Bits of plastic blow over the Earth, and they eventually break down into tiny particles.
Scientists recorded a daily rate of 365 microplastic particles per square meter falling from the sky in the Pyrenees Mountains in southern France.
"It was incredible how much microplastic was being deposited," said Deonie Allen, a researcher at EcoLab in the School of Agricultural and Life Sciences in Toulouse, France. There were no obvious sources for the microplastics within 60 miles (100 kilometers), said Allen, the lead author of the study published Monday in Nature Geoscience.
Microplastics are very small pieces of plastic waste. Their presence in oceans and waterways has received a great deal of scientific and media attention in recent years. However, only two previous studies have looked for the presence of microplastics in the air. Both were in cities and their results were comparable, says Allen. Microplastics in the air appear to be ubiquitous.
Allen and colleagues collected microplastics over a period of five months at a meteorological station about 4,500 feet (1,400 meters) above sea level using atmospheric deposition catchers that look like tall funnels. They counted and analyzed the plastic fragments, fibers, and films at the bottom of the collectors that were less than 300 microns in size. The human hair averages between 50 and 70 microns in diameter. The smallest particle a human eye can see is about 40 microns.
More than 50 percent of the microplastics found at the station were fragments less than 25 microns in size.
Researchers studied wind patterns to find a source of the microplastics collected, but found none within a 60-mile radius of the region—which is sparsely populated and without industrial, commercial, or large agricultural activities. A quantity of orange quartz-like fine dust was also collected, said co-author Steve Allen. This was likely Saharan dust, as past studies have shown such dust particles, which are as large as 400 microns, can travel thousands of miles. But "no one knows how far microplastics can travel," he added.
Scientists have warned we are creating a "plastic planet". Some 420 million tons of plastics were produced in 2015, up from just over two million tons in 1950. Over this 65-year period roughly six billion tons ended up either in landfill or in the natural environment, a 2017 study estimated. Plastic waste that starts out as bottles, packaging, and so on degrades over time to microplastic particles or much smaller nanoparticles. One study estimated there are 15 to 51 trillion microplastics particles floating on the surface of the oceans. A trillion is one thousand billion. A trillion seconds is nearly 32,000 years.
People are exposed to microplastics through food and air, but the health effects are unknown, said Stephanie Wright, a researcher at the Centre for Environment and Health at King's College London in the United Kingdom.
"We've only recently recognized human exposure to microplastics through the air," said Wright, who wrote a detailed review article on human health and microplastics in 2017.
What is known is that microplastics smaller than 25 microns can enter the human body through the nose or mouth and those less than five microns can end up in lung tissue. "We do know that other types of small particles do have health impacts," Wright said.
There is a great deal of concern about fine particulates in the air formed by burning fossil fuels, including black carbon or soot. These have been linked to a wide range of health impacts from asthma to heart attacks to impairing children's memory and IQ. Most countries have air pollution standards to limit the volumes of particles less than 10 microns, and especially those below 2.5 microns, respectively known as PM 10 and PM 2.5 standards.
It's also known that microplastics tend to be sticky and can accumulate heavy metals like mercury and persistent organic pollutants (POPs), including brominated flame retardants and polycyclic aromatic hydrocarbons (PAHs). Those materials have known health impacts, said Wright.
The volume of microplastics in the environment is likely going to increase with the rising amounts of plastics being produced, including synthetic textiles, the scientists warn. Plastics are now being used in roads, bricks, concrete, paints, and a host of other things that might not always be obvious to the public. Yet "there's too much we don't know about microplastics in the environment," Wright said.
Far less is known about nanoplastic particles. Nano means really, really small: A billion nanoparticles can fit on the head of a pin.
"No one should be surprised that microplastics are everywhere," said Roman Lehner of the University of Fribourg in Switzerland. Nanoplastics are also everywhere but the technology to detect them doesn't yet exist, said Lehner, who is working on the problem.
Nanoparticles can have markedly different chemical and physical properties than the same materials at micro or larger sizes. One of the unique characteristics of nanoplastics is that because they are so small more atoms are on the surface of a particle compared to its volume. This makes them more chemically reactive. The potential risks to human health and the environment of nanoplastic particles maybe different from microplastics, said Lehner, who co-authored a new review of the potential risks.
Lab studies have shown adverse impacts of nanoplastics on aquatic organisms. Studies have shown that polystyrene nanoplastics ingested by aquatic organisms passed through cell walls. This appeared to change behavior and affected endocrine function of fish and other marine species. Lab experiments have also shown nanoplastics cross cell walls in samples of human intestines.
Even as more research is needed it would be prudent to use fewer plastics, said S. Allen. Single-use plastics like shopping bags and straws need to be eliminated. Recycled plastic just delays its degradation into microplastics, so it is far better to reduce plastic consumption, he said.
As for bioplastics or biodegradable plastics? They still turn into microplastics you can't see, S. Allen said.
Climate change is yet another reason to reduce plastic consumption, a new study published at the same time warns. Nearly all plastics are made from fossil fuels and this industry resulted in emissions amounting to 1.7 billion metric tonnes of CO2 in 2015, according to a new study in Nature Climate Change. With volumes of plastics produced doubling every decade, by 2050 CO2 emissions could reach 6.5 billion tonnes, or about 15 percent of the global carbon budget.
If the plastics industry were a country it'd be the fourth largest CO2 emitter behind China, the U.S., and India. However, aggressive application of renewable energy, recycling, and biomass as a feedstock could keep emissions in 2050 on par with 2015 levels, the study noted. That said, there would also be four times as much plastic being produced.


text:
Karl Lagerfeld and Laura Bailey and Amanda Harlech
I Sew Did
On Couture 2011 Issue
Cute as a Button Girl
It doesn't get much more behind-the-scenes than hanging out with Karl Lagerfeld and the Chanel gang before the autumn/winter show-and actually mucking in to help out with a little last-minute tailoring. You did not! I sew did, says Laura Bailey.
By Laura Bailey
To Paris for the ultimate game of fashion I-SPY as a Chanel apprentice, off to assist with last-minute preparations for the autumn/winter 2011 couture at the mystical rue Cambon HQ, and hopefully learn a few tricks of the trade along the way. I get high in a haberdashery, feel smug if I tack together a fancy-dress costume. (I have been known to use Sellotape when the going gets tough.) I'm not qualified to join a friend's knitting circle, let alone the hallowed circles of haute couture, and my worst teenage school report was from my needlework mistress, who wrote that I "spent too much time sunbathing on the fire escape, unpicking my tie with a compass". I can only do better, but the stakes are high.
The chalky-classical rue Cambon is where Coco Chanel famously opened her first hat shop in 1910, before colonising half the block. I'm clocking in for work at my fashion Mecca as I enter through a side door and a tiny lift beams me up. Sliding screens tease with glimpses of treasures beyond, and I find myself whispering, as if afraid to ruffle the feathers of fashion ghosts past. A reverent hush falls at the heart of the building, but the graceful creatures skipping up the mirrored stairwell hint at the whirling-cogs within, spiralling skywards to the very chimney tops. I inhale, not Chanel No.5, but stony streams and ice cream and just-pressed linen. White on white.
Once upon a time, on a shoot, I might have swanned around those magic rooms in a mood-transforming dress or two. But I've never seen the real backstage beyond hair and make-up. Diva dramas, nervous breakdowns, feathers flying, caffeine-drips? Don't believe the hype. The devil doesn't wear Chanel.
A tiny twisting staircase leads me to the attic workshops (I may never find my way down again), and the first sound I hear is of laughter, as Madame Cécile, "la première", spectacles dangling on a chain around her neck, hair scraped back in a bun, welcomes me to her world, the sun-drenched Atelier Flou, arms cradling dresses on their way downstairs to meet their maker. I've scored a golden ticket to the ultimate dressing-up-box, and I drift around like a teenager in love, at first glancing shyly, then touching, then trying to resist draping myself in finery and asking if I can stay the night.
I am to shadow Judith Lopes, one of Cécile's gifted sidekicks, along with "her" dress. I'd imagined each piece attacked from all sides, but each look is very much the work of one pair of carefully selected petites mains, as these expert seamstresses are known.
There is thus a palpable sense of pride and ownership in the work, and a natural curiosity in the final, one-and-only customer. With 15 years' experience at Flou, Judith, twinkly-dimpled and charismatic, talks with passion of Chanel's couture legacy, the nuts and bolts of which are dependent on the skills she and her colleagues pass on.
"Today is a good day," she tells me, meaning that no last-minute changes of heart have been telegraphed from below. I sense they are all on their toes, despite appearances, never knowing quite who or what is next on Karl Lagerfeld's list. He's both omnipresent and completely mysterious. Like a lover who must be pleased but might not call. Preparation is all.
The worktops in the studio spread out before me like a fantasy patchwork of lace and ruffles, armour and embroidery, each zone delineated by a headless mannequin, to whose proportions first the toile and then the final samples are cut. There are finished dresses, zip-locked in plastic, signed and sealed, but the joy is in matching a pastel-squiggled frill on a sketch to a twirl of organza on a desk, or in scooping up handfuls of the inky navy beads, which will end up on model-of-the-moment Arizona Muse, and letting them run through my hands like pebbles on a beach.
All 25 or so women and a couple of men are in constant fast-fingered motion as I rummage through a desk in search of a pencil for Judith. Family photos, make-up, cigarettes-just like in any office. Oh, and original Lagerfeld sketches destined for the Chanel archives nestling between snapshots of the most beautiful models and actresses in the world.
Cécile runs a tight ship. Den mother as well as the eyes-and hands-of the big boss, she controls all with grace and perfect eyeliner. This is Paris, after all. She's all heels and tailoring, jewellery-clicking, in contrast to her team, whose traditional white coats cover normal work day T-shirts, jeans and pumps.
A couture client is bequeathed a mannequin for life, which may shrink, or grow, as the years pass, cotton stuffing sliced into or padded up. No one night stand, a couture dress can be altered and customised forever, till death do us part. An elite game, shrouded in mystery, and the privilege of the exceptionally rich and mostly anonymous few. Judith tells me that a client's first piece of couture is often her wedding dress, thus setting the bar dangerously high for life. (I'm hoping my own daughter will be grateful if I share my Top Shop discount one day.)
Just as I'm staring, seduced, at the ultimate work-in-progress couture collage tacked to a door, Judith, brave woman, beckons me over to the task in hand. I snap to attention and my apprenticeship begins. I am to stitch the buttons onto the shoulder of a complex pleated black dress, still split into delicate pieces of a silk so fine it could be sliced by a fingernail. I go out of my way not to ask the price of anything I'm touching (even the buttons are specially commissioned treasures from the Desrues atelier, owned by Chanel since 1985), and pretend I'm doing my kids' midnight mending. Judith, giggling, graciously promises not to unpick my work while my back's turned.
