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{"": {"ColourHEX": "", "ThemeDefinition": "Work design refers to the content and organisation of one\u0027s work tasks, activities, relationships and responsibilities."}, "Emotional": {"ColourHEX": "#6a3d9a", "ThemeDefinition": ""}, "Engagement": {"ColourHEX": "#b2df8a", "ThemeDefinition": "Learning is about relatively permant change in knowledge, skills and abilities."}, "HPWS": {"ColourHEX": "#fdbf6f", "ThemeDefinition": ""}, "Individual": {"ColourHEX": "", "ThemeDefinition": ""}, "Leadership": {"ColourHEX": "#1f78b4", "ThemeDefinition": "Engagement is the extent to which employees feel passionate about their jobs, are committed to the organization, and put discretionary effort into their work."}, "Learning": {"ColourHEX": "#33a02c", "ThemeDefinition": "Wellbeing is about the psychological and physical state of an individual."}, "Nothing": {"ColourHEX": "#cab2d6", "ThemeDefinition": ""}, "People Systems": {"ColourHEX": "#ffff99", "ThemeDefinition": ""}, "Performance": {"ColourHEX": "#b15928", "ThemeDefinition": ""}, "Personality": {"ColourHEX": "#a6cee3", "ThemeDefinition": "Leadership is about motivating others towards achieving a shared goal."}, "Wellbeing": {"ColourHEX": "#fb9a99", "ThemeDefinition": "Test"}, "Work Design": {"ColourHEX": "#e31a1c", "ThemeDefinition": "High-performance work systems establish practices that improve an organization\u0027s capacity to effectively attract, select, hire, develop, and retain high-performing personnel."}, "test": {"ColourHEX": "", "ThemeDefinition": ""}}
{"DriverConcept": ["Agreeableness", "Conscientiousness", "Emotional Exhaustion", "Extraversion", "High Blood Pressure", "Job Satisfaction", "Life Satisfaction", "Motivation", "Neuroticism", "Openness", "Parental mistreatment", "Peer Behaviour", "Perfomance", "Performance", "Posttraining knowledge", "Posttraining self\u2013efficacy", "Pretraining self\u2013efficacy", "Self Leadership", "Supervisor Behaviour", "Turnover Intentions", "Well-Being (Overall)", "Work environment"], "DriverTheme": ["Engagement", "Individual", "Leadership", "Performance", "Personality", "Wellbeing"], "OutcomeConcept": ["Charisma", "Commitment", "Creativity", "Destructive Leadership", "Emotional Exhaustion", "Entrepreneurial behaviour", "Fatigue", "Job Satisfaction", "Knowledge", "Learning Performance", "Life Satisfaction", "Neuroticism", "Organisational Commitment", "Overall Health", "Performance", "Positive Affect", "Psychological Well-Being", "Retention", "Self-esteem", "Skills", "Sleep Problems", "Somatic/Physical Symptoms/Complaints", "Team performance", "Transfer", "Wellness Behaviour", "Work Performance"], "OutcomeTheme": ["Engagement", "HPWS", "Individual", "Leadership", "Learning", "Performance", "Personality", "Wellbeing"]}
{"EffectSize": [0.01, 0.09, 0.16, 0.26, 1], "EffectSizeLabel": ["SMALL", "SMALL", "MODERATE", "LARGE", "VERY LARGE"]}
<p class="card-text">
<strong> ABOUT </strong>
metafinds lets you explore robust research results from meta analytics studies to:
> promote evidence-based decisions, practices and policies
> accelerate arduous processes of locating research findings
> help check facts during class, conferences and scientific clashes
<strong> META-ANALYSIS, SO WHAT? </strong>
A meta-analysis is a systematic synthesis of all the available evidence pertaining to a certain topic: they combine quantitative findings from many research studies pertaining to related phenomena. Accordingly, meta-analyses mitigate limitations typical in single studies, such as systematic biases and sampling issues. Ultimately, meta-analyses help establish robust estimates and general trends about the relationship of phenomena. In turn, you may use meta-analytics results to inform and increase the representativeness of claims and efficacy of decisions.
<strong> CONCEPTS & THEMES </strong>
The data underlying metafinds is continuously updated using only results from peer-reviewed publications in the social sciences. Concepts are nested in Themes: Concept describes the explanatory variable, also construct or metrics; it is represented in verbatim as named in the scientific source publication. Theme describes a broader idea that recurs in related concepts; it is established by metafinds to organise all information along some useful categories.
<strong> EFFECT SIZE </strong>
The effect size describes the direction and strength of the correlation between two concepts: how closely is the change to one variable followed by a change in the other variable. This value is always expressed between 0 (no association) and 1 (strongest possible relationship). In reality, the median correlation effect is about 0.16. For convenience, effect sizes may be labelled as small (below 0.09), moderate (0.10 to 0.16), large (0.17 to 0.26), or very large (above 0.27). The direction of a relationship can be positive, e.g.: +0.43 If Pay goes up, then Performance goes up. Or, the direction of a relationship can be negative, e.g.: -0.25 If Pay goes up, then Attrition goes down. Put differently, a plus + or minus – denotes this direction, though neither direction is inherently good or bad; that depends on the nature of the concepts.
<strong> DRIVERS & OUTCOMES </strong>
With correlation, the variables move together, there is no inherent direction of cause and effect. To aid practical utility, metafinds adopts the theoretical lens of the source publication to indicate directionality between plausible drivers and outcomes. If you want to build models that optimally predict the future, please use regression, and consult the literature ;)
<strong> CIRCULAR CHART </strong>
metafinds dynamically translates the data you view into a circular chart to visualise the relationships between concepts, which are nested in colour coded themes. An arc represents the connection between two concepts, and the hue indicates how much they share in common. The compactness of the circular form is inherently more appealing (shall we say beautiful) than a linear layout; it reduces massive information into a manageable cognitive space, which makes the chart ideal for exploring and communicating evidenced relationships. Why not download the chart as an image to share?
<strong> CONTRIBUTE & FEEDBACK </strong>
Want to add your meta-analytics results to metafinds? Add them <a class="faqLink" href="https://contribute.metafinds.org"> here </a>.
Got feedback or ideas that improve metafinds? Please <a class="faqLink" href="mailto:contact@metafinds.org"> contact us </a>.
<strong> USAGE & COPYRIGHT </strong>
metafinds is free to use and licensed under a <a class="faqLink" href="https://creativecommons.org/licenses/by-nc-sa/4.0/"> Creative CommonsAttribution-NonCommercial-ShareAlike 4.0 International License </a>. We all <a class="faqLink" href="https://en.wikipedia.org/wiki/Standing_on_the_shoulders_of_giants"> stand on the shoulders of giants </a>.
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