SRDR+

1. Review ID

(surname of first author and year first full report of study was published e.g. Smith 2001)


	Hui 2020

2. Review title


	Rewards of Kindness? A Meta-Analysis of the Link Between Prosociality and Well-Being

3. Date form completed


	05/08/2022

4. Initials of person extracting


	BN

5. Review funding source


	No information

6. Possible conflicts of interest


	No information

7. Aim of review


	we conducted a meta-analysis to examine the strength of the prosociality to well-being link under different operationalizations, and how a set of theoretical, demographic, and methodological variables moderate the link.

8. Number of databases searched


	5

9. Names of databases searched; date ranges of databases searched


	Social Sciences Citation Index, PsycINFO, PsycARTICLES, PubMed, and ProQuest Dissertations and Theses.

10. Date of last search


	The initial database searches were conducted in April, 2014, with follow-up searches on December 14, 2016 and September 30, 2019.

11. Number of included studies


	126

12. Exclusion criteria for participants

(e.g age, comorbidities) 


	Adults (over 18).

13. Exclusion criteria for volunteering

(e.g type of volunteering, for a specific organistion/purpose)


	At least one variable of prosociality. Studies that examined extraordinary altruism, such as kidney donation and religious prosociality were excluded.

14. Exclusion criteria for study type


	Studies were limited to those written in English.

15. Exclusion criteria for outcome measures


	At least one variable of wellbeing, of which Zero-order correlation/s (effect size/s) between variables had to be available.

16. Outcomes studied

(select all that apply)


	Psychological Physical Social General

17. Primary reported outcomes


	We identified 5 types of prosocilaity measures; (1) frequency of volunteering/helping, (2) volunteering/helping or not, (3) prosociality scales, (4) amount of charitable donation or prosocial spending, and (5) affiliation to or membership of any voluntary associations or not. Having located the prosociality variables, we extracted effect sizes involving different aspects of well-being, such as self-esteem, self-efficacy, social connectedness, happiness, positive affect, negative affect, life satisfaction, vitality, subjective well-being, purpose in life, self-actualization, hopelessness, self-reported mental health, depression, stress, mortality, self-rated health, chronic medical conditions, and so on.

18. Secondary reported outcomes (if applicable)


	Coded for moderators; formality of prosociality, edudaimonic (feeling of growth etc) vs hedonic wellbeing (positive affect and related feelings), psycholoigcal functioning vs malfunctioning vs physical health, demographics, study quality, primary or secondary data, and research design.

19. Number of participants included in the review


	No information

20. Review’s included study type (% of quant studies)


	100% quantitative

21. Included studies countries of publication


	No information

22. Range of included studies years of publication


	No information

23. Review’s population

(age, ethnicity, SES)


	No information

24. Social outcomes reported

25. Social outcomes not supported

(e.g cited as non-significant)

26. Physical outcomes reported

27. Physical outcomes not supported

(e.g cited as non-significant)

28. Psychological outcomes reported

29. Psychological outcomes not supported

(e.g cited as non-significant)

30. General outcomes reported

(i.e general health and wellbeing)


	Significant prediction of volunteering/helping frequency and yes/no on wellbeing, as with formal helping, although these effects were very small.

31. General outcomes not supported

(e.g cited as non-significant) 

32. Interactions reported

(i.e between each other or demographic variables)


	Prosociality measure, formality, and data collection type were independent moderators of prosociality and wellbeing relationship. Research design, sampling method, and retirement were not significant moderators. Specifically, concerning prosociality measures, the weighted mean effect size was the strongest (r ⫽ .20) when prosociality scales were used to operationalize prosociality, and the weakest (r ⫽ .10) when volunteering/helping frequency was asked. the weighted mean effect size for studies using prosociality scales was significantly larger than that for those using volunteering/helping frequency, and volunteering/helping (yes/no). Mixed and informal helping had the strongest effect, significantly more than formal. measurement reliability, measurement validity, and age (younger = more prosocial), but not female percentage, moderated the link between prosociality and well-being independently. only the link between prosociality and eudaimonic well-being was found to be moderated by age and percentage of female participants, such that studies with younger help-givers (vs. older help-givers), as well as studies with more females reported higher levels of eudaimonic wellbeing. Effect on psycholigcal functioning were moderated by formality and prosocialuty measure (same pattern as for general wellbeing). These two factors fid not moderate the effect on psychological malfunctioning or physical health..

