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Happiness

Happiness is a mental state of well-being characterized by positive emotions, contentment, and satisfaction with life.
It is a complex construct that involves various factors such as personal, social, and environmental influences.
Happiness is often associated with improved physical and mental health, enhanced social relationships, and increased productivity.
Researching the determinants and effects of happiness can provide insights into human behavior and well-being, and may lead to the development of interventions to promote happiness and enhance the quality of life.
However, the subjective nature of happiness makes it a challenging concept to define and measure, and there is ongoing debate about the best ways to study and understand this important aspect of the human experience.

Most cited protocols related to «Happiness»

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Publication 2009
Anger Disgust Face Fear

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Publication 2009
Adult Anger Arousal Asian Americans Europeans Face Fear Females Hair Latinos Males Muscle Tonus Negroid Races Oral Cavity
We used data that had been collected previously for a study of the validity of the Japanese version of the SF-36, and calculated national norm scores of all subscales of the SF-36 [8 (link),9 (link)]. Details of the nationwide survey have been described previously [9 (link)]. Briefly, a total of 4500 people 16 years old or older were selected from the entire population of Japan by stratified-random sampling in 1995. A self-administered questionnaire was mailed, and the subjects were visited to collect the questionnaires. The SF-36, the ZSDS [11 (link)] (described below), and questions about demographic characteristics were included in the questionnaire.
The ZSDS consists of 10 positively worded items and 10 negatively worded items asking about symptoms of depression. Several studies have established the ZSDS as a reliable and valid instrument for measuring depressive symptoms [12 (link)-14 (link)]. The ZSDS scores were used to define four categories of the severity of depression: within normal range or no significant psychopathology (below 40 points); presence of minimal to mild depression (40–47 points); moderate to marked depression (48–55 points); presence of severe to extreme depression (56 points and above). These score ranges result from the studies of Zung [15 (link)] and Barrett et al [16 (link)]. The ZSDS has been translated into Japanese and studies of the validity of the Japanese version have been published [17 (link)]. Because the ZSDS is not a clinical diagnostic tool, subjects with high scores are said to have depressive symptoms rather than "depression."
Like the rest of the SF-36, the MHI-5 was administered as a paper-and-pencil questionnaire. The instrument contains the following questions: 'How much of the time during the last month have you: (i) been a very nervous person?; (ii) felt downhearted and blue?; (iii) felt calm and peaceful?; (iv) felt so down in the dumps that nothing could cheer you up?; and (v) been a happy person?' For each question the subjects were asked to choose one of the following responses: all of the time (1 point), most of the time (2 points), a good bit of the time (3 points), some of the time (4 points), a little of the time (5 points), or none of the time (6 points). Because items (iii) and (v) ask about positive feelings, their scoring was reversed. The score for the MHI-5 was computed by summing the scores of each question item and then transforming the raw scores to a 0–100-point scale [18 ].
Items (i) and (iii) are almost identical to 2 items in the Zung Self-rating Anxiety Scale [10 (link)]. To make a scale that is even shorter than the MHI-5 and is focused on depression we removed those two anxiety-related items. Thus, the MHI-3 comprised only (ii), (iv), and (v) above. Possible scores on the MHI-3 ranged from 3 to 18 points.
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Publication 2005
2'-deoxyuridylic acid Anxiety Depressive Symptoms Diagnosis Feelings Japanese Nervousness
The present study focuses on the EBPAS, which consists of 15 items measured on a 5-point Likert scale ranging from 0 (Not at all) to 4 (To a very great extent) (Aarons, 2004 (link); Aarons, et al., 2007 (link)). The EBPAS is conceptualized as consisting of four lower-order factors/subscales and a higher-order factor/total scale (i.e., total scale score), the latter representing respondents’ global attitude toward adoption of EBPs. For the lower-order factors, Appeal assesses the extent to which the provider would adopt an EBP if it were intuitively appealing, could be used correctly, or was being used by colleagues who were happy with it. The Requirements factor assesses the extent to which the provider would adopt an EBP if it were required by an agency, supervisor, or state. The Openness factor assesses the extent to which the provider is generally open to trying new interventions and would be willing to try or use more structured or manualized interventions. The Divergence factor assesses the extent to which the provider perceives EBPs as not clinically useful and less important than clinical experience.
As described in Aarons (2004) (link), content validity of the EBPAS was based on initial development of a pool of items generated from literature review, consultation with mental health service providers, and consultation with mental health services researchers with experienced in evidence-based protocols. As additional evidence of content validity we also asked an expert panel of six mental health services researchers to rate each item of the EBPAS in terms of a) relevance in assessing attitudes toward evidence-based practice, b) importance in assessing attitudes toward evidence-based practice, and c) how representative the item is of the particular factor it is attempting to assess on a 5-point Likert scale (e.g., 1 = “not at all relevant”, 2 = “relevant to a slight extent”, 3 = “relevant to a moderate extent”, 4 = “relevant to a great extent”, 5 = “relevant to a very great extent”) . For individual items the mean rating across panel members ranged from 3.33 - 4.67 for relevance, 3.17- 4.67 for importance, and 3.17- 4.67 for representative. This result supports EBPAS content validity as every item was on average rated as at least “moderately” relevant, important, and representative of the factor it was purported to assess.
Previous studies suggest moderate to good internal consistency reliability in two samples for the total score (Cronbach’s α = .77, .79) and subscale scores excluding divergence (α range= .78-.93), with somewhat lower reliability estimates for divergence (α = .59, .66) (Aarons, 2004 (link); Aarons, et al., 2007 (link)). Construct validity in previous studies is supported by two previous scale development studies that have found acceptable model-data fit for previous confirmatory factor analysis models (Aarons, et al., 2007 (link)). In terms of construct and convergent validity, studies have found significant associations between EBPAS scores and mental health clinic structure and policies (Aarons, 2004 (link)), organizational culture and climate (Aarons & Sawitzky, 2006 (link)) and leadership (Aarons, 2006 (link)).
Publication 2010
Climate Mental Health Mental Health Services
We aimed to answer the following research questions:

