Clinical notes are unstructured text documents generated by clinicians during patient encounters, generally are annotated with International Classification of Diseases (ICD) codes, which give formatted information about the diagnosis and treatment. ICD code has shown its potentials in many fields, but manual coding is labor-intensive and error-prone, lead to researches of automatic coding. Two specific challenges of this task are (1) given an annotated clinical notes, the reasons behind specific diagnoses and treatments are  implicit; (2) explainability is important for practical automatic coding method, the method should not only explain its prediction output but also have explainable internal mechanics. This study aims to develop an explainable CNN approach to address these two challenges.Our key idea is that for the automatic ICD coding task, the presence of informative snippets in the clinical text that correlated with each code plays an important role in the prediction of codes, and an informative snippet can be considered as a local and low-level feature. We infer that there exists a correspondence between a convolution filter and a local and low-level feature. Base on the inference, we come up with the Shallow and Wide Attention convolutional Mechanism (SWAM) to improve the CNN-based models’ ability to learn local and low-level features for each label.We evaluate our approach on MIMIC-III, an open-access dataset of ICU medical records. Our approach substantially outperforms previous results on top-50 medical code prediction on MIMIC-III dataset, the precision of the worst-performing 10% labels in previous works is increased from 0% to 53% on average. We attribute this improvement to SWAM, by which the wide architecture with attention mechanism gives the model ability to more extensively learn the unique features of different codes, and we prove it by an ablation experiment. Besides, we perform manual analysis of the performance imbalance between different codes, and preliminary conclude the characteristics that determine the difficulty of learning specific codes.Our main contributions can be summarized into the following three: (1) We present local and low-level features, a.k.a. informative snippets play an important role in the automatic ICD coding task, and the informative snippets extracted from the clinical text provide explanations for each code. (2) We propose that there exists a correspondence between a convolution filter and a local and low-level feature. A combination of wide and shallow convolutional layer and attention layer can help the CNN-based models better learn local and low-level features. (3) We improved the precision of the worst-performing 10% labels from 0 to 53% on average. Clinical notes are written by clinicians during patient encounters, they are usually unstructured text narratives and accompanied by a set of metadata codes from the International Classification of Diseases (ICD), which present a standardized way of indicating diagnoses and procedures that were performed during the encounter. There is much research that demonstrates the practical application with ICD codes –3. For eManual coding is time-consuming and error-prone, so much research on automatic coding has been done in the pastdecades, some recent works are Zhang et al. ; KavulurTo address these two specific challenges together, in this paper, we develop CNN-based methods for automatic ICD coding assignment based on text discharge summaries from ICU stays, we come up with Shallow and Wide Attention convolutional Mechanism (SWAM), which allows our model to learn local and low-level features for each label. Our model design is motivated by the way human clinicians manual label the clinical notes, which is to look for informative snippets that are relevant to each code. We consider the informative snippets as local and low-level features. SWAM address the two challenges in automatic coding: first, by transferring the base representation  to the convolution representation which represents the presence of informative snippets, the model could filter out the irrelevant information in the text, and through the attention mechanism the model could learn the correlation between informative snippets and labels Second, SWAM gives informative snippets extracted from clinical notes as explanations of its prediction result, and provides a new perspective for understanding the internal mechanics of the machine learning method.We evaluate our approach on the MIMIC-III dataset , an openICD coding has been a long-established task in the medical informatics community for decades, from the perspective of data, the current approaches of this task can be divided into two factions: much recent research focuses on unstructured text data , 8, whilA tendency in recent years is developing Neural Network-based methods for this task. Shi et al.  applied Combing convolution with attention has been proved is efficient in different tasks among NLP –18. YangAttentional Convolution has also been applied to make explainable text classification. Some prior works like Rushet al.  and RockHoa et al.  comparedGong and Ji  find thaIn this paper, we use notations shown in Table We present SWAM, a CNN-based method for automatic ICD coding from the clinical text, which provides a good explanation of its internal mechanics.SWAM is motivated by the way human clinicians manual label the clinical notes, to help the reader understand the method, firstly here is a brief introduction of the way human clinicians manual label the clinical notes. Normally, human clinicians will look for informative snippets that are relevant to each code. For example, as shown in Fig. SWAM refers to the same idea of manual coding. As shown in Fig. Our explanation of the internal mechanics of SWAM builds on correspondences between “informative snippet” and convolution filter. Firstly, we classify the “informative snippet” into two categories: “generic snippet” and “non-generic snippet”. “generic snippet” refers to snippets that are informative for multiple labels, for example, in our task, “experience fever” is likely to be a “generic snippet” since it is the symptom correlated with multiple diagnoses. “non-generic snippet” refers to snippets that are only considered as informative to a specific or a few labels, for example, in top-50 code task, “endotracheal intubation” will be considered as a “non-generic snippet” since it brings little information gain to the other 49 labels than it brings to the code 96.04 “Insertion of endotracheal tube”.Then we infer that there exists a correspondence between “informative snippet” and convolution filter, which means one convolution filter can only generate a high activation value for a specific “informative snippet”. Given that in the CNN context, the “informative snippet” can be considered as a set of word embedding sequences that are close in the embedding space. For example, “large mucus plug” and “big mucus plug” are the same “informative snippet” since they have similar meanings and therefore are close in the embedding space. It is most likely that for different “informative snippets”, they will have very little chance to be close in the embedding space. For each filter, it will be “highly activated” ouput exceeds threshold when the snippet in its window is close to its parameters in embedding space, and this snippet can be considered as the “informative snippet” corresponds to this filter.Based on the above inference, an obvious conclusion is that the choice of the width of the convolution layers, a.k.a. the number of convolution filters should depend on the total numbers of “informative snippets” in the task, more accurately, the number of “non-generic snippet” since it will be much larger than the number of “generic snippet” in the large-scale coding task. Besides, empirical guidance in our architecture design is that there could be multiple “non-generic snippets” for each code .Therefore we develop Shallow and Wide Attention CNN for this task: the presence of the informative snippet of each code could be considered as a local, low-level feature learned by the shallow CNN, and we also need the convolutional layer to be wide since the model needs to learn the “non-generic snippets” of all codes.The convolutional layer should be sufficiently wide, a.k.a. enough convolution filters to not only extract all generic snippets that are informative for multiple labels, but also all non-generic features that are correlated to specific label and not informative to other labels, the certain number of filters depends on task context, a.k.a. the total number of generic features and non-generic features in the task.The network architecture should be shallow, this model is designed to extract snippets of text, which can be considered as local, low-level features, so a deeper network is unnecessary since informative snippets relevant to each label scattered at random locations in the input document, it is not likely that we can earn any benefit from the global, high-level features by combining the adjacent snippets.Attention mechanism should be introduced to learn the correlations between important/informative snippets and each code.The mechanism behind Shallow and Wide Attention CNN is general for a set of similar text classification tasks that informative snippets relevant to each label scattered at random locations in the input document. So SWAM can be regarded as a general architecture with the following three characteristics, and implement details can be varied  as