I don't even notice when I impale my left elbow on an upturned pin as I sew, extracting it without missing a beat as I nervously check for blood on the frothy sea of lace and tulle that surrounds me. Almost a fashion emergency, but adrenaline is the best anaesthetic.
Judith's bejewelled hands move fast and instinctively as "our" dress nears completion, and together we button it up on the mannequin, pleats falling into flowers falling into feathers. Cécile nods approvingly and I melt with grateful pride, even if I'm by now merely handing pins and smoothing cotton-wool hips. I'm their work experience "button girl", an upstart amateur, indulgently embraced and utterly charmed.
Over breakfast the next day with Amanda Harlech, more-than-muse to the house of Chanel, she explains the demands of couture as well as its powerful influence on the brand as a whole. For Karl and his team, couture allows "creativity without boundaries" and, seen up close, every detail is a work of art in miniature. The camera lies.
Amanda invites me back to the studio to witness "accessorisation", the dress rehearsal if you like, when models arrive one by one for hair and make-up tests, and the finished looks are presented to Karl and his trusted top tier. A serious treat. If my atelier apprenticeship had allowed me a glimpse of the raw, uncut rushes, now, with my late-night pass, I'd see the final edit plus added special effects.
It's the night before the show,and I return to rue Cambon in too-high heels, acting nonchalant, heart racing. I've been to thousands of fittings. I've worn couture (at work). I've met Karl briefly more than once. His empire, which now stretches across the worlds of fashion, photography, film and literature, cannot but intimidate. The prerogative of genius.
I hover outside the door, feeling like I've been summoned to the headmaster's office. The shiny white floor seems to have turned to treacle. I'm not sure if I should knock or who to kiss first or how many times. Luckily, "accessorisation" is already in full swing, and I manage to slip in almost undetected.
In a red-and-white-striped tie, a kind of optical illusion atop a matching shirt, purple jeans and his trademark gloves and rings, Karl sits behind a vast black desk, piled chaotically high with books and magazines, sketches and hot-off-the-press photography. (He shoots all the campaigns himself-I'm not quite sure how or when.) No pristine mausoleum of minimalism, Chanel base camp is a sprawling hub of creativity as the clothes take centre stage before the whispering gallery of photographers and models, stylists and seamstresses. Haute couture here is big business, and it's very much alive.
Everyone knows their part-it's a slick and polished performance. Karl holds court in the centre, springing out of his seat to scan and finesse, and sometimes simply to gossip with the models, many of whom have become part of Chanel's extended family over the years. Cécile pins and tucks, momentarily disappearing as she kneels to wrestle with an underskirt, re-emerging to beam at me when that black dress appears for its show-off spin on the stage. Karl knows I've been sewing in the attic. (He knows everything.) I'm not about to fish for compliments, I'm just relieved as our dress waltzes onwards, perfectly adored, ready for its close-up.
Amanda is in a floor-length sheer floral gown with an 18th-century tiara casually twisted into artfully dishevelled jet-black hair. She sits to Karl's left, admiring and cajoling as hair guru Sam McKnight sets feathered hats at just the right angle over wispy fringes to further accentuate the dark romance of the lace veils masking the models' sooty eyes.
Sasha Pivovarova pirouettes in her classic black suit, cuffs edged in white as if lightly dipped in snow. Virginie Viard, Karl's right-hand woman, the supremely still centre of the fashion tornado, approves Sunday-best white gloves and boots while coordinating more and more complex logistics as the clock ticks. It's a little like going to the ballet, but with a seat in the wings.
This is the first time I've seen the collection in its entirety, celebrating both androgyny and ultra-femininity, the diverse "Allures de Chanel". Stella Tennant switches from a classic boyish grey suit into a show-stopping black gown, all spiky curves, joking with Karl before slipping away into the Paris night.
He tells me that wearing couture should feel like wearing a T-shirt, albeit one with infinite intricate details and hidden layers. I, on the other hand, really am wearing a T-shirt. And it's definitely not the same thing at all. Why, clutching my notebook full of due diligence, am I schoolgirl giggling as I help Karl flick through gossip magazines in search of funny photo-love stories he wants to show me? I'm probably a little bit starstruck, if not just plain shy. Like an ex-boyfriend who knows all your secrets, he just has that gift of all-seeing soul-searching. Big twinkling mischievous eyes. The shades are off!
Too late, I will myself be mysterious and enigmatic (and ideally brunette) as I watch the divine Violette d'Urso (12-year-old daughter of Inès de la Fressange) dance around the studio in her high-school clothes, channelling the curious and carefree spirit of Coco Chanel. Some of us wait years for the invitation. Others are born into it. She gives the famously non-emailing maestro an iPhone masterclass, while I hope he resists temptation. Why text when you can draw your dreams? Karl's talents and passions infuse each other and the dots connect as our conversation darts from still photography to his new passion for film via The Tail of a Fairy, a short film he directed for Cruise in Cannes. And back to frocks. Invention and reinvention. Reverence and irreverence. History and comedy. Like in all the best (fashion) stories.
It's an hour before the show and I'm on a balcony at the Petit Palais with les fidèles, the Chanel girl-army, Anna Mouglalis, Milla Jovovich, Diane Kruger and others too pretty to mention, after a three course feast (all cream and carbs) and champagne toasts. It's the usual controlled chaos, Chanel style. A winter sky palette with flashes of navy and fuschia against the neon-starred Grand Palais. I whisper to Alexa Chung, next to me on the front row, "Those are my buttons." And as the model turns and the tiny silver-trimmed discs catch the light, I celebrate the world I eavesdropped on as the dressmakers' elf. Fade to black as the music is drowned out by the sound of a thousand stiletto heels leaving the building.
Much later, I'm at the Hemingway Bar at the Ritz, home of my Parisienne alter ego. It seems neat vodka is my new drink of choice as Amanda Harlech and her beautiful actress daughter Tallulah talk movies and Daphne Guinness and Hamish Bowles compare notes-or shopping lists-Alexa, Poppy Delevigne and I delay goodbyes, Chanel clutches pooled between us like we're at a fancy village disco.
My veil, the one I'd coveted in the studio, is "in the mail". The closest I'll get to owning a slice of couture. I'm not sure the effect will be the same with a pair of faded jeans. But next time I'm stitching my kids' name tags in the middle of the night, I'll use the sewing kit I stole from the Ritz, and threads of silver and gold.
English Ros
Luciana Val and Franco Musso
See More By Laura Bailey »
Paris Hilton Welcomes Baby Boy with Husband Carter Reum
"You are already loved beyond words," the heiress wrote to her newborn in an announcement on social media.
Kylie Jenner and Doja Cat Attend the Schiaparelli Couture Show in a Lion's Head and 30,000 Swarovski Crystals
The pop star was in the makeup chair for almost five hours to create her final bedazzled look.
Prince William Visits Youth Charity as Royal Family Remains Silent on Prince Harry's Memoir
The Prince of Wales also previously refused to answer reporters' questions during an outing with his wife Kate Middleton last week.
"He's a Bigger Daddy": Channing Tatum Bares All in Lie Detector Test
Vanity Fair's February cover star spills how he would beat Jennifer Lopez in a strip-off and why Jason Momoa is "a bigger daddy" than him.
By Savannah Walsh

redpajama_set_name: RedPajamaCommonCrawl


DOWNLOAD LINEAR ALGEBRA AND ITS APPLICATIONS 4TH EDITION SOLUTIONS MANUAL DAVID C LAY linear algebra and its pdf 9780134022697 / 0134022696 Linear Algebra and Its Applications plus New MyMathLab with Pearson eText... David C. Lay holds a B.A. from Aurora University (Illinois), and an M.A. and Ph.D. from the University of California at Los Angeles. David Lay has been an educator and research mathematician since 1966, mostly at the University of Maryland, College Park.
DOWNLOAD SOLUTION MANUAL OF LINEAR ALGEBRA BY DAVID C LAY 4TH EDITION solution manual of linear pdf Matrix Editions has scored a coup with this title. — SciTech Book News.


text:
Alonso and McLaren - the first time around
Fernando Alonso McLaren
Given his previous tenure at the team, many believed Fernando Alonso would never race for McLaren again. That all changed this week however, when the Spaniard agreed a move back to the Honda-powered team. As the parties prepare to reunite, we take a look back over Alonso's first spell with the former world champions...
"Sometimes in life things do not work out…"
With those words, issued in early November 2007, Fernando Alonso departed McLaren, his relationship with the team he'd supported as a boyhood Ayrton Senna fan eroded in barely 11 months.
It was all supposed to be so different.
Alonso arrived in Woking with the world at his feet; a 25-year-old double world champion who'd not only ended Michael Schumacher's unprecedented run of titles, but also helped usher the legendary German into retirement.
For McLaren, a team that had suffered the ignominy of seven title-free years despite their vast resources, the Spaniard was deemed the missing piece of the jigsaw puzzle: not only did he possess a devastating ability behind the wheel, but two drivers' crowns had done nothing to quench his thirst for success. Alonso was convinced he'd made the right move at the right time, as was McLaren's meticulous team principal Ron Dennis, who was no doubt delighted when the world champion reported for work in Woking with a neatly-cropped new haircut…
A new F1 superpower had seemingly been forged, with shared goals and a similar desire for immediate success. What could possibly go wrong? The answer was nothing, at first. Testing revealed the Mercedes-powered MP4-22 to be everything Alonso had hoped for when he'd agreed to leave home-from-home Renault a year earlier - a car capable of challenging for the world title, even in the face of strong opposition from Ferrari. However, at the season-opener in Australia it became obvious that the reigning champion would have more than just the red cars to contend with in 2007.
Almost no one had expected Lewis Hamilton to be such a strong competitor in his maiden F1 campaign, but there he was in Melbourne, the GP2 champion and a driver that McLaren had nurtured from childhood, brazenly sweeping around the outside of his elder team mate into the first corner.
It's too simplistic to suggest Hamilton's meteoric emergence (and the fanfare that accompanied it) was the sole reason for cracks appearing in the relationship between Alonso and McLaren over the 2007 season, but it certainly seemed to prevent the Spaniard - who had never faced such in-house rivalry - from settling at his new squad.
At first Alonso had the better of the exchanges, overhauling Hamilton in Australia and then leading him home for a one-two in Malaysia. But in Bahrain, where Dennis was pictured having an unusually public heart-to-heart with his star driver, he was outperformed by his rookie team mate. In two of the next three races he then made uncharacteristic errors as he was again bested by Hamilton, though he did win brilliantly at Monaco in between.
By the season's halfway point Hamilton's rock-solid consistency allied to wins in Canada and the USA had given him a 14-point lead over his elder team mate and, with McLaren committed to providing both their drivers with an equal chance, a legitimate shot at the title.
