Healthcare workers' informal uses of mobile phones and other mobile devices to support their work: a qualitative evidence synthesis.
Healthcare workers sometimes develop their own informal solutions to deliver services. One such solution is to use their personal mobile phones or other mobile devices in ways that are unregulated by their workplace. This can help them carry out their work when their workplace lacks functional formal communication and information systems, but it can also lead to new challenges.
To explore the views, experiences, and practices of healthcare workers, managers and other professionals working in healthcare services regarding their informal, innovative uses of mobile devices to support their work.
We searched MEDLINE, Embase, CINAHL and Scopus on 11 August 2022 for studies published since 2008 in any language. We carried out citation searches and contacted study authors to clarify published information and seek unpublished data.
We included qualitative studies and mixed-methods studies with a qualitative component. We included studies that explored healthcare workers' views, experiences, and practices regarding mobile phones and other mobile devices, and that included data about healthcare workers' informal use of these devices for work purposes.
We extracted data using an extraction form designed for this synthesis, assessed methodological limitations using predefined criteria, and used a thematic synthesis approach to synthesise the data. We used the 'street-level bureaucrat' concept to apply a conceptual lens to our findings and prepare a line of argument that links these findings. We used the GRADE-CERQual approach to assess our confidence in the review findings and the line-of-argument statements. We collaborated with relevant stakeholders when defining the review scope, interpreting the findings, and developing implications for practice.
We included 30 studies in the review, published between 2013 and 2022. The studies were from high-, middle- and low-income countries and covered a range of healthcare settings and healthcare worker cadres. Most described mobile phone use as opposed to other mobile devices, such as tablets. We have moderate to high confidence in the statements in the following line of argument. The healthcare workers in this review, like other 'street-level bureaucrats', face a gap between what is expected of them and the resources available to them. To plug this gap, healthcare workers develop their own strategies, including using their own mobile phones, data and airtime. They also use other personal resources, including their personal time when taking and making calls outside working hours, and their personal networks when contacting others for help and advice. In some settings, healthcare workers' personal phone use, although unregulated, has become a normal part of many work processes. Some healthcare workers therefore experience pressure or expectations from colleagues and managers to use their personal phones. Some also feel driven to use their phones at work and at home because of feelings of obligation towards their patients and colleagues. At best, healthcare workers' use of their personal phones, time and networks helps humanise healthcare. It allows healthcare workers to be more flexible, efficient and responsive to the needs of the patient. It can give patients access to individual healthcare workers rather than generic systems and can help patients keep their sensitive information out of the formal system. It also allows healthcare workers to communicate with each other in more personalised, socially appropriate ways than formal systems allow. All of this can strengthen healthcare workers' relationships with community members and colleagues. However, these informal approaches can also replicate existing social hierarchies and deepen existing inequities among healthcare workers. Personal phone use costs healthcare workers money. This is a particular problem for lower-level healthcare workers and healthcare workers in low-income settings as they are likely to be paid less and may have less access to work phones or compensation. Out-of-hours use may also be more of a burden for lower-level healthcare workers, as they may find it harder to ignore calls when they are at home. Healthcare workers with poor access to electricity and the internet are less able to use informal mobile phone solutions, while healthcare workers who lack skills and training in how to appraise unendorsed online information are likely to struggle to identify trustworthy information. Informal digital channels can help healthcare workers expand their networks. But healthcare workers who rely on personal networks to seek help and advice are at a disadvantage if these networks are weak. Healthcare workers' use of their personal resources can also lead to problems for patients and can benefit some patients more than others. For instance, when healthcare workers store and share patient information on their personal phones, the confidentiality of this information may be broken. In addition, healthcare workers may decide to use their personal resources on some types of patients, but not others. Healthcare workers sometimes describe using their personal phones and their personal time and networks to help patients and clients whom they assess as being particularly in need. These decisions are likely to reflect their own values and ideas, for instance about social equity and patient 'worthiness'. But these may not necessarily reflect the goals, ideals and regulations of the formal healthcare system. Finally, informal mobile phone use plugs gaps in the system but can also weaken the system. The storing and sharing of information on personal phones and through informal channels can represent a 'shadow IT' (information technology) system where information about patient flow, logistics, etc., is not recorded in the formal system. Healthcare workers may also be more distracted at work, for instance, by calls from colleagues and family members or by social media use. Such challenges may be particularly difficult for weak healthcare systems.
By finding their own informal solutions to workplace challenges, healthcare workers can be more efficient and more responsive to the needs of patients, colleagues and themselves. But these solutions also have several drawbacks. Efforts to strengthen formal health systems should consider how to retain the benefits of informal solutions and reduce their negative effects.
Glenton C
,Paulsen E
,Agarwal S
,Gopinathan U
,Johansen M
,Kyaddondo D
,Munabi-Babigumira S
,Nabukenya J
,Nakityo I
,Namaganda R
,Namitala J
,Neumark T
,Nsangi A
,Pakenham-Walsh NM
,Rashidian A
,Royston G
,Sewankambo N
,Tamrat T
,Lewin S
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《Cochrane Database of Systematic Reviews》
Strategies to improve smoking cessation rates in primary care.