the loss function, the optimization goal is to minimize the loss.MIMIC-III  is an opWe remove the tokens that contain no alphabetic characters . For those tokens that appear too few times to make their semantics difficult to learn, a threshold that only remains tokens that appear in no fewer than 3 training documents is setting, and all tokens that failed the threshold are replaced with an ‘UNK’ token. The distribution of discharge summaries conforms to the long-tailed distribution, 90% of discharge summaries are short than 2500 tokens, so we truncated discharge summaries to a maximum length of 2500 tokens.As mentioned in Correspondences between “informative snippet” and convolution filter, SWAM can be regarded as a general CNN architecture and implement details can be varied. In model part Attention layer two different implements of attention layer are adapt for different considerations, we name those two implements as “SWAM-textCNN”  and “SWAThe baseline we compare against is a bag-of-words logistic regression model, we also compare SWAM-CAML with the origin implement of CAML  at the sFor SWAM-textCNN and SWAM-CAML we initialize the embedding weights using the same pre-trained word2vec vectors. The logistic regression model consists of k, number of filters q as shown in Table We tune the hyper-parameters of our SWAM models using grid search. We sample parameter values for the learning rate mentclasspt{miniman highest-scored labels that are present in the ground truth. The reason we focus on Macro-averaged F1 is that it pays attention to per-label performance, which can reflect the average performance of the model on different label tasks. As for P@n, we choose it because it reflects the performance of the model as a practical decision support system which presents a fixed number of predicted codes to help user annotated the clinical text. To facilitate comparison with both future and prior work, we also report a variety of metrics includes the area under the ROC curve (AUC) and micro-averaged F1. For recall, Macro-averaged values are calculated by averaging metrics computed per-label. Micro-averaged values are calculated by treating each  pair as a separate prediction.We focus on two metrics: Macro-averaged F1 and precision at n (denoted as ‘P@n’), which is the fraction of the Our main quantitative evaluation involves predicting the 50-code set of ICD-9 codes based on the text of the MIMIC-III discharge summaries. These results are shown in Table According to our inference about the correspondence between the informative snippet and convolution filter, since each “non-generic snippet” has to correspond to a convolution filter, if the network is too narrow, the model will fail to learn the “non-generic snippets” of some labels. Therefore the impact of the width of the network can be observed from the perspective of per-label performance.We carry out an ablation experiment on the width of the network by comparing the per-label performance of the wide model (wide-SWAM) and the narrow model (narrow-SWAM) Fig. . The onlTo verify our inference about Correspondences between “informative snippet” and convolution filter, we also compare the informative snippets extracted by both the narrow and the wide model. In order to make the cases representative, from the five labels that has 0 precision in the narrow model, we pick up a label  that has a improved precision in the wide model, and the only label that has 0 precision in both models for analyse.Table The word “hyponatremia”, as a local and low-level feature can be learned by a single convolution filter according to our inference Correspondences between “informative snippet” and convolution filter. Since the only difference between the wide-SWAM model and the narrow-SWAM model is the number of filters in the convolutional layer. Table According to our inference, a narrow network will fail to learn the “non-generic snippet” of a part of labels, which naturally raises a question: what factors determine which “non-generic snippet” will not be learned? The essence of failing to learn different “non-generic snippet” is that the model converges to different local optimal parameters. The convergence result of the model is related to the distribution of data during training, in other words, the order that “non-generic snippets” appear during training: once a filter learns a specific “non-generic snippet” for some labels, the loss function will encourage it to keep its parameters unchanged, and after all the filters have learned corresponding “informative snippet”, it’s difficult for the model to leave the current local optimal solution and learn new “informative snippet”.Therefore we shuffle the training dataset with a different random seed and re-train the models with the shuffled dataset. The results are shown in Table The results in Table The ICD-9 code 285.9 “Anemia, unspecified” is failed to be predicted by both narrow and wide models. Through manual analyzing, we found there are more than 50 codes in the ICD-9 that are in form of “Anemia + specific reason”, which means the snippets related to anemia cannot are necessary but not sufficient for prediction of code 285.9. The prediction of 285.9 Anemia, unspecified is not only based on the presence of snippet related to ‘Anemia’, it is also based on the information that all possible reasons are absent. This is a blind spot in all current machine learning models. It is difficult for models to learn inferences based on missing information.Through the above experiments, we show that compared to other methods, SWAM significantly improves the precision of the worst-performing 10% labels meanwhile achieves better overall performance on the automatic coding task. We proved that this improvement is closely related to SWAM’s ability to learn a large scale of local and low-level features, which makes it suitable for the multi-label text classification task that informative snippets relevant to each label are not shared. Also, SWAM addresses the challenges of interpretability: it provides a satisfactory explanation of the internal mechanics of the deep learning method by establishing the correspondence between “informative snippet” and convolution filter.For future work, we are considering several different directions. From the application perspective, since our approach does work well on 50 labels task, the next step is to apply the approach to the full code set. A major challenge is for full code set, we may need tens of thousands of convolution filters, as the number of filters in the network increases, unnecessary overlap in the features captured by the network’s filters will also increase . We planOur main contributions can be summarized into the following three: 1) SWAM has achieved a significant improvement in the overall performance of the automatic coding task by emphasizing the learning of local and low-level features, thus validating that local and low-level features, a.k.a. informative snippets play an important role in the automatic ICD coding task. The informative snippets extracted from the clinical text provide explanations for each code, which address half of the explanatory challenge mentioned in Background that the model should provide explanations for its predictions. 2) Through ablation experiment on the width of the network, we validate that there exists a correspondence between a convolution filter and a local and low-level feature, and a combination of wide and shallow convolutional layer and attention layer can help the CNN-based models better learn local and low-level features. This finding can help understand the internal mechanics of deep learning methods on tasks like automatic coding, thus bringing progress in the other half of the explanatory challenge mentioned in Background. 3) We improved the precision of the worst-performing 10% labels from 0 to 53% on average.


The future of work paradigm has threatened many occupations but bolstered others such as engineering. Engineers must keep up to date with the technological and cognitive demands brought on by the future of work. Using an exploratory mixed-methods approach, our study sought to make sense of how engineers understand and use creative problem solving. We found significant associations between engineers’ implicit knowledge of creativity, exemplified creative problem solving, and the perceived value of creativity. We considered that the work environment is a potential facilitator of creative problem-solving. We used an innovative exceptional cases analysis and found that the highest functioning engineers in terms of knowledge, skills, and perceived value of creativity, also reported working in places that facilitate psychosocially safe environments to support creativity. We propose a new theoretical framework for a creative environment by integrating the Four Ps  and psychosocial safety climate theory that management could apply to facilitate creative problem solving. Through the acquisition of knowledge to engage in creative problem solving as individuals or a team, a perception of value must be present to enforce the benefit of creativity to the engineering role. The future of work paradigm requires that organisations provide an environment, a psychosocially safe climate, for engineers to grow and hone their sought-after skills that artificial technologies cannot currently replace.The future of work is forcing the world to adjust to a new paradigm of working. New skills will be required to create and adopt new technology and working methods. Additionally, cognitive