On the back foot for arguably the first time in his F1 career, Alonso found himself increasingly at odds with McLaren. First there was the sudden swerve towards the pit lane at Indianapolis whilst running a close second to Hamilton. Alonso denied it, but many attributed the act to his annoyance at McLaren's refusal to make the marginally slower British racer move aside. Then there was the furore that unfolded during a notoriously bad tempered qualifying session in Hungary where Alonso was docked five grid places after being found guilty of blunting Hamilton's pole charge by loitering in McLaren's pit box.
Later it emerged that emails between the Spaniard and test driver Pedro de la Rosa had formed part of the evidence in the McLaren-Ferrari 'spy scandal'; the controversy that ended up earning the Woking team an unprecedented $100 million fine.
Surprisingly, rather than going completely off the boil amid the growing rancour behind closed doors, Alonso's title charge intensified. Little by little the double world champion began to look more and more like the driver who had bettered Michael Schumacher the year before, winning with authority at the Nurburgring and Monza to close the points gap to Hamilton.
Ultimately both he and his team mate would lose out in the championship stakes to Ferrari's Kimi Raikkonen, though Alonso's third place at the Interlagos season finale did at least enable him to finish level on points with Hamilton, albeit a position lower in the standings by virtue of count back. Outside of his maiden season with Minardi, it remains the only time in the Spaniard's F1 career that he has finished below a team mate over a full season.
In total, Alonso won four of his 17 races with McLaren, taking eight other podiums as well as two pole positions - a very decent return in a season in which dominance swung back and forth between Woking and Maranello.
However, it was wholly unsurprising when, less than two weeks on from the final round in Brazil, McLaren and Alonso agreed to an amicable divorce.
"We have had our ups and downs during the season, which has made it extra-challenging for all of us, and it is not a secret that I never really felt at home," the exiting Alonso candidly explained.
"I know there have been suggestions of favouritism within the team and people say a lot of things in the heat of battle, but in the end I was always provided with an equal opportunity to win."
Seven years and a lot of water under the bridge later, winning remains Alonso's primary motivation, though he didn't do any in 2014, his fifth season with Ferrari. Despite several near misses, his tenure at the Scuderia also failed to yield any championships, meaning that he returns to McLaren with the same goal he had in 2007: winning that elusive third drivers' crown.
Who knows, perhaps like his boyhood hero Senna, he'll achieve it in a McLaren-Honda...


text:
New Comics Festival in Columbus, Ohio
Dan Gearino from The Columbus Dispatch.
Columbus will be the site of a new comics festival that will seek to attract a national and international audience, organizers said yesterday.
The first Cartoon Crossroads Columbus — CXC for short — will be held in October 2015.
Its organizers include Jeff Smith, a cartoonist and co-publisher of Cartoon Books of Columbus, and his wife, Vijaya Iyer, who is president and co-publisher.
"I'm very excited," said Smith, the festival's artistic director. "I love this city, and I'm so proud of what it's done in the last 15 years, the last 10 years, and I just want to show it off to the comics community."
The festival will work closely with the Billy Ireland Cartoon Library & Museum at Ohio State University.
Lucy Caswell, the museum's founding curator, is also among the festival's organizers.
Daily planning of the event will be led by Tom Spurgeon, editor of ComicsReporter.com, a comics news website. He will move to Columbus early next year.
The first festival will be Oct. 2-3, 2015. The first day will take place at the cartoon museum. The second day will take place at the Columbus Cultural Arts Center and is expected to feature as many as 35 exhibitors, comics artists and publishers selling their work.
In 2016, organizers plan to expand the festival to four days.
The Columbus event will cover comic books, comic strips, editorial cartoons and animation. It is likely to attract some of the same audience that attends events such as the Toronto Comic Arts Festival in Canada, Smith said.
The Toronto event began in 2005, and attendance has grown from a few thousand to 22,000, according to that festival's website.
The Columbus festival will have a somewhat different audience from comics and pop-culture conventions such as Wizard World's Ohio Comic Con, which is scheduled for Sept. 18-20 next year.
Central Ohio also has a long-standing independent comics festival called Small Press and Alternative Comics Expo, or SPACE. The next one will be April 11-12.
Megumi Robinson, spokeswoman for Experience Columbus, the local tourism office, expressed the group's pleasure at news of the new event. "We are excited that CXC will bring an annual festival to Columbus, as it will attract top-notch national, independent writers and artists to Columbus," she said.
dgearino@dispatch.com
@DanGearino
Tags : Animation, Comics, Editorial cartoon, Exhibitions
"You Might Be From New Brunswick If…"
RIP: Best Editorial Cartoons of the Year, 1971-2013
National Gallery of Art Welcomes First Comic Books...
Terry Gilliam: "Things Happen"
"The Art of Richard Thompson"
British Political Cartoon of the Year Awards
Seven Top Portrait Artists
Dušan Petričić Profiled
Ben Lafontaine 1963-2014
Bill Watterson draws the Angoulême 2015 Poster
Publicité Sauvage at L'Affichiste


text:
AP will be made knowledge hub of India: Chandrababu Naidu
ANI | Updated: Dec 27, 2017 15:16 IST
Amaravati (Andhra Pradesh) [India] Dec. 27 (ANI): Andhra Pradesh will be made knowledge hub of India, Chief Minister N. Chandrababu Naidu said on Wednesday.
He was addressing a function in which President Ram Nath Kovind dedicated Andhra Pradesh (AP) Fibre Grid and drone project to the nation.
"We are trying to make Andhra Pradesh no.1 in the country and it will be made knowledge hub of India. Students of AP are very strong in Information Technology (IT) and they are ruling in world IT industry," Naidu said.
Talking about the economy of the state, Naidu said, "Our economic parameters are very strong vis a vis India. However, post bifurcation we have got down in some parameters, but we are striving to reach top position."
He added that good economics coupled with good governance, and led by good politics make the state flourish.
Praising country, Naidu said, "India is the only country which can achieve and continue with double digit GDP (gross domestic Project) in near future. However, there are some problems too, like Indian Banking sector is suffering with NPAs of 10 lakh crore."
He, however, further added that 2017 is a landmark year in Indian economy.
"The Centre took some revolutionary steps, like the Budget was preponed, railway budget was merged with general budget. Moody's has recently upgraded India rating. Therefore, 2017 is landmark year in Indian economy," Naidu said.
He also said India will be one of top three economies along with USA and China.
"India is strong in English and technology. India is full of youth now. So, near future is very bright," the chief minister said.
He thanked President Kovind for dedicating Andhra Pradesh (AP) Fibre Grid and drone project to the nation. Andhra Pradesh Governor ESL Narasimhan was also present on the occasion.
The vision of Fibre Grid project is "to establish a highly scalable network infrastructure, accessible on a nondiscriminatory basis, to provide on demand, affordable and end-to-end broadband connectivity of 15 Mbps for all households and 100 Mbps to 1 Gbps for institutions & Offices by 2018, to enable realization of the Vision of Digital AP, in partnership with the Government of India and the private sector."
AP State FiberNet Limited (APSFL) is responsible for undertaking the works of AP Fibergrid , its operations and maintenance and business activities.
The AP government wants to use drones for governance, administration, and for the maintenance of law and order in the state.(ANI)
President Ram Nath Kovind
Andhra Pradesh Fibre Grid
AP surveillance & drone project
Governor ESL Narasimhan
Chief Minister N Chandrababu Naidu


text:
mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (393) Vaccination and Immunization in the Digital Age (244) mHealth for Wellness, Behavior Change and Prevention (2204)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20356, first published May 21, 2020 .
Social and Behavior Change Communication Interventions Delivered Face-to-Face and by a Mobile Phone to Strengthen Vaccination Uptake and Improve Child Health in Rural India: Randomized Pilot Study
Mira Johri 1, 2 ; Dinesh Chandra 3 ; Karna Georges Kone 1, 4 ; Marie-Pierre Sylvestre 1, 5 ; Alok K Mathur 6 ; Sam Harper 7, 8 ; Arijit Nandi 7, 9
Mira Johri1,2, MPH, PhD ;
Dinesh Chandra3, MA ;
Karna Georges Kone1,4, PhD ;
Marie-Pierre Sylvestre1,5, PhD ;
Alok K Mathur6, PhD, MBA ;
Sam Harper7,8, PhD ;
Arijit Nandi7,9, PhD
1Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
2Département de gestion, d'évaluation, et de politique de santé, École de santé publique de l'Université de Montréal, Montréal, QC, Canada
3Independent consultant, New Delhi, India
4Principal Technical Advisor for Health Financing at Management Sciences for Health (MSH)/USAID, Port-au-Prince, Haiti
5Département de médecine sociale et préventive, École de santé publique de l'Université de Montréal, Montréal, QC, Canada
6Indian Institute of Health Management Research University, Jaipur, India
7Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, QC, Canada
8Department of Public Health, Erasmus Medical Centre, Rotterdam, Netherlands
9The Institute for Health and Social Policy, McGill University, Montreal, QC, Canada
Mira Johri, MPH, PhD
Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM)
850, rue St-Denis
Montréal, QC, H2X0A9
Email: mira.johri@umontreal.ca
Background: In resource-poor settings, lack of awareness and low demand for services constitute important barriers to expanding the coverage of effective interventions. In India, childhood immunization is a priority health strategy with suboptimal uptake.
Objective: To assess study feasibility and key implementation outcomes for the Tika Vaani model, a new approach to educate and empower beneficiaries to improve immunization and child health.
Methods: A cluster-randomized pilot trial with a 1:1 allocation ratio was conducted in rural Uttar Pradesh, India, from January to September 2018. Villages were randomly assigned to either the intervention or control group. In each participating village, surveyors conducted a complete enumeration to identify eligible households and requested participation before randomization. Interventions were designed through formative research using a social marketing approach and delivered over 3 months using strategies adapted to disadvantaged populations: (1) mobile health (mHealth): entertaining educational audio capsules (edutainment) and voice immunization reminders via mobile phone and (2) face-to-face: community mobilization activities, including 3 small group meetings offered to each participant. The control group received usual services. The main outcomes were prespecified criteria for feasibility of the main study (recruitment, randomization, retention, contamination, and adoption). Secondary endpoints tested equity of coverage and changes in intermediate outcomes. Statistical methods included descriptive statistics to assess feasibility, penalized logistic regression and ordered logistic regression to assess coverage, and generalized estimating equation models to assess changes in intermediate outcomes.
Results: All villages consented to participate. Gaps in administrative data hampered recruitment; 14.0% (79/565) of recorded households were nonresident. Only 1.4% (8/565) of households did not consent. A total of 387 households (184 intervention and 203 control) with children aged 0 to 12 months in 26 villages (13 intervention and 13 control) were included and randomized. The end line survey occurred during the flood season; 17.6% (68/387) of the households were absent. Contamination was less than 1%. Participation in one or more interventions was 94.0% (173/184), 78.3% (144/184) for the face-to-face strategy, and 67.4% (124/184) for the mHealth strategy. Determinants including place of residence, mobile phone access, education, and female empowerment shaped intervention use; factors operated differently for face-to-face and mHealth strategies. For 11 of 13 intermediate outcomes, regression results showed significantly higher basic health knowledge among the intervention group, supporting hypothesized causal mechanisms.