What are the national norms for SWEMWBS in the general population in England and across socio-demographic subgroups? How do subgroup differences in scores on SWEMWBS compare with those on WEMWBS?

How well does SWEMWBS correlate with GHQ-12, EQ-VAS, happiness index, and self-reported health and limiting longstanding illness, as compared to correlation of WEMWBS with such instruments?

Does SWEMWBS reproduce associations with social and health behaviour variables similar to the full version?

How closely does the measurement of mental wellbeing with SWEMWBS approximate to the measurement by WEMWBS, and within different subgroups? In addition, how well does SWEMWBS capture those at the low and high ends of the mental wellbeing scale compared with WEMWBS?

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Publication 2016
Happiness

Most recents protocols related to «Happiness»

Women leaving home or becoming homeless at an early age were particularly vulnerable to predatory relationships with older men or romantic relationships of necessity and convenience. Prior studies found a particular association between intimate relationships as a source of increased violence and transitions into injection drug among females [67 (link)]. Consistent with these findings the women in this study frequently described how partners introduced them to drugs and were the catalyst to transition into “harder” drugs:

met a guy who was like 29 and he gave me heroin, like I’d never touched drugs in my life, he injected me, with heroin. I know. I had crack. I didn’t really know what I was taking. He introduced me to heroin at 15 (Gillian).

Intimate relationships were often based on the need for protection: “[partner’s name] is there all the time cos she protects us. She makes us like get up in the mornings and try and get ready and get washed, and stuff like that and she’ll like cooks for us and like she is there. If she hadn’t have been, I wouldn’t be here” (Carina).
Several women met their partners through drug networks and were subsequently coerced into drug dealing: [I met him] through different people in […], who were selling drugs and people knowing people and me being young he swept us off my feet, wined and dined us and I was a lot younger and – he used us basically, to his advantage. “Well if you do this, do that, I’ve got me third strike I’m out, you’ll have to sell this and that” (Delia).
Gillian illustrates the difficulty of getting away from the pull of street culture. Having had a relatively happy and stable relationship for several years, coinciding with better mental health, a job and sense of purpose, the end of that relationship swiftly led to her going back to where she felt a “connection”, a drug dealer who knew her which she associated with having a sense of belonging:

When I was with [partner] and we were both PT [Personal Trainers] everything was fine … my life was absolutely the best … No domestic violence or nothing. I was just happy … I was drug free, like totally, just normal just normal shit and he broke my heart and that and I ended up, like not back on heroin just crack. I started using cocaine and drinking and that you know, cos he left us. And then from then I went out like a coke dealer who I knew from all them years ago when I had [...] who used to serve us up. And I felt like a connection with him cos he knew us (Gillian).