skills, particularly  Creative problem-solving includes the combination of skills such as communication, critical thinking, complex problem solving, and creativity. The focus of the future of work literature and the need for creative problem-solving in the workplace is not recent; the The future of work is characterised by the integration of humans and automation, artificial intelligence, and cyber-physical systems and is forcing the world to adjust to a new paradigm of working . AdvanceIf creative people are put in situations that do not maximise their abilities, then the company loses many of the possible benefits.”To meet the future of work demands, industry will need to employ creative problem solvers. At the same time, reports on the future of work identify professional occupations with a heavy emphasis on cognitive skills such as engineering, science, and health will be required. Engineering occupations make up 11% of the top 100 jobs least negatively impacted by digital transformation . Since tOur innovative study employs mixed methods combining quantitative and qualitive perspectives to understand how creativity is experienced in the engineering workplace. Mixed methods research is well placed to answer questions that explore the concept of creativity, engineers’ experiences of creative problem-solving, and the psychosocial safety climate in the engineering workplace. In particular, this study interrogates exceptional cases to understand the features of engineers most prepared for the future of work. the interaction among aptitude, process and the environment by which an individual or group produces a perceptible product that is both novel and useful as defined within in a social context”  and malleable  aspects  Four Ps concept: Person, Process, Press, and Product. The ects see , p. 505.mate see , p. 505 Process - is a core component of engineering work. As previously stated, problem-solving – or the value for engineering firms creating an impetus to understand if engineers are creative. However, this information may be more implicit than explicit; knowledge that the knower can make explicit by means of a verbal statement.” Conversely, implicit knowledge is not easily verbalised, and tacit knowledge is not easily reported. Engineers may have better implicit – or tacit - knowledge of creativity than a self-report measure can tell us, and understanding this may be of use for preparations for the future of work, particularly when recruiting or re-training our current engineers. Equally, it is worthy to understand if engineers themselves perceive a value of creativity in their roles. While educators are aware of the new demands for skills in the future of work, there are engineers already practising and unlikely to return to the classroom. As such, this study asks:If the future of work calls for creative problem solving, then that ability has RQ1: Do engineers possess implicit knowledge of creativity?RQ1: Do engineers understand creativity in the context of problem-solving?RQ3: Do engineers value creativity in their role?At the same time that firms are seeking creative problem solvers, a concept gathering more attention is the positive impact on creativity when individuals are in a psychosocially safe work environment see . In thesOver time there has been a growth in literature and theory on the benefits of safe workplaces, starting with Safety Climate , then PsRQ4: How do engineers experience psychosocial safety at work?RQ5: Is there an association between the psychosocial safety climate at work and creative problem-solving in the engineering workplace?“The chain of discovery starts at the coalface with our human ability to notice the unusual or problematic – to swim through the stream of the unknowns and fuzzy concepts that cannot be fully articulated. This is where we collaborate to make sense of the world and create knowledge” (p. 140). This statement illustrates the benefit of exploratory approaches to understanding the current construction of the future of work and the core human skills in demand. New insights can leverage the engineering workforce. The circumstances of the engineering profession  provide a logical context for testing and exploring the theoretical propositions to identify implications for the engineering workforce and possible transferability to other domains.It is understood that assessing for creative potential alone is not enough and has been identified as a weak predictor of creative behaviour . As suchBuilding a research study that aims to understand the relationships between phenomena is complex. In light of limited existing research on associations between concepts included in this study makes it difficult to build on an established basis for hypothesis testing, experiments, or conducting and examining a case study. Thus, the following study is built on exploratory research methods and used mixed methods to provide a deeper, rich understanding of the potential association between the study phenomena. Exploratory research is undertaken when the phenomena under study have little systematic or empirical scrutiny, and the investigator wishes to inductively derive information to generalise about groups, processes, or situations related to the phenomena see . ExploraAlong with new insights derived from innovative approaches to understanding the phenomena, exploratory research can underpin further research that builds upon or tests initial findings. To strengthen this study, a cross-sectional design is used to enhance what generalisability there may be to the engineering workforce as a basis for further inquiry.From an initial exploratory convergent design where the qualitative and quantitative data are collected concurrently and then merged together to provide comprehensive analysis see , the curA strength of qualitative research is its reflexivity, flexibility, and capacity to permit deep insight where quantitative research cannot. Thus, it is essential to harness these characteristics to explore not just the experiences of the “central themes” but investigate the characteristics and world-view of specific, well-performing individuals . The narThe current study recruited a purposive, cross-sectional sample of 25 engineers  from South Australia. Participants were recruited through social media posts, and a peak Australian engineering organisation advertised the study to its local seniors’ group members. All participants held a recognised engineering qualification, with at least one year of experience in the engineering workforce. The mean years of work experience for the sample was 16.33 years, and the mean age of the participants was 48 years. Ethics approval was obtained from the University’s Human Research Ethics Committee. Participants received written information about the research before data collection and provided signed informed consent. Participants completed the interviews and measures individually in private rooms on university campuses of convenience over seven months. There are two reasons that the number of participants equates to 25. First, 25 is the minimum number of participants for statistical analysis to be conducted. Second, through the interview process it was evident that data saturation was being reached as similar responses were accruing from individual participants, therefore making 25 the required number of participants for the present study to answer the research questions.The demographic questionnaire collected information on participants’ age, education, employment, primary language, family, and hobbies.Semi-structured interviews were conducted to obtain meaningful data by exploring the phenomena and revealing participants’ knowledge and perceptions. The Psychosocial Safety Climate 12-item (PSC-12) scale  examinesThe PSC-12 is scored from 12 to 60 and has established benchmarks: a score below 37.6 is poor with respondents at high risk of job strain and mental health issues, and a score above 41 is considered good, with scores in between deemed to be at moderate risk . Based oThe research questions RQ1 through to RQ3 examine the participants’ implicit knowledge of creativity, if they understand creative problem solving (exemplified creative problem solving), and perceptions of creativity . To assess the phenomena, familiarity with the corpus of interview data was the priority. When deciding if the participants had implicit knowledge of creativity, an understanding was inferred by considering the gestalt of the interview responses together. Given that there are two questions about creativity, it allowed the participants to consider their experiences as the interviews progressed. At times, some participants stumbled on the first question inquiring about creative problem solving but later displayed knowledge when considering other questions and prompts. Additionally, the Four Ps  and the definition of creativity were referred to by the authors when considering implicit knowledge and creative problem-solving.Implicit knowledge of creativity, (2) Exemplified creative problem solving, and (3) Value of creativity  vity see . Based oThis scoring rubric facilitates the interview data’s subjective rating and allows the individual assessors (MO and VM) to share and justify their decisions. The factors are deemed favourable and score highly if the participants:1.Exemplify a high degree of understanding of creativity (implicit knowledge), for example, through direct and discrete statements that reveal comprehension through reiterating what creativity is, how it is used in their