Conclusions: A future trial of a new intervention model is feasible. The interventions could strengthen the delivery of immunization and universal primary health care. Social and behavior change communication via mobile phones proved viable and contributed to standardization and scalability. Face-to-face interactions remain necessary to achieve equity and reach, suggesting the need for ongoing health system strengthening to accompany the introduction of communication technologies.
Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN) 44840759; https://doi.org/10.1186/ISRCTN44840759
randomized controlled trial; immunization programs; child health; mHealth; health promotion; health services accessibility; implementation science; pilot projects; developing countries; global health
Expanding coverage of effective interventions is a critical challenge for many low- and middle-income countries (LMICs). In addition to technical improvements in service delivery, improving coverage often hinges critically on enhanced awareness and demand for services on the part of beneficiaries. Furthermore, in settings of low literacy, deep poverty, and poor access to information, behavior change is extremely challenging.
Immunization is a priority health strategy for LMIC policy makers seeking to advance the 2030 United Nations (UN) Sustainable Development Goals (SDGs) due to its inherent value in reducing the burden of disease and its potential role as a lever for health system strengthening. Immunization reaches more households than any other health service, bringing communities into regular contact with the health system [1]. The immunization platform can potentially be used to strengthen the delivery of universal primary health care, universal health coverage, and meet other SDG targets [1]. This approach may be particularly salient in areas where vaccination delivery systems function reliably, but important gaps exist in the delivery of other health services. In these contexts, increasing immunization coverage offers a potential pathway to expand the range and reach of health services and to advance a holistic health agenda.
In India, the government has prioritized immunization, making remarkable gains in recent years. However, coverage continues to fall short of the target to fully immunize 90% of India's infants against 7 vaccine-preventable diseases by 2020 [2]. Nevertheless, immunization delivery now outperforms other services, offering a potential lever for system strengthening. In rural north India, for example, research shows that high-priority primary care interventions, including vaccination, are being delivered quite well, whereas other basic health promotion and prevention services are largely not provided, constituting a critical missed opportunity for population health [3]. On the basis of analysis of Indian immunization program data, achieving and sustaining vaccine coverage targets especially requires new strategies to address gaps in beneficiary demand [2]. Recent systematic reviews and meta-analyses have demonstrated that knowledge translation and education strategies, such as those offering education at village meetings or at home, are likely to improve vaccination coverage [4,5]. However, strategies based on face-to-face communication may be challenging to standardize and deliver at scale.
The widespread availability of mobile phones in LMICs has stimulated interest in the potential of mobile health (mHealth) interventions to achieve health objectives. A recent systematic review found that mHealth interventions can improve maternal and neonatal service delivery and that text-based vaccination reminders are associated with improved vaccination coverage [6]. Although their potential for scalability at low cost is attractive, whether mHealth interventions can be effective for highly disadvantaged populations facing substantial barriers due to poverty, low literacy, and gender norms is uncertain.
Goal of This Study
We developed the Tika Vaani (vaccine voice in Hindi) model to educate beneficiaries about immunization and basic child health themes, dispel misinformation, and empower households to better care for their children and themselves. A key distinguishing feature of the model is that it integrates an mHealth component to increase standardization and scalability of social and behavior change communication. The interventions were delivered through small face-to-face meetings and via mobile phone using strategies (context-appropriate audio messages delivered via automated phone calls) adapted to disadvantaged populations. We conducted a pilot randomized controlled trial (RCT) applying an implementation research lens to inform a future large-scale RCT. This paper presents the main (quantitative) evaluation of the pilot trial focusing on two objectives: (1) to assess the feasibility of processes critical to the success of the main study (recruitment, randomization, retention, and contamination) and intervention uptake (adoption) and (2) to study key implementation outcomes to optimize successful delivery of the interventions at scale [7]. Objectives pertained to cluster and individual levels. A companion paper presents findings related to intervention fidelity, acceptability, and appropriateness using mixed (qualitative and quantitative) methods (Pérez et al, unpublished data, 2020).
Trial Design
In keeping with the plan for the main study, this pilot study adopted a cluster-randomized design with a 1:1 allocation ratio. A cluster design was chosen owing to the nature of the study interventions: face-to-face interventions are structured around communities rather than individuals, whereas mHealth interventions have a possibility of contamination. Clusters were rural villages in a district of Uttar Pradesh (UP), India. Villages were randomly assigned to either the intervention or control group (CG). The protocol was registered in a WHO International Clinical Trials Registry Platform-compliant registry (ISRCTN44840759 doi.org/10.1186/ISRCTN44840759). There were no important changes to methods after trial commencement. We originally sought to register the trial in the Clinical Trials Registry–India (CTRI), which is free of charge and has as the mission to enroll all clinical trials conducted in India. The CTRI took several months to follow-up; in the interim, we applied to a different registry. Owing to the delay caused by waiting and changing registries, the trial was registered shortly after patient enrollment was completed.
Setting and Location
India's most populous state of over 200 million residents, UP is an area of national focus due to lagging health and development indicators. Hardoi (population 4 million; under-5 mortality rate 118 per 1000; cf. UP under-5 mortality rate 90 per 1000, India under-5 mortality rate 57.3 per 1000) [8,9]) is a low-performing, rural district within UP comprising 19 administrative blocks. Thanks to recent Government of India (GoI) initiatives, the proportion of fully immunized children aged between 12 and 23 months in Hardoi district rose from 26.5% in 2007-2008 [10] to an estimated 65.9% (95% CI 62.0%-69.8%) in 2018 when this study was conducted [2]. A single administrative block of the Hardoi district was selected for this pilot based on criteria reflecting logistics and needs.
Villages (clusters) were eligible for inclusion if they had less than 4000 inhabitants and were located in Bawan Block, Hardoi, UP. In participating villages, interventions were offered to all residents. Participants in the baseline survey were consenting primary caregivers of children aged between 0 and 12 months residing in a study village. We excluded those who were not able to understand and speak Hindi or Urdu or those who did not intend to reside in the village for the study duration (6 months). The same individuals were approached for the end line survey.
The survey sampling unit was the household. We conducted a door-to-door census of the village and cross-checked administrative records from the Anganwadi workers (AWW) and Accredited Social Health Activists (ASHA) to identify all households containing a child in the age range of 0 to 12 months within each village. These households constituted our primary target group.
Formative Research
From January 1, 2017, to January 10, 2018, we conducted formative research using a social marketing approach to inform intervention design [11]. An iterative, participatory approach involving cocreation was favored to validate the need for the interventions, to make the interventions more compelling and linguistically and culturally appropriate, and to tailor approaches to different user segments [11]. Content was designed by Gram Vaani, an Indian social enterprise specializing in community media platforms for low-literacy rural populations, and Jagriti, a local NGO. Content fostered equity, empowerment, and social inclusion through positive portrayals of diverse characters. Technical experts assured information quality, including members of the research team and India's Ministry of Health and Family Welfare [11]. Extensive adaptations to interventions were made to meet target population needs during the formative research phase [12]. During the pilot RCT, all intervention components were frozen for evaluation, and deviations to intervention fidelity were systematically monitored (Pérez et al, unpublished data, 2020.
Pilot RCT
The study interventions took place over a 3-month period and offered social and behavior change communication (SBCC) for members of the general public in rural Indian villages, addressing topics related to child health. The primary target group was families residing in a selected village with a child in the age range of 0 to 12 months. Although vaccination was the primary focus of the study, the SBCC interventions addressed additional areas stipulated to be co-delivered with immunization during Village Health and Nutrition Days (VHNDs), such as health education related to health care entitlements; prevention, recognition, and management of common infectious diseases (diarrhea, pneumonia, dengue, and chikungunya); nutrition; and water, sanitation, and hygiene (WASH).
SBCC materials were delivered through 2 channels: (1) mHealth: educational audio capsules in entertaining formats (edutainment) and voice reminders for immunization sessions broadcast via mobile phone and (2) face-to-face: community mobilization activities, consisting of 1 large introductory meeting to introduce the project to communities and 3 small meetings offered to each participant covering specific themes. For the mHealth component, push messages (automated dial outs) and voice-based reminders were privileged owing to low education level and comfort with technology. For the face-to-face component, small group meetings were held separately for men and women and in different geographical locations within villages to ensure ease of communication. mHealth vaccination reminders were based on the child's birthdate and offered only to the target group; however, other interventions (mHealth edutainment and face-to-face meetings) were open to all village residents. Community workers (AWW and ASHAs) were encouraged to participate and received advance access to intervention materials. All interventions were free of charge to end users. The CG received standard GoI health and welfare services.
The mHealth strategy (Tika Vaani SBCC Version 1.5, released on July 7, 2017) was designed and delivered by Gram Vaani, a social tech startup incubated out of the Indian Institute of Technology Delhi, using the Mobile Vaani Interactive Voice Response System. Access was free and open to anyone who called the number. The participants could give a missed call to access the platform, and as a result receive a callback enabling them to access all content, record any queries or feedback, or be connected to a live expert. To simplify access, consenting households in intervention villages with children aged less than 12 months at baseline received automated outbound calls twice per week. In total, 26 content pieces were offered. In addition, child vaccination reminders were sent to target group households. Small group meetings lasting approximately 1 hour involving 2 trained facilitators with a minimum of 12 years of education were held once per month and open to all village residents. The access number was shared at each meeting. A video describing Mobile Vaani is available [13]. Additional information relevant to scale up and replication of the Tika Vaani system is available [11] and content is accessible [14]. A comprehensive intervention description is provided in Multimedia Appendix 1 [15]. The evaluation was conducted by a team of academic specialists distinct from the developers.
The pilot study considered a range of implementation outcomes (Table 1) [16].
Table 1. Outcome variables and data sources for the Tika Vaani social and behavior change communication pilot study.
Outcomes Definition Approach Analysis sample Data sources
Primary outcomesa
Feasibility of the future main study Ex-ante success criteria
Quantb IGc and CGd
Project records (all)
IVRe platform
HHf surveys (contamination)
Uptake (adoption) Participation in
Small group meetings
mHealthg
Quant IG
Project records (meetings)
IVR platform (mHealth)
Acceptability and appropriateness Perception among stakeholders that an intervention is agreeable, suitable, relevant, useful, and credible Mixed methodsh IG Refer to the study by Pérez et al (unpublished data, 2020)
Fidelity Ability to deliver the interventions as planned Mixed methods IG (and CG) Refer to the study by Pérez et al (unpublished data, 2020)
Coverage The degree to which a population eligible to benefit from an intervention actually receives it Quant IG
HH surveys
Adequacy of the program theory Intermediate outcomes reflecting changes in knowledge, attitudes, and practices of end users Quant IG and CG HH surveys
aOutcomes and definitions adapted from the study by Peters et al [16].
bQuant: quantitative.
cIG: intervention group.
dCG: control group.
eIVR: interactive voice response.
fHH survey: household survey.
gmHealth: mobile health.
hMixed methods: quantitative and qualitative.