Intimate relationships were entered into out of necessity, following crisis points (homelessness, death of previous partner) and women described partners exacerbating drug use, or precipitating further trauma and abuse.
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Publication 2023
Cocaine Domestic Violence Drug Abuse Feelings Females Foot Heart Heroin Mental Health Persons, Homeless Pharmaceutical Preparations SELL protein, human Woman Wounds and Injuries Youth
The Japanese version of the UMACL was used to evaluate the mood of comfort [23 ]. The original checklist, developed by Matthews et al., was created based on dimension theory, making it possible to assess arousal levels [24 (link)]. The scale has two subscales that can be used to evaluate energetic arousal (10 items; vigorous vs. tired: coefficient α = 0.79) and tense arousal (10 items; nervous vs. relaxed: coefficient α = 0.76) [25 ]. High energetic arousal represents active and happy, whereas low tense arousal represents calm and quiet. Participants were asked to respond on a 4-point Likert scale. In a previous study, the mean energetic arousal was 24.4 (standard deviation [SD]: 0.5) for males and 24.4 (SD: 0.4) for females, and the mean tense arousal was 18.5 (SD: 0.4) for males and 17.56 (SD: 0.3) for females [25 ].
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Publication 2023
Arousal Females Japanese Males Mood Nervousness
Study design and period
A retrospective cross-sectional study was carried out among individuals who had or are currently following the IF. In the four-week preparation period, we created our study title, reviewed the literature to gather information on typical side effects and how to measure the quality of life, and created a questionnaire. In the following four weeks, we completed our research, which included looking for the target group on social media, creating a Google Form for the survey, and testing the form by using a small sample of the findings to make sure they presented as we planned. We collected and examined our data for a further four weeks before writing our report.
Inclusion and exclusion criteria
The study includes people who have ever practiced or are currently practicing IF and who can speak the Arabic language. The target population is in Saudi Arabia in all regions of the kingdom. The initial assessment questions excluded participants who had never engaged in IF. The sample size was calculated automatically using Google Forms. A total of 300 people were registered in the Google Form; 147 of them had practiced IF, and 153 were excluded.
Data collection tool
We developed a questionnaire in Arabic to collect data about IF attitudes and quality of life (questionnaire in the Appendices section). The questionnaire was developed to meet the health-related quality of life (HRQOL) measures, which were translated into Arabic to be suitable for the participant's understanding of the question in our survey. The Centers for Disease Control and Prevention (CDC) HRQOL-4 measures had acceptable test-retest reliability and strong internal validity, which has been used by the CDC and its partners, for tracking population health status and HRQOL measures in states and communities [8 ]. The standard four-item set of healthy days’ core questions was developed by the CDC. The questionnaire consists of the following four main parts: (i) sociodemographic data, (ii) side effects assessment, (iii) participants' attitude toward IF assessment, and (iv) participants' quality of life assessment.
Data collection technique
We conducted the survey in an electronic self-assessment format using Google Forms. We targeted IF groups on social media in Saudi Arabia for a time interval of four weeks through messages and direct contact with the group administrator and ensured that only people who practiced IF participated in the survey. One of the first questions in the survey was “Have you tried Intermittent fasting?” If the answer was no, then the participant is excluded from the survey. The data obtained from the survey were reviewed and automatically copied into a personal computer.
Data entry and analysis
The data collected using the questionnaire was rearranged in Microsoft Excel data sheets. The data was mainly expressed as numbers and percentages. We used a chi-square test to evaluate participants’ perceived happiness, which also indicated the p-value for statistical significance. We also used a pie chart that displays the change in the participants’ body weight following their adoption of IF and to seek the perceived happiness of the participants' IF experience.
Ethical considerations
This study was approved by the Bioethics Committee for Scientific and Medical Research at the University of Jeddah (Approval number UJ-REC-069). Individual consent was required prior to data collection, and it was stated on the questionnaire's front page that completing it signified consent to participate in the study. All information was kept private and was solely utilized for scientific studies. Furthermore, we made sure that parental consent was given to participants less than 18 years old.
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Publication 2023
A 300 Administrators Happiness Human Body Self-Assessment Target Population
The experimenter did not perform the pain simulation at this age, but rather a sadness simulation (we thought that children at this age might be suspicious if two similar pain simulations were presented to them). The experimenter told the child excitedly that she brought her favorite doll (unisex doll of a cartoon figure) but then “discovered” that the doll’s arm had been broken. She feigned sadness for 50 s, without making eye contact, alternating between holding the doll (first 30 s), trying to fix it, and placing it between her and the child (remaining 20 s). Finally, the experimenter succeeded in fixing the doll and was happy. If the child was able to fix the doll at any point, the simulation ended. Similar simulations have been used to measure young children’s empathy and prosociality (e.g., Dunfield and Kuhlmeier, 2013 (link)). Prosocial behavior in this task was coded dichotomously (0 = not shown, 1 = shown), as well as on a 4-point scale reflecting the extent of assistance shown by the child: 0 = none, 1 = brief (a single or weak attempt), 2 = moderate (child tried to help/comfort a few times, or made a single intense or complex attempt), 3 = prolonged (child repeatedly and substantially engaged in prosociality). A 3-point spontaneity score was also coded, reflecting whether the child tried to fix the doll spontaneously, that is, even before the experimenter demonstrated how it might be repaired by trying to fix it herself, with 0 = no prosocial behavior, 1 = acted prosocially, but not spontaneously, 2 = spontaneous prosocial action. Inter-rater reliabilities, based on 20% of the sample, ranged from ICC = 0.97 to 1.00 for all the codes.
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Publication 2023
Child Debility Pain Sadness
To ensure that our elicitation material was recognizable to all participants vis-à-vis their autism diagnosis, age, and socio-cultural background, we first selected 50 potential visual stimuli. These were chosen based on the ‘Putonghua Communicative Development Inventory’ vocabulary checklist (Tardif et al., 2008 ), together with the results of two studies on functional echolalia by Brazilian children with ASD (Pascual et al., 2017 (link); Dornelas, 2018 ). These 50 images were presented to 175 Chinese parents of children with ASD, who scored each according to their children’s familiarity with the referents and recognition of the images using a Likert scale.
Based on this parental pre-test, we selected 12 professions (e.g., nurse) or (types of) individuals (e.g., baby) and 12 entities (e.g., birthday cake) with which the children were most familiar and that are commonly associated with fixed expressions in Mandarin Chinese (e.g., “da zhen!” ‘Give an injection!’, for the nurse; “sheng ri kuai le!” ‘Happy birthday!’ for the cake), see Figure 1 (All figures are found in the Supplementary materials folder).
A five-score Likert scale test on the children’s familiarity with the concepts and level of recognition of these designed images was filled in by the parents after the task, to prevent data contamination. Our eight participants were reported to be quite familiar with the concepts (Mean = 4.10, SD = 0.47) and to be able to recognize the images correctly (Mean = 4.14, SD = 0.44).
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Publication 2023
Autistic Disorder Child Chinese Diagnosis Echolalia Infant Nurses Parent

