the case of patients assuming oral anticoagulant therapy （OAT Patients） for various chronic and severe diseases （stroke, chronic arthritis, maintenance or substitution of cardiac valves）. This is a qualitative study, on a Civic Health Organization, the Italian Association of Anti Coagulant Patients （Associazione ltaliana Pazienti Anticolagulati, hereinafter A.I.P.A.） which promotes the rights of OAT patients. The study was carried out in the south of Italy at Cosenza＇s Hospital. Cosenza is a city in the north of Calabria, a poor Southern Italian region. The research, done between March 2010 and December 2012, involved focus groups, key-informant interviews with volunteers from the local A.I.P.A. unit and the hospital professionals （physicians, nurses, managers） of Cosenza＇s Annunziata Hospital. This essay mainly analyzes a micro-form of co-deliberative health care democracy： a stable partnership between AIPA members and the cited hospital professionals, based on a mix of advocacy, planning, and co-delivery service roles. In doing this, the paper sketches the development, aims, activities, internal structure and resources, and the role played by this specific citizen-user/patient/career organization in promoting and/or representing the interests of anti-coagulated patients within the legal arena of the Italian health policy. Finally, the paper comes to the point in which OAT patients refer their perceptions of relational rights.展开更多
Healthy relationships are important to functioning in daily life and across the life-span （e.g., Burman and Margolin 1992）. Personality factors could predict relationship satisfaction through the influence of indivi...Healthy relationships are important to functioning in daily life and across the life-span （e.g., Burman and Margolin 1992）. Personality factors could predict relationship satisfaction through the influence of individuals＇ relationship schemas （Fiske and Taylor 1991） and perceptions of their partners （Simpson and Rholes 1998）. Given the potential importance of attachment styles to relationship mechanisms and the well-established relationship between attachment and interpersonal behavior （Bartholomew and Horowitz 1992; Hazan and Shaver 1987）, interpersonal traits may influence relationship satisfaction directly. According to Leary＇s （1957） interpersonal reflex theory, any interpersonal act elicits responses from the other person that verify, validate, or otherwise reinforce the actor＇s own self-image and self-presentation, and thus increase the probability that the actor will emit similar interpersonal acts in future interactions. The Impact Message Inventory （IMI） attempts to measure individuals＇ perceptions of how others impact them by evoking interpersonal acts such as dominance and affiliation. This study examined the influence of perceived partner-evoked behavior and individuals＇ own interpersonal styles on relationship satisfaction. This study used IMI measures of evoked Dominance and Affiliation as well as revised Liking and Loving measures to predict relationship satisfaction using three different satisfaction outcome measures. The final analyses included 291 participants （134 men and 157 women） who completed a scantron survey. Partner impact, or the interpersonal behaviors, evoked from the individual during interaction, predicted relationship satisfaction well. Evoked affiliation was the most consistently strong predictor of satisfaction across all three outcome measures. Liking （distinct here from affiliation） is a stronger predictor of relationship satisfaction than is loving （distinct here from passion）, and it is significant across all three outcome measures. The liking measure appears to reflect a relatively high level of reward in the relationship and intrinsic enjoyment of the partner＇s company without the comparative cost of loving. Future research should examine interactions between couples, moving beyond intrapsychic self-reports of perceived experiences and feelings, although these are important in their own right.展开更多
基金supported by the Key Program of the National Natural Science Foundation of China (No. 41330960)the Global Change Research Program of China (No. 2015CB953900)
文摘In order to study the temporal variations of correlations between two time series,a running correlation coefficient(RCC)could be used.An RCC is calculated for a given time window,and the window is then moved sequentially through time.The current calculation method for RCCs is based on the general definition of the Pearson product-moment correlation coefficient,calculated with the data within the time window,which we call the local running correlation coefficient(LRCC).The LRCC is calculated via the two anomalies corresponding to the two local means,meanwhile,the local means also vary.It is cleared up that the LRCC reflects only the correlation between the two anomalies within the time window but fails to exhibit the contributions of the two varying means.To address this problem,two unchanged means obtained from all available data are adopted to calculate an RCC,which is called the synthetic running correlation coefficient(SRCC).When the anomaly variations are dominant,the two RCCs are similar.However,when the variations of the means are dominant,the difference between the two RCCs becomes obvious.The SRCC reflects the correlations of both the anomaly variations and the variations of the means.Therefore,the SRCCs from different time points are intercomparable.A criterion for the superiority of the RCC algorithm is that the average value of the RCC should be close to the global correlation coefficient calculated using all data.The SRCC always meets this criterion,while the LRCC sometimes fails.Therefore,the SRCC is better than the LRCC for running correlations.We suggest using the SRCC to calculate the RCCs.