We established ex-ante criteria for the feasibility of the main study related to recruitment, randomization, retention, and contamination. We were concerned about contamination among treatment groups for mHealth services, as the phone number is easily shared. We viewed a contamination proportion exceeding 15% as a threat to the feasibility of adopting a cluster-randomized design with village as the unit of randomization and geographical distances between villages (mean 15 km; range 5 km-50 km) similar to those in the pilot. As health interventions must achieve sufficient uptake to impact population health, we also established minimum criteria for participation in the new interventions.
We present quantitative findings for 2 secondary outcomes: (1) coverage or the extent to which the interventions reached specific populations and (2) adequacy of the program theory. We constructed a logic model describing the hypothesized program impact pathway and mechanisms of action (Figure 1) and adapted an established vaccination communication taxonomy to define indicators [17]. We compared treatment groups on outputs (intermediate outcomes, such as knowledge and attitudes) related to the intervention theory of change.
Figure 1. Conceptual model of the intervention. ASHAs: Accredited Social Health Activists; AWWs: Anganwadi Workers; CIHR: Canadian Institutes for Health Research; IC-IMPACTS: the India-Canada Centre for Innovative Multidisciplinary Partnerships to Accelerate Community Transformation and Sustainability; WASH: water, sanitation, and hygiene.
Quantitative data were collected from the following sources:
Face-to-face surveys: Interviewer-administered household surveys were conducted in all participating study villages. Surveys were administered at baseline before random group assignment and approximately 5 months later following interventions at end line.
Project administrative records: Standardized forms to assess delivery of study procedures and interventions were maintained by field staff to facilitate structured observation and data capture.
Interactive voice response (IVR) system: The IVR system automatically recorded all calls to the platform. IVR data can be disaggregated by various fields including caller phone number, date, time, frequency, duration (seconds), call type, content type, and user characteristics. IVR data were linked to phone numbers provided by target households during the baseline survey to map calls sent and/or received.
We measured the use of the IVR through the number and duration of calls from a unique phone number. We considered that an mHealth item was received if the caller remained connected for 80% or more of the item duration. Contamination was defined as the proportion of calls originating from control villages and assessed using 2 data sources: (1) the IVR system to identify unknown numbers and trace nonregistered callers to identify call origin and (2) questions were included about intervention use in the end line survey administered to the treatment and CGs (Multimedia Appendix 1). To construct wealth quintiles, we performed principal component analysis to create a relative index of household wealth from a list of assets used in major household surveys [10,18]. We used this index to divide the sample into quintiles [19]. A similar approach was used to construct women's empowerment terciles. Caste was represented in 4 categories (general, other backward caste, scheduled caste, or scheduled tribe) ranging from most to least advantaged, as for Indian national surveys. By convention, caste categories are applied to all population groups, irrespective of religion. For intervention group (IG) households only, implementation teams assessed whether households were able to attend small group meetings based on geographical distance from their place of residence to anticipated meeting sites. This categorization was made at the study baseline, before undertaking interventions.
Although the pilot was a cluster-randomized two-group study, the study size was based on the rate of contamination among controls. We estimated the required sample size needed for the CG using methods for a one-group descriptive study. We assumed that the true proportion of contamination (calls originating from controls) was 10%, that contamination was most likely to arise from parents of young children, and that there would be 20 households with children aged less than 12 months per village. On the basis of these inputs and using a binomial (exact) calculation, we would require 200 households in the CG to detect a 95% confidence interval of 6.2% to 15.0% [20]. The total sample size for the pilot was therefore set at double this number or 400 households.
Village Selection
The sampling frame was informed by the 2011 census [21], which indicated that the Bawan Block had a total population of approximately 234,000, including 217,000 rural residents distributed among 143 villages. We eliminated 3 urban villages, 11 villages with a population exceeding 4000, 15 villages recorded as having 0 population, and 57 villages in which we had previously worked (so as to gain experience in a treatment-naïve population). This left a sampling frame of 57 villages, from which an initial 20 villages were randomly selected using Microsoft Excel. The number of children in the target age range per village was not known in advance of the baseline survey. As villages vary in size, to attain our sample size target, we decided a priori that (1) any village with more than 1 but less than 10 children in the target age range would be retained and another randomly selected village would also be added and (2) villages with no children in the target age range would be dropped.
Sequence Generation and Allocation Concealment
Villages were assigned to either intervention or control using simple randomization with a 1:1 allocation following a computer-generated randomization schedule. The random allocation sequence was generated at the Centre de recherche du Centre hospitalier de l'Université de Montréal by a professional statistician (MPS) using commands for random samples and permutations in the R environment for statistical computing [22] and kept in a password-protected computer. The statistician was not involved in study implementation. Before the release of the randomization code, only the statistician had access to the allocation sequence. Randomization code was released all at once, and treatment groups were assigned only after completing all recruitment procedures and baseline measurements.
Field team leaders enrolled clusters by contacting village officials in person to explain study aims and activities and request consent to participate. Subsequently, in each participating village, surveyors conducted a complete enumeration to identify all households with children in the target age range and directly approached all such households to request participation in the baseline survey and pilot study. Consent was sought before randomization. No advertisements were used for recruitment, and no incentives or rewards were offered for participation. Surveyors communicated group assignments personally to households.
Due to the nature of the interventions, neither participants nor those delivering interventions were blinded to the group assignment. We hired independent surveyors at end line to assess study outcomes. These surveyors were not informed about study aims or group assignments.
Descriptive Analyses
We used counts, frequencies, and proportions to summarize categorical data, and means and standard deviations for continuous variables. We assessed bivariate associations using univariable logistic regression for continuous variables and the chi-square test for categorical variables.
Multivariable Analyses
We studied the degree to which target beneficiaries (IG households with a child aged less than 12 months at baseline) received the interventions.
To investigate patterns of uptake, we developed separate models for each intervention component: immunization reminders (mHealth), edutainment capsules (mHealth), and small group meetings (face-to-face). Outcomes were modeled as binary (0 uptake vs 1 or more instances of uptake). We followed guidance for the use of logistic regression in small data sets [23,24]. To identify candidate predictors of uptake and use, we developed a conceptual framework informed by the scientific literature and expert knowledge (Multimedia Appendix 1). The conceptual framework considered socioeconomic determinants, physical and infrastructure barriers, access barriers related to mobile phone use within households, and women's empowerment. Together, these variables represented 17 degrees of freedom. To develop the full models for implementation, we empirically refined the choice of variables to respect a minimum of roughly 10 events per variable for accurate prediction of binary outcomes [23]. Specifically, we excluded candidate variables if the bivariate chi-square test showed no relationship between predictor and outcome at the level of P<.25. We fit full statistical models using the Firth (penalized maximum likelihood) logistic regression to avoid overfitting [23] and handle data separation. The final models were fit within a cluster bootstrap algorithm (1000 iterations).
To study the determinants of intensity of participation, we repeated analyses specifying ordered logistic regression models for 2 outcomes: (1) the number of mHealth items heard and (2) the number of small group meetings attended. We tested the proportional odds assumption using an approximate likelihood ratio test [25]. All models used robust standard errors to account for clustering.
Adequacy of the Program Theory
We studied intervention impact on intermediate outcomes using generalized estimating equations (GEE): (1) we used the differences-in-differences method to study changes in variables measuring immunization knowledge in the 2 study groups between the baseline survey and the end line survey using unadjusted regression coefficients (with their 95% CIs) for the interaction between group (intervention or control) and time period (end line or baseline) [26]. (2) To assess knowledge of other basic health topics (assessed only at study end line), we estimated the probability of correct responses at the end line among those receiving the intervention (vs controls). All GEE models estimated binary outcomes with an exchangeable correlation structure adjusted for village-level clustering and robust standard errors. We ran crude models and models adjusted for unbalanced variables following randomization and prespecified potential confounders.
Feasibility outcomes were assessed using the intention-to-treat (ITT) sample; no clusters and no participants were excluded. Analyses of intervention uptake and coverage used the ITT IG; no clusters and no participants randomized to the IG were excluded. To assess the program theory, we analyzed intermediate outcomes using the sample that participated at both baseline and end line, for which 0 clusters, 68 households, and 69 caregivers were lost to follow-up, which is equivalent to an observational sample. For 2 households, missing data on caste were imputed based on the locality of residence within the village. There were no other missing data. Analyses were conducted in Stata 15 (Stata Corporation).
Research Ethics and Informed Consent
Permission was granted by the Institutional Committee for Ethics and Review of Research, Indian Institute of Health Management Research, Jaipur, on January 10, 2017, and by the Comité d'éthique de la recherche du Centre hospitalier de l'Université de Montréal (Research Ethics Committee of the University of Montreal Hospital) on January 11, 2017 (Reference number 16.084). All participants provided written, in-person informed consent. After completing the study, we offered CG residents access to the mHealth interventions.
The baseline survey and recruitment took place from January 19 to February 19, 2018. We approached 29 villages and 100% (29/29) consented to participate. Recruitment of individual participants was complicated by gaps in administrative data, as 13.9% (79/565) of recorded households were in fact nonresident. Only 1.4% (8/565) of the candidate households did not consent to participate. A total of 391 (185 IG and 206 CG) caregivers of children aged 0 to 12 months in 387 (184 IG and 203 CG) households in 26 (13 IG and 13 CG) villages were included in the study (Figure 2). Interventions were delivered from March 21 to July 9, 2018. The end line survey took place from July 17 to August 20, 2018, during the annual monsoon floods. Many households (17.6%, 68/387) were absent during the study end line; loss to follow-up was non-differential (31 IG and 37 CG). The trial ended when planned activities were successfully completed; Figure 2 describes the progress of participants through the trial.
Characteristics of the participating individuals (Table 2) and villages (Table 3) were similar across treatment groups at baseline. The CG was advantaged in terms of assets (wealth quintiles) and cell phone network quality.
Figure 2. Flow diagram of the parallel group cluster trial. ITT: intention-to-treat.
Table 2. Baseline characteristics of participating households, by treatment group.