practice, or use of terms such as “tinker” or “jerry-rig” or “novel” relevant to the example provided. The overall examples provided also indicate the level of understanding; if their example is overtly creative, it is clear that the participant has a high degree of understanding creativity.2.Exemplify creative problem solving through the description and articulation of the example provided by the participant, and whether it is a well-defined problem that was easily solved or one where the participant had to engage in creative problem-solving.3.Believe creativity to be important  to the engineering role, which is expanded upon through direct and discrete statementsFor example, a participant who scores a “3” on interrater rubric questions 1, 2, and 3, provides evidence that they understand creativity by providing examples of creativity, and at the same time acknowledge the importance of creativity to the discipline of engineering.n = 6) of interviews, allocating scores for each of the queries, and also reporting themes or points of interest. The purpose of including an additional rater was to ensure the primary author’s assessments were appropriate and unbiased. Through the questions we used to assess workplace PSC, creativity was also explored. After any discrepancies or biases were discussed in the interviews it was agreed that inter-rater saturation was met; both raters were independently scoring the interviews closely. As a result, a weighted Cohen’s Kappa for ordinal data was conducted, providing good interrater agreement (Kw = 0.61–0.80).Once all interviews had scores allocated for each query, and themes or points of interest noted , an independent academic with expertise on creativity (VM) analysed a random sample  Knowledge of Creativity (Implicit knowledge of creativity), (2) Value of Creativity, (3) Exemplified Creative Problem Solving, and (4) PSC-12. Before further qualitative analysis of the interview data to assess psychosocial safety at work, quantitative analyses were conducted to assess any potential associations between the four factors that could provide insights into all five research questions. We assessed implicit knowledge of creativity, exemplified creative problem solving, perceived value of creativity, and PSC-12 with a three-point ordinal scale from 1–3. Using SPSS statistical software, a Mantel-Haenszel Test of Trend was conducted on each potential association to search for associations between these factors.The Mantel-Haenszel Test of Trend is suited to assessing the three-point ordinal ranked data, subject to data normality. The test is a non-parametric, conservative test reported to be more powerful than chi-square test for association with less sensitivity to small sample sizes . ConsequSD = 7.86). All the raw scores and subsequent results for each measure were normally distributed in the current study through visualisation of Q-Q plots. The PSC mean score was 41.40 (n = 11) of the participants were able to provide clear evidence of implicit knowledge of creativity.RQ1 asked if engineers possess an implicit knowledge of creativity, with the results indicating that 44% (n = 12) of the participants were able to provide clear evidence of creative problem solving as exemplified in their descriptions.RQ2 asked if engineers understand creativity in the context of problem-solving, with the results indicating that 48% (n = 11) of the participants do value creativity in the engineering workplace.RQ3 asked if engineers value creativity in their workplace, with the results indicating that 44%  = 12.46, p ≤ 0.001, r = 0.721  Management facilitation of psychosocially safe workplaces, with an emergent theme of, (3) Teamwork. These are elaborated next.Using inductive analysis of the qualitative data from the Exceptional Cases and interpretations of meaning in the data provided along with the commonalities noted, two primary themes were identified as: (1) “novel” and then second-guesses her use of the term, showing she does understand creativity, even if it is not an academic definition:Exceptional Cases revealed a rich knowledge of, and value for, creativity in their roles. For example, P3C provided an example of explicitly valuing creativity in the engineering role but also implicit knowledge of creativity. P3C goes as far as to use the term I think creativity is thinking outside the box, what’s a novel, oh I shouldn’t say novel, but what’s another way to do it?” – P3CP3C further exemplifies this knowledge by describing a complicated situation involving an instrument malfunctioning in such a deviant manner that even the manufacturer had no precedent to guide solutions:“We came up with an interesting solution using one of our pumps and some flexible piping, a large number of connections, and we actually filled the system and managed to get a really dodgy, but effective, cleaning cycle on the dirty side to get it clean. We had to use a lot ‘what if we do this?’ and ‘what if we add this?’ and it worked!” – P3CP3C’s statement is interpreted as the process of divergent thinking that helps understanding, facilitating better outcomes than just the standard, well-defined solution. In other words, this could be considered innovation. P14N also describes a similar example of not simply selecting the known solution:“I’ve been pushing myself to do that [be creative], so I think the problem is when you know something then you probably know how to solve it, but if you go into a new problem you have never seen, you only have limited knowledge anyway, so if you do the same thing over and over again it might not be the best solution.” – P14Ninstead of taking the accepted method” to find their solution. When asked if this was risky, P91 stated emphatically, “absolutely.” P91 suggests creativity as an engineer is:One of the most experienced engineers, P91, also shared similar thoughts on creative problem-solving in his role and provided an example whereby he, with his team, had to take some risks ““Absolutely essential. You’ve got to think outside the box. You’ve got to. It’s the creativity that’s going to reduce the costs and shorten the time scale and meet what politicians and management want. You’re not going to do it [because] the management said we need it a year shorter… you can’t shorten the program by a year. If it’s only got to be this long, then what are you going to do about it? You’ve got to be creative. You’ve got to think of different ways of doing things. Think outside the box, work out how you’re going to do that. And that’s [sic] the creativity is essential.” – P9I:For one participant, P13M, deviation in the direct work that he performs in his role as an engineer was not an option. P13M works in pharmaceutical production and, much like in other consumable production systems, the role does not lend itself to the direct, practical application of creative processes such as tinkering. However, he does not let that prohibit his understanding and application of creative problem-solving in his task despite there being few opportunities to do so. His approach illustrates that practical boundaries are not an excuse for not understanding, valuing, or implementing creativity in the engineering role. For example“Boring means there are no deviations. Boring means there’s no production downtime. You know, you’re constantly pumping the product out and making money. So, in some cases, boring is good – not being creative is good. However, yeah, it’s crucial. It drives change. It brings us forward. I mean, it gives you a different approach to problem-solving. Continuous Improvement. It’s a good contributor to continuous improvement. I think it’s crucial [creativity], but unfortunately, most of us lack it” – P13Mmanagement facilitation of psychosocially safe workplaces.When the participants were asked if they felt supported psychologically in their workplaces, the Exceptional Cases had much to share on being supported psychologically through either information and culture of their workplaces or direct experiences through their own needs. The questions in the interviews directly asked the engineers to describe a time that they had to engage in creative problem-solving. The Exceptional Cases did not mention management or stakeholders constraining their engagement in creative problem solving; rather, they expressed how they were encouraged and supported to be creative. This finding resulted in a theme of Among good knowledge and experience of psychosocial safety and support in their workplaces, Exceptional Cases also revealed overt managerial support to engage in creative problem solving and provide the safety to test out their ideas. Exceptional Cases participants provided examples through their interviews, where evidence of open communication between management and multi-disciplinary team members facilitated effective solutions to problems. For example, P25Y is in middle management and experiences support from higher levels of management to take opportunities to test out ideas:“I love it [creativity]. Some people just don’t have enough! I love trying it! We are so fortunate where we’ve been given the opportunity to try stuff, pretty much to learn.” – P25Y“I suppose, to encourage people to try even if it is a risk of failure so that you can learn.” – P25YP14N, as an early career engineer, described how she relied on the knowledge and skills she was taught during her degree, and her manager suggested she try solving problems a different way. P14N’s experience, again, aligns with “When I was doing study, I was just ticking a lot of