Author: Steve Granger

I am an Assistant Professor in the Department of Management at the John Molson School of Business, Concordia University. I received my PhD in Organizational Behaviour and Human Resources from the Haskayne School of Business, University of Calgary. My research applies a psychological perspective in the core areas of occupational health and the future of work. My work has been published in various outlets, including the Journal of Occupational and Organizational Psychology, Human Relations, Personality and Social Psychology Review, Journal of Safety Research, and Organizational Dynamics. I have also taught multiple courses in Organizational Behaviour and serve as an editorial board member for Human Relations.

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Research Work

6 challenges of being a gig worker during the COVID-19 pandemic

Food delivery couriers congregate in Turin, Italy. (Shutterstock)

Erin Reid, McMaster University; Brianna Barker Caza, University of North Carolina – Greensboro; Steve Granger, University of Calgary, and Susan Ashford, University of Michigan

The gig economy, once associated mainly with musicians and artists, is stretching into more and more areas of the workforce. With the advent of tech platforms such as Uber, Airbnb and TaskRabbit, many of us have come to rely on gig workers to take us places, rent us rooms or take care of small tasks. Both the number and the type of workers employed in the gig economy has grown.

Yet these are only the most visible segments of the gig labour market. A number of specialist platforms focused on knowledge economy services have emerged, such as Kolabtree, which connects users to independent scientists, and Eden McCallum, a company which serves clients with teams of independent management consultants. https://www.youtube.com/embed/yPp6Q90paIE?wmode=transparent&start=0 CBC’s The National looks at a platform that connects workers and customers.

Gig workers’ day-to-day lives are fundamentally different from people with traditional employment in organizations who enjoy more predictable wages, supportive managers and steady relationships. As scholars of work, psychology and organizations, we have focused our recent research on the challenges these workers face and the personal resources they can draw upon to deal with them.

6 challenges of being a gig worker

Drawing on our own research and studies by other researchers, we identified six key challenges for these workers that are rooted in the structure of gig work itself:

• Remaining financially viable without a predictable salary.

• Organizing the logistics of work without the support of the administrative infrastructure (e.g., accounting, marketing).

• Crafting a clear work identity without the roles and communities that anchor identities in organizations.

• Navigating an uncertain career path and forecasting one’s future work without the more predictable career options offered by companies and industries.

• Coping with the heightened emotional turbulence occasioned by highs and lows of working independently.

• Maintaining work relationships without a clear and stable set of regular colleagues.

We developed The Gig Work Challenges Inventory (GWCI) to measure these challenges. We developed and validated 18 questions through a series of surveys conducted with many different types of gig workers including rideshare drivers, freelance editors, creative workers, consultants, designers and online digital piece-workers.

Our ongoing research is devoted to understanding what makes these challenges more or less salient to workers, as well as how they can cope with them. Our measure captures the experiences of workers around the world, including a global sample of scientists.

A smiling woman sits behind a laptop.
Internet and communications technologies now mean that gig workers compete globally for work. (Shutterstock)

Different experiences

Gig workers are not all alike and their experiences of these challenges are not all the same. They have different skills, do different kinds of work and find their gigs in different ways. Our studies suggest that these differences importantly shaped workers’ experiences of the six core challenges of gig work in the following ways:

• Professional status matters: Comparing professionals (e.g. editors, consultants) to non-professionals (e.g. delivery drivers), we find that non-professionals report generally higher levels of all six challenges than do the professionals.

• Income matters: Not surprisingly, a gig worker’s income impacts their experience of challenges — lower income gig workers report higher levels of all six challenges than do higher income workers.

• How gig workers find work matters: Workers who find their gigs through platforms like Upwork tended to report greater emotional and career path challenges than did those who found their work through other means, such as through their existing social networks.