Variablea Intervention (n=184), n (%) Control (n=203), n (%) All participants (n=387), n (%)
Wealth index (quintile)
(Q1) Lowest 48 (26.1) 30 (14.8) 78 (20.2)
(Q2) 37 (20.1) 40 (19.7) 77 (19.9)
(Q5) Highest 34 (18.5) 43 (21.2) 77 (19.9)
Religionb
Hindu 181 (98.4) 176 (86.7) 357 (92.3)
Muslim 3 (1.6) 27 (13.3) 30 (7.8)
General 38 (20.7) 37 (18.2) 75 (19.4)
Other backward caste 89 (48.4) 80 (39.4) 169 (43.7)
Scheduled caste 57 (31.0) 86 (42.4) 143 (37.0)
Maternal education (years)
None (0) 62 (33.7) 75 (37.0) 137 (35.4)
Primary (1-8) 85 (46.2) 84 (41.4) 169 (43.7)
Secondary (9-12) or more 37 (20.1) 44 (21.7) 81 (20.9)
Paternal education (years)
None (0) 29 (15.8) 26 (12.8) 55 (14.2)
Secondary (9-12) or more 65 (35.3) 78 (38.4) 143 (37.0)
HH lives far from meetingsd
No 142 (77.2) N/Ae N/A
Yes 42 (22.8) N/A N/A
Cell phone network poor
No 163 (88.6) 203 (100.0) 366 (94.6)
Yes 21 (11.4) 0 (0.0) 21 (5.4)
HH owns a mobile phone
No 11 (6.0) 15 (7.4) 26 (6.7)
Yes 173 (94.0) 188 (92.6) 361 (93.3)
In this HH, mother has phone
No 106 (57.6) 134 (66.0) 240 (62.0)
Yes 78 (42.4) 69 (34.0) 147 (38.0)
In this HH, father has phone
No 68 (37.0) 76 (37.4) 144 (37.2)
In this HH, someone else has phone
Yes 22 (12.0) 37 (18.2) 59 (15.3)
Mother's phone access
Cannot access 90 (48.9) 88 (43.4) 179 (45.0)
Can use easily 94 (51.1) 115 (56.7) 209 (54.0)
Mother can dial phone
No 47 (25.5) 55 (271) 102 (26.4)
Yes 137 (745) 148 (72.9) 285 (73.6)
Mother's frequency of phone use
Rarely 27 (14.7) 30 (14.8) 57 (14.7)
When needed 102 (55.4) 106 (52.2) 208 (53.8)
Almost daily 55 (29.9) 67 (33.0) 122 (31.5)
Women's empowerment score (tercile)
Lowest 83 (45.1) 94 (46.3) 177 (45.7)
Average 74 (40.2) 84 (41.4) 158 (40.8)
Highest 27 (14.7) 25 (12.3) 52 (13.4)
Permission to attend village meetings
aBaseline data are presented for the intention-to-treat sample of 387 households (184 IG and 203 CG).
bThis is the religion of the household head.
cCaste categories from most to least advantaged: general, other backward caste, and scheduled caste. The scheduled tribe category is missing, as there are no tribes in the study area.
dHH: household.
eN/A: not applicable.
Table 3. Baseline characteristics of participating villages, by treatment group.
Variablea Intervention Control All
Village population, mean (SD)b
Total 974 (673.84) 1129 (1056.51) 1051 (871.79)
Total 0-6 years 166 (111.05) 188 (171.36) 177 (141.95)
Total SCc 225 (194.85) 422 (484.76) 323 (375.62)
Village electrification, n(%)
No electricity 1 (7.7) 2 (15.4) 3 (11.5)
Less than 6 hours 2 (15.4) 0 (0.0) 2 (7.7)
More than 6 hours 10 (76.9) 11 (84.6) 21 (80.8)
Characteristics of participating HHd, mean (SD)
Number of Muslim HH per village 31 (61.39) 98 (168.96) 65 (129.25)
Number of eligible HHe per village 14 (7.39) 16 (12.46) 15 (10.07)
% poorf (Q1+Q2) per village 44.6 (0.19) 34.8 (0.23) 39.7 (0.21)
% better off (Q4+Q5) per village 39.3 (0.26) 47.5 (0.28) 43.4 (0.27)
% SC per village 31.0 (0.31) 41.5 (0.34) 36.3 (0.32)
% of mothers with 0 schooling per village 32.4 (0.17) 41.0 (0.24) 36.7 (0.21)
% of fathers with 0 schooling per village 14.6 (0.12) 9.8 (0.09) 12.2 (0.11)
aBaseline data are presented for the intention-to-treat sample of 26 villages (13 IG and 13 CG) containing 387 households (184 IG and 203 CG).
bData from the 2011 Census of India.
cSC: scheduled caste (least privileged).
eEligible household: at least one child aged less than 12 months at baseline.
fPoor versus better off households based on asset indices (wealth quintiles).
Ex-ante criteria were fully satisfied (Table 4). Results from 2 independent sources demonstrated a very low (1% or less) rate of contamination (Table 4; Multimedia Appendix 1). Uptake of interventions (adoption) was very high; overall participation in one or more new interventions was 94.0% (173/184), 78.3% (144/184) for the face-to-face channel, and 67.4% (124/184) for the mHealth channel (Table 4). A total of 38.0% (70/184) of participating households used the mHealth intervention weekly. Together, these results confirm the feasibility of the future main study and demonstrate the potential to impact population health.
Table 4. Primary outcomes.
Primary outcomesa,b Ex-ante criteria Ex-post results
Feasibility of the future main study
Recruitment and randomization (villages) 70% of villages approached will agree to participate and accept randomization 100% (29/29 villages) agreedb
Recruitment and randomization (households) In participating villages, 70% of eligible households will agree to participate and accept randomization 98.0% (387/395 households contacted) agreedb
Retention (households) 50% of households participating in the baseline survey will agree to participate in the end line survey 82.2% (318/387) enrolled households agreedb and 2.1% (8/387) households refused
Contamination Contamination proportion between treatment groups should be <15% 0.6% (1/166 control end line respondents called); 0.07% (1/1310 unique callers to IVR system from a control village)c
Uptake (adoption) 50% of households recruited to the study will participate 94.0% (173/184) of households participated
mHealthd interventions Either by listening to ≥1 mHealth item 67.4% (124/184) listened to ≥1 mHealth item
Small group meetings Or by attending ≥1 small group meeting 78.3% (144/184) attended ≥1 meeting
aFeasibility outcomes were computed using the intention-to-treat (ITT) sample of 387 households (184 IG and 203 CG). Uptake was computed using the ITT intervention group sample (184 households).
bSee flow diagram (Figure 2).
cSee Multimedia Appendix 1.
dmHealth: mobile health.
Uptake of the 3 intervention channels (mHealth vaccination reminders, mHealth edutainment capsules, and face-to-face small group meetings) differed among user segments (Tables 5 and 6 present modeled results; Supplementary Table 1 provides bivariate associations).
The ownership of a mobile phone was common among IG households (173/184, 94.0%) and a critical precondition for uptake of both mHealth strategies. Owing to the very few (n=11) households without a mobile phone and the prognostic importance of this variable, effect size estimates for mobile phone ownership are unreliable. However, estimates for other variables are, in principle, unbiased:
mHealth audio vaccination reminders were accessed by 62.5% (115/184) of households. In addition to mobile phone ownership, 2 factors predicted higher uptake: high maternal education (secondary 9 years or higher vs none; OR 4.45, 95% CI 1.17-16.88; P=.03) and mothers' ease of access to the mobile phone (OR 3.55, 95% CI 1.08-11.71;P=.04).
mHealth edutainment capsules were accessed by 60.3% (111/184) of households. In addition to mobile phone ownership, intervention uptake was predicted by high (as compared with low) women's empowerment (OR 3.29, 95% CI 1.28-8.47;P=.01), with some evidence of greater uptake by the lowest castes (members of scheduled castes vs general castes; OR 2.79, 95% CI 0.95-8.21;P=.06). However, poor phone network quality impeded the uptake of edutainment capsules (OR 0.29, 95% CI 0.12-0.71;P=.01).
Face-to-face small group meetings were attended by 78.3% (144/184) of households. Living far from the meeting site reduced the uptake of small meetings (OR 0.07, 95% CI 0.02-0.33;P <.001); no other factor predicted uptake.
We also studied factors shaping the intensity of uptake. In modeled analyses, the number of mHealth items heard was influenced by 3 factors: mother's possession of a mobile phone, mother's ease of phone access, and women's empowerment. The number of small group meetings attended was influenced by 2 factors: living far from the meeting site and women's empowerment (Multimedia Appendix 1).
Table 5. Determinants of mobile health intervention uptake.
Variablea,b,c,d Vaccination reminders Edutainment
OR (95% CI) P value OR (95% CI) P value
Wealth quintile
Poorest (Q1; reference) —e
(Q2) 0.51 (0.12-2.15) .36 0.42 (0.12-1.52) .19
Highest (Q5) 0.43 (0.09-2.11) .30 1.24 (0.40-3.92) .71
Casted
General (reference) — — — —
Other backward caste — — 1.15 (0.36-3.67) .81
Scheduled caste — — 2.79 (0.95-8.21) .06
Education of mother
None (reference) — — — —
Primary 0.80 (0.26-2.50) .70 1.21 (0.53-2.79) .65
Secondary or higher 4.45 (1.17-16.88) .03 1.95 (0.56-6.80) .29
Education of father
Secondary or higher 2.01 (0.62-6.47) .24 1.52 (0.52-4.44) .45
HHf owns phone
Yes versus no 23.90 (5.09-112.1) .001 16.80 (4.27-66.18) .001
Cell network: poor
Yes versus no — — 0.29 (0.12-0.71) .01
HH phone belonging to mother
Yes versus no 1.21 (0.5-2.61) .64 — —
Easy versus no access 3.55 (1.08-11.71) .04 — —
Mother can dial
No versus yes 0.82 (0.27-2.55) .74 — —
Lowest (reference) — — — —
Average — — 0.96 (0.4-2.09) .91
Highest — — 3.29 (1.28-8.47) .01
aAnalyses based on the intention-to-treat intervention group sample comprising 184 households.
bEstimates produced using Firth logistic regression with cluster bootstrapped standard errors (1000 iterations).
cWe present the full models implemented for each outcome. Potential determinants with no evidence of association at the P<.25 level were not included in the models.
dCaste categories from most to least advantaged: general, other backward caste, and scheduled caste. The scheduled tribe category is missing, as there are no tribes in the study area.
e—: empty cells signify that variables were not included in models. Please see the Methods section on Multivariable Analyses subheading Coverage for further details.
fHH: household.
Table 6. Determinants of face-to-face intervention uptake.