boxes. We were trained to think this way. When I joined here - my manager is a very creative person - and when I first get a problem, I was doing it a textbook way, putting the formula in there and then putting the variables in there, and then doing exactly what I was trained four years for, and then he [manager] inspired me to, ‘why don’t you just do something else?” – P14NThe Exceptional Cases provided rich descriptive responses to the question about psychological safety and support in their workplaces. The two younger engineers (P13M and P14N) stated they felt supported but did not have any personal experiences where they required direct support. Nonetheless they perceived a high level of managerial engagement for those requiring support. The other three engineers had experiences of psychological safety and support they could elaborate on.P3C shares that she has a mental health disorder and that she felt stigma due to the way some staff she had worked with in the past treated her, explaining that this carried through into her accepting work at her current place of employment, where psychological safety has improved:“When I first started working [as an engineer], I was always a little quiet about the fact that I have depression… I didn’t tell people about it because I didn’t want a bad view. And, truthfully, when it did come out, and it came out during a bad time in my life when I was working with [previous employer] as a contractor before I got my job [at current employer]. It was raised, ‘can you actually handle the stress?’ You know, because she’s got a mental problem? And I’m like, ‘yes’ but yeah, so it was, obviously, once known it came as part of how they viewed me.” – P3CP3C goes on to explain how she experiences her workplace and that despite an awkward initial conversation, their understanding of mental health has progressed:“But since then, you know, that was five years ago, and mental health has changed its stigma, and it is improved now, and I’m actually quite vocal, not that I have depression, but a mental health issue. Purely because I don’t want stigma to be there. I want people to know that yes, I have a mental health issue, but I’m totally capable to do my job! So, I think I try change the idea that people have of people with depression.” – P3C[Investigator: And work is supportive?]“Yep! Truthfully, if I went to my boss and said, ‘I need a mental health day because I am not coping,’ he’s like *thumbs up*…He’s good with that, and I think he, I think he also acknowledges that you can have those days.” – P3CThe history of mental health and psychological support was expanded upon while interviewing P9I, who has over 30 years of experience as an engineer. He reports that it was well-managed before the 1980s. P9I reports:“Oddly enough, the whole person was considered well from when I was a younger engineer through ‘til I was in the 1980s, the early 80s period. The finance people got involved, and huge pressures were put on to meet time scale and costs and that sort of thing, and when that happened, the staff management went backwards, due to, I think, those financial pressures. We lost the ability to manage the whole person.” – P91Despite no longer being able to discuss family, personal, and psychological problems with staff; P91 highlights that with progression into management and more experience, instead of reprimanding staff who did not fit the environment, he would seek to find other means for improvement, such as moving them into a different team. P13M, a younger and less experienced engineer, shares his contrasting experience of psychological safety and support as a priority for his workplace:“If there is one thing that’s incredible about the larger corporation is the safety and psychological aspect. Everybody talks about safety and psychological aspect. Everybody talks about its safety. Everybody talks about reducing stress levels. It’s part of the culture. R U OK? That’s the biggest question.” – P13M“They [management] try and encourage honest communication and obviously if you are experiencing an issue you are more than welcome to reach out to a manager or a colleague and report it, how you feel. They are very good like that.” – P13MAnother young engineer, P14N, enthusiastically discussed psychological support from her workplace, particularly in reference to her gender and experience.“I have been [supported]. So, I can confidently answer that question. My manager has been supportive. I think I’m very lucky because you don’t normally get it.” -P14NAs the only female in the company, P14N highlighted the positive impact of her manager supporting and prioritising her safety and boundaries. One example included an after-hours social event with a predominantly male group. Her manager spoke to her in advance and told her that if she feels uncomfortable or harassed, she should talk to him about it, and he will find a way to fight it and take the matter further if not addressed. She reports:“I feel very supported. No such thing has ever happened to me, yet *laughs*, I hope not, but knowing that [support] is in the background is very good.” – P14N“pretty good.” In his prior role, he said, “my phone was never off. It was 24/7 for six years” and described a physical reaction to the phone ringing, both at work and pervading his social life. P25Y currently works in a management position and, in contrast to his own previous experiences, he makes a point of checking that his staff are alright. He expressed the importance of awareness and how he had lost a young friend [not colleague] to suicide the week prior. He shared why he is aware and how he makes sure to keep an eye on his young male subordinates:Excessive job demands underpinned P25Y’s decision to change firms. He reports favourably on his current place of employment and describes it as “It’s probably just more the awareness of bullying. You know… you do of course see on TV and A Current Affair [TV news program] or whatever it is. You see scenarios of where people have been bullied in the workplace and self-harm. And, it’s more, I think, just more about looking after him.”I hope the people in my department feel that they could just grab me and say, ‘hey do you have a sec?’ and we’ll go upstairs to the meeting room.” – P25Y“…[Investigator: What about if you were the one?]“I suppose I see the position I’m in. If I’ve got an issue, I need to make sure… I dragged my boss into a room the other week regarding safety, and, well, I nearly broke down at the time because I was just getting so frustrated about feeling that my team were getting put into unsafe situations, and it was like, ‘I’ve had enough!’ I suppose until you let fly and do get emotional…now I have seen a change in him.” – P25YAt first glance, the above description appears to criticise his current workplace. Rather, P25Y is stating that as a manager, if he needs to talk to his own managers and discuss his concerns, he can do this face-to-face because he feels comfortable doing so. In addition to emphasising the importance of managerial support, emerging from the current study is that teamwork is also an important factor for both creativity and psychosocial safety.“we” over “I.” In fact, in many examples, it was difficult to separate the impact of teamwork and creative problem-solving. The theme of teamwork and open communication between stakeholders in their work was evident in most of these exceptional cases, in particular, to facilitate creativity. P91 does not explicitly state the value of teamwork or examples of where the team or management helped, but he did use the pronoun “we” for all of the examples provided, even in his mentoring role at the end of his professional career; the results were because of “we” and not “me/I.” P3C was the same; she reports on an example of creative problem solving and illustrates that problem solving was a team pursuit when “we came up with an interesting solution.” These implicit examples of the problems being solved through a team process illustrate how an environment of teamwork and communication can lead to new and useful solutions. These examples demonstrate the safety afforded to them to try something, even if it fails, contributes to learning and is not seen as a waste. Here, P25Y also describes how teamwork and open discussions lead to creative problem solving by facilitating risk-taking:The influence of a positive psychosocial workplace was expected to relate to creative problem-solving in the present study, although not specifically explored. Nevertheless, teamwork emerged as a new theme in the rounds of revision of the data through direct examples of the use of “Quite often in this meeting we talk, we’ll have our conditioning monitoring guys, we’ll have a couple of tradesmen, oil analysis guru, and we’ll be talking about an issue. And we’ll say, ‘what do you think the issue is? What are we going to do, and how can we make this better?’ And we might go, ‘Okay, well what about this?’ and at the end of the day, we will say, ‘let’s try it!’ I suppose, to encourage people to try even if it is a risk of failure so that you can learn.” – P25YThe purpose of this research was to answer the primary research question that aimed to understand how engineers experience creative problem solving and psychosocial safety. The current study employed a novel and rigorous approach with advanced iterative methodology and analyses through a mixed-method exploratory design which provided insights to answer specific research questions and provided both depth and breadth of the phenomena, leading to an understanding of the primary research aim. Quantifying the interview data with a second author experienced in scholarly research of creativity was useful as it provided agreement that could be assessed statistically. The final results and interpretations were also considered between the authors, and any misconceptions or disagreements were discussed and resulted in an agreement. The collaborative nature of involving academics from related specialised fields including creativity, human factors, and organisational psychology bolstered the overall interpretations and agreement of the current study. Data from the quantified interviews revealed significant positive associations between three factors: implicit knowledge of creativity, exemplified creative problem solving, and perceived value of creativity to the engineering role.The first iteration of results in the current study led to identifying a clear contrast between specific participating engineers. As a group, the Exceptional Cases all provided detailed understanding and examples of both creativity and psychosocial safety in their engineering workplaces, with a strong perception of the value of creativity in the engineering role. While there was no statistically significant association between PSC-12 and other factors in the statistical analysis, the Exceptional Cases all provided above-average scores on the PSC-12 measure.The next iteration of results led to further scrutiny and interpretation of the Exceptional Cases’ qualitative data. Transforming the qualitative data into ordinal ranked data gave insight into the expected responses of the Exceptional Cases in reference to creativity knowledge, examples, and value. Further examination of commonalities was conducted to explore if other demographic factors could explain the Exceptional Cases; however, nothing of salience was identified.The final examination of the Exceptional Cases highlighted the following factors as meaningful to understanding the primary research question of how engineers experience psychosocial safety and creative problem-solving in the engineering workplace. This process answered RQ4, finding that engineers experience psychosocial safety at work, both formally and informally, with engineers generally experiencing good psychosocial safety. Engineers in more junior levels of experiences revealed their experience of psychosocial safety to be more formalised, whereas the more senior, experienced engineers felt their experiences were less formal but no less supportive. RQ5 asked if there is an association between the psychosocial safety climate and creative problem-solving in the engineering workplace? The deeper qualitative examination of the exceptional cases found that there is an association as the psychosocial safety climate and creative problem solving occurred through management facilitating safe environments to engage in creative behaviours. To summarise, the key factors that impact engineers experience of psychosocial safety climate and creative problem solving are (1) Knowledge and Value of Creativity, (2) Management Facilitation of Psychosocially Safe Workplaces, and (3) Teamwork.potential benefit for the knowledge-holder  would be associated; logic would imply that one cannot perceive the value of creativity if there is no knowledge of creativity because the value of knowledge derives from its e-holder . Furtherormation . This renow-how” . Howevere domain , while acyclical in nature, as described by The importance of imparting knowledge in practice is a characteristic of engineering due to the evolving nature of the discipline through innovation and market demands. Due to the common practice of engineering educators teaching engineering solutions through well-defined problems, ill-defined problems that require divergent thinking are approached with less confidence. When an engineer is educated through well-defined problems, real-world, ill-defined problems provide a challenge that requires creative problem solving to provide solutions. For the engineer, creative problem solving can be experienced as The findings from the current study, bolstered with evidence from other research, highlight that for positive, effective outcomes in the workplace, including creative problem solving, the workers need to feel psychosocially safe. Workplaces with organisational climates that are psychosocially safe influence the work of engineers two-fold: first, the benefits of workplaces where management prioritises the communication, support, and inclusivity of workers in terms of psychological safety facilitates protection and investment in the team’s health and safety. Second, fostering a psychosocially safe workplace where management cultivates safety at the team level will foster an environment that encourages safe and open discussions, not just about psychological health and safety, but to also share and test out ideas without fear of failure. These findings are not altogether new; does have a positive psychosocial safety climate. There may be a disconnection between those who have relied upon management support and those who have not. The Exceptional Cases all reported above-average PSC-12 scores, indicating high levels of psychosocial support from management in all four dimensions. However, as a group, they experienced more practical requirements of psychosocial support, such as requesting time off for mental health care and engaging in open discussions about their psychosocial safety needs. Without further research with the current study participants, the extrapolated evidence is that those who require psychosocial support are in the best position to accurately assess if their workplace The current study explores the engineering profession but argues that psychosocially safe work environments that facilitate creative problem solving may benefit all organisations and workers. The engineering industry must continue to facilitate and support managers to psychosocially safe work environments to foster creativity. Such support provides safety for all team members to openly communicate, test out ideas, and engage in appropriate risk-taking, which, through a virtuous cycle, leads to more creative problem-solving. Recent organisational research acknowledges that psychosocial hazards and risks contribute to harm and are intrinsic to the design of work, but that they should be viewed as strategic points of prevention and/or intervention to reduce prevalent adverse outcomes such as work-related stress and psychological injury , which cSolving problems creatively in the workplace rarely occurs in isolation. In the engineering workplace, engineers have to coordinate with people and willingly and conscientiously contribute their expertise as it develops, so bi-directional learning is always a component of engineering practice see . It is eAdditionally, while the ability to teach engineers to think divergently in educational settings is being espoused, the engineers, as discussed, share information on the job, and if a group comprises some highly creative workers and some less creative, the knowledge exchange can still occur despite differing approaches leading to more possible complex outcomes . Earlierboth team psychological safety and creativity  while neglecting other competing priorities . The foceativity . This iswhy it is perceived as valuable , an author with expertise in their respective discipline of creativity was recruited to validate the interpretations of findings see . In futuThe future of work paradigm is augmenting the traditional understanding of teams as workers are becoming more distributed with the lessening reliance on the physical workplace, and remote working becoming a viable and attractive option for many workers. Through this lens, Value needs further understanding in the creativity literature for scholars, educators, and external stakeholders to exemplify why investing in knowledge acquisition of creativity is beneficial in light of the future of work paradigm.meta-creativity (see The novelty of exploring the various factors through an exploratory study is a strength, as exploratory mixed-methods research is laborious and not afforded to many scholars. In fact, the approach to understanding the phenomena through exploratory methods epitomises vity see . By its michelle.oppert@unisa.edu.au.The datasets presented in this article are not readily available due to continued research on other aspects of the data. All quantitative data are provided in the manuscript. Requests to access the datasets should be directed to the corresponding author MO, The studies involving human participants were reviewed and approved by University of South Australia Human Research Ethics Committee. The patients/participants provided their written informed consent to participate in this study.MO conceptualized the design, collected and analyzed the data, interpreted the findings, and wrote the first draft and subsequent revisions of the manuscript. VM reviewed the interview data and provided inter-rate agreement. MD, RR-P, and DC provided methodological and theoretical guidance. VO’K reviewed the qualitative findings and provided agreement. MO, MD, AR, and VO’K contributed to writing the manuscript. All authors approved the revisions and submitted manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Based on the 2017 China General Social Survey data, with 5,439 observations as research objects, this paper empirically tests the impact of flexible employment on workers’ wellbeing and introduces labor