scholarly journals Italian onco-haematological patients’ preferences in bad news communication: a preliminary investigation

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ramona Bongelli ◽  
Alessia Bertolazzi ◽  
Ludovica Piccioni ◽  
Roberto Burro
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Descriptive Analysis ◽  
Preliminary Investigation ◽  
Active Role ◽  
Self Report ◽  
Bad News ◽  
Truth Telling ◽  
Intergenerational Change ◽  
Haematological Patients

Abstract Background The manner in which bad news is communicated in oncological contexts can affect patients’ engagement, their coping strategies and therapeutic compliance. Although this topic has been broadly investigated since the nineties, to the best of our knowledge, little has been written about Italian patients’ experiences and preferences concerning what the oncologists should disclose and how they should intimate patients about their health conditions in different stages of oncological disease. Methods In an attempt to fill this gap, an online self-report questionnaire was administered to a sample of Italian onco-haematological patients. Data were analysed both qualitatively (by a content analysis) and quantitatively (by descriptive analysis and Generalized Linear Mixed Model). Results While the majority of patients elected to know the truth during their clinical course, a polarisation between those arguing that the truth be fully disclosed and those claiming that the truth be communicated in a personalised way was observed at the attitude level. Among demographic variables accounted for, age seems to most affect patients’ preferences. Indeed, younger Italian patients decidedly reject concealment of the truth, even when justified by the beneficence principle. This result could be a reaction to some protective and paternalistic behaviours, but it could even reflect a relation according to which the more the age increases the more the fear of knowing rises, or an intergenerational change due to different ways of accessing the information. The qualitative analysis of the final open-ended question revealed three main sources of problems in doctor-patient encounters: scarcity of time, absence of empathy and use of not-understandable language that makes it difficult for patients to assume a more active role. Conclusions The results of the present study, which represents a preliminary step in the subject investigation, will be deployed for the construction and validation of a more sophisticated questionnaire. Better awareness of the Italian onco-haematological patients’ preferences concerning bad news communication and truth-telling could be useful in adopting more suitable medical practices and improving doctor-patient relationships.

A comparison of the Remote Food Photography Method and the Automated Self-Administered 24-hour Dietary Assessment Tool for measuring full day dietary intake among school-aged children

2021 ◽  
pp. 1-26
Author(s):  
Traci A. Bekelman ◽  
Corby K. Martin ◽  
Susan L. Johnson ◽  
Deborah H. Glueck ◽  
Katherine A. Sauder ◽  
...  
Keyword(s):  
Dietary Intake ◽  
Energy Intake ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Assessment Tool ◽  
Dietary Assessment ◽  
Ease Of Use ◽  
Self Report ◽  
Food Photography ◽  
Photography Method

Abstract The limitations of self-report measures of dietary intake are well known. Novel, technology-based measures of dietary intake may provide a more accurate, less burdensome alternative to existing tools. The first objective of this study was to compare participant burden for two technology-based measures of dietary intake among school-age children: the Automated-Self Administered 24-hour Dietary Assessment Tool-2018 (ASA24-2018) and the Remote Food Photography Method (RFPM). The second objective was to compare reported energy intake for each method to the Estimated Energy Requirement for each child, as a benchmark for actual intake. Forty parent-child dyads participated in 2, 3-day dietary assessments: a parent proxy-reported version of the ASA24 and the RFPM. A parent survey was subsequently administered to compare satisfaction, ease of use and burden with each method. A linear mixed model examined differences in total daily energy intake (TDEI) between assessments, and between each assessment method and the EER. Reported energy intake was 379 kcal higher with the ASA24 than the RFPM (p=0.0002). Reported energy intake with the ASA24 was 231 kcal higher than the EER (p = 0.008). Reported energy intake with the RFPM did not differ significantly from the EER (difference in predicted means = −148 kcal, p = 0.09). Median satisfaction and ease of use scores were 5 out of 6 for both methods. A higher proportion of parents reported that the ASA24 was more time consuming than the RFPM (74.4% vs. 25.6%, p = 0.002). Utilization of both methods is warranted given their high satisfaction among parents.

scholarly journals O003 The impact of wind farm noise in a laboratory setting on objective and subjective sleep efficiency

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A1-A2
Author(s):  
T Liebich ◽  
L Lack ◽  
G Micic ◽  
K Hansen ◽  
B Zajamsek ◽  
...  
Keyword(s):  
Sleep Disturbance ◽  
Wind Farm ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Sleep Efficiency ◽  
Self Report ◽  
Sleep Diary ◽  
Noise Condition ◽  
Subjective Sleep ◽  
The Impact