Primary care is an important setting in which to treat tobacco addiction. However, the rates at which providers address smoking cessation and the success of that support vary. Strategies can be implemented to improve and increase the delivery of smoking cessation support (e.g. through provider training), and to increase the amount and breadth of support given to people who smoke (e.g. through additional counseling or tailored printed materials).
To assess the effectiveness of strategies intended to increase the success of smoking cessation interventions in primary care settings. To assess whether any effect that these interventions have on smoking cessation may be due to increased implementation by healthcare providers.
We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and trial registries to 10 September 2020.
We included randomized controlled trials (RCTs) and cluster-RCTs (cRCTs) carried out in primary care, including non-pregnant adults. Studies investigated a strategy or strategies to improve the implementation or success of smoking cessation treatment in primary care. These strategies could include interventions designed to increase or enhance the quality of existing support, or smoking cessation interventions offered in addition to standard care (adjunctive interventions). Intervention strategies had to be tested in addition to and in comparison with standard care, or in addition to other active intervention strategies if the effect of an individual strategy could be isolated. Standard care typically incorporates physician-delivered brief behavioral support, and an offer of smoking cessation medication, but differs across studies. Studies had to measure smoking abstinence at six months' follow-up or longer.
We followed standard Cochrane methods. Our primary outcome - smoking abstinence - was measured using the most rigorous intention-to-treat definition available. We also extracted outcome data for quit attempts, and the following markers of healthcare provider performance: asking about smoking status; advising on cessation; assessment of participant readiness to quit; assisting with cessation; arranging follow-up for smoking participants. Where more than one study investigated the same strategy or set of strategies, and measured the same outcome, we conducted meta-analyses using Mantel-Haenszel random-effects methods to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs).
We included 81 RCTs and cRCTs, involving 112,159 participants. Fourteen were rated at low risk of bias, 44 at high risk, and the remainder at unclear risk. We identified moderate-certainty evidence, limited by inconsistency, that the provision of adjunctive counseling by a health professional other than the physician (RR 1.31, 95% CI 1.10 to 1.55; I2 = 44%; 22 studies, 18,150 participants), and provision of cost-free medications (RR 1.36, 95% CI 1.05 to 1.76; I2 = 63%; 10 studies,7560 participants) increased smoking quit rates in primary care. There was also moderate-certainty evidence, limited by risk of bias, that the addition of tailored print materials to standard smoking cessation treatment increased the number of people who had successfully stopped smoking at six months' follow-up or more (RR 1.29, 95% CI 1.04 to 1.59; I2 = 37%; 6 studies, 15,978 participants). There was no clear evidence that providing participants who smoked with biomedical risk feedback increased their likelihood of quitting (RR 1.07, 95% CI 0.81 to 1.41; I2 = 40%; 7 studies, 3491 participants), or that provider smoking cessation training (RR 1.10, 95% CI 0.85 to 1.41; I2 = 66%; 7 studies, 13,685 participants) or provider incentives (RR 1.14, 95% CI 0.97 to 1.34; I2 = 0%; 2 studies, 2454 participants) increased smoking abstinence rates. However, in assessing the former two strategies we judged the evidence to be of low certainty and in assessing the latter strategies it was of very low certainty. We downgraded the evidence due to imprecision, inconsistency and risk of bias across these comparisons. There was some indication that provider training increased the delivery of smoking cessation support, along with the provision of adjunctive counseling and cost-free medications. However, our secondary outcomes were not measured consistently, and in many cases analyses were subject to substantial statistical heterogeneity, imprecision, or both, making it difficult to draw conclusions. Thirty-four studies investigated multicomponent interventions to improve smoking cessation rates. There was substantial variation in the combinations of strategies tested, and the resulting individual study effect estimates, precluding meta-analyses in most cases. Meta-analyses provided some evidence that adjunctive counseling combined with either cost-free medications or provider training enhanced quit rates when compared with standard care alone. However, analyses were limited by small numbers of events, high statistical heterogeneity, and studies at high risk of bias. Analyses looking at the effects of combining provider training with flow sheets to aid physician decision-making, and with outreach facilitation, found no clear evidence that these combinations increased quit rates; however, analyses were limited by imprecision, and there was some indication that these approaches did improve some forms of provider implementation.
There is moderate-certainty evidence that providing adjunctive counseling by an allied health professional, cost-free smoking cessation medications, and tailored printed materials as part of smoking cessation support in primary care can increase the number of people who achieve smoking cessation. There is no clear evidence that providing participants with biomedical risk feedback, or primary care providers with training or incentives to provide smoking cessation support enhance quit rates. However, we rated this evidence as of low or very low certainty, and so conclusions are likely to change as further evidence becomes available. Most of the studies in this review evaluated smoking cessation interventions that had already been extensively tested in the general population. Further studies should assess strategies designed to optimize the delivery of those interventions already known to be effective within the primary care setting. Such studies should be cluster-randomized to account for the implications of implementation in this particular setting. Due to substantial variation between studies in this review, identifying optimal characteristics of multicomponent interventions to improve the delivery of smoking cessation treatment was challenging. Future research could use component network meta-analysis to investigate this further.
Lindson N
,Pritchard G
,Hong B
,Fanshawe TR
,Pipe A
,Papadakis S
... -
《Cochrane Database of Systematic Reviews》