income as mediator and social security as moderator to explore the mechanism of action. The empirical results show that: flexible employment has an inverted U-shaped relationship with workers’ wellbeing, which indicates that increasing employments’ flexibility will first rise and then reduce their perceived subjective wellbeing after reaching the peak; labor income plays a mediating role in the relationship of flexible employment and wellbeing of workers; social security moderates the mediating effect of labor income whereas the moderating role in the relationship between flexible employment and workers’ wellbeing is not observed. Implications and future development of flexible employment are discussed. With the continuous deepening and application of Internet technology in various industries, the platform economy is booming, and new employment forms have emerged . Some prEasterlin first explored happiness from the perspective of economics , and theDoes flexible employment increase or decrease happiness? How does flexible employment affect happiness? These questions are worth thinking about. Existing research rarely discusses that. Although some scholars have proposed the impact of employment on happiness from different aspects , there iFlexible employment includes part-time employment, temporary employment, dispatched labor, part-time labor, self-employed labor, network platform shared labor, etc. . ScholarNevertheless, from a broader perspective, the negative problems cannot be underestimated. According to the theory of dual segmentation of the labor market, workers in the primary labor market can generally enjoy a better working environment, higher self-employment benefits, and more stable jobs, while those in the secondary labor market often face worse work and poor life quality, and their welfare and health conditions are also worse . In factH1: Flexible employment has an inverted U-shaped relationship with workers’ wellbeing: increasing employments’ flexibility will first rise and then reduce their perceived subjective wellbeing at the individual level after reaching the peak.The field of economics usually substitutes “utility” for “happiness.” It is believed that when income increases, an individual’s disposable budget increases and personal utility increases as a result. This implies a greater sense of happiness. Therefore, mainstream economics supports income is positively related to happiness. Flexible employment can increase workers’ income. On the one hand, unemployed workers can obtain temporary job as “stepping stone” through flexible employment, thereby increasing their income during the unemployment period. Especially women who are mothers can benefit from flexible working time arrangements and can obtain higher job satisfaction and happiness in life . On the Existing literature studies have basically confirmed the positive correlation between income and happiness, that is, happiness increases as income level increases  and decrH2: Labor income will mediate the association between flexible employment and workers’ wellbeing. That is, flexible employment will negatively impact labor income, which in turn will decrease workers’ wellbeing.Social insurance is the core content of state social security system. It helps to improve people’s livelihood and maintain social equity. It is of great significance to guarantee life quality of people and enhance the national sense of security. In a large survey of American, individuals with health insurance were more likely to be “very satisfied” or “satisfied” with life . A largeThe social security status of flexible employees is mostly at a low level . On the H3a: The direct and/or indirect associations between flexible employment and workers’ wellbeing via labor income will vary as a function of social insurance. The higher level of social security will attenuate the negative impact of flexible employment on workers’ wellbeing.With the continuous increase in the number of flexible employment groups, the state has paid more and more attention to the insurance of flexible employees and has also issued relevant policies to support it, aiming to adjust the income gap between different groups through the social insurance system and improve people’s happiness. H3b: Social security will moderate the mediating role of labor income in association between flexible employment and wellbeing. The higher level of social security will attenuate mediating effect of labor income in association between flexible employment and wellbeing.To sum up, the research model is as follows .The research data comes from the 2017 China Comprehensive Social Survey. The survey, investigating more than 10,000 households across the country every year to provide data for social research, is a national, comprehensive, and continuous large-scale social project jointly implemented by Renmin University of China in 2003 and academic institutions across the country. In 2017, the data sampling design adopted a multi-stage stratified probability home visit method, and a total of 12,582 valid observations were completed, and the data contained 783 variables. The research selects 10 items in the questionnaire for data processing, deletes observations with missing data, data errors, and data with different values. The study obtains a benchmark sample containing 5,439 observations finally.According to the definition and description of variables, this study summarized and sorted out the relevant items in the questionnaire and re-coded the variables, as shown in b = .378, p < .001), indicating this measurement is reasonable.Flexible employment. We used the question “Which of the following situations is more suitable for your current work situation” to measure “flexible employment” with 5 items. Participants choose form “self-employed entrepreneurs,” “self-employed households,” “formal employed,” “gig employment,” “labor dispatching,” and “freelancing,” where “formal employed” =1, “labor dispatching” =2, “self-employed entrepreneurs” or “self-employed households” = 3, “gig employment” = 4, and “freelancing” = 5. Larger value indicates more flexibility. In order to make the measurement more robust, we tested it with another item which can reflect job flexibility (“To what extent can you decide your own way of working in your current job”). Results show that “flexible employment” significantly positively predicts job flexibility ?” to measure labor income and take the logarithm as the variable value. Choosing “annual labor income” instead of “monthly income” can avoid data errors caused by unstable monthly income of flexible employees and more accurately measure the relationship between variables.Control variables. Drawing lessons from existing studies, age, gender, education level, household registration, and health status may affect the results of the analysis, so these variables are controlled.r = .036, p < .001); the correlation coefficients between flexible employment and the labor income, social insurance variables are .212, −.028, respectively and the correlation coefficients between workers’ wellbeing and the labor income, social insurance variables are .172, .130, respectively. The correlation coefficient between core variables and most of the control variables is significant, which indicates the rationality of selecting these control variables, to a certain extent.The results of the Pearson correlation coefficients are shown in In this study, the hypothesis test is performed by the hierarchical linear regression method. Gender, age, education level, household registration, and health status, are controlled in the regression model. Prior to the regression analysis, the Variance Inflation Factor (VIF) is checked. The results showed that the VIF value is between 1.055 and 1.715, indicating that there is no serious multicollinearity problem between the variables.b = .078, p < .001; b = −.016, p < .05) In addition, we tested the value range of the inflection point. Completing with the quadratic function inflection point formula, it can be seen that the inflection point appears near FE = 2.4375, which is in a reasonable range. According to suggestion of The results of the level regression analysis of each variable are shown in b = .480, p < .001), and the regression coefficient of the square term of flexible employment negatively predicted labor income . Labor income has a positive and significant impact on workers’ happiness , seen in Model 7, indicating that the mediating effect of labor income exists. High labor income stronger the sense of worker’s wellbeing. On the contrary, the lower level of income will reduce the worker’s happiness. Finally, we used bootstrap method to examine the mediating effect of labor income. Results show that the 95% confidence interval of the mediation effect does not include 0 in the test of both FE  and FE2 , indicating that the mediation effect of labor income has reached a significant level, which confirms that labor income plays an mediating role between flexible employment and workers’ wellbeing. Hypothesis 2 is supported.According to the method provided by Baron and Kenn to verify the mediating role of labor income between flexible employment and workers’ wellbeing. In Model 2 of b = .068, p < .001), but the interaction item of FE and SI, positively predict the wellbeing of workers insignificantly as well as the interaction item of FE2 and SI. In order to more intuitively understand the moderating effect of social insurance, we drew a diagram of the moderating effect, as shown in According