Abstract Introduction Well-controlled studies of wind farm noise (WFN) on sleep are lacking despite complaints and known effects of other noise types on sleep. This laboratory-based study investigated the impact of continuous full-night WFN exposure replicated from field recordings on polysomnography-measured (objective) and sleep diary-determined (subjective) sleep efficiency compared to a quiet control night. Methods Based on residential location and self-report data, 50 participants were categorised into three groups (14 living <10km from a wind farm and self-reporting sleep disturbance; 19 living <10km from a wind farm and self-reporting no sleep disturbance and 18 controls living in a quiet rural area). Participants underwent full in-laboratory polysomnography during exposure to continuous WFN (25 dB(A)) throughout the night and a quiet control night (background noise 19 dB(A)) in random order. Group and noise condition effects were examined via linear mixed model analysis. Results Participants (30 females) were aged (mean±SD) 54.9±17.6 range: 18–80 years. Sleep efficiency in the control condition was (median [interquartile range]) objective: 85.5 [77.4 to 91.2]%; subjective: 85.7 [69.2 to 92.7]%) versus the WFN condition (objective: 86.1 [78.6 to 91.7]% subjective: 85.8 [66.2 to 93.8]%) with no significant main or interaction effects of group or noise condition (all p’s >0.05). Conclusion These results do not support that WFN at 25 dB(A) significantly impacts objective or subjective sleep efficiency in participants with or without prior WFN exposure or self-reported WFN-related sleep disturbance. Further analyses to investigate potential sleep micro-structural changes remain warranted.

Caregiver psychoeducation for schizophrenia: Is gender important?

2007 ◽  
Vol 22 (5) ◽  
pp. 323-327 ◽  
Author(s):  
Stephen McWilliams ◽  
Shane Hill ◽  
Nora Mannion ◽  
Anthony Kinsella ◽  
Eadbhard O'Callaghan
Keyword(s):  
Gender Differences ◽  
Knowledge Acquisition ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Signs And Symptoms ◽  
Self Report ◽  
Caregiver Support ◽  
Before And After ◽  
Male Caregivers

AbstractIntroductionFemales care for individuals with chronic illness more commonly than males and have different attitudes to illness. Additionally, they experience greater burden and reduced quality of life, when compared to their male counterparts. Since knowledge has been shown to be related to burden, we sought to determine whether there were gender differences in knowledge acquisition during a six-week caregiver psychoeducation programme (CPP).MethodsCaregivers of people with schizophrenia completed a 23-item adapted version of the self-report Family Questionnaire (FQ) before and after the six-week CPP. Using a Generalized Linear Mixed Model, we studied the differences in proportions of correct answers before and after the programme by gender.ResultsOver a 46-month study period, 115 caregivers (58% female) participated in the programme. There was an overall improvement in knowledge with an effect size of 1.12. The improvement was statistically significant (P < 0.001) within each of six specific areas of knowledge. However, female caregivers gained more knowledge overall and specifically regarding signs and symptoms, recovery and especially caregiver support. Knowledge gains regarding medication were roughly equal, while male caregivers gained more knowledge about risk factors.DiscussionOur findings indicate that there are gender differences in the amount and type of knowledge gained during a CPP, with female caregivers showing greater knowledge acquisition than their male counterparts in most areas. Interventions designed to assist caregivers may be improved by targeting areas of knowledge specific to each gender. Such an approach might further reduce burden and improve the outcome for their relatives affected by schizophrenia.

Associations between insomnia and reward learning in clinical depression

2021 ◽  
pp. 1-10
Author(s):  
Gabrielle I. Liverant ◽  
Kimberly A. Arditte Hall ◽  
Sarah T. Wieman ◽  
Suzanne L. Pineles ◽  
Diego A. Pizzagalli
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Unipolar Depression ◽  
Reward System ◽  
Reward Processing ◽  
Clinical Depression ◽  
Self Report ◽  
Reward Learning ◽  
Potential Mediator ◽  
The Impact