Prosociality measure, formality, and data collection type were independent moderators of prosociality and wellbeing relationship. Research design, sampling method, and retirement were not significant moderators. Specifically, concerning prosociality measures, the weighted
mean effect size was the strongest (r ⫽ .20) when prosociality scales were used to operationalize prosociality, and the weakest (r ⫽ .10) when volunteering/helping frequency was asked. the weighted mean effect size for studies using prosociality scales was significantly larger than that for those using volunteering/helping frequency, and volunteering/helping (yes/no). Mixed and informal helping had the strongest effect, significantly more than formal.
measurement reliability, measurement validity, and age (younger = more prosocial), but not female percentage, moderated the link between prosociality and well-being independently. 
only the link between prosociality and eudaimonic well-being was found to be moderated by age and percentage of female participants, such that studies with younger help-givers (vs. older help-givers), as well as studies with more females reported higher levels of eudaimonic wellbeing. 
Effect on psycholigcal functioning were moderated by formality and prosocialuty measure (same pattern as for general wellbeing). These two factors fid not moderate the effect on psychological malfunctioning or physical health..

33. Was a meta-analysis performed?

34. Number of included studies in the meta-analysis


	Wellbeing Volunteering/helping frequency: 56 Volunteering/helping or not: 75 Psychological functioning Volunteering frequency: 53 Volunteering yes/no: 72 Formal helping: 108 Psychological malfunctioning 35 30 55 Physical Health: 33 36 74

35. Heterogeneity

(e.g I squared)


	Amount of heterogeneity accounted for Volunteering/helping frequency: .11 (for type of prosociality) Volunteering/helping or not: Formal helping: .08 (for formality) Psychological functioning: Volunteering frequency: .18 Volunteering yes/no: Formal helping: .14 Psychological malfunctioning .05 .00 Physical health: .09 .00

36. Pooled estimates


	Volunteering/helping frequency: .10 Volunteering/helping or not: .14 Formal helping: .11 Psychological functioning: Volunteering frequency: .12 Volunteering yes/no: .14 Formal helping: .12 Psychological malfunctioning .07 .14 .11 Physical health: .08 .10 .09

37. Confidence intervals (95%)


	Volunteering/helping frequency: .07, .13 Volunteering/helping or not: .11, .16 Formal helping: .09, .13 Psychological functioning: Volunteering frequency: .09, .14 Volunteering yes/no: .11, .16 Formal helping: .10, .13 Psychological malfunctioning .03, .12 .08, .20 .07, .13 Physical health: .06, .09 .08, .12 .07, .10

38. Key conclusions from study authors


	To sum up, in explaining the variations of the link between prosociality and well-being, prosociality measures, formality of prosociality, data collection, measurement reliability, measurement validity, and age of participants were found to be significant moderators in the univariate analysis, among which data collection played the strongest moderating role in the multivariate analysis. after a close inspection of all relevant literature, we have found that there is only a modest relationship between them. Furthermore, we have discovered that the link between prosociality and well-being depends heavily on a variety of theoretical, demographical, and methodological factors. It is our hope that this work contributes to more nuanced views of the effects of prosociality.

39. Review limitations


	few studies included in the present meta-analysis were preregistered . In our meta-analysis, publication bias has become a concern in the severe one-tailed selection (i.e., assuming almost all nonsignificant findings were included), with many of the effect sizes dropping by over 43%.

40. AMSTAR 2 quality appraisal rating


	-12

41. Quality appraisal tool used by review (if applicable)


	study quality was assessed by three codes of measurement reliability, measurement validity, and sample representativeness. (internal reliability, measure validity, and sampling method.

42. Quality of included studies (if applicable)


	measurement reliability, and measurement validity modreated the effect of prosociality on wellbeing and psychological functioning, but not sampling method.

43. Publication bias reported (if applicable)


	Despite efforts to include all available unpublished data, the results of our meta-analysis might still be confounded by publication bias. We adopted three traditional and recent approaches to examine any possible publication bias. the distributions in the funnel plots seemed to be roughly asymmetric. these findings indicated minimal evidence of publication bias. the Egger’s regression approach indicated possible bias in the data. also used the approach fo selection methods. By and large, the three approaches suggested different degrees of potential publication bias in our data. By reporting multiple publication bias analyses, we sought to present a real current state of the empirical data in the field and interpret our results cautiously.

44. Was correspondence required for further study information?

45. What further correspondence was required, and from whom?

46. What further study information was requested (from whom, what and when)?

47. What correspondence was received (from whom, what and when)?

Extraction form for project: The effect of volunteering on the health and wellbeing of volunteers: an umbrella review

Design Details