Resources for coping

A document showing an inventory of gig work challenges
The survey tool used to capture challenges faced by gig workers. (Reid, Caza, Granger and Ashford), Author provided

Gig workers’ experiences of these challenges have shifted during the COVID-19 pandemic. Surveys that we conducted with a sample of independent scientists before and during the pandemic reveal how this global disruption reduced the number of available work opportunities and amplified workers’ difficulties with fluctuating emotions, organizing day-to-day work and maintaining relationships.

However, our data also suggest some psychosocial resources that may help gig workers cope with layers of work and non-work challenges. Specifically, when gig workers felt that their work was meaningful and that they had emotional support in their social networks going into the pandemic, they reported higher levels of psychological resilience and well-being, and less loneliness, during the pandemic.

These results show how doing work that is meaningful and having strong relationships can help buffer the challenges of gig work, even as they become amplified during a pandemic.

We anticipate that our work will be useful to gig workers, organizers, practitioners, managers and scholars. We encourage workers themselves to use the inventory to evaluate their own work lives and consider where they need to invest in building resources to sustain themselves.

Protestors holding signs saying FIX THE GIG ECONOMY in pink letters on a white background
Gig economy protesters block a downtown street in Toronto, Ont. on May 1, 2020. (THE CANADIAN PRESS/Frank Gunn )

Third-party platforms such as Kolabtree and Upwork as well as freelancer unions and other organizations might use this measure as a basis for creating supportive services and programs for their workers.

Last, we hope that researchers can use this inventory to continue to better understand gig workers’ lived experiences and generate new insights about the implications of this increasingly prominent way of working.

Erin Reid, Associate professor, Human Resources & Management, McMaster University; Brianna Barker Caza, Associate Professor of Management, University of North Carolina – Greensboro; Steve Granger, PhD Candidate, University of Calgary, and Susan Ashford, Michael and Susan Jandernoa Professor of Management and Organizations, University of Michigan

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Research Uncategorized Work

In Pressions — January 7th 2021

Fostering personal resilience is a vital goal of much occupational health psychology.

A recent study by Falon and colleagues in press at the Journal of Occupational Health Psychology approached this issue from the lens of self-reflection training.

The self-reflection model they rely on poses that resilience can be strengthened through a mixture of practices that promote the self-awareness, self-evalution, and self-development of one’s values, goals, coping strategies in the face of adversity.

A potential hurdle to this model the authors anticipate is the self-absorption paradox (Trapnell & Campbell, 1999), whereby dwelling on one’s self can improve the accuracy of self-knowledge while coming at a cost of psychological well-being — a phenomenon often exhibited by individuals who experience depression.

However, the authors emphasized that the self-reflection model involves constructing solutions, being curious, creating time-boundaries, and having a desire to learn from experience, as opposed to brooding on the stressors one experiences.

In their clustered-randomized controlled trial, the authors compared two groups as they went through stressful military training: an experimental self-reflection resilience training group and a control training group.

The self-reflection resilience training group engaged in weekly guided self-reflection journaling for 15 minutes each for 5 weeks, while the control group completed a communication skills seminar for 15 minutes each for 5 weeks.

Results indicated a clearer picture for depression and stress than anxiety: depression and stress were stable among the experiemental group in the short- and long-term (immediately following training and 3 months after training), whereas they increased across both for the control group; anxiety increased for the experiemental group in the short-term and increased for the control group in the long-term.

Importantly, the authors were able to show that self-reflection was indirectly related to less depression, anxiety, and stress in the long-term by decreasing the tendency to ruminate.

A key “in pression” from this study appears to be how individuals reflect on the stressors they experience and the approaches they take in dealing with or overcoming this adversity. This adds more evidence to the idea that it is important to frame adversity as an opportunity for growth and engaging in self-reflective journaling can be a useful way of doing this.

In Pression posts: brief summaries from one or multiple articles “In Press” at leading journals.

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Research Work

In Pressions — December 2nd 2020

Sleep has been in the blue-light filtered limelight of occupational health research over the last couple years given how much our society and culture has chronically understimated the negative consequences of putting off the ZZZs.