Variablea,b,c,d Small group meetings
OR (95% CI) P value
Poorest (Q1; reference) —e —
(Q2) 0.67 (0.12-3.69) .64
Highest (Q5) 0.68 (0.16- 2.88) .60
None (reference)
Primary 0.62 (0.11-3.33) .58
Secondary or higher 0.41 (0.04- 3.87) .44
None (reference) — —
Primary 2.76 (0.32-23.70) .35
Secondary or higher 2.84 (0.25-31.73) .40
HHd lives far
No (reference) — —
Yes 0.07 (0.02-0.33) .001
HH phone belonging to father
Yes versus no 2.19 (0.6-8.03) .24
HH phone belonging to someone else
Yes versus no 0.41 (0.08-2.12) .29
No versus yes 1.79 (0.2-15.63) .60
Permission to attend meeting
bEstimates produced using the Firth logistic regression with cluster bootstrapped standard errors (1000 iterations).
cWe present the full models implemented for each outcome. Potential determinants with no evidence of association at the P=.24 level were not included in the models.
e—: empty cells signify that variables were not included in models.
Immunization knowledge was low at baseline in both study groups. For 3 of the 4 indicators studied, knowledge improved in the IG at end line (Table 7). Differences-in-differences estimates of impact suggest that observed improvements were owing to the study interventions (Table 8). Effect sizes increased after adjustment for baseline imbalances.
For 8 of 9 intermediate outcomes, the regression results showed significantly higher basic health knowledge among the IG at end line (Table 9). For one topic (whether subjects had heard of diarrhea), knowledge at end line was equal for both treatment groups (P=.44). This was likely owing to an independent immunization and hygiene intervention in the study area run by the Gavi Alliance and Unilever.
Table 7. Proportion of correct responses on intermediate outcomes related to immunization knowledge, by study group.
Outcomea Baseline End line
Treated, n (%) Control, n (%) P valueb Treated, n (%) Control, n (%) P valueb
Knows immunization schedulec
Yes 49 (26.6) 70 (34.5) .095 102 (66.7) 74 (44.6) <.001
Knows how many times to vaccinated
Correct 2 (1.1) 3 (1.5) .734 30 (19.6) 6 (3.6) .001
"On the vaccination card, what does each box represent?"e
Correct 21 (11.4) 29 (14.3) .400 42 (27.5) 34 (20.5) .144
"One should vaccinate a child with a minor illness"f
True 112 (60.9) 119 (58.6) .652 110 (71.9) 95 (57.2) .006
aAll responses are binary.
bP value for the chi-square test of independence.
cThis is self-assessed knowledge of the schedule from birth to 5 years.
dThe correct response is 7 times before age 5.
eThe correct response is a vaccine dose.
fThe correct response is True.
Table 8. Impact of the intervention on intermediate outcomes related to immunization knowledge.
Outcomea Model 0b Model 1c
Knows immunization schedule from birth to 5 years 7.87 (1.90-32.49) .004 8.40 (2.05-34.35) .003
Knows how many times to vaccinate by age 5 3.52 (2.08-5.98) .001 4.21 (2.25-7.85) .001
"On the vaccination card, what does each box represent?" 1.84 (1.12-3.03) .016 2.00 (1.18-3.40) .011
"Children with a minor illness should be vaccinated" 1.53 (0.72-3.28) .27 1.54 (0.71-3.34) .27
aThese are differences-in-differences estimates of intervention impact.
bModel 0=unadjusted.
cModel 1=adjusted for variables imbalanced at the time of randomization (wealth index and cell network).
Table 9. Estimated probability of correct responses for intermediate outcomes reflecting basic health knowledge, intervention group versus controls.
Outcomesa Model 0b Model 1c
Childhood pneumonia
Has heard of 4.60 (2.68-7.89) .001 4.98 (2.89-8.56) .001
Can state signs 3.36 (1.58-7.13) .002 3.67 (1.54-8.74) .003
Can state how to prevent 4.12 (1.94-8.74) .001 5.09 (2.16-12.02) .001
Can state signs 4.14 (1.64-10.44) .003 2.81 (1.48-5.32) .002
Can state how to prevent 3.71 (2.06-6.67) .001 3.82 (2.20-6.61) .001
Dengue or chikungunya
Can state how it is transmitted 3.61 (2.13-6.12) .001 3.94 (2.45-6.31) .001
aThese are basic health topics other than immunization, evaluated only at study end line.
cModel 1=adjusted for wealth index, maternal education, paternal education, caste, and women's empowerment.
We conducted a pilot trial of SBCC interventions focusing on immunization and other basic themes important for child and family health. Interventions were delivered through small face-to-face meetings and via mobile phones using pushed audio messages and other strategies suitable for disadvantaged populations. The pilot trial aimed to assess the feasibility of a future planned main study and to draw lessons to optimize delivery of the interventions at scale.
This paper offers 4 salient findings: First, all ex-ante feasibility criteria related to recruitment, randomization, retention, and contamination were satisfied, providing compelling evidence that the planned future main trial is feasible as planned. Uptake of interventions (adoption) was near universal (50% ex-ante vs 94% in practice), demonstrating strong interest and acceptability. Second, analyses of uptake and use demonstrated that intervention use was shaped by social determinants but that the chosen combination of strategies reached all population groups, even the most vulnerable. Third, constellations of determinants differed by intervention delivery channel. Ownership of a mobile phone was critical for participation in mHealth (vaccination reminders and edutainment) interventions, whereas distance from place of residence to the meeting site was important for small group meetings. mHealth vaccination reminders were taken up preferentially by more educated women and those with easy phone access within the household, whereas mHealth edutainment capsules were favored by more empowered women and by lower caste groups, for whom the content was likely novel and useful. Face-to-face meetings were the most equitable intervention channel; participation was equal or higher among those with greater needs. Women's empowerment was an important transversal determinant, increasing uptake and intensity for all interventions. Fourth, we found that the study interventions lead to measurable improvements in basic health knowledge, supporting the potential for impact at scale. Changes in intermediate outcomes are consistent with the intervention theory of change.
At least five important caveats should also be considered. First, an important potential bias relevant for the future definitive trial relates to vaccination coverage assessment. As documented in our pilot study and elsewhere, the population denominator used in administrative estimates is often inaccurate (and the reported number of doses unreliable) [27]. Although household surveys are considered superior, they are also affected by seasonal and chance variations and do not shed light directly on population immunity gaps. Improvements in vaccination coverage assessment methods would strengthen the ability of the main trial to assess immunization program performance. Second, those delivering and receiving interventions could not be blinded due to the nature of the interventions. We attempted to limit potential bias due to lack of blinding by hiring independent outcome assessors unaware of study purpose and group assignment, using indicators based on objective measures where possible, and triangulating between multiple measures and data sources to strengthen inference. Third, although interventions were able to achieve widespread reach in highly disadvantaged populations to ensure equity and impact, these findings are limited by the relatively small size of the IG. Fourth, quality of intervention delivery may be more difficult to achieve in a routine care setting. The personnel delivering the RCT interventions were highly motivated, well trained, and closely supervised. It may be difficult to maintain delivery quality at scale, particularly for face-to-face components. Fifth, the pilot study duration was too short (and sample size was too small) to assess definitive changes in health outcomes. Future research is required to demonstrate whether these gains in health knowledge result in improved vaccination coverage and child health.
Generalizability
We highlight 3 insights relevant to the future definitive trial and other studies: The first relates to adapting mHealth interventions for highly disadvantaged populations. In rural India, mobile phone penetration and infrastructure is increasing rapidly, reducing barriers to delivering mHealth interventions. Our experience demonstrates that mHealth interventions can achieve reach and improve knowledge even in highly underprivileged populations, but that technical delivery and content must be substantially adapted. Although mHealth interventions using SMS have shown promise [6], we privileged audio messages with pushed dial outs owing to the low literacy, numeracy, and technological comfort levels of our target beneficiaries. We found that engaging story formats inclusive of diverse social groups were appreciated and that pure informational approaches such as vaccination reminders were taken up preferentially by the (relative) elite. As compared with SMS, audio messaging is more amenable to culture-specific contextualization and an edutainment approach. The second insight concerns how gender-related barriers shape immunization access [28] and affected the study interventions. Participation in mobile phone interventions was limited by women's ease of access to mobile phones, and, to a lesser degree, with technological familiarity. Participation in face-to-face meetings was limited by norms governing women's freedom of movement. Barriers were mitigated over time as families came to understand and value the interventions (Pérez et al, unpublished data, 2020). Unexpectedly, men, particularly fathers, were highly active participants. Future interventions should include a focus on men and families to strengthen inclusion and mitigate gender barriers. The third insight concerns the complementarity of mHealth and face-to-face communication: Although mHealth audio messaging is a promising strategy to deliver basic health information, our experience shows that it must be accompanied by face-to-face contact to enhance uptake [29] and equity. An mHealth strategy can extend the reach of face-to-face communication at high fidelity and low cost. Particularly among vulnerable populations, it is unlikely to fully replace in-person interaction. Future research exploring innovative delivery modalities while considering potential trade-offs between equity and efficiency (cost-effectiveness) is recommended.
A novel SBCC intervention model using face-to-face and mHealth approaches is feasible to evaluate in a future randomized trial and has the potential to strengthen the delivery of immunization and universal primary health care. The interventions achieved widespread reach in a highly disadvantaged population and showed early evidence of impact on participants' knowledge, supporting the intervention theory of change. Behavior change communication via mobile phones proved viable and contributed to standardization and scalability. Face-to-face interactions remain necessary to achieve equity and reach, suggesting the need for ongoing health system strengthening to accompany the introduction of promising mobile phone technologies.
The authors gratefully acknowledge the support of IC-IMPACTS (the India-Canada Centre for Innovative Multidisciplinary Partnerships to Accelerate Community Transformation and Sustainability), Grand Challenges Canada (Award # R-ST-POC-1707-06282), and the Canadian Institutes for Health Research (Award # 342296), who funded this study. The study sponsors played no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. The authors would like to thank Aaditeshwar Seth, Rohit Singh, Vijay Sai Pratap, Sangeeta Saini, Dinesh Rautela, and the entire Gram Vaani team (Gurgaon, India) for expert leadership of the mHealth interventions. Valuable contributions to research design and instruments were made by Claudia Bojanowski, Alexandra Otis, Myriam Cielo Perez, and Dr Isabelle Michaud-Letourneau (Université de Montréal), and Frédérique Sauvé (McGill University). Dr Bhupendra Tripathi (Bill & Melinda Gates Foundation) has been a constant source of guidance and encouragement. At the state and district levels, the authors would like to thank Mr Pankaj Kumar (Mission Director, National Health Mission, UP), Dr Arun Chaturvedi (State EPI Officer, UP), Dr Ved Prakash (General Manager, Routine Immunization, UP), Dr SK Rawat (Chief Medical Officer, Hardoi), Dr PN Chaturvedi (Former Chief Medical Officer, Hardoi), Dr Vijay Singh (District Immunization Officer, Hardoi), Dr Prakash Kumar Chaurashiya (Former District Program Officer, Hardoi), Mrs Buddhi Mishra (District Program Officer, Hardoi), Mr CK Shrivastav (Assistant Program Officer, Hardoi), Dr Prabhakar Tripathi (Medical Officer In-charge, Bawan Block, Hardoi), and Ms Gayatri Tiwari (Block Program Manager, Bawan Block, Hardoi). Study interventions were codeveloped and implemented in partnership with communities. The authors thank Mr Ajit Solanki (Chief Executive Officer of Jagriti Foundation) and the entire Tika Vaani field team for their dedication and commitment to community development. The authors highlight the remarkable contributions of Shailendra Singh Somvanshi, Dhiresh Singh (Chanchal), Madhavi Shukla, and Mohd. Haneef Siddiqui, Poonam Bauddh, Priyanka Mishra, and Shivam Pal.