Abstract Background Depression and insomnia commonly co-occur. Yet, little is known about the mechanisms through which insomnia influences depression. Recent research and theory highlight reward system dysfunction as a potential mediator of the relationship between insomnia and depression. This study is the first to examine the impact of insomnia on reward learning, a key component of reward system functioning, in clinical depression. Methods The sample consisted of 72 veterans with unipolar depression who endorsed sleep disturbance symptoms. Participants completed the Structured Clinical Interview for DSM-IV, self-report measures of insomnia, depression, and reward processing, and a previously validated signal detection task (Pizzagalli et al., 2005, Biological Psychiatry, 57(4), 319–327). Trial-by-trial response bias (RB) estimates calculated for each of the 200 task trials were examined using linear mixed-model analyses to investigate change in reward learning. Results Findings demonstrated diminished rate and magnitude of reward learning in the Insomnia group relative to the Hypersomnia/Mixed Symptom group across the task. Within the Insomnia group, participants with more severe insomnia evidenced the lowest rates of reward learning, with increased RB across the task with decreasing insomnia severity. Conclusions Among individuals with depression, insomnia is associated with decreased ability to learn associations between neutral stimuli and rewarding outcomes and/or modify behavior in response to differential receipt of reward. This attenuated reward learning may contribute to clinically meaningful decreases in motivation and increased withdrawal in this comorbid group. Results extend existing theory by highlighting impairments in reward learning specifically as a potential mediator of the association between insomnia and depression.

Enhancing Community Suicide Risk Assessment and Protective Intervention Action Plans Through a Bystander Intervention Model-Informed Video

Crisis ◽  
2021 ◽  
Author(s):  
Karien Hill ◽  
Ralf Schwarzer ◽  
Shawn Somerset ◽  
Philippe A. Chouinard ◽  
Carina Chan
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Time Frame ◽  
Bystander Intervention ◽  
Self Report ◽  
Intervention Model ◽  
Community Information ◽  
Self Report Data ◽  
Protective Intervention

Abstract. Aim: The effects of a bystander intervention model (BIM)-informed intervention (video) for the general community on participant risk of suicide assessment ability (ROSAA) and protective intervention ability (PIA) were compared with an active control (non-BIM-informed video). Method: Video interventions with 628 participants ( Mage = 47.99, SDage = 17.34, range = 18–85 years) were conducted online. ROSAA and PIA were assessed immediately preintervention, postintervention, and at 2 months follow-up ( n = 126). Results: Linear mixed model analyses indicated that the experimental and control conditions improved on both outcome variables postintervention/Time 2 (T2); however, the former yielded better outcomes than the latter (moderate ESs in both variables). Follow-up/Time 3 (T3) experimental ROSAA scores were higher than Time 1 (T1) and lower than T2 scores. Follow-up experimental PIA scores were higher than T1 and lower than T2 scores. Follow-up control ROSAA scores were higher than those of T1 and similar to T2. Follow-up control PIA scores were similar to T1 and T2 scores. Limitations: Limitations of the study include: sample homogeneity, small n at follow-up, self-report data only (no observable behavior was tested), fair inter-rater reliability, and a brief follow-up time frame. Conclusion: Current community information increased ROSAA and PIA. A BIM-informed intervention significantly enhanced these effects, which seemed to wane somewhat over time with the effect being lower at follow-up compared with postintervention. The BIM should be explored further as a basis for community suicide prevention interventions.

Understanding the Relationship between Mood Symptoms and Mobile App Engagement Among Breast Cancer Patients: A Machine Learning Process (Preprint)

2021 ◽  
Author(s):  
Anna N Baglione ◽  
Lihua Cai ◽  
Aram Bahrini ◽  
Isabella Posey ◽  
Mehdi Boukhechba ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mental Health ◽  
Random Forest ◽  
Cancer Patients ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Self Report ◽  
Breast Cancer Patients ◽  
The Relationship

BACKGROUND Health interventions delivered via smart devices are increasingly being used to address mental health challenges associated with cancer treatment. Engagement with mobile interventions has been associated with treatment success, yet the relationship between mood and engagement among cancer patients remains poorly understood. One reason is the lack of a data-driven process for analyzing mood and app engagement data for cancer patients. OBJECTIVE The purpose of this study is to provide a step-by-step process for using app engagement metrics to predict continuously assessed mood outcomes in breast cancer patients. We describe the steps of data preprocessing, feature extraction, and data modeling and prediction. We then apply this process as a case study to data collected from breast cancer patients who engaged with a mobile mental health app intervention (IntelliCare) over 7-weeks. We compare engagement patterns over time (e.g., frequency, days of use) between high- and low-anxious and high- and low-depressed participants. We then use a Linear Mixed Model to identify significant effects and evaluate the performance of Random Forest and XGBoost classifiers in predicting weekly state mood from baseline affect and engagement features. METHODS We describe the steps of data preprocessing, feature extraction, and data modeling and prediction. We then apply this process as a case study to data collected from breast cancer patients who engaged with a mobile mental health app intervention (IntelliCare) over 7-weeks. We compare engagement patterns over time (e.g., frequency, days of use) between high- and low-anxious and high- and low-depressed participants. We then use a Linear Mixed Model to identify significant effects and evaluate the performance of Random Forest and XGBoost classifiers in predicting weekly state mood from baseline affect and engagement features. RESULTS We observed differences in engagement patterns between high- and low-anxious and depressed participants. Linear Mixed Model results varied by the featureset; these results revealed weak effects for several features of engagement, including duration-based metrics and frequency. Accuracy of predicting state mood varied according to classifier and featureset. The XGBoost classifier achieved the highest accuracy for state anxiety prediction when self-report scores and engagement features were used for only the most highly-used apps. The Random Forest classifier achieved the highest accuracy for state depression prediction when self-report scores and engagement features were used from all apps. CONCLUSIONS The results from the case study support the feasibility and potential of our analytic process for understanding the relationship between app engagement and mood outcomes in breast cancer patients. The ability to leverage both self-report and engagement features to predict state mood during an intervention could be used to enhance decision-making for researchers and clinicians, as well as assist in developing more personalized interventions for breast cancer patients.