to the suggestions of Aiken and West, when the adjustment effect is tested, we make the square term of flexible employment and social security variables standardized and then calculate interaction term to avoid the problem of collinearity. The results of Model 6 see  show thab = .125, p < .001), but the value of the interaction item of FE and SI is not significant. Similarly, we got similar results in the moderating test of social insurance on labor income. In Model 3 of b = .057, p < .001). Bootstrap test is performed on the intermediary adjustment model, and the results are shown in In the intermediary adjustment model shown in Model 7 of This study uses 5,439 observations in the 2017 CGSS data to explore the relationship between flexible employment and workers’ wellbeing and analyzes the mediating role of labor income and the moderating role of social security, which draws the following conclusions:There is an inverted U-shaped relationship between flexible employment and workers’ wellbeing, that is, flexible employment can enhance workers’ wellbeing within a certain range, and then reduces the level of wellbeing after reaching the peak. According to the analysis results, appropriate flexibility, providing employees with freedom to work, can improve workers’ wellbeing and labor income in varying degrees. However, with the continuous development of this state, flexibility may evolve to the opposite, manifesting as “extremely unstable.” This negative impact will have a greater impact on individuals. In other words, flexibility and autonomy cannot completely compensate for “informality,” which results in the loss of workers’ wellbeing owing to insecurity and instability. The risk of unemployed at any time and the sense of insecurity felt at work have a direct negative impact on the happiness and health status of employees. These workers who lack stable jobs and economic security are often viewed as typical “urban drifters” with a low sense of social belonging. Thus, it is hard for them to be embraced by strong sense of happiness.Labor income mediated the relationship between flexible employment and workers’ wellbeing. Flexible employment not only directly affects the wellbeing of workers, but indirectly affects that through labor income. Thus, inadequacy in satisfaction of labor income may be one of the explanatory mechanisms for why flexible employment are more likely to develop low-level wellbeing. The effect of flexible employment on labor income is basically the same as the effect of flexible employment on happiness. Flexible employment can help increase the income of workers within a certain range, but this “good” situation will not increase with the increase of flexibility. However, continuing to rise, it reduces labor income after a certain level. There are two possible explanations for flexible employment to reduce labor income. One is, higher-income groups  deliberately sacrifice their labor income in order to seek flexibility and autonomy of work to obtain more disposable time; the other is, the instability of flexible employment itself is directly lead to the instability of labor income, which in turn affects its total income level.Our findings confirmed the moderating role of social security in the mediating effect of labor income. Increasing the level of social security can weaken the negative impact of flexible employment on workers’ wellbeing, or even turn it into a positive impact. This effect is not significant. Furthermore, this result shows that social security can comfort and compensate the unhappiness of flexible employees to a certain extent, but only increasing the level of social security cannot significantly improve their happiness. This is related to a wide range of factors affecting happiness. Although the overall level of labor income is higher than the low-level social security group, the income of flexible employees in high-level social security suffers more “income discount” because of the high cost of social insurance. Those who engaged in flexible employment may have the possibility of paying social insurance at their own expense, which will affect their incomes. As we all known, the compensatory effect of pension works only after retirement for individuals, and medical insurance provide medical expenses compensation only after disease problems emerging.The most substantial contribution of this study is the examination of a mediated moderation model which embraces four variables to explore the inner mechanism of flexible employment’s influence on happiness. As far as we are aware, the existing literature on flexible employment mainly involves the legal risks of labor relations and pay less attention to employees’ wellbeing. Although some scholars have studied that through relevant data, they do not take income and social security into consideration. This study examines both linear and non-linear effects of flexible employment on happiness and simultaneously incorporates labor income and social security into the research model as mediating and moderating variables to interpretate how flexible employment affects workers’ wellbeing, revealing that labor income is one of the primary mediation mechanisms and the level of social security is one way to account for the heterogeneity in the impact of flexible employment on workers’ wellbeing.In addition, the study redefines “flexible employment” from the perspective of “flexibility” and enriches the research perspective. In the past, most researches used “informal employment” rather than “flexible employment” to explore. Those definitions tend to focus on “informal.” When selecting research objects for group restraint, more often they conduct it based on whether employees signed a labor contract and whether they paid social insurance. This research measures “flexible employment” from three aspects, including signation of labor contract, full-time or part-time work, and one or multiple part-time jobs. Considering the attribute of “flexibility and autonomy,” we take both informal employees and formal employees with highly flexibility into this model. Apart from this, non-linear analysis provides new evidence for the study of the relationship between flexible employment and workers’ wellbeing from a new perspective.First, Improving the quality of flexible jobs is a top priority. The impact of flexible employment on labor income is closely related to the quality of employment. High employment quality can increase income and increase the sense of job satisfaction. It can also maximize the time advantages and skill benefits of employees to narrow the income gap between flexible and formal employees. This will enhance the happiness of workers. The quality of employment should also include protecting the basic rights and welfare of workers as much as possible and meeting their safety needs. When income levels no longer cause too much “damage” to happiness, the flexible and autonomous advantages of flexible employment can play a greater role and even produce higher life satisfaction than formal employment. The inverted U-shaped relationship between flexible employment and labor income and happiness can also be effectively improved. In addition, from the perspective of social development, high-quality flexible employment can increase labor productivity and promote economic transformation, which is also of great significance to high-quality development.Second, moderately reducing social insurance rates is a beneficial policy for flexible employees. The high rate of social insurance not only easily increases the probability of informal employment of enterprises, but reduces the willingness of flexible employees to voluntarily pay for social insurance. Appropriate reduction of social insurance rates can improve the level of protection for flexible employees, increase social insurance coverage, and reduce the risk of flexible employees becoming poor due to illness. At the same time, pension income can narrow the income gap , which iSeveral limitations must be considered when interpreting the results of the present study. Firstly, the data adopts the cross-sectional data of 2017, but flexible employment has been in a process of dynamic change in recent years. The impact of flexible employment on workers’ wellbeing may vary across time nodes. In future research, the data of multiple periods can be considered for longitudinal comparative research to explore the change trend of the impact of flexible employment on workers’ wellbeing; Secondly, flexible employment has a wide range of forms where different types of flexible work have different effects on workers’ wellbeing. Future research can classify and distinguish industries or work contents to further study this theme; Finally, there are many paths for the impact of flexible employment on workers’ wellbeing, and the impact results under different paths may be different. The analysis of other path factors is also worth exploring.The original contributions presented in the study are included in the article/supplementary material, and further inquiries can be directed to the corresponding author.DJ: conceptualization, methodology, and project administration. TL and QL: data curation, formal analysis, writing—original draft, and writing—review and editing. All authors contributed to the article and approved the submitted version.This research was funded by General Research Project of Humanities and Social Sciences of the Ministry of Education, grant no. 20YJCZH209.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.