Finally, the authors express heartfelt gratitude to the residents of Hardoi district for collaborating to improve basic health conditions for their children, families, and communities.
MJ designed the study, acquired the funding, performed the statistical analyses and wrote the draft manuscript; DC contributed to intervention design, oversaw study implementation, contributed to data management, and revised the manuscript; GK had primary responsibility for data management, contributed to the statistical analyses, and revised the manuscript; MPS, AM, SH, and AN advised on study methodology and revised the manuscript.
All authors gave final approval of the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Supplementary methods and results.
PDF File (Adobe PDF File), 606 KB
Sustainable Development Goals. Gavi, the Vaccine Alliance. URL: https://www.gavi.org/about/ghd/sdg/ [accessed 2020-04-01]
Gurnani V, Haldar P, Aggarwal MK, Das MK, Chauhan A, Murray J, et al. Improving vaccination coverage in india: lessons from intensified mission Indradhanush, a cross-sectoral systems strengthening strategy. Br Med J 2018 Dec 7;363:k4782 [FREE Full text] [CrossRef] [Medline]
Johri M, Rodgers L, Chandra D, Abou-Rizk C, Nash E, Mathur AK. Implementation fidelity of village health and nutrition days in Hardoi District, Uttar Pradesh, India: a cross-sectional survey. BMC Health Serv Res 2019 Oct 26;19(1):756 [FREE Full text] [CrossRef] [Medline]
Oyo-Ita A, Wiysonge CS, Oringanje C, Nwachukwu CE, Oduwole O, Meremikwu MM. Interventions for improving coverage of childhood immunisation in low- and middle-income countries. Cochrane Database Syst Rev 2016 Jul 10;7:CD008145 [FREE Full text] [CrossRef] [Medline]
Johri M, Pérez MC, Arsenault C, Sharma JK, Pai NP, Pahwa S, et al. Strategies to increase the demand for childhood vaccination in low- and middle-income countries: a systematic review and meta-analysis. Bull World Health Organ 2015 May 1;93(5):339-46C [FREE Full text] [CrossRef] [Medline]
Sondaal SF, Browne JL, Amoakoh-Coleman M, Borgstein A, Miltenburg AS, Verwijs M, et al. Assessing the effect of mhealth interventions in improving maternal and neonatal care in low- and middle-income countries: a systematic review. PLoS One 2016;11(5):e0154664 [FREE Full text] [CrossRef] [Medline]
Thabane L, Cambon L, Potvin L, Pommier J, Kivits J, Minary L, Discussion Panel. Population health intervention research: what is the place for pilot studies? Trials 2019 May 30;20(1):309 [FREE Full text] [CrossRef] [Medline]
Annual Health Survey 2010-11 Fact Sheet. Office of the Registrar General & Census Commissioner, India (ORGI). 2020. URL: http://www.censusindia.gov.in/vital_statistics/AHSBulletins/AHS_Baseline_Factsheets/U_P.pdf [accessed 2020-04-01]
Ram U, Jha P, Ram F, Kumar K, Awasthi S, Shet A, et al. Neonatal, 1-59 month, and under-5 mortality in 597 Indian districts, 2001 to 2012: estimates from national demographic and mortality surveys. Lancet Glob Health 2013 Oct;1(4):e219-e226 [FREE Full text] [CrossRef] [Medline]
District Level Household and Facility Survey: Uttar Pradesh. International Institute for Population Sciences (IIPS). 2010. URL: http://www.rchiips.org/pdf/rch3/report/UP.pdf [accessed 2020-04-01]
Pérez M, Singh R, Chandra D, Ridde V, Seth A, Johri M. Development of an mHealth Behavior Change Communication Strategy: A case-study from rural Uttar Pradesh in India. In: Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies. 2020 Presented at: COMPASS'20; June 15-17, 2020; Guayaquil, Ecuador. [CrossRef]
Kevany S, Khumalo-Sakutukwa G, Murima O, Chingono A, Modiba P, Gray G, et al. Health diplomacy and the adaptation of global health interventions to local needs in sub-Saharan Africa and Thailand: evaluating findings from project accept (HPTN 043). BMC Public Health 2012 Jun 20;12:459 [FREE Full text] [CrossRef] [Medline]
Mobile Vaani. YouTube. URL: https://www.youtube.com/watch?v=XYsMQM50qCs [accessed 2020-04-01]
Mobile Vaani. Gram Vaani. URL: http://voice.gramvaani.org/vapp/mnews/912/show/tags/episode/ [accessed 2020-04-01]
Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. Br Med J 2014 Mar 7;348:g1687. [CrossRef] [Medline]
National Department of Health. In: Peters DH, editor. Implementation Research in Health: A Practical Guide. Geneva, Switzerland: World Health Organization; 2013.
Kaufman J, Ames H, Bosch-Capblanch X, Cartier Y, Cliff J, Glenton C, et al. The comprehensive 'communicate to vaccinate' taxonomy of communication interventions for childhood vaccination in routine and campaign contexts. BMC Public Health 2017 May 10;17(1):423 [FREE Full text] [CrossRef] [Medline]
DHS Model Questionnaire. The DHS Program. 2008. URL: http://dhsprogram.com/publications/publication-dhsq6-dhs-questionnaires-and-manuals.cfm [accessed 2020-04-25]
Filmer D, Pritchett LH. Estimating wealth effects without expenditure data--or tears: an application to educational enrollments in states of India. Demography 2001 Feb;38(1):115-132. [CrossRef] [Medline]
Sample Size Calculator. URL: http://www.sample-size.net/ [accessed 2020-04-25]
CD Block Wise Primary Census Abstract Data (PCA) - Uttar Pradesh. Office of the Registrar General & Census Commissioner, India (ORGI). 2014. URL: http://censusindia.gov.in/pca/cdb_pca_census/Houselisting-housing-UP.html [accessed 2020-04-25]
R: A language and environment for statistical computing. R Foundation for Statistical Computing. 2008. URL: https://www.r-project.org/about.html [accessed 2020-03-01]
Steyerberg EW, Eijkemans MJ, Harrell FE, Habbema JD. Prognostic modeling with logistic regression analysis: in search of a sensible strategy in small data sets. Med Decis Making 2001;21(1):45-56. [CrossRef] [Medline]
Steyerberg EW, Eijkemans MJ, Harrell FE, Habbema JD. Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets. Stat Med 2000 Apr 30;19(8):1059-1079. [CrossRef] [Medline]
OMODEL: Stata Modules to Perform Tests on Ordered Probit and Ordered Logit Models. EconPapers. 1997. URL: https://EconPapers.repec.org/RePEc:boc:bocode:s320901 [accessed 2020-04-01]
Khandker S, Koolwal G, Hussain AS. Handbook on Impact Evaluation: Quantitative Methods and Practices. Geneva, Switzerland: The World Bank; 2010.
Cutts FT, Claquin P, Danovaro-Holliday MC, Rhoda DA. Monitoring vaccination coverage: defining the role of surveys. Vaccine 2016 Jul 29;34(35):4103-4109 [FREE Full text] [CrossRef] [Medline]
Feletto M, Sharkey A. The influence of gender on immunisation: using an ecological framework to examine intersecting inequities and pathways to change. BMJ Glob Health 2019;4(5):e001711 [FREE Full text] [CrossRef] [Medline]
Chakraborty D, Gupta A. Seth Axperiences From a Mobile-based Behaviour Change Campaign on Maternal and Child Nutrition in Rural India. In: Proceedings of the Tenth International Conference on Information and Communication Technologies and Development. 2019 Presented at: ICTD'19; January 4-7, 2019; Ahmadabad, India URL: https://doi.org/10.1145/3287098.3287110 [CrossRef]
ANM: Assistant Nurse Midwives
ASHA: Accredited Social Health Activists
AWW: Anganwadi Workers
CG: control group
CTRI: Clinical Trials Registry–India
GoI: Government of India
GEE: generalized estimating equations
IG: intervention group
ITT: intention-to-treat
IVR: interactive voice response
LMIC: low- and middle-income country
SBCC: social and behavior change communication
SDG: Sustainable Development Goals
UN: United Nations
UP: Uttar Pradesh
VHND: Village Health and Nutrition Day
WASH: water, sanitation, and hygiene
Edited by G Eysenbach; submitted 21.05.20; peer-reviewed by S Kevany, F Palmieri; comments to author 27.06.20; revised version received 01.07.20; accepted 22.07.20; published 21.09.20
©Mira Johri, Dinesh Chandra, Karna Georges Kone, Marie-Pierre Sylvestre, Alok K Mathur, Sam Harper, Arijit Nandi. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 21.09.2020.
Johri M, Chandra D, Kone KG, Sylvestre M, Mathur AK, Harper S, Nandi A


Anxiety-The New "Common-Cold" of Mental Health?
Posted on December 2, 2016 at 12:48 pm.
Tony is a clinician in the Article 16 Clinic. He wrote the following article for the ReHab Center's health and wellness monthly newsletter.


Thank you so much for your interest in one of our Brand Bar Brands! Please fill out this form completely and in detail as it will allow us to better serve you through our custom fitting process.
Note that filling out this form does not confirm your purchase. Brands are sold on a first come, first serve (pending fit) basis and multiple inquiries may be received at one time. If your inquiry to purchase is accepted, you will be contacted by A thousand Faces via email within 24 hours (excluding weekends) and sent your first invoice for the full listing price. Once this invoice is completed, we will mark this brand item as "SOLD" to take it off the market as we begin your customization process as each brand listing is only sold once. Please note that this invoice is final and non-refundable.
A Thousand Faces specializes in unique branding solutions for women in business. I listen to your story, get to know your business and create a beautifully crafted brand that both reflects your personal style and serves as an effective marketing tool for years to come.


Take a virtual trip to the ancient world to discover more about it. Move the video forward - to 6:00 - to begin the trip.
MEET ME AT THE CORNER, Virtual Field Trips for Kids takes you to New York City. Learn about THE COMIC BOOK PROJECT in an interview with Michel Bitz, founder of the Comic book Project at Columbia University. Children learn about the history of comics and how to create their own comic book hero. Links to Fun Websites and a Learning Corner of questions and Extended Activities.