scholarly journals Patient safety culture according to nursing professionals of an accredited hospital

2020 ◽  
Vol 41 ◽  
Author(s):  
Eliana Melo ◽  
Alexandre Pazetto Balsanelli ◽  
Vanessa Ribeiro Neves ◽  
Elena Bohomol
Keyword(s):  
Patient Safety ◽  
Safety Culture ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Descriptive Analysis ◽  
Patient Safety Culture ◽  
Two Dimensions ◽  
Cross Sectional ◽  
Nursing Team ◽  
Nursing Professionals

ABSTRACT Objective: To evaluate the perception of the nursing team regarding the patient safety culture of an accredited hospital and to identify the differences between shifts, professional category and units. Method: Cross-sectional study, conducted in a private hospital in the city of São Paulo, SP, Brazil, with application of the Survey on Patient Safety Culture Hospital to 497 nursing professionals. Descriptive analysis, instrument consistency and generalized linear mixed model were performed. Results: The organizational learning and continuous improvement dimension was considered a strong area (77%) and the personal adequacy (47%), shift / shift change and transfer (47%) and non-punitive response to errors (25%) dimensions were considered. fragile. Differences in perception were found between the professional categories in two dimensions; between shifts in six and between units in seven dimensions. Conclusion: The nursing team identified weaknesses in the patient safety culture in the hospital, with the need to standardize the improvement processes.

Analyzing discontinuities in longitudinal count data: A multilevel generalized linear mixed model.

2020 ◽  
Author(s):  
James L. Peugh ◽  
Sarah J. Beal ◽  
Meghan E. McGrady ◽  
Michael D. Toland ◽  
Constance Mara
Keyword(s):  
Count Data ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Generalized Linear Mixed Model ◽  
Longitudinal Count Data

Predicting bycatch hotspots based on suitable habitat derived from fishery-independent data

2020 ◽  
Vol 641 ◽  
pp. 159-175
Author(s):  
J Runnebaum ◽  
KR Tanaka ◽  
L Guan ◽  
J Cao ◽  
L O’Brien ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Gulf Of Maine ◽  
Homarus Americanus ◽  
Management Tool ◽  
American Lobster ◽  
Suitable Habitat ◽  
Climate Conditions ◽  
Suitability Index

Bycatch remains a global problem in managing sustainable fisheries. A critical aspect of management is understanding the timing and spatial extent of bycatch. Fisheries management often relies on observed bycatch data, which are not always available due to a lack of reporting or observer coverage. Alternatively, analyzing the overlap in suitable habitat for the target and non-target species can provide a spatial management tool to understand where bycatch interactions are likely to occur. Potential bycatch hotspots based on suitable habitat were predicted for cusk Brosme brosme incidentally caught in the Gulf of Maine American lobster Homarus americanus fishery. Data from multiple fisheries-independent surveys were combined in a delta-generalized linear mixed model to generate spatially explicit density estimates for use in an independent habitat suitability index. The habitat suitability indices for American lobster and cusk were then compared to predict potential bycatch hotspot locations. Suitable habitat for American lobster has increased between 1980 and 2013 while suitable habitat for cusk decreased throughout most of the Gulf of Maine, except for Georges Basin and the Great South Channel. The proportion of overlap in suitable habitat varied interannually but decreased slightly in the spring and remained relatively stable in the fall over the time series. As Gulf of Maine temperatures continue to increase, the interactions between American lobster and cusk are predicted to decline as cusk habitat continues to constrict. This framework can contribute to fisheries managers’ understanding of changes in habitat overlap as climate conditions continue to change and alter where bycatch interactions could occur.

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