文摘The activism of patients associations, in decision making, about health and social services, is an expanding phenomenon in Italy and elsewhere. But the civic roles of these patients associations, in health care settings, remain largely unexplored, especially in the case of patients assuming oral anticoagulant therapy （OAT Patients） for various chronic and severe diseases （stroke, chronic arthritis, maintenance or substitution of cardiac valves）. This is a qualitative study, on a Civic Health Organization, the Italian Association of Anti Coagulant Patients （Associazione ltaliana Pazienti Anticolagulati, hereinafter A.I.P.A.） which promotes the rights of OAT patients. The study was carried out in the south of Italy at Cosenza＇s Hospital. Cosenza is a city in the north of Calabria, a poor Southern Italian region. The research, done between March 2010 and December 2012, involved focus groups, key-informant interviews with volunteers from the local A.I.P.A. unit and the hospital professionals （physicians, nurses, managers） of Cosenza＇s Annunziata Hospital. This essay mainly analyzes a micro-form of co-deliberative health care democracy： a stable partnership between AIPA members and the cited hospital professionals, based on a mix of advocacy, planning, and co-delivery service roles. In doing this, the paper sketches the development, aims, activities, internal structure and resources, and the role played by this specific citizen-user/patient/career organization in promoting and/or representing the interests of anti-coagulated patients within the legal arena of the Italian health policy. Finally, the paper comes to the point in which OAT patients refer their perceptions of relational rights.
文摘Healthy relationships are important to functioning in daily life and across the life-span （e.g., Burman and Margolin 1992）. Personality factors could predict relationship satisfaction through the influence of individuals＇ relationship schemas （Fiske and Taylor 1991） and perceptions of their partners （Simpson and Rholes 1998）. Given the potential importance of attachment styles to relationship mechanisms and the well-established relationship between attachment and interpersonal behavior （Bartholomew and Horowitz 1992; Hazan and Shaver 1987）, interpersonal traits may influence relationship satisfaction directly. According to Leary＇s （1957） interpersonal reflex theory, any interpersonal act elicits responses from the other person that verify, validate, or otherwise reinforce the actor＇s own self-image and self-presentation, and thus increase the probability that the actor will emit similar interpersonal acts in future interactions. The Impact Message Inventory （IMI） attempts to measure individuals＇ perceptions of how others impact them by evoking interpersonal acts such as dominance and affiliation. This study examined the influence of perceived partner-evoked behavior and individuals＇ own interpersonal styles on relationship satisfaction. This study used IMI measures of evoked Dominance and Affiliation as well as revised Liking and Loving measures to predict relationship satisfaction using three different satisfaction outcome measures. The final analyses included 291 participants （134 men and 157 women） who completed a scantron survey. Partner impact, or the interpersonal behaviors, evoked from the individual during interaction, predicted relationship satisfaction well. Evoked affiliation was the most consistently strong predictor of satisfaction across all three outcome measures. Liking （distinct here from affiliation） is a stronger predictor of relationship satisfaction than is loving （distinct here from passion）, and it is significant across all three outcome measures. The liking measure appears to reflect a relatively high level of reward in the relationship and intrinsic enjoyment of the partner＇s company without the comparative cost of loving. Future research should examine interactions between couples, moving beyond intrapsychic self-reports of perceived experiences and feelings, although these are important in their own right.