However, recent research has continued to add nuance to our understanding of when or how much sleep is good for our work (and vice versa).

Sayre and colleagues (2020) explored whether sleep is seen as a resource gain (improved well-being) or resource loss (less time) and appeared to find stronger evidence for the latter, with more sleep reducing percieved performance, and reduced perceived performance relating to more sleep – what they referred to as a loss spiral.

Another study ‘in press’ by Hur and colleagues (2020) contributes to this line of thought in that they found better performance was related to improved relaxation in the evening and improved positive affect the next morning.

Together, it appears that work performance can be an influential antecedent to a good night’s respite and according to another ‘in press’ article by Carleton and Barling (2020) on treatment for sleap apnea, experiencing a good quality sleep is rather important to reducing withdrawal behaviours which affect performance.

So key “in pressions”? Target improving sleep quality, which will help you stay focused at work so you can relax afterwards knowing you did a good job that day.

In Pression posts are an approach I’ll be trying out where I very briefly summarize key takeaways from one or multiple articles “In Press” at leading journals.

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Stats Work

Compressing Long Lists of Variables for Tidier SPSS Syntax

You just pasted a long list of variables into your SPSS syntax that you want to delete from or rename in your dataset.

Maybe you normally just leave it as is or maybe you manually compress the list with a committed effort of backspaces and spaces. Both options I find quite frustrating: you either deal with the laggy scrolling of SPSS as you move up and down your syntax for the former (which is even more frustrating if you have thousands of variables and you’re still working on the syntax) or you let it consume your time as you meticulously work through the list for the latter.

Well, I’m here to tell you about one way I’ve found to quickly compress long lists of variables.

Step 1: Copy and paste your variables into Microsoft Word.

Step 2: Go to Edit -> Find -> Replace…

Step 3: In the Find menu, select “Paragraph Mark” and within the Replace menu, manually press the spacebar once to effectively replace paragraph marks with a single blank space (you could also use the dropdown menu to select “Nonbreaking Hyphen” or “Nonbreaking Space”). Press Replace All.

Formatting marks (the blue markings) are shown for clarification
Formatting marks (the blue markings) are shown for clarification

Step 4: With the list now compressed into a single paragraph, you can either copy and paste this into your syntax and add in the paragraph breaks where you desire (as this will just give you one long row of variables) or you can add in the paragraph breaks within Word first and then copy it into your syntax (example below)

Paragraph breaks manually added in Word, again format markings shown for clarification
After adding paragraph breaks in Word, this is what it will look like after copying and pasting it into your syntax.

That’s it! Depending on how many variables you have, the manual paragraph breaks afterwards can still be a bit time consuming, but much less time consuming than removing the paragraph breaks one variable at a time within the syntax.

If you are aware of an even faster approach, please let me know. If not, I hope this helps! Happy syntaxing.

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Stats Work

Variable and Value Labels in SPSS

Let’s face it, a well prepped SPSS dataset has informative and accurate labels for each variable and their respective values. However, it’s all too easy to plow ahead and think you’ll remember what each obscure acronym you create in the moment and the values assigned to them will mean some years down the road. Maybe, maybe not, but what I know is that if you spend a little extra time prepping your dataset, you can save your colleagues or yourself a great deal of time that would be spent trying to understand what your past-self was thinking.

Luckily, the business of renaming variable and value labels is fairly straightforward, yet there are still some tips and tricks that you can use in special cases that I will mention below.

But first, I’ll quickly go over the basics.

Syntax for Labeling or Relabeling Variable Labels

Labeling one variable

VARIABLE LABELS varname ‘Type your variable label here’.

e.g.,
VARIABLE LABELS FPK ‘MEAN SCALE SCORE: Follower’s political knowledge’.

Labeling more than one variable

VARIABLE LABELS varname ‘Type your variable label here’
/varname2 ‘Type your variable label 2 here’
/varname3 ‘Type your variable label 3 here’.

e.g.,
VARIABLE LABELS FPK ‘MEAN SCALE SCORE: Follower’s political knowledge’
/FPS ‘MEAN SCALE SCORE: Follower’s political skill’
/FPW ‘MEAN SCALE SCORE: Follower’s political will’.