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More about "Happiness"

Subjective Well-being, Life Satisfaction, Positive Emotions, Contentment, Quality of Life, Personal Factors, Social Influences, Environmental Factors, Physical Health, Mental Health, Social Relationships, Productivity, Determinants of Happiness, Measuring Happiness, E-Prime 2.0, Presentation Software, SPSS version 22.0, SPSS version 24, SPSS 25.0, Stata 14.
Happiness is a complex and multifaceted construct that encompasses an individual's overall sense of well-being, positive emotions, and satisfaction with life.
It is influenced by a variety of personal, social, and environmental factors, and is often associated with improved physical and mental health, enhanced social relationships, and increased productivity.
Researchers have long been interested in understanding the determinants and effects of happiness, and have utilized a range of tools and software, such as MATLAB, E-Prime 2.0, Presentation software, SPSS (versions 22.0, 24, and 25.0), and Stata 14, to study this important aspect of the human experience.
While happiness can be challenging to define and measure due to its subjective nature, continued research in this area can provide valuable insights into human behavior and well-being, and may lead to the development of interventions to promote happiness and enhance the quality of life.
The PubCompare.ai platform can be a useful tool for researchers, as it allows them to easily locate and compare protocols from the literature, pre-prints, and patents, and use AI-driven comparisons to identify the best protocols and products to optimize their research on happiness and reproducibility.