Syntax for Labeling or Relabeling Value Labels

Labeling the values for one variable

VALUE LABELS varname #’Type your value number here’.

e.g.,
VALUE LABELS FPK 1’Strongly disagree’ 2’Somewhat disagree’ 3’Neither agree nor disagree’ 4’Somewhat agree’ 5’Strongly agree’

Labeling the values for more than on consecutive variable

VALUE LABELS varname1 to varname9 #’Type your value number here’.

e.g.,
VALUE LABELS FPK1 to FPK9 1’Strongly disagree’ 2’Somewhat disagree’ 3’Neither agree nor disagree’ 4’Somewhat agree’ 5’Strongly agree’

Labeling the values for more than one non-consecutive variable

VALUE LABELS varname1 #’Type your value number here’
/varname6 #’Type your value number here’.

e.g.,
VALUE LABELS FPK1 1’Strongly disagree’ 2’Somewhat disagree’ 3’Neither agree nor disagree’ 4’Somewhat agree’ 5’Strongly agree’
/ABSENCE 0’No’ 1’Yes’.

Tips and Tricks for Renaming Variable Labels

The most important thing to remember when labeling or relabeling variable labels is that you have something for each variable. The idea is that you should understand what each variable is without having to open any other file or going back to your original survey or source material.

Often times, you will have special variables that you created solely to conduct analyses on, such as mean scale scores, clinical cut-off scores, and so forth. I find it helpful to make these important variables pop out by beginning their label with an all-caps description (e.g., MEAN SCALE SCORE: Follower’s political knowledge; CLINICAL CUTOFF SCORE: HADS depression).

Tips and Tricks for Renaming Value Labels

The same general informative tip applies to value labels. It’s easy to leave these blank, but you can make your life easier by labeling these where appropriate.

Occasionally your source material will have or produce wonky values and value labels for you that you want to change (recoding variables is another related but separate topic that I will write about soon). After recoding the variable values, there is a very easy method of removing the old value labels and replacing them with ones that match your updated values.

Here is the syntax:
VALUE LABELS varname.
VALUE LABELS varname #’Type your value label here’.

e.g.,
VALUE LABELS FPK.
VALUE LABELS FPK 1’Strongly disagree’ 2’Somewhat disagree’ 3’Neither agree nor disagree’ 4’Somewhat agree’ 5’Strongly agree’

Here, the first VALUE LABELS command will remove the existing value labels and the second VALUE LABELS command will produce new value labels for your variable.

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Bikes Life

Ride into the storm

Time has come to finally end my summer blogging hiatus as the fall winds sweep in. A lot has happened over the last two months in and outside of graduate school — from my very first first-author publication to countless cycling adventures (photo above being from the latest ride northwest of Calgary). While it’s sad to see summer wind down, I’m excited to embrace the beginning of the fall and the challenges it will offer. It’s time to ride into the storm.

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Research Work

Project WIMH: Post #6

One of the arguments I’ve been working on in my proposal to explain the link between prior issues with mental health and subsequent work injuries is the role of cognitive resources (memory, attention, acuity, etc.).

The basic argument goes something like this: cognitive resources that are negatively impacted by mental health problems are the same resources that reduce the likelihood of experiencing a work injury.

While I was working through papers on the meta-analysis, I came across one that brought this idea to the forefront.

Arlinghaus and colleagues (2012) assessed the intermediary role of fatigue as a result of inadequate sleep in predicting work injuries. One of the core predictive variables of inadequate sleep that they assessed was psychological distress.

They find that psychological distress was not only directly related to an increased chance of experiencing a serious work injury, but that it was also indirectly related to experiencing a serious work injury through obtaining less sleep.

The implication of this is that the effect of mental health on cognitive resources is also complex, potentially reducing a persons day-to-day acuity and functioning by influencing other factors such as the amount of sleep they get the night before.

References

Arlinghaus, A., Lombardi, D. A., Willetts, J. L., Folkard, S., & Christiani, D. C. (2012). A structural equation modeling approach to fatigue-related risk factors for occupational injury. Am J Epidemiol, 176(7), 597-607. doi:10.1093/aje/kws219

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Bikes Research

Bicycle helmets

Do they matter?

The answer is an overwhelming yes.

Here are just a few numbers from a meta-analysis (i.e., a summary of all existing quantitative research) by Oliver & Creighton (2017) assessing the effectiveness of bicycle helmets in crashes and falls:

51% less likely to experience a head injury
69% less likely to experience a serious head injury
33% less likely to experience a facial injury
And 65% less likely to experience a fatal injury

To boot, other meta-analyses find relatively similar results (Attewell et al., 2001; Elvik, 2011; Høye, 2018).

So yes, bicycle helmets matter.

But recent innovations in bicycle helmet tech have improved their effectiveness a considerable amount.

Here I’m talking about WAVECEL and MIPS (Multi-Directional Impact Protection System).

While these two helmet technologies work in slightly different ways, they essentially soften the impact on the head by separating the helmet and your head from the initial shock.

With a traditional helmet, there is essentially a plastic and foam barrier between your head and what it hits, but your head rotates with the helmet at the same speed (and it’s this initial rotation and acceleration that leads to most head injuries, such as concussions and traumatic brain injuries).

With MIPS and WAVECEL, there is within the helmet a moving liner or collapsible structure, respectively, that decreases this rotation, and ultimately the chance of head injuries (Bliven et al., 2019).

So if you’re in the market for a helmet, I would highly recommend looking out for either MIPS or WAVECEL, with MIPS helmets tending to come in at slightly lower costs because the tech has been around for quite a bit longer.

If you’d like more information about bicycle helmet testing, check out the website for Virginia Tech’s helmet testing lab. They run comprehensive third-party testing on helmets for various sports, including cycling.

References

Attewell, R. G., Glase, K., & McFadden, M. (2001). Bicycle helmet efficacy: a meta-analysis. Accident Analysis & Prevention, 33(3), 345-352.Chicago

Bliven, E., Rouhier, A., Tsai, S., Willinger, R., Bourdet, N., Deck, C., … & Bottlang, M. (2019). Evaluation of a novel bicycle helmet concept in oblique impact testing. Accident Analysis & Prevention, 124, 58-65.

Elvik, R. (2011). Publication bias and time-trend bias in meta-analysis of bicycle helmet efficacy: a re-analysis of Attewell, Glase and McFadden, 2001. Accident Analysis & Prevention, 43(3), 1245-1251.

Høye, A. (2018). Bicycle helmets–To wear or not to wear? A meta-analyses of the effects of bicycle helmets on injuries. Accident Analysis & Prevention, 117, 85-97.

Olivier, J., & Creighton, P. (2017). Bicycle injuries and helmet use: a systematic review and meta-analysis. International Journal of Epidemiology, 46(1), 278-292.Chicago

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Bikes Life

Two wish list destinations, one (110km) ride

This summer I wanted to find the cycling path to and visit Chestermere, as well as visit and ride through Fish Creek provinicial park in southern Calgary. I never thought I’d do this in a single ride, but that’s what ends up happening when you get slightly lost. Besides, it’s never really getting lost or going in the wrong direction when you’re on a bike, it’s called exploration. Kudos to my buddy Kevin for the company and hammering through. Ride on.

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Bikes Life

First ride in the mountains

Had the wonderful opportunity to ride out in Kananaskis Country on a highway that is closed to cars for half of the year (how awesome is that?!). Apparently Highwood Pass is the highest paved road in Canada at 2206 meters. Definitely one of my favourite rides so far. Shout out to my buddy Vaarun for letting me know about this and inviting me out. Ride on!